Socially shared regulation of motivation and emotions in

E 110
OULU 2010
U N I V E R S I T Y O F O U L U P. O. B . 7 5 0 0 F I - 9 0 0 1 4 U N I V E R S I T Y O F O U L U F I N L A N D
U N I V E R S I TAT I S
S E R I E S
SCIENTIAE RERUM NATURALIUM
Professor Mikko Siponen
HUMANIORA
University Lecturer Elise Kärkkäinen
TECHNICA
Professor Hannu Heusala
ACTA
SOCIALLY SHARED
REGULATION OF MOTIVATION
AND EMOTIONS IN
COLLABORATIVE LEARNING
MEDICA
Professor Olli Vuolteenaho
SCIENTIAE RERUM SOCIALIUM
Senior Researcher Eila Estola
SCRIPTA ACADEMICA
Information officer Tiina Pistokoski
OECONOMICA
University Lecturer Seppo Eriksson
EDITOR IN CHIEF
Professor Olli Vuolteenaho
PUBLICATIONS EDITOR
Publications Editor Kirsti Nurkkala
ISBN 978-951-42-6329-3 (Paperback)
ISBN 978-951-42-6330-9 (PDF)
ISSN 0355-323X (Print)
ISSN 1796-2242 (Online)
U N I V E R S I T AT I S O U L U E N S I S
Hanna Järvenoja
E D I T O R S
Hanna Järvenoja
A
B
C
D
E
F
G
O U L U E N S I S
ACTA
A C TA
E 110
FACULTY OF EDUCATION,
UNIVERSITY OF OULU
E
SCIENTIAE RERUM
SOCIALIUM
ACTA UNIVERSITATIS OULUENSIS
E Scientiae Rerum Socialium 110
HANNA JÄRVENOJA
SOCIALLY SHARED REGULATION
OF MOTIVATION AND EMOTIONS
IN COLLABORATIVE LEARNING
Academic dissertation to be presented with the assent of
the Faculty of Education of the University of Oulu for
public defence in Kaljusensali (Auditorium KTK 112),
Linnanmaa, on 5 November 2010, at 12 noon
U N I V E R S I T Y O F O U L U, O U L U 2 0 1 0
Copyright © 2010
Acta Univ. Oul. E 110, 2010
Supervised by
Professor Sanna Järvelä
Professor Marja Vauras
Reviewed by
Professor Susan B. Nolen
Academy Research Fellow Janne Lepola
ISBN 978-951-42-6329-3 (Paperback)
ISBN 978-951-42-6330-9 (PDF)
http://herkules.oulu.fi/isbn9789514263309/
ISSN 0355-323X (Printed)
ISSN 1796-2242 (Online)
http://herkules.oulu.fi/issn0355323X/
Cover design
Raimo Ahonen
JUVENES PRINT
TAMPERE 2010
Järvenoja, Hanna, Socially shared regulation of motivation and emotions in
collaborative learning
Faculty of Education, University of Oulu, P.O.Box 2000, FI-90014 University of Oulu, Finland
Acta Univ. Oul. E 110, 2010
Oulu, Finland
Abstract
This study focuses on motivation and emotions in collaborative learning. The aim is to investigate
the kinds of socio-emotional challenges learners experience during learning processes, and to
examine how motivation and emotions are regulated during challenging situations, in order to
develop appropriate methods of identifying socially shared regulation of emotions from situated,
real life data.
The study includes the development and implementation of an instrument that collects data
regarding learners’ situation-specific interpretations of their socio-emotional experiences, as well
as analyses of the data derived from two different data collections. The first empirical data set is
composed of elementary school students’ interviews and video-observations. The second data set
includes higher education students’ self-reports, video-observations, and interviews. The analyses
combine different data sources and qualitative and descriptive quantitative methods in order to
create a comprehensive understanding of the regulation of motivation and emotions in
collaborative learning situations.
A lack of instruments that gather data of learners’ situation-specific, real-life experiences has
been evident in motivation and self-regulated learning research, where static, general self-report
measures have been dominant. In this study, the results from the first empirical data collection are
implemented in the development of an AIRE (Adaptive Instrument for Regulation of Emotions)
instrument. The AIRE collects situation-specific data dealing with learners. experienced socioemotional challenges and their regulation within a group. The second empirical data collection of
this study employs the AIRE instrument as a method.
In social learning situations, learners’ can experience a variety of emotions that influence
learning. The results of this study show that students can regulate their emotions in order to
maintain a goal-oriented learning process. Furthermore, the results indicate that group members
can regulate emotions and motivation together within the group. This socially shared regulation is
distinct from self-regulation as well as from co-regulation, where development of self-regulation
is supported by others, or where group members regulate their own learning processes in parallel
with each other.
Keywords: collaborative learning, emotions, motivation, self-regulated learning
Järvenoja, Hanna, Sosiaalisesti jaettu motivaation ja emootioiden säätely
yhteisöllisessä oppimisessa
Kasvatustieteiden tiedekunta, Oulun yliopisto, PL 2000, 90014 Oulun yliopisto
Acta Univ. Oul. E 110, 2010
Oulu
Tiivistelmä
Tämä tutkimus tarkastelee motivaation ja emootion ilmentymistä yhteisöllisessä oppimisessa.
Tavoitteena on selvittää, millaisia sosio-emotionaalisia haasteita oppijat kohtaavat oppimisprosessin aikana ja miten motivaatiota ja emotionaalisia tuntemuksia säädellään näissä tilanteissa.
Lisäksi tavoitteena on löytää ja kehittää tilannekohtaisia analysointimenetelmiä erityisesti sosiaalisesti jaetun emootion säätelyn tutkimiseksi.
Tutkimus koostuu oppijoiden tilannesidonnaisia sosio-emotionaalisia tulkintoja keräävän
instrumentin kehittelystä sekä kahdesta empiirisestä tutkimusaineistosta. Ensimmäinen tutkimusaineisto koostuu peruskoulun oppilaiden haastatteluista ja videoidusta työskentelystä. Toinen tutkimusaineisto sisältää korkeakouluopiskelijoiden kyselyaineistoa, videoitua työskentelyä
ja haastatteluita. Kokonaisvaltaisen ymmärryksen luomiseksi aineiston analyysissä yhdistetään
näitä erityyppisiä aineistoja ja kuvailevaa kvantitatiivista analyysiä käytetään tukemaan kvalitatiivisia tulkintoja.
Itsesäädellyn oppimisen tutkimuksessa on ollut nähtävillä tarve löytää metodisia ratkaisuja,
joiden avulla voidaan kerätä aineistoa yksilöiden vaihtelevista kokemuksista todellisissa oppimistilanteissa. Aikaisemmin pääpaino on ollut staattisissa, yksilöiden yleisiä käsityksiä mittaavien aineistojen analyysissä. Tässä tutkimuksessa ensimmäisen tutkimusaineiston tuloksia hyödynnetään AIRE (Adaptive Instrument for Regulation of Emotions) -instrumentin kehittelyssä.
AIRE kerää tilannekohtaista tietoa sosio-emotionaalisten haasteiden kokemuksista ja näihin liittyvästä ryhmässä tapahtuvasta emootioiden säätelystä. AIRE:a käytetään toisen tutkimusaineiston yhtenä keruuvälineenä.
Sosiaalisten oppimistilanteiden aikana oppijoissa herää erilaisia tuntemuksia, jotka vaikuttavat oppimistilanteeseen. Tämän tutkimuksen tulokset osoittavat, että oppijat voivat säädellä
emotionaalisia tuntemuksia ylläpitääkseen tavoitesuuntautunutta opiskelua. Tulosten perusteella
voidaan todeta, että yhteisöllisen oppimisen tilanteissa ryhmän jäsenet voivat yhdessä kontrolloida motivationaalisia ja sosio-emotionaalisia haasteita. Tämä sosiaalisesti jaettu emootioiden säätely (socially shared regulation) eroaa itsesäätelystä sekä yhdessä säätelemisestä (co-regulation),
jossa tuetaan yksilön kehittymistä itsesäätöiseksi oppijaksi tai jossa ryhmän jäsenet säätelevät
kukin rinnakkain omaa toimintaansa.
Asiasanat: emootiot, itsesäätöinen oppiminen, motivaatio, yhteisöllinen oppiminen
Acknowledgements
The road to completing this dissertation has been a long one. I am certain that I
would never have successfully reached this point without a great group of
colleagues and friends. Without my collaboration with them, the moments of new
insight and inspiration would have been less enjoyable, and the moments of
disbelief and doubt would have felt insuperable. Furthermore, without these
people, I would have missed a lot of fun!
I want to express my gratitude to Professor Sanna Järvelä, the supervisor of
my Ph.D. studies. This thesis would not have been possible without her. From the
first step to the last, she supported my growth as a researcher in innumerable
ways. Over the years, she always believed in me and encouraged me to face new
challenges. I appreciate her as an honorable colleague who not only inspires me
but with whom I can discuss, agree, disagree, and co-construct our understandings.
I also owe my gratitude to my second supervisor, Professor Marja Vauras. I
wish to thank her for her guidance, especially in the first years of my Ph.D.
studies. With her experience, she has supported me throughout the process. It has
always been stimulating to discuss with her, and our regular encounters in
different parts of the world have take my thinking further.
It has been an honor to work with Professor Simone Volet. She has taught me
a lot by being an inspiring example of a greatly distinguished academic, who
warmly welcomed a young Ph.D. student to work with her and made the student
feel that her ideas and thoughts are valuable. I wish to thank Professor Volet for
her time, elaborate comments, and productive discussion, especially in dealing
with developing methods and writing co-authored publications.
I am grateful to the reviewers of the thesis, Professor Susan B. Nolen and
Academic Research Fellow Janne Lepola. Their thoughtful and constructive
feedback has helped me to better understand the entity of the thesis and see it in a
larger frame. I highly appreciate Professor Nolen’s scientific work and thoughts,
her open-minded but considered approach to motivation research; therefore, I feel
especially privileged to have received her comments on my thesis.
This thesis would also never have been completed without the great group of
people that I worked with. My former and current colleagues and friends in the
Learning and Educational Technology Research Unit, who have shared the daily
hard work as well as the daily laughs and events in everyday life, made this
journey possible, and even enjoyable. In particular, Jonna Malmberg and Niina
Impiö deserve my sincere thanks for their support and contributions in various
7
issues. I particularly wish to express my appreciation and gratitude to Piia Näykki,
who has been a most important fellow for me from the day when we almost drove
through a red light because we were so enthusiastic about our scientific discussion.
After that meaningful day, she has made her interest and support available in a
number of ways. Thank you all and LET’s keep up the spirit in the future!
There are several other colleagues to whom I am indebted for their
contributions and support. I wish to thank Susan Beltman and her family for
warmly welcoming me into their home and for providing me with a friendly place
to stay down under and far away from home. I want to give my warm thanks for
Allyson Hadwin for her valuable academic and non-academic support. I also want
to express my gratitude to Tarja-Riitta Hurme, Piritta Leinonen and Marjaana
Veermans for the shared experiences, fellowship, and support in various issues.
This thesis was financially supported by the Finnish Doctoral Programme in
Education and Learning, the Academy of Finland and the Finnish Cultural
Foundation. I am grateful for these grants that allowed me to finish my thesis. I
would also like to express my gratitude to the Faculty of Education at the
University of Oulu as well as to all the participants who were involved in the
empirical studies.
I have been fortunate to have great friends who are always ready to listen and
chat, even after a long period of not seeing or hearing from each other. I have also
been blessed with lovely parents-in-law Seija and Sakari, as well as sisters-in-law
Marianne and Marjaana and their families. I want to express my warmest thanks
to you all. Marjaana specifically deserves added gratitude for her efforts in
correcting the Finnish language of the abstract in this thesis.
Furthermore, I want to express my thanks to my family. I am grateful for my
parents for their consistent encouragement and faith in me in all aspects of life.
My siblings Matti and Leena, as well as my brother-in-law Mikko, have always
engaged in lively conversations and debates with me, irrespective of the topic.
From you, I have learned to enjoy good arguments, to have fun, and to recognize
what is really important in life. Thank you all for being a part of my life.
Finally, I owe my deepest gratitude to two of my most beloved people in the
world: my daughter Iida, who brings joy and meaning to my life, and my husband
Jarkko, who is my best friend, my love, and my companion. Thank you for
existing.
Oulu, September 2010
8
Hanna Järvenoja
List of original articles
This thesis is based on the following articles:
I
Järvenoja, H., & Järvelä, S. (2005). How students describe the sources of their
emotional and motivational experiences during the learning process: A qualitative
approach. Learning and Instruction 15(5), 465–480.
II Järvenoja, H., Volet, S. & Järvelä, S., (2010). Regulation of emotions in socially
challenging learning situations: An instrument to measure the adaptive and social
nature of the regulation process. Manuscript.
III Järvenoja, H., & Järvelä, S. (2009). Emotion control in collaborative learning
situations - Do students regulate emotions evoked from social challenges? British
Journal of Educational Psychology 79(3), 463–481.
IV Järvelä, S. & Järvenoja, H. (2011, in press). Socially constructed self-regulated
learning in collaborative learning groups. Teacher College Record.
V Järvelä, S., Volet, S., & Järvenoja, H. (2010). Research on Motivation in
Collaborative Learning: Moving beyond the cognitive-situative divide and combining
psychological and social processes. Educational Psychologist 45(1), 15–27.
9
10
Table of contents
Abstract
Tiivistelmä
Acknowledgements
7
List of original articles
9
Table of contents
11
1 Introduction
13
2 Theoretical framework
17
2.1 Emotions and motivation in learning and performance .......................... 19
2.1.1 Emotions....................................................................................... 19
2.1.2 Motivation .................................................................................... 21
2.2 Self-regulated learning ............................................................................ 22
2.2.1 Regulation of emotions and motivation........................................ 26
2.3 Motivation and emotions in collaborative learning contexts .................. 31
2.4 Different forms of regulation of motivation ............................................ 34
2.4.1 Individual regulation .................................................................... 35
2.4.2 Social regulation ........................................................................... 36
2.5 Regulation in social learning contexts .................................................... 39
3 Methodological challenges
41
3.1 Self-report measures ............................................................................... 42
3.2 Using multiple contextual and situation-specific methods...................... 45
3.3 Validity and reliability ............................................................................. 47
4 Aims of the study
49
5 Methods
51
5.1 Participants and Instructional settings ..................................................... 51
5.2 Research design....................................................................................... 52
5.3 Data collection ........................................................................................ 53
5.3.1 Interviews ..................................................................................... 54
5.3.2 Video records ................................................................................ 55
5.3.3 AIRE instrument........................................................................... 55
6 An overview of the articles
59
6.1 Article I Järvenoja, H., & Järvelä, S. (2005). How students
describe the sources of their emotional and motivational
experiences during the learning process: A qualitative approach.
Learning and Instruction 15(5), 465–480. ............................................... 60
11
6.2 Article II Järvenoja, H., Volet, S., & Järvelä, S. (2010).
Regulation of emotions in socially challenging learning
situations: An instrument to measure the adaptive and social
nature of the regulation process. Manuscript. ......................................... 62
6.3 Article III Järvenoja, H., & Järvelä, S. (2009). Emotion control
in collaborative learning situations - Do students regulate
emotions evoked from social challenges? British Journal of
Educational Psychology 79(3), 463–481................................................. 63
6.4 Article IV Järvelä, S., & Järvenoja, H. (2010, in press). Socially
constructed self-regulated learning in collaborative learning
groups. Teacher College Record. ............................................................ 64
6.5 Article V Järvelä, S., Volet, S., & Järvenoja, H. (2010). Research
on motivation in collaborative learning: Moving beyond the
cognitive-situative divide and combining psychological and
social processes. Educational Psychologist 45(1), 15–27. ...................... 65
7 Discussion
67
7.1 Main findings .......................................................................................... 68
7.2 Adaptive instrument for regulation of emotions ..................................... 70
7.3 Final remarks and implications for future research ................................. 72
References
77
Original articles
89
12
1
Introduction
In today’s world, the boundaries of the term “learning” have broadened. Learning
competence is needed to perform well not only in studies but also at work. People
across the world are increasingly overwhelmed by the growing demands of their
everyday lives. Wellbeing can be ensured only if the different aspects of life, such
as relationships with friends, family’s welfare and leisure obligations are
effectively managed. Fulfilling all these obligations and coping with life’s
demands require a high level of engagement, persistence, and competence to learn.
