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Socially shared regulation of learning (SSRL) has been recognized as a new and growing field in the framework of self-regulated learning theory in the past decade. In the present review, we examine the empirical evidence to support such a phenomenon. A total of 17 articles addressing SSRL were identified, 13 of which presented empirical evidence. Through a narrative review it could be concluded that there is enough data to maintain the existence of SSRL in comparison to other social regulation (e.g., co-regulation). It was found that most of the SSRL research has focused on characterizing phenomena through the use of mixed methods through qualitative data, mostly video-recorded observation data. Also, SSRL seems to contribute to students’ performance. Finally, the article discusses the need for the field to move forward, exploring the best conditions to promote SSRL, clarifying whether SSRL is always the optimal form of collaboration, and identifying more aspects of groups’ characteristics.
Socially Shared Regulation of Learning 1
Socially Shared Regulation of Learning: A Review
Ernesto Panadero 1 & Sanna Järvelä 1
Author Note
1 Department of Educational Sciences and Teacher Education. Learning and Educational
Technology Research Unit (LET), University of Oulu, Finland.
To cite this paper: Panadero, E., & Järvelä, S. (2015). Socially shared regulation of learning: A
review. European Psychologist. doi: 10.1027/1016-9040/a000226
Correspondence concerning this article should be addressed to: Ernesto Panadero. Departamento de
Psicología Evolutiva y de la Educación. Despacho 31. Facultad de Psicología. Universidad
Autónoma de Madrid, Cantoblanco, Madrid. 28049, Spain. Tel. +34 914973553 E-mail:
Acknowledgements: Research funded by the Finnish Academy, project name PROSPECTS (PI:
Sanna Järvelä).
Socially Shared Regulation of Learning 2
Socially shared regulation of learning (SSRL) has been recognized as a new and growing field in
the framework of self-regulated learning theory in the past decade. In the present review, we
examine the empirical evidence to support such a phenomenon. A total of 17 articles addressing
SSRL were identified, 13 of which presented empirical evidence. Through a narrative review it
could be concluded that there is enough data to maintain the existence of SSRL in comparison to
other social regulation (e.g., co-regulation). It was found that most of the SSRL research has
focused on characterizing phenomena through the use of mixed methods through qualitative data,
mostly video-recorded observation data. Also, SSRL seems to contribute to students’ performance.
Finally, the article discusses the need for the field to move forward, exploring the best conditions to
promote SSRL, clarifying whether SSRL is always the optimal form of collaboration, and
identifying more aspects of groups’ characteristics.
Socially Shared Regulation of Learning 3
Socially Shared Regulation of Learning: A Review
How students regulate their own learning through the use of strategies has been one
of the most important topics in educational psychology for the past decades. These studies
started receiving considerable attention after Flavell (1979) introduced the metacognition
theory, and this attention continued when self-regulation theories started to develop
(Boekaerts, Pintrich, & Zeidner, 2000; Zimmerman & Schunk, 2011). Currently there is a
strong consensus that successful learners use a repertoire of strategies cognitive,
behavioral, and motivational to guide and enhance their learning processes while
completing academic tasks (Schunk & Zimmerman, 2008). The mainstream of research on
self-regulation has focused on individual learning situations, but the notion that social
context is important in students’ self-regulated learning is evidenced in a wide range of SRL
researches, and research into social aspects of SRL has increased considerably in recent
years (Hadwin, Järvelä, & Miller, 2011).
Grounded in Zimmerman’s (1989) social cognitive model of self-regulation, research
has been guided by the principles that social context and environment play a reciprocal role
in self-regulated learning (SRL),which is embedded in social context and influence. SRL
research is also framed by sociocultural explanations: social interactions with others who are
more capable facilitate students’ development of SRL through internalizing the modeled
cognitive processes (e.g., Vygotsky, 1978). The premise of this research is that SRL is an
internal process, assisted and influenced by social interaction (e.g., Zimmerman, 1990).