But, how can people meet various demands on their time and attention and strike
balance between the many compartmentalized aspects affecting on their
persistence to learn and maintain studying?
Well-developed self-regulation skills seem to be a functional way to respond
to the various demands of today’s world. Research on self-regulated learning
strives to explain how one can master one’s own learning process (Zimmerman,
2008). Models of self-regulated learning (SRL) argue that in order to overcome
difficulties and act effectively, learners need to take a purposeful role in their own
learning and life in general by regulating their activity (Pintrich, 2000a; Schunk,
2001; Zimmermann, 2000). In addition to cognitive regulation, the ability to
regulate motivation and emotion are vital for coping with the competing demands
of life and for making appropriate choices. However, as empirical research has
evidenced, it is not easy to make appropriate choices, prioritize, resist temptation,
and strategically plan work (Volet & Järvelä, 2001). Students may not want to
engage in planning activities and deploy the affective learning strategies even
when they possess these abilities (Azevedo & Cromley, 2004). It can be argued
that without motivation, cognitive regulation skills are ineffective. Providentially,
motivation and emotions can be regulated successfully.
Social interaction has become increasingly essential in learning because
creating deeper understanding and new knowledge cannot be reached alone as
effectively as in collaboration with other learners. Social constructivist
perspectives on learning emphasize the interdependence of social and individual
processes in problem-solving and construction of knowledge (Palincsar, 1998). So,
if individual regulation of learning is not easy, what happens when learners need
to construct knowledge in collaboration with other people? Today, regulating
learning is rarely a solitary task. There is increased pressure for active motivation
and emotion regulation in shared learning situations because of complex
interactions in changing learning contexts (Järvelä, Volet, & Järvenoja, 2010); for
13
example, study groups, work teams, or social networks require increased
collaborative competence (Scardamalia & Bereiter, 2006).
To conclude, the need to study the motivational and affective processes active
in social learning situations has been recently acknowledged in two separate
fields of research: motivation and self-regulated learning and collaborative
learning. First, in studies on motivation and self-regulated learning, there is an
increased focus on understanding motivation regulation processes in a social
context (Hadwin, Järvelä, & Miller, 2010; Nolen & Ward, 2008). “Social” is
making its way from a peripheral variable that affects individual motivation to an
essential component of the motivation to learn (Järvelä & Volet, 2004; Turner &
Patrick, 2004; Volet, Vauras, & Salonen, 2009; Walker, 2010). To accomplish
their aims, researchers have formulated new, open-minded questions, and strive to
answer them with innovative methodological choices and approaches.
Second, in collaborative learning research, there is an emerging trend toward
theorizing the conditions for collaboration (Crook, 2000; Dillenbourg, 1999;
Krejns, Kirchner, & Jochems, 2003). Theoretical discussions, supported by the
results from empirical studies have stressed the critical role of motivational and
emotional processes in successful collaboration (Dillenbourg, Järvelä, & Ficher,
2007; Häkkinen & Järvelä, 2006). Overall, in recent work on collaborative
learning, there is growing support for the claim that regulation and control of
emotions and motivation are critical for successful learning and collaboration.
The object of this dissertation is to investigate the regulation of motivation and
emotions in social learning contexts. That is why this dissertation is interested in
answering questions such as: What kind of challenges do students experience in
collaborative learning? And, how are students able to activate motivation and
emotion regulation in these social learning contexts and in groups? The first
objective of the dissertation study is to investigate the regulation of motivation
and emotions as it emerges in collaborative learning situations. The second
objective is to develop situation-specific methods for collecting data in these
situations. The dissertation addresses the challenges in methodology that result
from investigating socially constructed regulation of motivation and emotions.
The focus, especially, is on developing an instrument that can capture the social
nature of regulation during real learning contexts.
The results show that students experience a variety of emotional and
motivational challenges while learning. To overcome these challenges in social
learning situations, students employ both individual and socially shared regulation.
Through the shared regulation processes, group members can co-construct their
14
motivation together. Furthermore, in this dissertation, an ”Adaptive Instrument
for Regulation of Emotions” (AIRE) was developed and tested. Even though the
AIRE still needs further development, the results from implementing the
instrument in real learning tasks have already shown its advantages in collecting
data from group members and proven that students experience socially shared
regulation.
Accordingly, this dissertation contributes to an on-going discussion about the
theoretical relationship between the individual and social in motivation to learn as
well as the dynamic nature of motivated learning (e.g., Martin, 2007; Nolen &
Ward, 2008; Turner & Patrick, 2008; Järvelä & Volet, 2004; Volet, Vauras, et al.,
2009). It is argued that learners’ adaptation to social learning situations requires
cognitive, motivational, and socio-emotional skills that are often more
challenging than those used in more conventional and well-structured learning
situations (Järvelä, Hurme, & Järvenoja, 2010; Winne & Perry, 2000).
The dissertation consists of two parts. The first part grounds the theoretical
framework. It introduces and portrays the theoretical basis for the main constructs,
motivation, emotions, and self-regulated learning. The constructs are first
elaborated from perspective of individual learning. After that the elaboration is
expanded on social learning situations, especially on collaborative learning. The
first part also describes how, in this dissertation, motivation is approached from a
situative perspective. It presents the background and need for methodological
solutions that have been developed and implemented in this dissertation. This part
also introduces the specific aims and includes an overview of five original articles.
The first part concludes with the main results and discussion. The second part
includes five original articles published in international peer-reviewed journals.
These five articles constitute the body of this PhD dissertation work.
15
16
2
Theoretical framework
When are people curious or excited to learn new things? Or when do they feel
bored or anxious? How do they cope with feelings of hopelessness when faced
with a problem that seems too difficult or complex? And, do people feel relief or
pride when, after investing effort, they manage to complete a difficult task? There
is considerable anticipation and wariness associated with learning, and how
individuals deal with these feelings indicates their motivation to learn and ability
to regulate the learning process—from their initial thoughts to the final reflections
on their success.
Motivation and self-regulated learning research focus on investigating the
mechanisms through which motivation affects learning and performance. The
motivation to learn can be described as a student’s tendency to see the activity as
meaningful, worthwhile, and beneficial (Brophy, 2008). Interest and motivation
affect a student’s ability to learning anything new. The will or volition to put to
use previously learned skills, strategies, and knowledge affect students’
performance. Learning and performance are not, however, only a matter of will.
The research on the role of emotions and motivation for learning has led to
numerous definitions and theoretical perspectives, which explain the complexity
of the nature and operation of motivation and emotions in learning. Despite the
varied and profound theories, there are, however, many aspects of individual
motivation to learn that researchers focusing on the individual are not able to
explain comprehensively.
In his review of the history of motivation research in education, Weiner (1990)
predicted the future direction of the research. He emphasized two issues: how
motivation influences affective experience (among some other variables) and how
the concept of motivation is linked to the self. The first issue is considered by
stating that educational psychologists must consider the impact of motivation
extensively. This means that motivation is not only influenced by and affecting on
the cold cognition of cognitive processing, reasoning, and problem solving.
Motivation to learn also involves the hot cognition of experienced emotions and
personal interest (Pintrich, Marx, & Boyle, 1993). The hot and cold processes are
deeply intertwined in learning and mediated through motivational beliefs and
processes. With regard to the second issue about the “self,” Weiner speculates on
the problem of a “psychology of the individual.” From the motivation research
point of view, researchers discuss the “general motivation of an individual.” In
research on motivation to learn, an emerging trend is to examine motivation as
17
situation and domain specific (Nolen & Ward, 2008). To identify the composition
of an individual’s motivation in different situations, it should be considered within
the context of social values and the goals of the individual. Motivation to learn
does involve personal dispositions but needs to be (re)constructed and maintained
constantly in learning situations (Volet & Järvelä, 2001). Furthermore, social
aspects do not only influence individuals’ motivation to learn. Motivation is also
created and maintained within a social context and cannot be divorced from the
social fabric. That is, motivation in social learning situations can be
conceptualized as socially co-constructed (Järvelä, Volet, et al., 2010).
Today, the issues Weiner (1990) highlighted as the future direction of
motivation research have emerged as an area of interest for researchers in the field.
Many researchers aim at stressing the interdependence of motivation, emotions,
and cognitions, especially at the theoretical level (e.g., Boekaerts & Corno, 2005;
Brown, 1988; Dweck, Mangels, & Good, 2004; Hickey, 1997; Järvelä, 2001;
Lazarus, 1991, Linnenbrink, 2006; Zimmerman, 2008). Different paradigms, such
as socio-cognitive, sociocultural, and situative approaches, have brought new
perspectives under discussion, stressing the agentic role of learners (Bandura,
2001), the meaning of context (Volet & Järvelä, 2001), and the social nature of
human learning (Levine, Resnick, & Higgins, 1993; Palincsar, 1998). However,
often in empirical studies, one aspect, such as individual or group, is emphasized
at the expense of the others (Meyer & Turner, 2006). A need for research that
genuinely integrates motivational and emotional processes with the social context
and recognizes the situational nature of the learning process is evident. The
situative approach can bring theoretical principles and educational practices
closer because it focuses on authentic problems within real-life learning situations
(Boekaerts & Cascallar, 2006).
This dissertation aims to contribute to the research on motivation by
addressing the regulation of motivation and emotions in the social context.
Motivation to learn is not seen as a static and stable state of mind, but an active,
changing process. In this dissertation, motivation and emotion regulation are
believed to provide an approach to motivation that considers motivation as an
active, constantly re- and co-constructed activity. That is why motivation to learn
is studied as a part of the active process of self-regulated learning. Skilful learners
can be seen to possess “motivational skills,” which they implement to regulate
their motivation and emotions in complex learning settings. These motivational
skills are not static individual characteristics, but adaptive actions that can be
learned, practiced, and applied by regulating emotion and motivation. Regulation
18
of motivation and emotions is always situated into a certain moment and context,
and how the regulation of the learning process succeeds in different situations can
vary irrespective of individual motivational dispositions.
2.1
Emotions and motivation in learning and performance
Research in academic learning settings has indicated that many difficulties faced
by learners in a variety of learning contexts and situations are related to the noncognitive aspects. These non-cognitive reasons can lead to situations where
perfectly capable learners never engage in cognitive processes or give up easily,
even when they possess sufficient knowledge and skills to complete a task.
Learning does not involve only cognitive skills and operations but also includes
aspects of how students feel about learning. Students are more likely to pay
attention, concentrate, invest effort, and be persistent when learning is related to
their personal interest (Hidi & Ainley, 2008), and when it elicits appropriate
emotions (Schutz & Pekrun, 2007). But then intense dissonant emotions can
easily distract students’ attention and shift their focus away from academic tasks.
2.1.1 Emotions
The operational definition of emotions describes them as short, intense reactions
to something, usually directed toward an object or achievement. The valence of
these emotional experiences can vary, in that the reaction can be positive, such as
joy, excitement, or hope, or negative, such as boredom, anxiety, or anger. The
intensity and duration of these emotional experiences can change, but when the
intensity decreases or the duration increases considerably, the experience can be
better described as a mood or even an affective state than an intense emotional
experience. Hence, emotions can be differentiated from moods, which are less
intensive, long lasting, and more non-specific than emotions, and from affective
traits, which are stable emotional dispositions (Frijda, 2005; Goetz, Zirngibl,
Pekrun, & Hall, 2003). While research on intense emotional experiences focuses
on identifying and naming specific emotions and their functions, research on less
intensive emotional experiences often concentrates on a negative-positive valence
of the feelings or affective state (Linnenbrink, 2006; Schutz & Pekrun, 2007).
This is rational, because mood and affective state are usually more diffused and
unfocused than emotions. The relationship between a short intense emotional
experience and a longer lasting and more stable mood or affect is, however,
19
reciprocal. Moods and affective state are present when situational emotions are
experienced. Individuals’ emotional state of mind has an impact on how they
experience and interpret the situation, how they will be aroused by situational
circumstances, and what type of intense emotions they will experience.
Academic emotions are feelings that derive from a special source in an
academic context. In learning situations, the emotions experienced can derive
from a source that is directly associated with one’s personal interest, learning task,
achievement, or context. Alternatively, the source of emotional experience can be
external to the academic context. Emotions experienced in academic settings can
also be social in nature as they relate to interpersonal interaction, and they may
also occur within groups as “collective emotions” (Andersen & Guerrero, 1998;
Geen, 1991; Goetz et al., 2003). There is a growing number of researchers who
study students’ emotional experiences in academic context as well as the
relevance of these experiences in learning and performance (Linnenbrink, 2006;
Turner, Meyer, & Schweinle, 2003).
Research on academic emotions, from the educational psychology
perspective, has mainly implemented correlational and experimental studies and
focused especially on studying anxiety in academic test situations (Covington &
Omelich, 1987; Schutz & Davis, 2000). In these studies, the researchers have
consistently reported a correlation between low achievement and a wide range of
anxiety measures. Other studies also exist that focus on some other specific
emotion(s), such as shame, boredom, wellbeing, or anxiety, and the correlations
between the experience of these emotions and academic achievement within a
specific domain (Hascher, 2003; Laukenmann et al., 2003; Turner, Husman, &
Schallert, 2002). In situation-specific qualitative studies, researchers have
targeted the more intense and fine-grained relationship between emotions and
other aspects of the learning process (e.g., Meyer & Turner, 2006). Until today,
however, it is still unclear which emotional experiences would be optimal for
students’ learning on the one hand and for their well-being on the other. Arousal,
for example, has been shown to be beneficial for the quality of performance when
the level of the emotional experience is optimal, but if the level of arousal is too
low or high, it can hinder learning (Woolfolk, Winne, & Perry, 2004). The
appropriate level is not stable but depends on the circumstances of the learning
situation, such as the learning task, situation, and context.
20
2.1.2 Motivation
The emotions experienced, the level of emotional arousal, the classroom structure,
and the emotional atmosphere within a classroom as well as the interaction
between learners all contribute to the motivation to learn (Meyer & Turner, 2006).
Motivation can be defined as an internal state of mind, a thought that arouses,
directs, maintains, hinders, or inhibits behavior. Contemporary theories and
models clearly define and explain the individual motivation and are much more
precise than the ill-defined early views on motivation, which relied on
philosophical considerations of the mind and were considered to deal with inner
forces, instincts, or behavioral responses to stimuli. For example, the will (or
motivation) was a reflection of an individual’s desire and volition to perform
concrete acts to fulfill these desires. Today, the construct of motivation includes
several motivation theories, such as attribution theory (Weiner, 1985), theories
about self-efficacy (Bandura, 1997), goal theories (Pintrich, 2000b), volition
(Corno, 1994), and models of interest and affect (Schutz & Pekrun, 2007), which
address people’s motives to learn, explain their efforts toward learning certain
subjects, and capture the quantity and quality of these efforts (e.g., self-efficacy
beliefs, goal orientations, or attributions). The theories are also used to explain
how certain motivational dispositions are developed and what makes some
learners persistent in the face of difficulties while others give up more easily.
Because many of the motivational concepts are rooted in experimental
psychology, they have originally focused on the self while the contextual aspects
have been sidelined (Weiner, 1990; Volet & Järvelä, 2001). Contemporary
research, however, perceives that motivation is formed from both the general,
enduring traits of a student, such as goal orientations and sets of beliefs, and
situation-specific motivational states, such as emotional arousal or motivation
regulation. In other words, situation-specific motivational states are
contextualized reactions and interpretations of the current situations and can vary
from situation to situation. Today, many researchers are interested in studying
how motivation is influenced, developed, and constructed within these learning
contexts and situations. The focus is on the reciprocal relationship between
individual motivation and schools, classrooms, family, peers, community, culture,
etc. (Meyer & Turner, 2006). Furthermore, researches that adopt the situative
approach (Nolen & Ward, 2008) stress how motivation is a situational construct
and an active process that is constructed and shaped through participation and
21
collaboration with others. This dissertation adopts this situative approach to study
emotions and motivation in social learning context.