Thus, it means investigating social support as an independent variable on SRL and
examining a wide variety of social supports, including modeling, scaffolding, and other-
regulation, such as support provided by peers, teachers, and parents (McCaslin & Hickey,
2001; Paris & Paris, 2001).
Socially Shared Regulation of Learning 4
The term co-regulated learning is grounded in Vygotskian views of higher psychological
processes being socially embedded or contextualized (Vygotsky, 1978) and Wertsch and Stone’s
(1985) notion that these processes are internalized through social interaction (McCaslin, 2009).
McCaslin and Hickey (2001) defined co-regulation as a manifestation of emergent interaction
within a zone of proximal development, and Volet, Vauras, and Salonen (2009) grounded the
concept of other-regulation in the Vygotsky (1978) notions of the Zone of Proximal Development
and scaffold guidance from other-regulation to self-regulation.
Recently, the concept of socially shared regulation of learning (SSRL) has emerged, which
occurs when groups regulate together as a collective, such as when they construct shared task
perceptions or shared goals. When groups co-construct plans or align monitoring perceptions to
establish a shared evaluation of progress, they are engaged in shared regulation (Järvelä, Järvenoja,
Malmberg, & Hadwin, 2013). SSRL involves interdependent or collectively shared regulatory
processes, beliefs, and knowledge (e.g., strategies, monitoring, evaluation, goal setting, motivation,
metacognitive decision making) orchestrated in the service of a co-constructed or shared outcome
(Winne, Hadwin, & Perry, 2013; Järvelä & Hadwin, 2013).
Interest in shared regulatory group processes has emerged since a change in pedagogical
practices in current learning environments. Past decades have witnessed the success of collaborative
learning, since it allows opportunities for shared knowledge construction and productive
collaborative interactions (Dillenbourg, 1999; Roschelle & Teasley, 1995). Information and
communication technologies as CSCL have fundamentally changed how people communicate,
collaborate, work, play, and learn but have also brought new challenges for group coordination,
argumentation, and engagement (Järvelä, Volet, & Järvenoja, 2010). Hadwin et al. (2011) claim that
regulated learning is the quintessential skill in collaborative learning. Working together means co-
constructing shared task representations, shared goals, and shared strategies. It also means
Socially Shared Regulation of Learning 5
regulating learning through shared metacognitive monitoring and control of motivation, cognition,
and behavior.
In sum, in the past decade there has been a shift in the SRL field: the role that collaborative
learning and CSCL environments imply for the regulation of learning is now a research focus (e.g.,
Järvelä et al., 2010; Vauras, Iiskala, Kajamies, Kinnunen, & Lehtinen, 2003). The focus in this
research line is on how the groups regulate their collaborative work and how this affects their
learning experience as a group. Currently, the concept of socially shared regulation is increasingly
being used in educational psychology literature and it is spreading to other related fields as well, for
example computer-supported collaborative learning (Kirschner & Erkens, 2013). Compared to other
regulatory concepts, such as SRL and co-regulation, the empirical evidence of regulatory processes
in collaborative learning this is to say, socially shared regulation of learning (SSRL) is still
minor and distributed. Our aim is to review all empirical research about the existence of SSRL to
find confirmation that it is a real construct that can be found in collaborative learning situations.
Even though the research is still limited, a review of current empirical evidence is needed to
increase conceptual clarity and find rigorous evidence of the phenomena.
Related Concepts of Social Aspects of Regulated Learning
In this section concepts which are closely related to SSRL will be discussed to clarify the
differences and connections to SSRL. Vauras and Volet (2013) use an umbrella concept of
‘‘interpersonal regulation’’ to explain the functioning of groups as complex and dynamic situational
interplays across different systemic levels (Volet, Vauras, & Salonen, 2009), showing that the study
of interpersonal regulation of learning is located at the articulation of individual and social
processes (Järvelä et al., 2010). Most conceptualizations of interpersonal regulation of learning
research have been inspired by Greeno’s (2006) situative learning framework which integrates the
individual and social perspective in ‘‘learning in activity’’ (Greeno, 2006, p. 92) and complements
Socially Shared Regulation of Learning 6
the interactional focus on participatory processes with a cognitive focus on information processes.