Overall, individuals’ emotions and motivation are formed at the interface of
personal, contextual, and social aspects (Ainley & Hidi, 2002; Nolen & Ward,
2008; Turner, 2001; Volet & Järvelä, 2001). Thus, emotional and motivational
structures do not exist outside of context, but they are bound to and constructed
within that context. They emerge through interactions and change over time and
situations. And, most importantly in terms of successful learning, emotions and
motivation are essential aspects of a constructive self-regulated learning process.
This means they can be shaped, redirected, or changed – essentially regulated –
during the process of learning.
2.2
Self-regulated learning
Today, there is a large and diverse body of research on self-regulation from
different areas of psychology. Protecting “self” against threats influence
individuals in many situations and areas of life. Early self-regulation research
focused on therapeutic contexts as well as personality or social psychology
studies (Boekaerts, Pintrich, & Zeidner, 2000; Scunk & Zimmerman, 2008). The
concept of self-regulation is also used in organizational and health psychology.
Together in all these fields exists a number of self-regulation constructs, such as
self-management or self-control that are related but differ somehow from each
others. Also educational psychology has been involved in researching selfregulation. Self-regulated learning is an important field in the research on
academic learning and achievement (Boekaerts et al., 2000).
Successful self-regulation related to academic studying and learning is a
combination of cognitive skills, will, and self-control that make their learning
easier (Schunk & Zimmerman, 2008). Self-regulated learners can put into use
their knowledge, motivation, and volition to set learning goals, assess their
progress toward a goal during the learning process, and adjust their goals if
necessary. They plan their actions according to their goals, implement appropriate
learning strategies in varying learning situations, and adjust these strategies if
they seem to be insufficient. Successful self-regulators also monitor their
motivation, are persistent, and apply motivation regulation strategies in order to
sustain their motivation and goal-oriented actions. They control their emotional
state, adapt to the surrounding environment to better support their goal striving,
and seek help when needed. Thus, the construct of self-regulated learning (SRL)
22
integrates cognitive, motivational, emotional, social, and behavioral theories and
concepts, and can also acknowledge cultural and contextual aspects that influence
learning and performance (Boekaerts et al., 2000). Furthermore, most of the
models of SRL include the basic assumption that learning is primarily a process,
not just a result, which is composed of varying combination of static individual
characteristics and skills that contribute to the performance.
While the recent definitions and models of SRL seem to recognize cognition,
motivation, emotions, and social factors as important to the process, they still
differ somewhat in their definitions of self-regulation. This means that the
emphasis on emotional and motivational processes varies according to the SRL
model. This is because different models consider self-regulated learning in their
own terms, emphasizing different aspects and sub-processes, such as cognitive
learning strategies (Paris & Paris, 2001), metacognitive processes (Winne &
Hadwin, 1998), motivational goal orientation (Pintrich, 2000b), or well-being
(Boekaerts & Corno, 2005). Nevertheless, all contemporary models divide the
SRL process into phases, during which each has a different focus. Furthermore, in
all the models, emotions and motivation are recognized as an essential dimension
of SRL regardless of the actual emphasis given to these processes (Zimmerman &
Schunk, 2008). Figure 1 presents one possible outline of the SRL process. In this
outline, the different phases are relative to the learner’s goals. Also, in each of the
phases, certain emotional and motivational aspects are especially influential.
23
Fig. 1. An outline of the self-regulated learning process
The development of SRL research in the 1990s started with studies focused on
cognitive processes that learners use to activate and sustain goal-oriented learning.
These studies produce valuable information about cognitive functioning, which
was then used in intervention studies, in which the aim was to develop students’
self-regulation skills and improve poor students’ deficient control over their
learning processes (Zimmerman & Schunk, 2008). Many of these intervention
studies produced successful outcomes, but the challenge in these studies was that
the desired processes did not always transfer to less-structured learning situations.
Lately, researchers have focused also on motivational aspects that contribute to
self-regulation, such as goals (Fryer & Elliot, 2008), self-efficacy, beliefs (Pajares,
2008), and interest (Hidi & Ainley, 2008). Currently, there exists a solid body of
research on how various motivational concepts are involved in students’
regulation of cognition, motivation, and affect.
24
The SRL model proposed by Pintrich (2000a) lays a strong emphasis on
motivational aspects. In his model, students’ motivation is considered as a
necessity for engaging in self-regulated learning. Motivation and affect are
considered one of the four areas that require students’ regulation, the other areas
being regulation of cognition, behavior, and context. In this model, together with
the area of cognitive regulation, motivation plays a strong role in successful selfregulated learning. The four areas are regulated in four phases (see also Figure 1).
These phases consist of a forethought phase, a monitoring phase, a control phase,
and a reflection phase. In terms of the motivation and affect area in the
forethought phase, students make judgments of their efficacy and ability based on
motivational self-beliefs. They evaluate their interest and the value of the learning
task. Based on these motivational criteria, they set goals that fit their goal
motivational preferences and goal orientation. The monitoring and controlling
phases are intertwined and include awareness and observation of motivation and
the progress of goal-oriented work. When necessary, students select and adapt to
the appropriate emotion and motivation regulation strategies to influence their
motivation and to maintain, shape, or redirect goal-oriented work. They can also
re-evaluate and change the choices they have made and committed to in the
forethought phase. Finally, in the reflection phase, students make causal
attributions based on their success, efficacy, and abilities, judged from their
evaluations of the performance and achieved outcomes as against their goals. In
Pintrich’s model, motivational structures and beliefs are involved in every phase
and play an important role in how students react to learning tasks and employ
self-regulation strategies.
In contrast to Pintrich’s SRL model, which is clearly focused on academic
performance, the model proposed by Boekaerts and her colleagues (e.g.,
Boekaerts, 2007; Boekaerts & Corno, 2005) is founded on a wider perspective,
where academic performance is seen only as one of the possible motives that
students consider in learning situations. This model views self-regulated learning
as adaptable, in that during every learning situation, students evaluate the
circumstances also in terms of their personal well-being. In new learning
situations, the students make general appraisals of the situation, and the outcomes
of these appraisals lead them to choose either a growth pathway (top-down) or a
well-being pathway (bottom-up). When engaging in the growth pathway, students
choose to focus on learning, in that it refers to activities related to expansion of
personal knowledge and mastery over the learning process. In the well-being
pathway, students concentrate on activities that are aimed to protect their well25
being and to prevent negative emotions. Students on the well-being pathway
concentrate on coping in stressful situations, often at the expense of learning. All
in all, Boekaert’s model draws attention especially to the meaning of strategic
emotion regulation by highlighting the role of emotions in successful selfregulated learning.
Despite the varying focus on different sub-processes or the emphasis on
certain variables, the strength of many self-regulated learning models is that they
see learning as a whole system, where different aspects influence the entity
(Zimmerman & Schunk, 2008). At its best, it integrates the knowledge of
different sub-processes, and thus can be a powerful way to explain students’
learning processes and provide practical solutions to support students’ selfregulation skills. One example of applying a self-regulation framework for
supporting students’ development of self-regulation in practice is the gStudy
learning environment, which is designed specifically to prompt cognitive selfregulation (Winne, Hadwin, Nesbit, Kumar, & Beaudoin, 2005).
In this study, the self-regulation framework offers the possibility to study
motivation as an active process. This means that motivational state and arousal of
emotions are different from active process of regulating them. Through the
process of self-regulation, students themselves can influence their emotional
experiences or motivation instantaneously by regulating, for example,
motivational goals, situational emotions, and self-efficacy in social learning
contexts. That is why this chapter explains in greater detail the regulation of
motivation and emotions during the active phase of learning. This does not imply
that other phases, such as goal commitment or evaluation, are not as important a
part of the self-regulation as the actual executive phase; instead, this chapter
acknowledges the sub-process on which the dissertation is focused.
2.2.1 Regulation of emotions and motivation
Self-regulated learning can offer a suitable framework for considering emotions
and motivation as an active and situated process, which can be studied as a
dimension of self-regulation. The interest in the relationship between a certain
motivational construct and self-regulated learning has inspired many researchers
to provide theoretical and empirical evidence about the role of motivation for
(un)successful self-regulation and learning. In recent years, researchers have
published papers on self-efficacy, achievement goals, and goal orientation,
perceptions of the task difficulty and value, interest, emotions, and self-regulation
26
(Pintrich, 2004; Schunk & Zimmerman, 2008; Schutz & Pekrun, 2007). These
researches have evidenced the essential and intertwined relationship between
motivation and its components and self-regulated learning.
The regulation of motivation differs conceptually from motivational
constructs dealing with learners’ various beliefs and attitudes toward subjective
control of choice, effort, and persistence (Kuhl, 1985). First, a distinction can be
made based on the level of awareness of students’ motives and actions (Wolters,
2003). Motivational beliefs can be seen to affect students’ learning process,
whether or not they are conscious of these beliefs, whereas self-regulation
processes are always considered intentional (Zimmerman & Schunk, 2008).
Furthermore, regulation of motivation is a process that is realized through
strategic actions and active control. In other words, regulation of motivation
refers to “the activities through which individuals purposefully act to initiate,
maintain, or supplement their willingness to start, to provide, work toward, or to
complete a particular activity or goal” (Wolters, 2003, p. 190) whereas
motivational beliefs contribute to the will and reason to start and achieve
something. Interpretations of success in the process of regulation influence
students’ motivational beliefs. Consequently, even though the concepts are
distinct from each other, students’ motivation and motivation regulation are
deeply interrelated (Järvelä, Järvenoja, & Veermans, 2008). The difference
between motivation and regulation of motivation is especially clear in the modern
theory of volition in which commitment and purposive striving are separated from
each other (Corno, 2001). Motivation leads to goal commitment but the followthrough of this commitment often requires volition, in other words regulation of
motivation (Kuhl, 2000). In the models of self-regulation, these motivational
aspects are usually built-in as internal, and hence, inseparable elements of the
process. The focus on regulation of motivation has provided us with a processoriented approach to study this situational motivation in context and to recognize
students’ active role in shaping their motivation.
Research has specified several motivational activities and motivation
regulation strategies or volitional control strategies that contribute to the selfregulated learning process in different phases of learning (Boekarts, 1996; Corno
& Kanfer, 1993; McCann & Garcia, 1999; Pintrich, 2004; Wolters, 2003). In
addition to the regulation of motivation, volitional control also includes the
regulation of emotions as well as controlling some other aspects that affect the
process of learning. This is consistent with models of self-regulated learning
where strategies that target the regulation of emotions have often been
27
conceptually included in the motivation regulation process (Pintrich, 2000a;
Wolters, 2003) although some models treated the two as conceptually separate,
though inter-related processes (Schutz & Davis, 2000). Despite the conceptual
categorization of these strategies, the aim of the specific actions and tactics,
categorized as regulation of motivation and emotions, is to regulate the
motivational beliefs, affect, and emotions that are activated to maintain
commitment during learning when faced with external or internal distractions and
obstacles. In practice, they can include various tactics attempting to affect
purposes for completing the task, beliefs of one’s own competence as well as
importance or relevance of the task, or purely coping with negative emotional
experiences.
Researchers have introduced many practical descriptions of concrete actions
considered as regulation activity, such as students promising themselves a
concrete reward in order to enhance extrinsic motivation (Corno & Kanfer, 1993)
or turning a boring task into a game to increase interest in the task (Sansone, Weir,
Harpster, & Morgan, 1992). One way to classify these concrete realizations of
motivation and/or emotion regulation activities is to organize them according to
the purpose or aim of certain actions, as has been done by Wolters (2003), who
reviewed several studies on motivation and emotion regulation strategies for this
categorization. According to Wolters, strategies that aim to maintain engagement
and persistence in learning by identifying or permitting extrinsic rewards or
punishments, whether concrete or mental, can be called self-consequating
strategies. Examples of the use of these strategies are situations where a student,
when studying for a test, promises herself or himself a new outfit or candy if the
performance is good enough. An opposite example could be a situation where a
student promotes his or her motivation in the same situation by denying herself
something if the test doesn’t go well. The first example is an example of a
rewarding strategy whereas the latter is an example of self-punishment. Research
on these strategies indicates that rewarding oneself can be an effective method to
encourage persistence. High achievers, for example, have been known to use
these types of strategies (Zimmerman & Martinez-Pons, 1990).
Strategies that focus on intensifying goals associated with an academic task
are classified as goal-oriented self-talk (Wolters, 2003). These strategies aim to
clarify the reasons for persisting or completing the task through thoughts or
statements. In other words, the students who use goal-oriented self-talk strategies
highlight the importance of the task for themselves while they are engaged in a
task. They can, for example, look for connections between the task and their
28
career plans, to confirm how important it is to understand the issues they are
dealing with, or imagine how satisfying it would be to get high grades or perform
better than others. Wolters (1998) argues that this type of strategy can be
associated with students’ achievement goals.
Strategies classified as interest enhancement aim to increase intrinsic
motivation, immediate enjoyment, or the situational interest students experience
while completing an activity. Strategies classified as efficacy management refer to
students’ ability to monitor, evaluate, and purposefully control their own
expectations, perceptions of competence, or self-efficacy for a task. According to
Wolters (2003), strategies that represent the first type are concrete attempts to
make the learning more interesting or less boring. This may mean adding some
kind of twist to a repetitive task, making the task funnier, or turning it into a game.
For example, in a study by Järvenoja, Hurme, and Järvelä (2004), students
solving a boring math task increased situational interest by mentally replacing a
ball with a human head when the task required them to count the volume of a ball.
The second type, efficacy management, involves strategies that aim at
purposefully controlling one’s own expectations, perception of competence, or
self-efficacy for task. This may mean, for example, setting proximal (sub)goals
for learning or engaging in thoughts or statements that encourage them with the
ongoing task.
Wolters (2003) also includes control of attributions and self-handicapping to
his categorization. The empirical evidence of students’ ability to manipulate their
causal attributions is still rare. However, it can be argued that students, who are
able to purposefully channel causal attributions during self-regulated learning and
hence positively shape their situational motivation, are engaging in strategic
activity. Students may, for example, emphasize their possibilities to influence and
control the learning task or their personal responsibility of good outcomes in
order to increase their volition and persistence for completing the task. But then,
these causal attributions can also be manipulated so that it negatively affects the
students’ sense of personal influence and effort and hence, decreases motivation.
In this case, it can be seen as a self-handicapping strategy. There are other
examples where students decrease their own possibility to succeed, such as when
they postpone studying for the test until the last minute (Urdan & Midgley, 2001).
These types of strategies can rather be seen as emotion regulation, aiming to
protect students from negative emotional experiences, even though they
negatively affect students’ motivation as a consequence. Hence, self-handicapping
strategies that have a negative impact on the motivation to learn can be
29
convenient for students’ broader well-being in their lives (Boekaerts & Corno,
2005). Defensive pessimism, which Wolters (2003) includes in efficacy
management, is another example of strategic activity that targets well-being at the
expense of learning. For example, learners who spend more time on imagining
what could go wrong instead of focusing on a task, prepare themselves
emotionally for a failure but reduce their capacity invested in learning.
The purpose of emotion regulation strategies is to manage feelings and
emotional reactions that may disrupt learning (Corno & Kanfer, 1993; Lazarus,
1991). Emotion regulation strategies are used to cope with stressful situations,
reduce negative affective responses in learning situations, and control harmful
emotional experiences associated with performance. There may be as many
specific emotion regulation strategies as there are people who use them. Strategies
such as slowly counting to ten, imagining positive things that are related to
academic activities, or just concentrating on breathing are a few examples of the
strategies most people have employed when they need to control anxiety, anger,
or frustration. However, regulation of emotions may not always focus on
controlling negative emotions, since there may be also a need for strategies
intended to control positive emotions that disturb academic functioning, such as
over-enthusiasm. Furthermore, there are studies that show that the use of emotion
regulation strategies can be problem- or task-focused, but they can also be
avoidance-focused and used to escape from emotionally unpleasant situations at
the expense of learning and performance (Op't Eynde, De Corte, & Verschaffel,
2007). Hence, emotion regulation can focus on ensuring the appropriate
motivation to learn or, instead, restore emotional well-being (Boekaerts & Corno,
2005). When the use of a particular emotion regulation strategy aims to ensure a
favorable atmosphere and adequate effort for completing an academic task it is, in
fact, a strategy for regulating motivation (Wolters, 2003).
Finally, environmental structuring can be classified as a motivation regulation
strategy, if the aim of the action is to decrease possibilities for off-task behavior
and, hence, maintain or “defend” motivation and goal-oriented work. This can be
done by reducing the probability to encounter distraction before it interrupts the
work or after it has been interrupted. For example, the student can close a window
before starting to do homework to avoid being distracted by voices and noise
outside.
What combines all these different types of strategies and what defines them
as motivation and/or emotion regulation is the intended purpose of these actions,
that is, to ensure motivation and focus to complete the academic task by
30
controlling emotions and/or to maintain or redirect motivation during the learning
process. Hence, regulation of motivation and emotions can be realized through
cognitive or behavioral actions, or it can happen internally without any noticeable
signs (except of the learning process that continues), such as efficacy self-talk.
Because many emotional and motivational processes are internal, without any
directly observable activity, empirical studies have often been forced to rely on
either students’ own interpretations or circumstantial evidence. Only little is
known about how students regulate their motivation and emotions in real-life ongoing learning events, even though in previous empirical studies, regulation of
motivation and emotions have been found essential for self-regulated learning
(Hadwin, Boutara, Knoetzke, & Thompson, 2004; Schutz, Hong, Cross, & Osbon,
2006).
The last part of this chapter will first focus on emotions and motivation in
collaborative learning contexts. In this dissertation, it is assumed that in social
learning situations motivation and emotion regulation processes can become
visible, for example in dialogue. The aim is to target the central aspect of this
dissertation: the nature and form of regulation processes in group learning
situations. That is why this chapter concludes with the elaboration of socially
constructed regulation processes, which complement both conventionally
individually focused self-regulation discussions and discussions about motivation
as a social phenomenon (Nolen & Ward, 2008).
2.3
Motivation and emotions in collaborative learning contexts
Many researchers have discussed the beneficial effects of group processes and
social interaction for learning, and these advantages are utilized in several
educational approaches and pedagogical designs (Krejns et al., 2003; Light,
Littleton, Messer, & Joiner, 1994). One of them is the collaborative learning
approach, which aims to design and implement learning tasks for groups of
learners who form a social entity and solve problems and complete tasks together
(Dillenbourg & Traum, 2006; Resnick, 1991). At its best, collaborative learning
combines the many advantages of individual and social processes, which can
contribute to group members’ engagement and motivation, ultimately resulting in
better performance (Jones & Isroff, 2005). The main idea in collaborative learning
is that by means of collaborative knowledge construction, co-ordination of
different perspectives, commitment to joint goals, and shared evaluation of
31
collective activities, a group creates something that exceeds what any one
individual could achieve alone (Roschelle & Teasley, 1995).
Genuine collaborative learning processes, however, are not as frequent as
could be expected. Learning through collaboration is not something that just takes
place whenever learners with adequate cognitive capacity come together.
Empirical studies have shown that while members of a group may co-operate, the
group itself, as a social entity, does not always follow the mutually shared
cognitive and social processes of collaboration (Barron, 2003; Järvelä &
Häkkinen, 2002). In any joint venture, team members need to be committed to a
shared goal, on-going negotiation, and to the joint monitoring of progress and
achievement. This involves cognitive, motivational, and emotional engagement.
However, in collaborative learning research, very few studies have explicitly
addressed motivation and emotions (Dillenbourg et al., 2007). Rather, their role in
hindering or supporting collaboration processes have emerged from the data as an
outcome and a possible explanation for certain type of group dynamics. These
indications about the critical role of motivational and emotional processes for
successful collaboration suggest that there is a need in collaborative learning
research to focus on details for the emotional and motivational conditions for
collaboration (Järvelä, Hurme, et al., 2010; Van den Bossche, Gijselaers, Segers,
& Kirchner, 2006).
The social context is both a source of emotional reactions and motivation for
individuals (Dowson & McInerney, 2003; Isaac, Sansone, & Smith, 1999;
Järvenoja & Järvelä, 2005). This dissertation especially focuses on emotional
conditions affecting the motivation to learn and collaborate. In interpersonal
contexts, many emotional reactions are social in nature as they relate to
interpersonal interaction, or include considerations of other people or social
norms (Andersen & Guerrero, 1998; Goetz et al., 2003; Hareli & Weiner, 2002).
Both negative and positive emotions experienced within the group can derive
from multiple sources that can relate to other contexts and areas of lives of the
individual group members, their personality differences, or the dynamics and
processes experienced within the collaborative group (Karabenick, 2003;
Mäkitalo, Häkkinen, Järvelä, & Leinonen, 2002; Järvenoja, Volet, & Järvelä, 2010;
Van den Bossche et al., 2006; Volet & Mansfeld, 2006). In any case, the group
faces these socio-emotional benefits or challenges as they unfold. Group members
interpret the situation from their own point of view based on their experiences and
affective state, which then shapes how they contribute to the collaboration and
how they construct group dynamics. Furthermore, how others react and create a
32
social environment leads individual members to make interpretations of the
situation, of the group, and of the motivation within the group. In other words, the
group interactions and socio-emotional dynamics within the group will influence
and shape individual group members’ motivation. The individual interpretations
can be positive and thus lead to increased motivation in group activities;
alternatively, they can be negative and lead to de-motivation and withdrawal.
The socio-emotional experiences and group members’ interpretations give
rise to unique group dynamics and situational motivation. The meaning of social
aspects as the source of both individual emotional experiences and groups’ shared
emotional experience is especially clear in settings that highlight interaction and
reciprocity. In consequence, when aiming for true collaboration with shared
understanding, it is likely that conflicting views emerge and put emotional
pressure on individuals in a group to restore well-being and motivation.
Furthermore, these socio-emotional challenges can compromise or undermine
wellbeing and the benefits of collaborative, goal-directed group work as an entity
(Boekaerts & Corno, 2005; Vauras, Salonen, & Kinnunen, 2008).
Together, groups can face multiple types of situations where collaboration
and task completion is compromised or endangered (e.g., Blumenfeld, Marx,
Soloway, & Krajcik, 1996; Bosworth & Hamilton, 1994; Burdett, 2003; Pauli,
Mohiyeddini, Bray, Michie, & Street, 2008; Salomon & Globerson, 1989; Webb
& Palincsar, 1996). A clash of individual viewpoints and interpretations of the
situations or task requirements can lead to conflicts and negative emotional
arousal. To overcome these challenges, group members are forced to exercise
control over their emotions, their motivation, and sometimes their social
environment to be successful with learning and interaction. These regulatory
processes aim to address a variety of distractions and disturbances, which may
interrupt the activity, so that motivated, productive engagement can be maintained.
Given the challenging nature of most group activities, the strong regulation
strategies to control emotions is often needed from all the group members for
continued productive engagement toward goal achievement (Frydenberg & Lewis
2002; Järvenoja & Järvelä, 2005; Wolters, 2003).
In addition, social learning situations, and especially collaborative learning,
call for group level emotion regulation (Järvenoja et al., 2010). Collaborative
learning groups are social systems, where beliefs about and (inter)actions in the
interpersonal context affect the groups’ learning. Individuals and social context
are considered as inseparable and mutually constitutive (Nolen & Ward, 2008).
When motivation is constructed together through interactions and shared
33
regulation processes, it can be conceptualized as co-constructed among group
members (Greeno, 1997; Järvelä, Volet, et al., 2010; Vauras et al., 2008). This
exceeds the conceptualization where motivation is considered as a characteristic
of individuals and influenced by others or the context.
2.4
Different forms of regulation of motivation
Conventionally, socio-cognitive self-regulation theories have focused
predominantly on the individual. Recent discussions, however, have shifted the
emphasis toward socially constructed (self)-regulated learning (Hadwin, Oshige,
Gress, & Winne, 2010). This extension is argued to be critical for understanding
productive engagement and participation in real-life learning environments and
social learning situations (Hadwin & Järvelä, 2011; Järvelä et al., 2008; Kempler
& Linnenbrink-Garcia, 2007; Patrick, 1997). This is not to say that social aspects
and influence for self-regulation has not been recognized before. Socio-cultural
and also socio-constructivist approaches, on the one hand, and a developmental
psychology approach, on the other hand, have, for example, studied the process of
co-regulation.
To outline how motivation and emotions are regulated in socially shared and
collaborative learning contexts, one of the main aims of this dissertation has been
to conceptualize different forms of regulation in the social, interactive learning
settings. Researchers have used varying definitions and constructs when social
aspects of regulation has been studied, such as self-regulation (Zimmerman,
2000), other-regulation, co-regulation (McCaslin & Hickey, 2001; Volet,
Summers, & Thurman, 2009), communal regulation (Jackson, MacKenzie, &
Hobfoll, 2000), social self-regulation (Patrick, 1997), or shared regulation (Iiskala,
Vauras, & Lehtinen, 2004; Järvenoja & Järvelä, 2009; Volet, Summers, et al.,
2009). In this dissertation different forms of regulation have been classified based
on the intended target and motive for engaging in the regulation process. More
specifically, this implies that in social learning situations, students can engage in
individual forms of regulation, where the aim is to ensure individual’s own
successful learning regulation, and socially shared forms of regulation, where the
aim is to ensure successful group work. These parallel processes are not exclusive
from each other, but they can be used together, in co-ordination. Furthermore, the
ultimate motive of the processes that appear to be some form of regulation is not
always obvious. For example, strategic actions that seem to indicate co-regulation
can originate from individual group members’ personal goals. To achieve these
34
goals functional group work and co-regulation are required. Hence, the form of
regulation depends on both the motives and the actual behavior of the students,
and in practice the line between individual and socially shared forms of regulation
is not strict or absolute.
2.4.1 Individual regulation
Individual forms of regulation focus on individual students’ efforts to maintain
and direct their goal-oriented learning. Self-regulation is rather easy to classify as
an individual form of regulation, and solidly grounded on theoretical and
empirical evidence derived from the socio-cognitive perspective. By definition,
the concept of self-regulated learning is the most common and also the most
theoretically thorough form of individual regulation. It refers to the process of
becoming a strategic learner by regulating one’s own cognition, motivation, and
behavior to optimize learning (Schunk & Zimmerman, 1994). In all likelihood,
other terms and concepts referring to individual regulation in learning contexts
can be interpreted with reasonable effort as a component of the self-regulated
learning process. Different models emphasize behavioral or mental processes or
target the cognitive, emotional, or motivational aspects. However, they all focus
on a phenomenon where individuals aim to regulate their learning process in one
way or another.
In self-regulated learning theories, the individual is considered as the
regulator of his or her behavior, and the social is seen as a context, where
individual learning and the regulation process occur. The social context set
conditions and standards that influence individual learning (Zimmerman, 2000).
The social influence is especially essential and strong in developing individual
self-regulatory skills because social context affords opportunities for modeling,
prompting, guided practice, and instrumental feedback (Hadwin, Oshige, et al.,
2010). These processes play an essential role in promoting individuals’ SRL
processes (Zimmerman, 2000). Eventually, the social context is still a completely
distinct entity that can be separated from the individual process of self-regulated
learning.
If the concept of self-regulation is consistently used in educational literature,
the concept of other-regulation can be used at least in two ways. In
developmental research, it can describe the regulation process, where the more
capable others regulate the growth of learners’ capacity to regulate their own
learning (Schunk & Zimmerman, 1997; Volet, Vauras, et al., 2009). The role of
35
other-regulation (and co-regulation) has been seen as an important mediating
phase in the development of self-regulation (Schunk & Zimmerman, 1997).
Other- and co-regulation processes represent a less developed pre-stage in the
progress toward the higher level self-regulation stage. In the co-regulation process
the more capable, usually older other is seen as a promoter and supporter of
adolescents’ learning processes.
Other-regulation can also be seen as a form of individual regulation, and
hence, as a part of self-regulated learning. However, it employs the conventional
distinction between the self and the social context, in that it changes the role of
the individual learner from the target of social influence to an active agent, whose
aim is to shape the social context. When engaging in this type of other-regulation,
an individual attempts to influence others to adopt more favorable conditions for
learning and collaboration (Järvenoja et al., 2010). This may sometimes serve the
individual’s own purpose; alternatively, the scaffolding process of others’
cognitive processes, emotions, and motivation may be intended to benefit the
whole group.
The main body of studies grounded on the self-regulated learning concept
and socio-cognitive approach rely on the individual as the unit of the analysis.
This appears to be quite natural, given that the individual is the most salient
element in these approaches. Data collected in these studies usually focus on
different aspects of self-regulated learning, such as individual performance, or on
different factors assumed to affect self-regulation, such as self-reports on
individuals’ motivational goals or beliefs and cognitive strategies (Zimmerman,
2008). However, the actual process of self-regulated learning in context has been
less frequently the target and unit of the data analysis.
2.4.2 Social regulation
The socio-cognitive perspective has been a dominating approach in the field of
learning sciences on the research of the regulation of learning. As stated above,
these researches usually consider regulation as an individual process that is
influenced by social aspects. However, other approaches have also been proposed
(See Hadwin, Järvelä, et al., 2010; Volet, Vauras, et al., 2009). Particularly, studies
relying on the socio-cultural perspective emphasize intersubjectivity,
interpersonal interaction, and the shared responsibility of regulation. The origins
of motivation are viewed as social and consequential; the regulation of motivation
is also considered from a social viewpoint (Hickey, 2003; Walker, 2010).
36
The concept of co-regulation is most often used to refer to the process, where
the demands of challenging learning tasks are eased by sharing the responsibility
of the regulation process between the learner and some (more capable) other. In
the beginning of the process, the responsibility of the regulation is mainly on the
co-regulator. This means that the focus is on the unequal interaction between
more and less capable individuals. This phase is greatly convergent with the
developmental perspective on other-regulation. In a co-regulation process, the
responsibility, however, gradually shifts from the co-regulator to the learner
through a scaffolding process. During this process, the learner can acquire
learning skills that support his or her progress to becoming a self-regulated learner.
In other words, in the socio-cognitive perspective, social influences indirectly and
externally contribute to the development of individuals’ independent selfregulation, and the individual cognitive progress can be separated from external
social influences. In contrast, co-regulation can also be seen as a coordinated
regulation process between the participants.
Social learning situations, which demand advanced interaction between
cognitively equal individuals, present a different type of situation in
developmental process of infants to adolescence. In the developmental angle, the
focus is ultimately on the individual, and not on equal relations between colearners. Until recently, research focusing on socially shared learning processes,
such as collaborative learning, has mainly relied on individualistic concepts when
dealing with regulation of learning (Volet, Vauras, et al., 2009). With few
exceptions, the discussion of socially shared or collective regulation in which
groups develop a shared awareness of goals, progress, and tasks for coconstructed regulatory processes has just emerged (Hadwin, Oshige, et al., 2010;
Järvelä, Volet, et al., 2010; Volet, Vauras, et al., 2009).
In a situative perspective, the social dimension of regulation appears to be
framed such that it deals with learning situations that involve emotional and
cognitive reciprocity. In such a situative approach, socially shared forms of
regulation refer to the processes by which multiple people regulate their collective
activity, and where individual regulatory processes are embedded in a social entity.
From this viewpoint, it could be argued that social forms of regulation are the
most sophisticated forms of regulation in that they require both individual and
joint processes. Also, earlier research dealing with learning settings that promote
collaboration and knowledge-sharing activities implicitly indicates that these
types of processes are essential for successful collaborative learning, even though
37
these issues have not been explicitly linked to the concept of socially shared
regulation (Van den Bossche et al., 2006).
In line with such discussion on the role of the social in the conceptualizations
of learning, researchers have talked about self-in-social-settings (Volet, 2001) or
individual-in-social-learning-contexts (Volet & Järvelä, 2001) (also e.g.,
Anderson, Reder & Simon, 1996; Billett, 1996; Greeno, 1997; 1998; Mason,
2007; Nolen & Ward, 2008; Sfard, 1998; Turner & Patrick, 2008). In terms of
self-regulated learning, researchers have discussed self-regulation in group
contexts (Kempler & Linnenbrink-Garcia, 2007), co-regulation (Butler, 2002),
and also socially shared regulation (Hadwin, Oshige, et al., 2010; Hurme,
Merenluoto, & Järvelä, 2009; Iiskala et al., 2004; Järvenoja & Järvelä, 2009;
Vauras, Iiskala, Kajamies, Kinnunen, & Lehtinen, 2003). From this perspective,
individual strategies and processes that are used to regulate motivation and
emotions can be complemented with group members’ collective and interactive
activities aimed at creating and maintaining motivation and emotional balance
within the group.