In those studies the concept of regulation has been used to describe the social processes the groups
use to regulate their joint work on a task (Rogat & Linnenbrink-Garcia, 2011) or the nature and
processes of collaborative interactions (Volet, Summers, et al., 2009), and the conceptualization of
regulation has been used as productive engagement in collaborative interactions.
Other fields of interest to regulation of learning derive from sociocultural learning theory
and the Vygotskian perspective. Concepts such as co-regulation and other-regulation have been
used to explain the transitional processes toward self-regulation. According to McCaslin and
Hickey (2001), the social system that individuals are part of is assumed to provide affordances and
constraints for members to fully engage, to stay at the periphery until ready, or alternatively to
avoid engagement. For example, Vauras and colleagues’ studies on socially shared co-regulation
(e.g., Salonen, Vauras, & Efklides, 2005; Vauras et al., 2003) point to the social context as the
developmental source of self-regulation, and provide support for the contention that teacher
scaffolding, involving an emphasis on collaborative learning and opportunities for co-regulation,
provided an appropriate context for students to learn and deploy academic regulatory strategies.
The concept of metacognition is also related to the discussion of regulated learning.
Dinsmore, Alexander, and Loughlin (2008) have discussed the clarity of meaning of metacognition,
self-regulation, and self-regulated learning that are often used in parallel, even though they are
different phenomena. The three concepts involve individuals’ monitoring and regulation of their
learning, but the articulation of conceptual boundaries between these terms is overlapping. This is
the case also when considering metacognition in social aspects of regulated learning. Metacognition
researchers have acknowledged the role of peers and more knowledgeable others in mediating and
sharing metacognitive knowledge (Brown, 1987; Goos, Galbraith, & Renshaw, 2002). For example,
Artz and Armour-Thomas (1992) examined the role of metacognition in small-group mathematical
problem-solving by tracking individual students’ cognitive and metacognitive behaviours and
Socially Shared Regulation of Learning 7
concluded that successful group problem-solving requires the constant interplay of cognitive and
metacognitive processes, and individuals competent enough to adapt the metacognitive statements
to the process. Recently, researchers have described and operationalized metacognition at peer
interaction or group level, and concepts such as socially shared metacognition (Hadwin, Oshige,
Gress, & Winne, 2010; Hurme, Merenluoto, & Järvelä, 2009; Iiskala, Vauras, & Lehtinen, 2004) or
socially shared metacognitive regulation (Iiskala, Vauras, Lehtinen, & Salonen, 2011) have
emerged in reference to regulation of cognitive processes in interactive learning tasks. In these
studies, the central idea has been that group members monitor and control each other’s actions to
advance the group’s problem-solving.
In this review the studies that have explored socially shared metacognition and socially
shared metacognitive regulation have also been included for our analysis. This was done on the
basis that SSRL also embraces the cognitive and metacognitive aspects of the group activity and,
therefore, the inclusion of these studies offers a more complete picture of the regulation at the group
Identified Challenges in the Field
In spite of increasing interest in SSRL, three identified challenges emerge in this research
area. The first challenge is dealing with conceptual clarity issues. There seem to be considerable
differences in how authors and research teams define and operationalize social aspects of self-
regulated learning, such as self-regulation, co-regulation, other regulation, high-level co-regulation,
shared metacognition, self in social setting regulation, and socially shared regulation, which have
been applied in recent theoretical and empirical discussions, and there still seems to be a lack of
congruence (e.g., Dinsmore et al., 2008).