Shared-regulation refers to a process where a group forms a social entity that
regulates its learning consensually so that regulatory processes are co-constructed
in reciprocal interaction. This requires having a shared goal, which determines the
course of the group’s joint effort. Basically, shared regulation therefore refers to a
collective agency realized in a socially coordinative and interdependent effort to
achieve joint goals (Bandura, 2001). It can be framed using shared cognition and
through research on collaborative learning: the co-construction of shared
understanding (Teasley & Rochelle, 1993). Perspective taking, mutuality, and
shared understanding are co-processes of regulation in socially shared learning
(Gehlbach, 2004; Thompson and Fine, 1999).
Regulation can be classified as shared-regulation or co-regulation depending
on whether the group is operating as a social entity and aiming toward a joint goal,
or whether the group of is merely cooperating to achieve its personal goals or
goals assigned externally. According to a strict definition, a group of learners
engage in shared regulation processes only on rare occasions when they seem to
transcend the individual so that they can proceed with a single mind and by
merging their concurrent self-regulation into a single entity (Volet, Vauras, et al.,
2009). In this definition, individual and social forms are fully integrated and form
an inseparable process. However, whether groups’ regulation activities are
analyzed as shared or co-regulation can relate to the level of analysis. This is,
different analyses can reveal different aspects, for example, about a group, which
38
seems to be sharing goals and is engaged in joint problem solving. On a detailed
level, where the focus is on situated micro processes within the group, the group
members do not necessarily engage in shared-regulation processes all the time
while working as a group. The same group work, however, when examined as a
single entity on a more general level, can reveal that the group engaged in a
genuine shared regulation process during the task.
Following this line of thought, shared regulation can emerge when the
instructional settings emphasize shared activities, as in collaborative inquiry. The
learning tasks that emphasize the construction of joint goals create both the need
and the possibilities for regulating learning consensually with each other. Shared
regulation emerges and is expressed in the reciprocal interaction between the
group members. However, shared regulation does not occur in situations where
group members are regulating their work side-by-side without any reciprocity,
even when there seems to be a consensus regarding the direction of the group
work. This is not to say that individual regulation cannot exist in parallel with
shared regulation.
2.5
Regulation in social learning contexts
Social learning environments rely on smooth interactions between individuals, but
at times, group processes contradict and challenge individuals’ personal aims and
well-being. Individual and social regulation processes can promote each other,
exist in parallel, and function equally, without any subordinate relationship in
either direction. For example, in situations that require collaborative learning, the
learners need to adjust their personal goals with the group’s shared goals for a
particular learning task. These goals can merge, but it does not mean that the joint
and personal goals cannot exist in parallel. Furthermore, even if genuine shared
regulation emerges within the group, it does not mean that individual group
members need to give up their unique experiences, interpretations, and beliefs. In
other words, group members need not neglect individual perspectives from which
they make situational interpretations. Rather, when individual differences and
strengths are accepted and put to use, they can serve as a resource for successful
regulation processes within the group. In an ideal learning situation, individual
and social forms of regulation serve both individual and shared purposes, and the
two processes can promote each other. In other words, collective process will not
overstep individual processes or vice versa.
39
The perspectives that conceptualize the regulation of learning as interactive,
dynamic, and situated in context also bring motivation and emotions to the centre
of the process in a completely new way. This is because situational experiences
and socio-emotional aspects are instrumental in task-processing regulation (Volet,
Vauras, et al., 2009). This dissertation has stated that, in a genuine collaboration,
conflicting views and socio-emotional challenges exist. When these situations
emerge and challenge motivational and affective processes, they can affect the
group as entity. In such situations, at least a minimal level of self-regulation is
always needed to regulate one's own actions and the actions of the collaborative
learning group (Volet, Vauras, et al., 2009; Winne & Hadwin, 1998). But it is only
when the group members are also willing to invest their energy in shared
regulation processes that they can become closely attuned to the opportunities
associated with the experience of shared understanding (Crook, 2000).
This dissertation aims to study the regulation of motivation and emotions in
authentic situations as it evolves in groups. In practice, when regulation is
examined in a group, individual regulation is always studied in relation to the
regulation of co-members and the group (Hadwin, Oshige, et al., 2010).
Respectively, socially shared regulation is composed of the bidirectional
interaction between the group members (Järvelä et al., 2008). This is to say that
the group operates through the interaction and behavior of its members (Bandura,
2000). It is people with their personal beliefs within the group who act in a
coordinated manner for achieving a shared goal, not some disembodied group
mind.
This section of the dissertation has outlined the theoretical basis for
individual and socially shared regulation. For individual and socially shared
regulations to be complementary to each other, the divide between the individual
and the social should be overcome also in empirical research. This calls for
methodological solutions that can capture the complex relationship and
simultaneous interdependence between different forms of regulation. Hence, the
next section of the dissertation discusses methods applied in studies of motivation
and self-regulated learning.
40
3
Methodological challenges
The research on regulation of emotions and motivation as a social phenomenon
that evolves over time poses challenges for methodology. New methods that
capture the phenomenon in context are needed. That is why one of the two main
aims of this dissertation is to develop and employ situation-specific methods for
collecting data in real collaborative learning situations. The focus is on
developing an instrument called Adaptive Instrument for Regulation of Emotions
(AIRE), which can capture the social nature of regulation during real learning
contexts. AIRE offers an adaptive way to measure learners’ individual and
socially shared regulation. The development and innovative use of situationspecific methods are seen as essential for collecting data from authentic, dynamic
situations and students’ varying experiences.
Within the learning sciences, motivation and self-regulated learning
researchers have always emphasized rigorous scientific design and methods.
Researchers have done valuable work in studying motivation, emotions, and selfregulation that constitute and have an effect on learning and academic
performance. They have developed several motivational frameworks and models
of SRL that can explain how learners transform their mental abilities through
behavior, actions, engagement, and cognitive processes into academic
performance (Dweck, et al., 2004). Nevertheless, in these fields of research, there
has been a strong emphasis on the individual. For decades, learning research
focused on static aptitudes, abilities, and characteristics of individual learning
(Barab & Kirchner, 2001; Zimmerman, 2008). This emphasis was reflected in the
choices researchers made about the development and utilization of methods and
analyzing protocols (Salomon, 1992). For a long time, studies concentrated
mainly on laboratory research, static self-report measures, and large-scale surveys
and inventories of certain mechanisms. The challenge in these types of studies is
in how they can capture actual practices in authentic contexts.
In the 1990s, researchers displayed an increased interest in the contextual and
social aspects and their role in (individual) learning. Pioneering work in
developing methods had been carried out already earlier when, for example,
think-aloud methods (Ericsson & Simon, 1993) and experience sampling methods
(Csikszentmihalyi & Larson, 1987) were developed. The theoretical shift towards
a contextual perspective on learning began to lay more emphasis on these
contextual, situation-specific methods. Today, an increased interest in processoriented methods that focus on capturing changes in and during the process and
41
within the social context is evident (e.g., Gläser-Zikuda & Järvelä, 2008; Perry,
2002; Turner, 2006).
There are obvious arguments for using situation-specific methods for
studying the regulation of motivation and emotions in authentic contexts. First,
there is empirical evidence which shows that generic self-reports are often
incongruent with measures that depict the actual traces of the process (Winne,
2006). Secondly, situation-specific methods do not make firm assumptions of
intra-individual stability, and hence, are more open to natural progression of the
process as well as contextual influences and “unpredictable” changes in learners’
activity. And third, analyses employing situation-specific methods often aim for
holistic descriptions that reveal the dynamics within the situation and hence are
more suited to recognize the context-bound individual-social continuum.
Taken together, both static and general measures and situation-specific
methods are valuable for increasing our understanding of motivation and selfregulated learning. This dissertation aims to contribute to the existing knowledge
by adopting multiple methods, especially to capture the situational and interactive
process of regulation of motivation and emotions.
3.1
Self-report measures
Conventionally, self-report measures have been the dominant method for
measuring motivation and self-regulation (see recent discussions e.g. in GläezerZiguda & Järvelä, 2008; Perry & Winne, 2006; Schutz, et al., 2006). Studies
employing these measures have provided valuable information about students’
interpretations of self-regulated learning as well as the role of motivation for
learning. The instruments used have varied from structured interviews
(Zimmerman, 1986) to a variety of standardized tests and scales. For example,
Pintrich and his colleagues (1993) developed a self-report instrument named
Motivated Strategies for Learning Questionnaire (MSLQ) to study students’
motivational goals and their self-regulation strategies. In his studies, Wolters
(1998; 2003) continued this work by combining SRL and motivation research. In
his studies, Wolters has focused on strategies for regulation of motivation and
emotions by developing scales for several motivational regulation strategies. Selfreport measures have also been used to identify the relationship between different
motivation or SRL components and other constructs. For example, Wolters and
Rosenthal (2000) studied the relationship between students’ motivational beliefs
and their use of motivational control strategies, and Schutz and Davis (2000) have
42
focused on investigating emotions and self-regulation during test-taking. The unit
of the analysis in these types of research has usually been an individual or a
variable, and the main focus is to discover general trends or orientations of
individuals, the connection between concepts in terms of statistical dependences
between variables, or differences between individuals. Typically, these studies
seek to identify learning strategies that students need to adopt in order to
successfully and independently direct their learning (Boekaerts & Cascallar,
2006).
These lines of research have led to different, valuable models and
conceptualizations of motivation and self-regulated learning. The need to
implement different self-report measurements cannot be denied when the focus is
on motivational constructs and processes, such as beliefs and goals, that often
cannot be observed otherwise. A good example is the development of the
motivational goal theory. Research on motivational goals has grown to emerge as
one of the biggest contemporary theories that explains the motivation to learn
(Pintrich, 2000a). The interest to study goals in learning was based on suggestions,
which emphasized that the value which an individual attached to a learning task
affected how he or she interpreted and reacted to that task (Dweck, 1986). Since
the 1980s, research on goals has focused on investigating how achievement goals
are related to learning, establishing firm goal orientation types (Pintrich, 2000a;
Urdan & Schoenfelder, 2006), and debating different goal orientation systems.
This research was largely based on surveys and general questionnaires and
produced several protocols and standardized measures for goal orientation. Lately,
however, there has been a shift towards investigation of situation-specific and
context-bound goals that are not necessarily in line with the person’s general goal
orientation and can vary from time to time (e.g., Boekaerts, De Koning, & Vedder,
2006; Järvelä & Salovaara, 2004). These studies naturally require different types
of methods and analyses, even though both usually rely on some type of selfreport. There are also questionnaires that are developed to measure these types of
motivational goals (such as Boekaerts, 2002). Both trends have added to our
understanding of motivational goals, and, when results deriving from both of
these “approaches” are taken into account, this knowledge is also useful in
practice.
The value of the conventional self-report measures for certain SRL processes
is similar to achievement goal research. Today, many researchers acknowledge
the situational nature of motivation and self-regulation, but methods and analysis
in empirical studies still often implement measures that treat the phenomenon as
43
stable and unvarying and do not take into account varying situations and
contextual aspects. Hence, the following questions need to be considered: what is
the validity of the measures used in a specific study; when is it reasonable to
measure static aptitudes and slowly changing motivational traits with static
measures, and when is there a need to focus on situation-specific emotional
experiences and motivational constructs using, for example, interviews or other
situation-specific instruments? The key factor to be considered when choosing the
method(s) is whether the foundation of the phenomenon under investigation is
context-bound and dynamic or relatively stable.
Because researchers in the fields of self-regulation, motivation, and emotions
seemed to be employing the same trend with respect to methodological approach
and analysis, it seems reasonable to elaborate on self-report methods. The selfreport measures usually ask students to estimate how often they do something
(estimation of frequency) or how they usually react to something or how they
approach something (estimation of average reaction) (Nolen, 2006). But, as
Schoenfeld (1992) argues, what do we do when these methods fail to provide
explanations for situations where students do not act as they are “supposed to”
according to their general self-reports and controlled laboratory tests? In other
words, many of the conventional measures of student motivation and SRL report
perceptions, but not what really happens in the learning context (Järvelä, Salonen,
& Lepola, 2001; Winne, 2004).
These are the questions that challenge the researchers to reconsider the
validity of self-report measures as the only data source (Perry & Winne, 2006).
Even if the context is taken into account, it is often done so that context is only
the generalization of certain types of situations, disconnected from any specific
experience. Alternatively, respondents can be asked to think of any condition they
have experienced before. In both cases, it is difficult to know what respondents
have in mind when reporting their interpretations. Conditions and situations that
the respondents consider can vary, which creates difficulties when the results are
interpreted. With this type of data, it is possible to study students’ general
impression of their learning, if it is believed that a measured attribute is valid
because it exists on such a general level (Borsboom, Mellenbergh, & van Heerden,
2004). However, the second limitation pertaining to validity is that self-report
measures, particularly those that are not contextualized and situated in any
specific event, create more opportunities to report biased conceptions of one’s
intentions for action. Students are not always very accurate in their perceptions of
their learning or truthful about their motives (Winne & Jamieson-Noel, 2002).
44
Furthermore, the limitation of the cognitive memory system produces information
that is distorted or prevents information from being retrieved from the memory
(Borsboom et al., 2004).
Another subject for discussion is the analysis methods. Conventionally,
experts have heavily relied on quantitative analyses, which provide a powerful
way to obtain generalizable results from standardized tests. Qualitative analyses
have remained mainly as methods, which are useful in pilot studies when
standardized tests are developed. It needs to identify what type of result can be
generated by using only one type of approach, and even more importantly, what
remains undetected. In an analytic and systemic approach to educational research,
the underlying assumption is that events in a learning environment are contextbound and tied to each other systemically (Salomon, 1991). It is the whole system
that changes through interaction with the individuals, not just the individuals’
perceptions and motivations. That is why these aspects also need to be considered.
According to other recent approaches, the cognitions, motivations, and learning of
individuals cannot be comprehended unless their social and cultural contexts are
taken into consideration (Dowson & McInerney, 2003; Hickey & McCaslin, 2001;
Volet & Järvelä, 2001).
3.2
Using multiple contextual and situation-specific methods
When research aims at capturing the complexity of motivational and selfregulation processes as a situational activity, which exist in relation to a context,
evolve over time, and dynamically emerge and dissolve, single and static methods
that treat motivation and SRL as an individual aptitude became insufficient
(Butler, 2002; Hadwin et al., 2004; Volet & Järvelä, 2001; Winne, 2004).
Moreover, interest in the social systems of learning and motivation, which shift
between the individual-social continuum, have set new challenges for motivation
and SRL research and in turn call for innovative ways to study these processes. As
defined by Turner (2001, p.88), “…context is no longer a background variable but
a major constituent of motivation. Similarly, motivation, while incorporating
individual experience, is integrally intertwined with group experience.”
Situation-specific data become critical when the focus is on real situations,
which are context-bound in nature (Salomon, 1992) in other words happen in a
certain time in a certain place. Situative approaches consider individuals to be
part of their social contexts where motivation is continually co-constructed and
negotiated by their members. It grounds the use of multiple methods that capture
45
different angles of the process of (regulation of) motivation and social context in
which it is formed and shaped (Greeno, 2006; Nolen & Ward, 2008). To achieve a
holistic understanding of the motivation and regulation in various situations,
many researchers have developed, used, and refined several situation-specific,
context-bound methods, such as process-oriented interviews (DeGroot, 2002),
observations (Perry, VandeKamp, Mercer, & Nordby, 2002), tracing activity
(Hadwin, Nesbit, Code, Jamieson-Noel, & Winne, 2007), experience sampling
method (Csikszentmihalyi & Larson, 1987), and other “on-the-fly” measures (e.g.,
Ainley & Patrick, 2006; Boekaerts, 2002).