Secondly, during the past few years, researchers involved in collaborative learning and
CSCL research (Hmelo-Silver & Barrows, 2008; Kirschner & Erkens, 2013) and self-regulated
Socially Shared Regulation of Learning 8
learning research (Hadwin et al., 2011; Volet, Vauras, et al., 2009; Winne et al., 2013) have worked
in parallel to investigate ‘‘regulation of learning,’’ which has resulted in concepts which partly
overlap, but still have various conceptual and empirical foci. For example, collaborative learning
research and computer-supported collaborative learning research have targeted the general level of
regulation of social interactions and knowledge co-construction processes (Saab, 2012). Research
on team learning has introduced the concept of task regulation, with a focus on task and domain-
specific regulation (Saab, van Joolingen, & van Hout-Wolters, 2012), and the concept of team
regulation, focusing on social aspects of team formation (Fransen, Kirschner, & Erkens, 2011;
Fransen, Weinberger, & Kirschner, 2013).
The third challenge deals with methodological development. Research methods, which
consider the interplay between individual and social processes as they unfold in authentic activity
(Greeno, 2006), are still in their infancy. Even though there are new and promising methodological
opportunities for studying interpersonal regulation (see Vauras & Volet, 2013), the lack of
empirical findings may derive from inadequate methods, which focus either on individual
regulatory activities or on social and collaborative interaction processes. For example, Järvelä and
Hadwin (2013) have identified that current empirical research is obscure to differentiate shared
regulation from shared knowledge construction, mostly because of a lack of methods and analytical
techniques for examining individual and collaborative performance outcomes associated with
interactional processes. These three challenges will be addressed through the empirical review
conducted in this paper.
Aim and Research Questions
The aim of this review is to analyze the empirical evidence that supports the theoretical
concept of socially shared regulation of learning (SSRL) including the related terms socially shared
Socially Shared Regulation of Learning 9
metacognition and co-regulation when used with the purpose of distinguishing among qualitative
different types of social regulation in collaborative learning. Our research questions are:
a) What are the main characteristics of SSRL?
b) Can different levels of social regulation be identified (SSRL vs. co-regulation)?
c) What is the relationship of SSRL and other studied learning variables?
d) What are the salient features of SSRL research?
While answering these questions we will identify the following features of SSRL research:
type of study, sample, subject or task, type of data, data analysis, procedure, and main results. We
will also consider the limitations of the current research and discuss where the field should move
Criteria for Inclusion
Studies from different disciplines were reviewed and included or rejected based on their
relevance. First, a study was considered relevance to our research goals if it contained empirical
data on the existence of socially shared regulation of learning or related concepts such as socially
shared metacognition, shared regulation, or high-level co-regulation. Articles with theoretical
arguments were considered if they addressed crucial aspects for the development of the field and
their conclusions were based on empirical research. Second, the selection was limited only to
printed and peer-reviewed material, such as articles in journals, edited books, research reports, and
doctoral dissertations. Third, articles had to be written in English.
Search Keywords, Databases, and Selection Process
A first literature search was conducted in October 2012 via the PsycINFO, ERIC, and
Thomson Reuters Web of Knowledge databases with no limitation on the year of publication. The
Socially Shared Regulation of Learning 10
following keywords were used: socially shared regulation (SSRL), socially shared metacognition
(SSM), co-regulation, and social regulation. A total of 16 hits were found for SSRL, 8 hits for SSM,
83 hits for co-regulation, and over 5,000 for social regulation. All hits for SSRL and SSM were
selected for further exploration, five of them being repeated hits. To obtain hits with a more specific
scope in the 5,000 hits group, new searches were performed using co-regulation and social
regulation adding the terms: educational psychology and educational research. This reduced the hits
to 75 for co-regulation and 145 for social regulation which were analyzed.