Data collected from real-life situations provide the best view on the actual
meaning or effect of regulation processes. Qualitatively oriented, situational
research usually involves the application of multiple qualitative methods,
combining qualitative and quantitative approaches, gathering process-oriented
data, and use of various units of analysis (Butler & Cartier, 2005). For example,
classroom motivation research combines observations and interviews and uses
varying approaches in analysis to capture the nuances and dynamics within the
social learning context (Dowson & McInerney, 2003; Hickey & McCaslin, 2001;
Järvelä & Järvenoja, 2011; Perry, 1998; Turner & Meyer, 1999). Perry et al.
(2002), for example, studied teachers’ verbal and non-verbal actions in classroom
to identify how teachers supported children’s metacognition, intrinsic motivation,
and strategic actions. They created a detailed observation protocol, which
distinguished different elements of high- and low-SRL environments. Their
analysis revealed that teachers can promote SRL in many ways. Children can also
have more differentiated motivational profiles than conventional self-report
researches have suggested. Also Meyer & Turner (2002) focused on observing
teacher behavior in classrooms to find out how they scaffold students’ selfregulation processes. They utilized the discourse analysis method and showed
how favorable scaffolding can engage students to co-regulate their motivation and
learn along with the teacher. Meyer and Turner argue that these types of methods
have great potential to capture the reciprocity that occurs within the classrooms.
Both these studies demonstrate how important it is to employ dynamic methods to
study dynamic and evolving concepts. In recent years, a number of SRL
researchers have published work that employed a combination of multiple data
sources or analysis of both qualitative and quantitative data (Hadwin et al., 2004;
Thompson, 2004; Järvelä et al., 2008; Järvelä & Salovaara, 2004; Perry, 2002).
The value of integrating gathered data using different methods but focusing on the
46
same event or process is now widely recognized by experts in the field of SRL
research (Patrick & Middleton, 2002; Perry, 2002).
3.3
Validity and reliability
Using multiple data sources is not, however, a simple process. Aspects dealing
with the unit of the analysis and the different units used in different pieces of data;
the grain size (micro-macro-maso) of the analysis of different data sources; and
the issue of whether or not the analysis focuses on the same phenomenon in each
individual piece of the analysis need to be considered each time, case-specifically.
Also, in order to really benefit from the use of multiple methods, the analysis go
beyond presenting separate results from each data piece and present some type of
cross-data summary. This, of course, needs to be considered case-specifically.
Sometimes it could be reasonable to first publish the results of each data analysis
separately and combine the results later. The study conducted by Hadwin and her
colleagues (2004) is an example of how combining multiple data sources and the
efforts of several researchers can result in comprehensive and descriptive results.
In a cross-case study, they employed several data sources to create SRL profiles
for eight students and then examined their SRL proficiency and performance.
It is clear that to look at situated motives and behaviors, new methods need to
be considered (or new ways to use old methods). If they are invented, the issue of
their validity needs to be addressed (Schoenfeld, 1992). The validity in qualitative
research is based on the following: right choice of methods, compatibility
between research problems and the aims of data collection and analysis, and the
integration of theory and earlier research (Eisenhart & Howe, 1992; KoroLjundberg, 2005). In situation-specific and process-oriented data analysis,
concerns regarding validity always surround the interpretation of the data. For
example, when students’ self-regulation is analyzed by looking at the choices they
made and their actions, when it is valid to assume that they are indications of selfregulation (Hadwin & Järvelä, 2011; Nolen, 2006)? This is an even bigger
concern when students’ motivation and motivated actions (in this dissertation this
would be the regulation of motivation and emotions) are traced. The motivational
meaning of the actions is embedded in the context, situation, and individuals; it
cannot be interpreted without perceiving this complex entity. That is why
researchers should report different phases of the analysis process with sufficient
accuracy to make it possible for others to evaluate the validity (in other words, are
we studying what we are saying). This also increases the reliability as it makes
47
the process, its conditions, and background assumptions more explicit and hence,
replicable.
Another way to increase the validity is triangulation. This can be realized in
many ways. In coding situation-specific data, it is possible to use several
independent coders or repeat blind coding cycles several times. Furthermore, in
the situative, process-oriented approach it is natural to increase validity by
bringing multiple, sometimes even contrasting data, into the analysis and blending
different perspectives (e.g., individual and group) together in order to increase
validity. From this perspective, the distinct data pieces do not necessarily present
a validity problem; instead they are different representations of the same
phenomenon. In other words, the same situation provides possibilities for
different interpretations and perspectives, as it really is in real life. Hence, these
perspectives complement rather than handicap each other. The distinct data may
challenge the researcher to genuinely strive to understand the entity of the process.
This, however, challenges the traditional conceptions of reliability, which
expect repeatability and control over background variables. Research that follows
the situative approach and uses situation-specific methods can never be repeated
in exactly the same way. This would be a violation of the basic assumption of the
situational nature of the learning process. However, the issue of reliability cannot
be neglected or ignored, but rather approached within the situation-specific
approach. For example, (video) recordings enable other researchers to crossanalyze data and compare interpretations. Clear descriptions and adequate
example categories, codings, and narratives make analyses of transcribed data
more reliable and repeatable. By piloting and practicing observation and
interview protocols and techniques, reliability can be further improved. Thorough
descriptions of context and design can also increase reliability, especially if they
include an explanation of the contextual aspects (e.g., how situation and language
use or behavior are related) in the analysis. To conclude, strong theory combined
with well-explicated methodological choices and analyses form the basis for valid
and reliable research in studies using process-oriented methods (Gläzer-Zikuda, &
Järvelä, 2008; Greeno, 2006; Karabenick et al., 2007; Nolen, 2006; Winne, 2004).
48
4
Aims of the study
The general objective of this study is to investigate socially shared regulation of
motivation and emotions in social learning contexts. The aim is to investigate
what kind of challenges students experience in collaborative learning situations
and to analyze individual and social forms of motivation and emotion. To enable
the study of these phenomena in real-life context and varying situations, a specific
instrument was developed and used to complement other qualitative, situationspecific methods. Also, appropriate analytical methods were implemented to
identify and examine the different aspects that affected processes of selfregulation in collaborative learning.
The empirical analyses of this dissertation are composed of the data derived
from two different studies. The common factor of these two studies was the
requirement to work collaboratively to accomplish challenging tasks. The first
study was conducted over three years with secondary school students. During this
time, the students worked on four different projects in literature. The main aim of
this first study was to identify different sources of emotional experiences in
challenging collaborative learning settings.
The second study focused specifically on socio-emotional challenges, which
were identified as one of the sources of emotional experiences in the first study.
The aim was to investigate, in more detail, the different reasons for socioemotionally challenging experiences and to discover whether the students
engaged in socially oriented regulation processes to regulate motivation and
emotions when needed.
The specific aims of this dissertation can be divided in two, where the first set
of aims deals with empirical questions, and the second set considers
methodological issues.
The empirical aims are as follows:
1.
To identify and specify the different sources for emotional experiences in
collaborative learning.
The varying source for emotional challenges is addressed in articles I and III.
Also article II considers socio-emotional challenges, when it describes the
development of the AIRE instrument.
2.
To determine and provide evidence of socially shared motivation and emotion
regulation processes.
49
This question is addressed in articles III and IV, as well as in article II.
The methodological aims are as follows:
3.
To develop an instrument that offers an adaptive method to measure learners’
individual and socially shared regulation.
This aim is addressed in article II, and the instrument is employed in articles III
and IV.
4.
To combine data from different sources in order to conceptualize the role of
motivation and emotions in collaborative learning.
Articles I, IV, and V deal with issues related to this aim.
50
5
Methods
5.1
Participants and Instructional settings
The participants of the first study were eighteen secondary school students. The
data collection was carried out over three years (grades 7, 8 and 9) as they studied
four different literature topics. The pedagogical instructions were adapted to the
idea of inquiry-based learning (Hakkarainen & Sintonen, 2002) and computersupported learning environments called CSILE and Knowledge Forum were
utilized (Scardamalia and Bereiter, 1994). Each project lasted for six to eight
weeks and included two to three lessons per week. The literature teacher
volunteered to participate in the research project and was actively involved in
designing the four topics.
The participants of the second study were 63 higher education students, who
studied educational psychology topics through three different collaborative
learning tasks during nine working sessions (including one orientation lesson).
Each of the tasks followed a different pedagogical structure, but each of the tasks
assumed that students had a shared goal. The first task required students to find
answers individually to a set of questions and then use these answers to formulate
a joint response as a group.. The aim was to create productive cognitive conflicts
between group members and stimulate group members’ argumentation and
negotiation (Dillenbourg & Traum, 2006). The second task employed authentic
cases as the bases for collaborative learning. First, the group members were
provided some basic literature on the phenomenon under study, and then they
were encouraged to freely discuss the ideas, thoughts, and experiences that
emerged during the reading. In the next phase, the group members chose one reallife case for a more detailed discussion and analysis. The aim of this type of
collaborative task was to encourage discussion and sharing of authentic real-life
experiences and prompt students to share expertise, which is seen as a benefit of
successful collaborative learning (Brown & Campione, 1994; CTGV, 1990). The
third task provided students with the possibility to plan and organize their group’s
work as they wished. Only general themes and some basic materials were offered
for the groups and they were advised to study the theme so that they were able to
create a “scientific” poster as a result. The group members first had to agree on
the theme they wanted to study and then plan how to organize their collaborative
work. The aim in this last task was to stimulate groups to take responsibility and
51
encourage students to be persistent and tolerate uncertainty, both of which are
important parts of successful self-regulation, also on a group level.
5.2
Research design
The research design of the first study involved using different qualitative methods,
namely video observations and individual interviews. The aim was to understand
how students describe their use of volitional strategies and how it can be observed
from their activity; in other words, how students engage themselves in
motivational self- regulation. The data collection emphasized students’ contextual
interpretations and explanations of motivational aspects that affected their
inquiry-based learning.
The research design of the second study involved multiple methods and
pedagogical structures that varied during the data collection. The learning period
during which the data was collected was designed to illustrate different
characteristics of collaborative learning. The general aim was to collect data from
both the individual and group perspective, to gain an understanding of the
dynamics of motivation in collaborative learning. The data collection focused on
the collaborative group work done by groups of 3–5 members, who worked
together on three different collaborative learning tasks. The first and second task
spanned two lessons, whereas the third task was performed over four lessons (one
lesson lasting 90 minutes). The research design is presented in Figure 2. It
included the videotaping of volunteer student groups’ collaborative group work (n
= 4), collecting individual interpretations of the group work after every
collaborative task using the AIRE instrument (Järvenoja et al., 2010), and group
interviews of the videotaped groups after the completion of each task. In addition,
before the learning period, the students completed a self-report questionnaire that
assessed their general goal orientations. However, this data was not used in this
dissertation.
52
Fig. 2. Research design of the second study.
5.3
Data collection
The data collection for this dissertation focused on two different studies, and the
empirical results of these studies are reported in three (I, III and IV) of the five
articles. The data collection in both studies employed situation-specific,
qualitative methods. Table 1 presents a summary of the participants, aims, data
collection and analysis methods in relation to these three empirical articles.
Table 1. Summary of the four aspects of the empirical articles.
Article
Participants
Focus
Methods
Analysis
Article I
Secondary school
Emotional experiences Individual
Study 1
students
interviews,
analysis
(n = 18,
video records
Case descriptions
AIRE
Descriptive quantitative
& Study
Qualitative content
age 12–15 years)
Article III Higher education
Study 2
experiences,
analysis
(n = 63,
individual and social
Qualification of
average age 23 years)
forms of emotion
quantitative data through
regulation
case comparison
Article IV Higher education
Study 2
Socio-emotional
students
students
(n = 16)
Socially constructed
AIRE
Descriptive quantitative
motivation regulation
video records,
analysis
group interviews Qualitative content
analysis
Descriptive qualitative
analysis
53
Next, each of the data collection methods is introduced. The focus is on the
validity and reliability of the data and analyses. The implementation of specific
methods and data analysis procedures are described in more detail in the articles.
5.3.1 Interviews
In this study, interviews were used to collect data on students’ experiences and
situational interpretations. In both studies, a semi-structured interview protocol
was followed to identify and concretely describe students’ “motivationally
affected” learning experiences, sources of their emotional and motivational
experiences, and motivation regulation strategies. To enhance situation-specific
interpretations, both interviews were conducted between or right after learning
sessions.
The interview data of individual students play a central role in article I. The
data were analyzed by a qualitative content analysis (Chi, 1997) and several
classes were composed according to the research questions, theory, and empirical
data. A qualitative content analysis includes clear instructions to ensure validity
and reliability. In article I, the validity of the interview data analysis was
improved by (1) providing a theoretical framework, reflected in the creation of
the coding categories and (2) in the detailed description of the analysis procedure.
Article I also includes tables where definitions and examples of each category are
presented, helping the reader evaluate the terms defined for each category. The
reliability of the qualitative content analysis in article I was ensured with several
rounds of independent coding and with inter-coding procedures for 30% of the
coding. In consequence, the whole data set was re-coded such that the coding
corresponded with the new consensus gained in the negotiation between the
coders.
Article IV utilized group interviews in the analysis. In this analysis, the
interviews were one of the three data sources, and its purpose was to complement
the other two data sources on which the analysis relied. In other words, the
interview data were used to add validity to the analysis through examples of
student groups’ interpretations and explanations of their group work. In terms of
the interview data, the reliability of the analysis in article IV was improved with
triangulation between data from three different sources (interviews, AIRE, and
video) and by composing a cross-data summary, where the data from all the three
sources were contrasted with each other.
54
5.3.2 Video records
Video records provided data that illustrated what students actually do and how
they act during the learning process. In both studies, a few voluntary students or
students’ groups were selected for video observation. These students were
videotaped as they worked through the whole learning period.
Article I utilized two case students’ video records in order to describe their
use of volitional control strategy. Students’ activities were traced, and descriptive
narratives were created for both cases. To increase both validity and reliability of
this analysis, the two narratives are presented to the reader for comparison. Also,
links to the analysis of the whole interview data as well as the two case students’
interviews are included to increase triangulation between the data sources. Also, a
few quotations from the students’ interview responses are presented to help the
readers make their own validity judgments.
Article IV utilized four student groups’ video records. The aim of the video
data analysis in this article was to identify socially shared motivation regulation
strategies. Because there were no readymade protocols for this type of analysis,
the analysis proceeded through cycles where the analysis was intensified to locate
and trace the phenomenon under investigation. In article IV, the validity of the
video data analysis was improved by providing a theoretical framework and by
reutilizing well-established categories for individual regulation (Wolters, 2003)
which were reflected when the coding categories were formulated. Since the
analysis did not follow any specific analysis method, the procedure of the analysis
was described in detail to increase reliability. Also, there was a cross-coding
agreement from the last cycle, where specific coding was performed. Finally, a
detailed description and examples were presented to help the reader evaluate both
validity and reliability.
5.3.3 AIRE instrument
Articles II, III and IV introduce and implement the Adaptive Instrument for
Regulation of Emotions (AIRE), developed as a part of this dissertation work.
AIRE is an instrument that offers an adaptive way to measure learners’ individual
and socially shared regulation. It has two main aims. First, AIRE identifies
specific socio-emotional challenges group members experience during real-life,
student-led collaborative learning situations. Then it attempts to capture group
55
members’ individual and socially shared efforts to regulate their emotions (and
motivations) in these challenging situations.
AIRE comprises four interrelated sections, and each section has a different
focus. Because the different sections are interrelated, AIRE has can adapt to the
unique personal and contextual circumstances of different situations where
students employ regulation processes. Each section of the instrument is sensitive
to students’ responses to earlier section. The main emphasis is on sections two
and three, which collect data about socio-emotional challenges and the regulation
of emotions. The other two sections focus on personal goals and reflections on
perceived goal attainment.
Article II explains our rationale behind developing an instrument that
investigates the regulation of emotions in social learning settings. It also provides
a thorough description of the theoretical foundations of the instrument. When a
new instrument is introduced, it origins, uses, and its strengths and limitations
need be described (Schoenfeld, 1992). This would also be the case with the AIRE
instrument. Article II is written primarily to provide the reader with the possibility
to assess the theoretical validity of AIRE. In addition, article II also includes
illustrations of the use of AIRE in empirical work and basic reliability analysis
(Cronbach’s alpha) for parts of the instrument.