In the following step the authors read all the selected abstracts. When a decision could not
be taken whether the article had relevant information by reading the abstract alone, the Results and
Discussion sections were also read. The main reason for rejecting articles was that they focused on
aspects other than our research aim. A significant number of articles addressed aspects of co-
regulation in relation to the parental relationship 59, breastfeeding , or development at early
childhood stages 23. Therefore, out of the 225 articles from the co-regulation and social
regulation search, 5 were selected for a complete reading adding to the 19 articles coming from the
search using SSRL and SSM. Finally, out of those 24 selected articles only 10 addressed empirical
evidence related to our research aim.
Finally, the ‘‘snow-ball’’ method was used which consists of selecting new articles that
could be of interest based on the content and references of the articles already chosen. Using this
method six additional articles (three theoretical and three empirical) were included. In February
2013 a new search was conducted using only three of the keywords (socially shared regulation,
socially shared metacognition, and co-regulation) finding the same hits. In June 2014 the procedure
was repeated and one additional article was included in the review.
Socially Shared Regulation of Learning 11
Method of Analysis
Due to the fact that the socially shared regulation field has just recently been developed, this
review is of a qualitative nature, the approach adopted being narrative content analysis (Dochy,
2006). The main purpose in terms of our analysis is to identify patterns in the research on the field
and whether it can be concluded that, based on the existent empirical evidence, socially shared
regulation theoretical concepts can be maintained. The possibility of conducting a meta-analysis
was excluded as there are a restricted number of studies on the topic and most of them explore the
phenomenon using qualitative approaches.
The selected articles were read and coded to explore their relevance for this study aim.
Different information was extracted and included in a table (see an abbreviated version in Table 1):
type of study, sample, subject/task, method/type of data, data analysis, procedure, results, and
evidence on SSRL. Then the information was contrasted to find research patterns, to extract
conclusions from the studies, and to judge the direction of future research.
A total of 13 of the 17 selected articles presented empirical data on the existence of SSRL.
We next describe these results organized around two sections: evidence on SSRL and features of
Evidence on SSRL
All of the empirical articles excluding the two reviews and the three theoretical papers
show empirical evidence on the characteristics of SSRL (see Table 1). In particular, the results point
to a distinguishably collaborative work regulation level called socially shared regulation or socially
shared metacognition. Seven of the articles differentiate between co-regulation and SSRL in terms
Socially Shared Regulation of Learning 12
of the latter being a more collaborative approach to group work (e.g., Volet & Mansfield, 2006),
while the other half just characterize SSRL without presenting empirical data about co-regulation or
other types of regulation (e.g., Iiskala et al., 2011). When considering different aspects of the
evidence on SSRL, we will first present how SSRL is characterized from the reviewed studies, as
expressed in our first research question. Second, we will focus on the studies comparing SSRL and
co-regulation to answer our second research question. Third, we will analyze what is the interaction
of SSRL with other studies’ learning variables. Finally, we will analyze the evidence on the
relationship between SSRL and performance. These two last sections will answer our third research
Characterizing SSRL
One of the most important features of the SSRL research is to analyze how SSRL happens
in collaborative work. It is a common practice for SSRL papers to present examples, mostly verbal
interactions, regarding how the groups worked, making visible how the collaborative process
developed. The most salient features of SSRL that have been identified are in terms of shared
regulatory activities: (a) joint cognitive and metacognitive regulatory strategies (e.g., planning) and
(b) group motivational efforts and emotion regulation. We will analyze them next in further details.
The first mentioned feature of SSRL, the use of joint cognitive and metacognitive regulatory
strategies, can be found in one of the earliest works in the field, Iiskala et al. (2004). They found
evidence on how high-achieving dyads regulated their joint cognitive constructions by shared
monitoring of their progress and adapting their performance. The authors analyzed the dyads’
interactions through flowcharts using two types of arrows to differentiate between interindividual
metacognitive actions and interindividual cognitive actions. They concluded that interindividual
metacognition was an observable phenomenon and that the dyads could monitor and regulate their
performance jointly. In a similar fashion, Hurme, Merenluoto, Salonen, and Järvelä (2014) found
Socially Shared Regulation of Learning 13
that six triads used different regulatory strategies named metacognition, verifying, implementation,
exploration, analysis, among other strategies at the group and task level. They concluded that
socially shared metacognition was a ‘‘differentiator making problem solving successful in groups’’
(p. 28). Similar cognitive and metacognitive shared strategies traces can be found in Iiskala et al.