Article III utilized data collected with the AIRE instrument as the only data
source. In the article, the process of performing different descriptive quantitative
tests is described and the results are reported, including figures that relate to the
reliability. In addition to the results and standard figures, the section of the AIRE
from which the data is used in the analysis and the settings based on which the
data is collected, are described in detail. Also, both quantitative and qualitative
analyses were applied, which enabled triangulation between analysis methods.
Qualitative analysis is reported in detail, so that the reader can understand how it
was performed.
AIRE data is one main data source in article IV. The article utilized data on
the socio-emotional challenges students reported in its analysis and combined it
with video- and interview data in cross-data summary. To improve the validity
and reliability of the instructional setting, the section focusing on challenges in
the AIRE instrument and the analysis performed were described. The reliability of
the analysis in article IV was also improved with triangulation between the data
from three different sources (interviews, AIRE, and video) and by composing a
cross-data summary, where the data from all the three sources were contrasted
with each other.
56
In conclusion, the development of an instrument, such as the AIRE, is a long
process, especially when the aim is to study a phenomenon that is also
theoretically under development. AIRE was initiated by the idea that motivation
and emotions are situation-specific, and in social learning situations, they can be
socially constructed through shared regulation processes. AIRE is not yet in its
definite form. In fact, if the instrument is found useful, it will also be developed
further by its users once both theoretical and empirical understanding increases.
Keeping the incompleteness in mind, it should be emphasized that AIRE’s
validity for the research at hand and the reliability of the empirical findings is
considered every time it is used for research purposes.
57
58
6
An overview of the articles
This dissertation consists of five articles. Articles I, III, and IV describe empirical
studies focusing on motivation and emotions in social learning settings (see Table
2). Article I considers the sources of emotional and motivational experiences that
secondary school students undergo during computer-supported collaborative
learning projects. Article III focuses in more detail on the socio-emotional
challenges reported by higher education students. Socio-emotional challenges
were identified as a cause of emotional experiences in the study described in
article I. Article III also examine how emotions are regulated in these challenging
situations. Article IV identifies higher education students’ socially constructed
motivation regulation in collaborative learning on a more comprehensive level by
combining different viewpoints in its analysis.
Article II focuses on methodological issues by introducing an instrument
called “Adaptive Instrument for Regulation of Emotions” (AIRE). This
instrument is used to collect data in the study presented in articles III and IV.
Finally, article V adopts a wider perspective by discussing motivation as an
individual-social phenomenon.
The five articles are guided by two principal hypotheses. First, motivation is
an active and situation-specific process. Learners can affect their motivation
through long-term development and in every situation in which they participate.
Second, motivation is both socially influenced and socially constructed through
verbal and non-verbal interactions. The aim of each article is summed up in Table
2, along with the research responsibilities of the author of this dissertation in
those articles. The dissertation starts with investigating learners’ active role at an
individual level, but focuses on socially shared processes as the research evolves,
and finally concludes by combining individual and social processes at both
theoretical and empirical levels.
59
Table 2. Focus
(empirical,
methodological
or
theoretical),
main
aims,
and
responsibilities of the present author in the five articles.
Article
Focus
Article I
Empirical
Aim
Author’s main responsibility
Identify sources of emotional
1st author, responsible for
experiences and describe how
empirical data analysis and
emotions and motivation are
theoretical grounding.
expressed and controlled during
learning.
Article II
Methodological
Introduce an instrument for
1st author, responsible for
studying socio-emotional
development of the instrument.
challenges and regulation of
emotions in collaborative learning.
Article III
Empirical
Investigate students’ interpretations 1st author, responsible for
of the reasons for socio-emotionally empirical data analysis and
challenging situations and provide
theoretical grounding.
evidence of socially shared emotion
regulation in collaborative learning.
Article IV
Empirical
Identify students’ socially
2nd author, responsible for the
constructed motivation regulation
AIRE and cross-data analysis,
process in collaborative learning.
contributing to the analysis of
other two data sets and
theoretical grounding.
Article V
6.1
Theoretical
Contribute to ongoing discussion on 3rd author, responsible for data
the role of individual and social
illustration, contributing to the
processes in research on
theoretical grounding of the
motivation to learn.
empirical work.
Article I
Järvenoja, H., & Järvelä, S. (2005). How students describe the
sources of their emotional and motivational experiences during
the learning process: A qualitative approach. Learning and
Instruction 15(5), 465–480.
The aim of the study reported in Article I was to define the sources of secondary
school students’ emotional and motivational experiences in a computer-supported,
inquiry-based learning project. The study employed interview data, from which a
60
variety of the sources for emotional reactions that can affect students working
during inquiry-based learning, were decoded. Furthermore, two cases of students’
control of emotions and motivation was traced from video data. The study
implemented the theory of volition, which was seen as an executive phase of the
self-regulation process. It was expected that emotional experiences and students’
volitional control are related. The framework was used to examine how the
sources of different emotions function as specific components in students’
emotional and motivational experiences.
In the interviews, which were conducted over four different projects in the
course of three years, 18 students described their motivational goals, beliefs, and
feelings related to the learning tasks they were performing. The data analysis
involved a qualitative content analysis. From 136 interviews, about 550 responses,
including statements related to the aims of this research, were located. In addition,
a video record of two students working was analyzed to compose short narrative
case descriptions that demonstrated the phenomenon under investigation.
The results of the study revealed that students’ emotional experiences stem
from a variety of origins. Sources that related to the self and context were
experienced most often instead of the sources that related to the academic activity
per se (task and performance). In addition, social-driven feelings emerged as the
fifth source for emotional experiences. Despite the relatively few explanations of
social sources, this category was seen as an important finding. The nuances and
affects are often reduced to one variable in studies focusing on individual learning
and motivation, and a need to study them more specifically was recognized.
The results of the two cases of students’ narrative descriptions demonstrated
different ways to control emotions and how these differences can affect the selfregulated learning process. The study argued that already the two case
descriptions can demonstrate the importance of functional regulation. The case
descriptions revealed a need for more investigations involving multiple situationspecific methods that could capture and portray the actual process of selfregulated learning.
61
6.2
Article II
Järvenoja, H., Volet, S., & Järvelä, S. (2010). Regulation of
emotions in socially challenging learning situations: An
instrument to measure the adaptive and social nature of the
regulation process. Manuscript.
The purpose of Article II was to introduce an instrument called the “Adaptive
Instrument for Regulation of Emotions” (AIRE), which was developed to expand
on the emotional challenges stemming from social interactions. The main aim of
AIRE was to explore the individual-social continuum of the emotion regulation
processes in group learning situations. Article II presents the AIRE instrument and
justifies why it was seen as essential to develop an instrument that could be used
to specifically focus on these covert emotional processes that are often overrun by
more overt cognitive actions.
Article II begins by elaborating the two main theoretical ideas of the
instrument. These key concepts are self- and socially regulated learning and
regulation of emotions. The use of both concepts is grounded in existing literature
and previous empirical studies. Self- and socially shared forms of regulation are
classified into three different forms of regulation, namely self-, other-, and
shared-regulation, and the theoretical relevance and empirical usefulness of this
division can be evaluated when the instrument is used. The article continues by
introducing the conceptual underpinnings of each of the four components that
compose the instrument. Each component focuses on a certain aspect, namely
students’ situation-specific goals, the type of socio-emotional situation the student
has encountered within his or her group, the form of regulation processes the
student has employed either individually or jointly with his or her group members
in order to control his or her emotions and maintain motivation to work, and the
metacognitive reflection of goal attainment and group work. These aspects are
seen as relevant when the regulation of emotions is studied in a collaborative
learning context.
Article II concludes by elaborating the most profitable ways to use the
instrument. The instrument needs to be used in actual situations and provides
more possibilities for analysis if it is completed several times and by each group
member. In this way, it is possible to see situational differences and combine
individual and group-level perspectives in the analysis. The value of the data
gathered in this way is especially evident in the group profiles that can be
composed based on the individual group members’ responses. These group
62
profiles provide information on the level of proximity of the group members’
interpretations of the situation. However, the most profitable way to benefit from
the instrument is to use it along with other data collection methods and combine
the various data gathered in the analysis to create a comprehensive picture of
social aspects of self-regulated learning.
6.3
Article III
Järvenoja, H., & Järvelä, S. (2009). Emotion control in
collaborative learning situations - Do students regulate
emotions evoked from social challenges? British Journal of
Educational Psychology 79(3), 463–481.
The study reported in article III implements the instrument presented in Article II.
It was initiated by the on-going discussion on social aspects of motivation in the
field of educational psychology and especially in learning motivation research
(Nolen & Ward, 2008). However, despite the growing interest in the topic, even
today there is a lack of empirical research from this new point of view.
The aim of Article III was to investigate socio-emotional challenges
experienced by first-year teacher education students (n = 63) during collaborative
learning and the students’ regulation of the emotions evoked during these
situations. The students studied in groups of 3–5 and participated in three
different collaborative learning tasks. After each collaborative learning task,
students completed an “Adaptive Instrument for Regulation of Emotions” (AIRE),
resulting in 181 responses for the data analysis. In addition to the aim of studying
students’ individual experiences, it was also aimed to demonstrate the level of
variation in the group members’ interpretations of the situation. For this purpose,
a case comparison of two groups was presented, and a graphical representation to
illustrate the differences in the group profiles was developed.
The results of the study showed that students experience a variety of socioemotional challenges during collaborative learning and that the group members’
interpretations of the sources of the challenges varied in some situations. This
may indicate that group members did not always have a shared idea of what the
source of these challenges was. Furthermore, the results tentatively suggested that
the amount of joint experience and/or structure of the task may have an impact on
the quality of the socio-emotional challenge. The students reported that they used
both individual self-regulation and socially shared regulation in socio-emotionally
challenging situations.
63
Both group profiles demonstrate the dual nature of emotion control in
collaborative learning situations; it is constructed in the interaction between
individual and social aspects (Volet & Järvelä, 2001; McCaslin & Hickey, 2001).
Group dynamics are shaped by individual interpretations of the situation, and by
the way in which group members manage to reach a shared understanding and
maintain emotional balance in the group. The group profiles show that it is
possible to work successfully together even if the situation is interpreted from
each individual’s own perspective. The analysis of the entire data set suggests the
same: the students reported the use of shared-regulation in collaborative learning
tasks although the source for the socio-emotional challenging situation was
usually interpreted differently between the group members.
6.4
Article IV
Järvelä, S., & Järvenoja, H. (2011, in press). Socially
constructed self-regulated learning in collaborative learning
groups. Teacher College Record.
The data used in the study reported in article IV are from the same data collection
as the data in article III. The aim of this article was to combine data from different
sources to identify higher education students’ socially constructed regulation of
motivation comprehensively. This is different from article III which utilized one
data source to specifically study socially shared regulation of emotions. Hence,
the focus of the analysis of article IV is on four groups of students (n = 16),
whose motivations during collaborative work were studied using several
situation-specific data collection methods. The analysis combined the different
data and focused on investigating the challenges experienced by certain groups
during collaborative learning and measures to overcome the challenging
situations adopted by the group members.
In the study, three different data collection methods, namely the AIRE
instrument, video records and group interviews, were implemented. In this article,
the regulation of motivation was seen as a dynamic process (Turner, 2006), which
includes elements of intrapersonal characteristics, context, and interpersonal
interactions, and that is why the unit of the analysis and the focus switched
between individual (thinking), group (thinking), and the activities and interaction
within the group. In other words, the analysis proceeded by following three
perspectives: identified challenges (what was a person thinking?), activated
motivation regulation strategies during collaboration (what was the group doing?)
64
and explanations of how SRL was socially constructed (what was the group
thinking?). With these perspectives, it was possible to identify situations where
the group members felt their motivation was challenged, follow the joint
regulation processes that they possibly activated in these situations, and also pay
attention to the students’ own interpretations of these situations.
Each piece of the data in article IV was first analyzed independently. These
results showed that students from the four groups experienced a variety of socioemotional challenges affecting their motivation (AIRE data), employed different
types of socially shared strategies to overcome emotional challenges and to
maintain motivation within the group (video records), and supported the
hypotheses of socially shared regulation of motivation in their group explanations
(group interviews). Consequently, all these pieces of data analysis supported the
idea of socially constructed regulation of motivation. To further elaborate the
results, and in order to enhance the benefit from using several data collection
methods, these data sets were drawn together in a cross-data summary. The crossdata summary linked the data together. The results showed the coherence between
individual and group thinking and their actions, which is not always clear. It also
revealed tentative links between certain types of challenges and socially shared
motivation regulation strategies.
6.5
Article V
Järvelä, S., Volet, S., & Järvenoja, H. (2010). Research on
motivation in collaborative learning: Moving beyond the
cognitive-situative divide and combining psychological and
social processes. Educational Psychologist 45(1), 15–27.
The aim of the fifth article of this particular dissertation is to frame theoretical
ideas of the preceding four articles and situate these articles in the on-going
discussion on individual and social aspects of motivation. The article provides an
overview of our perspective, which derives from a long-term focus on both
research on collaborative learning and the role of motivation and emotions in
group learning situations. It sums up our approach on social motivation, which
has had a significant impact on and led to the theoretical development of this
dissertation.
The main argument in the article is that research on motivation needs to move
beyond the individual-social divide, when motivation is studied in social and,
particularly, in collaborative learning situations. Furthermore, when knowledge is
65
constructed in collaboration between the group members, individuals’ motivation
is not always only “socially influenced” but can also be “socially constructed”
within the group. This argument also leads to the other articles of this theses,
which study individuals’ motivation in group learning situations as “socially
influenced” (article I, and partly articles II and III) and groups’ and their members’
“social construction” of motivation (partly articles II and III, article IV).
Article V is divided into five sections. In the first three sections, our
theoretical perspective is outlined by augmenting the significance to study
motivational aspects of collaboration, how the role of these aspects can be
conceptualized, and why individual and social dimensions need to be combined in
research on motivation in collaborative learning. The fourth section introduces
recent research on these issues, and explains the theoretical approaches and
methodologies used by different studies in an attempt to bridge the divide
between individual and social perspectives in motivation research. The data
illustration presented at the end of this section is from our own studies, discussed
in more detail in articles III and IV. At the end of article V, our argument is
summarized and the direction for future research is discussed.
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7
Discussion
The objective of this dissertation was to examine regulation of motivation and
emotions in a social learning context. There exists a firm body of research dealing
with regulation of motivation or emotions, but it has remained mainly on
individual level. Through the development of methods and results from empirical
studies, this study adds to the understanding of socially shared regulation of
emotions. It provides empirical evidence of the phenomenon where group
members share responsibility to regulate emotional atmosphere within the group.
The study also addresses the need for methodological considerations when
regulation is studied in collaborative learning. At a more general level, the results
contribute to the research on the role of social aspects in the motivation to learn
(Järvelä, Volet, et al., 2010; Nolen & Ward, 2008; Volet, Vauras, et al., 2009).
The focus of the current research was the regulation of motivation and
emotions as it occurs in authentic learning situations. A situation-specific
approach was implemented in order to acknowledge situational factors, which
included collaboration with other students, aspects of (computer-supported)
learning environments and instructions, as well as individual characteristics. The
dissertation concludes that motivation can be socially constructed in interaction
with collaborative learners. Co-construction of motivation is activated through
shared regulation processes, which maintain and channel group activity.
It is important to note that some ideas of this dissertation, especially aspects
dealing with the relationship between the individual and social aspects, stem from
collaborative learning research. Theoretically, however, this dissertation is
grounded in the research on motivation and self-regulated learning. The
theoretical framework can be seen to be derived from socio-cognitive and
situative approaches, which acknowledge and target the role of the context and
interaction. The validity and reliability of the theoretical ideas that have been
presented and investigated in this dissertation is improved because of a firm
grounding in previous research and theoretical thinking. Methodological choices
have been guided by the idea of triangulation at different levels, such as using
multiple data sources and cross-data analysis, other researchers’ independent
interpretations and coding of the data, and by combining and contrasting analyses
that use both the individual and the group as a unit of the analysis. These are the
foundations of this dissertation, and when decisions about design, implementation,
and results are evaluated it should be acknowledged that these choices certainly
have had an impact on the ways in which this dissertation was constructed.