(2004), Volet and Mansfield (2006), Hurme et al. (2009), Volet, Summers, et al. (2009), Iiskala et
al. (2011), Järvelä and Järvenoja (2011), Rogat and Linnenbrink-Garcia (2011), Grau and
Whitebread (2012), Janssen, Erkens, Kirschner, and Kanselaar (2012), DiDonato (2013), Järvelä et
al. (2014), and Hurme et al. (2014).
Second, the characteristics of shared regulation of motivation and emotion have also been
explored. For example, Rogat and Linnenbrink-Garcia (2011) analyzed six groups’ collaboration in
three different tasks exploring the role of emotions on SSRL. They included the following
categories in their analyses (which had different subcategories): social regulation, positive
socioemotional interactions, negative socioemotional interactions, collaborative interactions, and
non-collaborative interactions. They concluded that ‘‘Negative socioemotional interactions also
appeared to diminish the quality of social regulation’’ (p. 410), the more interactions with negative
valence the more problems for the group and for SSRL to occur. Additionally, Volet and Mansfield
(2006) found that the two analyzed groups shared regulated motivation and emotion in different
fashion depending on the group members personal goals. As an example, they found groups using a
contract to motivate members that were not collaborating. Also, Järvelä and Järvenoja (2011)
explored shared regulation of motivation in four groups of four members each. They found that the
students activated a number of joint motivation regulation strategies (e.g., social reinforcement),
which were used and enhanced by the interactions between the group members. Other empirical
articles that have addressed emotional and motivational aspects of SSRL are: Volet, Summers, et al.
(2009), Grau and Whitebread (2012), indirectly Janssen et al. (2012), and Järvelä et al. (2014).
Socially Shared Regulation of Learning 14
Evidence of Different Levels of Social Regulation: SSRL Versus Co-Regulation
In this section we analyze the empirical evidence on the comparison of SSRL and co-
regulation and if they unfold different collaborative processes. Again, one of the problems is in the
use of the terminology (e.g., co-regulation is not always named that way). Five of the empirical
articles included in this review show direct show direct empirical evidence of the comparison SSRL
and co-regulation. In addition two other articles (DiDonato, 2013; Janssen et al., 2012) show
indirect empirical evidence of qualitative different types of social regulation. Next we present in
detail the five studies showing the direct evidence.
First, Volet and Mansfield (2006) compared two small groups (size of the groups is not
reported) of 3rd year Business students, using interviews and a questionnaire on Students’
Appraisals of Group Assignments (SAGA). They identified two forms of regulation that reflected
the differences in the groups that were influenced by the members’ goals for the task.
‘‘Overall, the two small groups of students reflected two distinct mind-sets and related
regulatory approaches. Students with negative appraisals and an exclusive focus on
performance tended to be more self-centered and saw group assignments in terms of
themselves within the group. Consistent with that approach, their regulatory strategies (often
maladaptive to the group activity) displayed elements of control, direction and
empowerment. In contrast, students with positive appraisals and multiple goals
(performance, social and learning) were at least in part, focused on group learning outcomes.
They perceived group assignments in terms of group dynamics and their regulatory
strategies reflected facilitation, modeling and empowerment’’ (p. 13).
The most adaptive type of social regulation was named as ‘‘self-regulation in cooperation.’’
Therefore, there are three main findings for this review research purposes research purposes: (a)
they identified different levels of social regulation, (b) one of the two levels showed better effects
Socially Shared Regulation of Learning 15
on the group collaboration, and (c) they explored the effect of different types of goals on the
occurrence of SSRL.