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7.1
Main findings
In general, the findings of this dissertation support the perspective that
emphasizes the role of social aspects in motivation. It suggests that students can
share the regulation process within collaborative groups and through this
interactive process. The main results can be summarized as follows:
Students experience a variety of emotional and motivational challenges
during learning. These challenges can be social in nature. A number of
researchers would agree that individuals’ emotions and motivation are formed
at the interface of personal, contextual, and social aspects (Ainley & Hidi,
2002; Nolen & Ward, 2008; Turner, 2001; Volet & Järvelä, 2001). Students’
emotional responses to these challenges may be different when serving
fundamentally different needs, which derive for example, from differences in
personal goals and former experiences (e.g., Sorrentino & Higgins, 1986).
However, social learning situations and open learning tasks that aim at shared
knowledge construction are typically more challenging than conventional and
well-structured learning situations. In this dissertation, socio-emotionally
challenging situations were considered as critical points in collaborative
group work in terms of successful learning and interaction (Järvenoja et al.,
2010). In order to maintain coordinated activities within a group, participants
have to overcome the challenges that emerge due to the social nature of the
situation (in addition to those experienced in any learning setting) (Järvenoja
& Järvelä, 2005).
The engagement and choice of motivation and emotion regulation processes
can differ depending on the interpretation of social challenges as well as
personal aspects. In social learning situations, students can use both
individual self-regulation strategies and socially shared strategies to
overcome socio-emotional challenges. Inevitably, the interaction of
individuals’ characteristics, goals, and demands leads to a situation that
arouses emotions and motivational conflicts, which give rise to the need to
control individual’s own motivation and emotions, the environment in which
the individuals interact, and their behavior. But, in social learning situations,
it is not sufficient for students to try to adjust and prioritize only their own
regulation processes according to their own multiple personal goals
(Wosnitza & Volet, 2009). Given that students are engaged in a collaborative
learning situation, they also have to take into consideration the other group
68
members’ goals and emotional reactions. This means further adjusting their
own goals to fit the shared goals that the group decides to pursue.
Researching self-regulation in such contexts presents further challenges, as it
requires a re-definition of the regulation of motivation and emotions in terms
of how these may be socially constructed. In turn, this also means
determining new methods to study regulation processes that may be shared
within groups and between group members (Järvelä, Volet, et al., 2010).
Socially shared regulation can be activated regardless of each group
member’s individual interpretation of the situation. Through the shared
regulation processes, group members co-construct their motivation. There is
research suggesting, however, that to genuinely share regulation processes,
group members need to commit themselves to the pursuit of a joint goal and
their working and interaction should be equal (Volet, Vauras, et al., 2009).
Conceptualizing motivation as a dual phenomenon that combines individual
and social perspectives can be viewed as enrichment for the individual
psychological concept of motivation. However it also raises issues of
theoretical clarity and theory-methodology consistency. It calls for integration
of different theoretical traditions, methodological developments, and above
all, a lot of unprejudiced empirical research.
The social learning situations are influenced by multiple aspects that derive from
individual, group, community, and cultural levels. Regulation processes are
embedded in this setting and need to be adjusted accordingly. Viewing (self)regulated learning from a situative, contextual perspective grounds the discussion
that aims toward an approach that integrates individual and social regulation. In
this integrative perspective, neither process is emphasized over another (Järvelä,
Volet, et al., 2010; Nolen & Ward, 2008; Volet, Vauras, et al., 2009). Both forms
of regulation play a unique but concurrent role in the multidimensional view on
regulation of learning in real-life, collaborative learning situations (see Figure 3).
69
COLLABORATIVE
LEARNING
INDIVIDUAL
PERSPECTIVE
Individual regulation of
motivation and emotions
GROUP
PERSPECTIVE
Co-construction
of situational
motivation
Socially shared regulation of
motivation and emotions
Socioemotional
challenges
Fig. 3. Framework of the dissertation’s main constructs and their interrelationships.
To conclude, the results of this dissertation suggest that individual and social
forms of regulation can be in balance and employed side-by-side. This supports
the considerations where motivation in collaborative learning is conceptualized as
situation-specific and co-constructed within and between the group members. On
the one hand, group members’ co-construction of motivation contributes to
individuals’ perceptions of their situational motivation. On the other hand,
through the co-construction process the group members’ create, maintain and
redirect their joint goals, motives and efforts related to the joint task. In Figure 3,
this conceptualization is outlined from the perspective of the current study. It
portrays how the socio-emotional challenges experienced can trigger both
individual and socially shared regulation processes in collaborative learning.
Through these regulation processes, group members can co-construct their
motivation as the situation unfolds.
7.2
Adaptive instrument for regulation of emotions
In this study, methodological development was a central aspect in addition to the
empirical research. An instrument called “Adaptive Instrument for Regulation of
Emotions” (AIRE) was developed to expand on emotional challenges deriving
from social interactions. The main aim of AIRE was to explore the individualsocial continuum of the emotion regulation processes in group learning situations.
70
The development of the instrument was initiated for two reasons. First, the
research on group learning and collaborative learning has indicated that the
benefits of collaboration for learning cannot be taken for granted. Successful
collaboration requires the group members to establish a common ground and joint
goals, which requires firm emotional balance and atmosphere within the group.
This, in turn, requires successful emotion regulation when socio-emotional
challenges are encountered. With many data collection methods, however, it is
complicated to trace situation-specific emotional and motivational aspects. This
may be because in many types of data, these processes are overcome by or
reflected through more visible and accessible cognitive activity and regulation
processes. Secondly, empirical studies, including our own, have shown that
learners are more capable and/or willing to recognize emotional challenge if the
challenge derives from more “objective” sources, such as a context or a learning
task. Challenges deriving from social interaction seem to be more difficult to
recognize or appoint, maybe because it includes “criticizing” your fellow students
(See, e.g., Article I). That is why we decided to explicitly focus on socioemotional challenges and their regulation, linked to learners’ actual experiences.
There exists a range of recent assessment technique schedules that do not
assume SRL as a stable aptitude (Boekaerts & Cascallar, 2006; Perry, 2002).
AIRE adds to these methodological approaches that access self-regulatory
processes in innovative ways through the perspective it adopts on shared
regulatory processes. AIRE not only collects data on individual and socially
shared processes, but the analysis of data collected with AIRE can be situated on
an individual and also on a group level (Järvenoja & Järvelä, 2009). There have
been studies shifting individual data on a group level analysis especially in
collaborative learning research (e.g., Van den Bossche et al., 2006). In selfregulated learning, these types of empirical studies, however, have just started to
emerge (Hurme et al., 2009; Iiskala et al., 2004; Kempler & Linnenbrink-Garcia,
2007; Vauras et al., 2003; Volet, Summers, et al., 2009).
Finally, AIRE does not aim at being only a data collection tool.
Contemporary educational research has shown that cognitive regulation processes
can be successfully promoted with different tools and scaffolds (Winne & Nesbit,
2009). But, although the importance of motivation and emotion regulation in
classroom learning is recognized, there are not many tools that focus on
scaffolding learners’ motivation and emotions. AIRE can also be useful in helping
learners to recognize covert emotional and motivational aspects that influence
learning. Awareness is a key feature in activating the use of regulation strategies
71
(Zimmerman, 2001). With AIRE, the assumption is that it is possible to provide
scaffolds for students’ motivation and emotions by prompting students’ awareness
of their situational emotions and the sources of these emotional experiences.
Furthermore, this awareness enables students to develop their self-regulatory
aptitude purposefully by bringing these aspects to their consciousness as they
work. In other words, AIRE can prompt learners to actively take charge of their
own motivation and emotional wellbeing (Boekaerts & Corno, 2005).
7.3
Final remarks and implications for future research
Self-regulated learning theory, employed to study the motivation to learn in
authentic situations, provided a valuable theoretical framework for this study.
Self-regulated learning models broadly cover learners’ cognitions, affect, and
motivational and behavioral aspects related to learning (Boekaerts et al., 2000).
The theory provided a comprehensive view of learning that considered learners as
active, participating human agents within a network of social systems (Bandura,
2001). For this study, it was important that the meaning of social interaction was
acknowledged because entering into a collaborative venture meant engaging in an
interpersonal exchange and continuous investment in constructing shared
meaning. The regulation of motivation and emotions within and between group
members differs from individual forms of regulation in that it is realized in
interactions and reciprocity.
However, the comprehensiveness of self-regulation models can be a source of
criticism as well. It can be argued that it is challenging, if not impossible, to
effectively cover a great deal in psychology (McKeachie, 2000). Can the selfregulation theory explain the learning process as broadly as it claims? It may be
that models that are too general and cursory fail to explain anything specifically
enough. Hence, research fails to provide exact findings that would be profitable in
practice. That is why researchers have to be accurate when implementing a
framework of self-regulation in empirical research. Different studies focus on
different viewpoints and constructs, which need to be acknowledged, when the
results are aggregated together into one large construct of self-regulation. Then,
perhaps the self-regulated learning models can be both broad and specific.
Moreover, even if there is a lot of research in the area of self-regulation in
general, and a fair amount on the regulation of motivation and emotions, studies
concentrating on how social and contextual factors facilitate and/or constrain
regulation processes have only just started to emerge (Hadwin, Järvelä, et al.,
72
2010; Pintrich, 1999; Vauras et al., 2008; Volet, Vauras, et al., 2009). Further,
little attention has been paid to how these processes vary in contextual, real-life
learning situations (Winne & Nesbit, 2009). This may be due to the fact that
research on self-regulation has mainly relied on static self-report instruments
instead of more dynamic (qualitative) measurements (Winne & Perry, 2000). This
trend has also been dominant in motivation research (however, see Nolen & Ward,
2008). Nevertheless, in reality, learning is a process that takes place in real,
concrete places where many different things are happening simultaneously and
where learners are real people with personal histories who interact with each other.
Critics have argued that empirically supported knowledge does not necessarily
translate into classroom practice (Murphy & Alexander, 2000; Pintrich, 2003).
Some people actually claim that many of the motivation constructs used do not
relate to real learning processes in classrooms. Therefore, the practical
implications of empirical research are weak (Boekaerts & Corno, 2005).
Hence, a key question is what can be done to ensure that teachers and
students benefit from research results? It is justifiable to say that, in practice,
teachers and students would benefit from well-developed emotional and
motivational skills. However, self-regulated learning skills, especially motivation
and emotion regulations, is often only superficially acknowledged in everyday
school life. Knowledge and results that are more concrete and measurable in the
short run than more vague goals undermine easily efforts to support students’
development to become self-regulated learners. This study explains why the
ability to regulate learning processes is an essential part of twenty-first century
learning skills. The results of the study provide reasons for teachers to consider
and apply teaching methods that foster students’ self-regulated learning. They
demonstrate how pedagogical designs that explicitly emphasize collaboration
between the students also provide possibilities to develop both individual and
socially shared regulations of learning. With AIRE, the study provided an
example of one possible way to increase both teacher and student awareness of
emotional and motivational aspects that are situation-specific and embedded in a
certain time and context.
Teachers can scaffold students’ motivation and emotional regulation only if
their pedagogical choices and teaching practices challenge the students to be
active participants and hence create possibilities to be regulative learners. This
study provided examples how different pedagogical structures challenge different
motivational or emotional aspects. With everyday practices and pedagogical
methods, teachers can equally create a classroom culture that enables self73
regulated learners to grow. However, creating a school culture that emphasizes
learning environments and pedagogical methods where the students’ opinions,
choices, activities, and responsibilities cannot be created only by individual
teachers. These aims need to be acknowledged in the school community as well.
Therefore, it is suggested that self-regulated learning should be articulated in
school curricula and expressed in everyday practices. For researchers, this poses a
challenge to continue studies in real-life school contexts in order to provide better
elaborated suggestions for practice.
In the future, one way to produce research knowledge that is more effective
for practitioners is to try to develop research designs and methods that capture the
learning process and students’ motivational expectations in real contexts.
Research designs that aim explicitly to increase students’ awareness of their
motivation and their role as active regulators of learning can effectively channel
new knowledge back into practice, as data are generated. Furthermore, teachers
can adopt ideas from these designs to plan pedagogical intervention, which
increase students’ motivation to learn. Methods such as AIRE can be used to
scaffold learners’ regulation processes and support them to become active agents
in their own learning. Hence, the development of AIRE and designs of empirical
studies that aim to influence students’ motivation have added to the practical
value of this dissertation.
Finally, this dissertation aimed to add to the field of motivation and selfregulated learning research. It argued that in social learning situations, the
regulation of motivation and emotions can be socially shared between the group
members if they have a common goal and engage within the group in the coconstruction of motivation. This socially shared regulation can exist parallel to
individual group members’ self-regulation processes.
It is hoped that the results of the studies contribute to the efforts to understand
motivation and emotion regulation as a socially constructed process. There is still
a lot to understand, such as the time and manner in which individual and group
regulations can be activated, scaffolded, and supported, or the point at which selfregulation processes start to compete with information processing and optimal
performance. These and many other important issues must be addressed in future
research. At the moment, it could be argued that well-developed motivation and
emotion regulation can improve the quality of learning at the individual and group
levels, and, most importantly, successful motivation and emotion regulation can
also increase general well-being in life. That is why it is excellent that these
74
strategies can be learned and improved. This dissertation is a concrete example of
this.
75
76
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Original articles
I
Järvenoja, H., & Järvelä, S. (2005). How students describe the sources of their
emotional and motivational experiences during the learning process: A qualitative
approach. Learning and Instruction 15(5), 465–480.
II Järvenoja, H., Volet, S. & Järvelä, S., (2010). Regulation of emotions in socially
challenging learning situations: An instrument to measure the adaptive and social
nature of the regulation process. Manuscript.
III Järvenoja, H., & Järvelä, S. (2009). Emotion control in collaborative learning
situations - Do students regulate emotions evoked from social challenges? British
Journal of Educational Psychology 79(3), 463–481.
IV Järvelä, S. & Järvenoja, H. (2011, in press). Socially constructed self-regulated
learning in collaborative learning groups. Teacher College Record.
V Järvelä, S., Volet, S., & Järvenoja, H. (2010). Research on Motivation in
Collaborative Learning: Moving beyond the cognitive-situative divide and combining
psychological and social processes. Educational Psychologist 45(1), 15–27.
Reproduced with permission from Learning and Instruction ©Elsevier (I), the
British Journal of Educational Psychology ©The British Psychological
Society
(III),
Teachers
College
Record
(IV)
and
Educational
Psychologist ©Routledge (V).
Original publications are not included in the electronic version of the dissertation.
89
90
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Rautio, Pauliina (2010) Writing about everyday beauty in a northern village. An
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OULU 2010
U N I V E R S I T Y O F O U L U P. O. B . 7 5 0 0 F I - 9 0 0 1 4 U N I V E R S I T Y O F O U L U F I N L A N D
U N I V E R S I TAT I S
S E R I E S
SCIENTIAE RERUM NATURALIUM
Professor Mikko Siponen
HUMANIORA
University Lecturer Elise Kärkkäinen
TECHNICA
Professor Hannu Heusala
ACTA
SOCIALLY SHARED
REGULATION OF MOTIVATION
AND EMOTIONS IN
COLLABORATIVE LEARNING
MEDICA
Professor Olli Vuolteenaho
SCIENTIAE RERUM SOCIALIUM
Senior Researcher Eila Estola
SCRIPTA ACADEMICA
Information officer Tiina Pistokoski
OECONOMICA
University Lecturer Seppo Eriksson
EDITOR IN CHIEF
Professor Olli Vuolteenaho
PUBLICATIONS EDITOR
Publications Editor Kirsti Nurkkala
ISBN 978-951-42-6329-3 (Paperback)
ISBN 978-951-42-6330-9 (PDF)
ISSN 0355-323X (Print)
ISSN 1796-2242 (Online)
U N I V E R S I T AT I S O U L U E N S I S
Hanna Järvenoja
E D I T O R S
Hanna Järvenoja
A
B
C
D
E
F
G
O U L U E N S I S
ACTA
A C TA
E 110
FACULTY OF EDUCATION,
UNIVERSITY OF OULU
E
SCIENTIAE RERUM
SOCIALIUM