Second, Volet, Summers, et al. (2009) identified different levels of co-regulation in 18
second year veterinary students (groups of six members). There are two aspects to remark before we
present their findings. First, Volet, Summers, et al. (2009) presented a theoretical framework with
four areas (p. 131) based in two continuums: Individual regulation versus Co-regulation, and Low-
level knowledge constructions versus High level. Second, what they are referring to as high co-
regulation is a close concept to SSRL (e.g., page 131). Their two main conclusions were that (a) it
was possible to find evidence of the four areas, meaning that it is possible to differentiate among
different types of social regulation, and (b) there is a higher level of co-regulation characterized by
the use of joint regulatory activities and higher knowledge construction, which aligns with what
other researchers would name SSRL.
Third, Rogat and Linnenbrink-Garcia (2011), of which we have already presented some
findings, found differences in the quality of social regulation identifying that positive
socioemotional interactions ensured more informal ways of giving feedback and monitor as a group.
This produced differences in the groups’ activation of cognitive and behavioural regulation which
resulted in high-quality regulation if the groups had interactions with positive valence. In sum, they
found evidence for different levels of social regulation and explored the influence of the
socioemotional interactions valence in the occurrence of SSRL: if the valence was positive the joint
activity increased.
Fourth, Grau and Whitebread (2012) observed the interactions of eight 3rd graders while
working in two groups during five sessions. The authors explored the intentionality of actions as
categorized in three levels: self-regulation, co-regulation, and shared regulation. The main findings
were that (a) individual and social regulation are related, (b) primary students are already able to
engage in shared regulation actions, (c) two categories of social regulation could be identified, and
Socially Shared Regulation of Learning 16
(d) shared regulation led to higher ‘‘talk about essential aspects of the task, such as relevant
knowledge’’ (p. 408) which could lead to higher learning.
Fifth, Järvelä et al. (2013) identified three types of SSRL in 18 graduate students working as
triads. They did not consider co-regulation, but identified strong, progressive, and weak SSRL
processes. The main findings were that (a) groups with different profiles reported different types of
learning challenges, (b) there were differences on the type of shared strategies the groups used
(more deep strategies in the strong SSRL), and (c) there seems to be a relationship between the type
of SSRL and performance.
In sum, these five studies have identified different levels of social regulation, ranging from
more collaboration and shared regulation activities, to less joint work and use of strategies.
Following Grau and Whitebread (2012) and theoretical proposals (e.g., Hadwin et al., 2011), we
will name to the first type SSRL and to the second co-regulation, in the discussion section where
these results will be further analyzed.
Evidence on the Interaction of SSRL and Other Learning Variables
There are four variables that have been studied in relation to SSRL: goals (Volet &
Mansfield, 2006), feelings of difficulty (Hurme et al., 2009), content processing (Volet, Summers,
et al., 2009), and performance (see the next section for the latest research). First, Volet and
Mansfield’s (2006) study indicated that the appearance of different types of social regulation (co-
regulation and SSRL) was triggered by different goals: co-regulation was triggered by individual
and control goals and SSRL by collaborative goals. They explained these results as ‘‘during group
activities, personal goals and perceptions of teaching and group contexts interacted dynamically to
produce regulation strategies compatible with goal pursuits’’ (Volet & Mansfield, 2006, p. 12).
Nevertheless, there is still a need for more research into how different goals (individual or
group-related) might trigger SSRL. Second, Hurme et al. (2009) explored whether engaging in
Socially Shared Regulation of Learning 17
socially shared regulation helped the students to feel tasks were less difficult for which they found
empirical evidence. Their main conclusion is that when students engaged in socially shared
metacognition, their experience of difficulty in the task decreased. Volet, Summers, et al. (2009)
studied two separate but related concepts: social regulation and content processing. Each had two
continuums: social regulation could move between individual self-regulation and group co-
regulation, while content processing could move between low-level knowledge acquisition and
high-level construct meaning. One of their findings was that high-regulated groups showed a higher
level of construct meaning, but they left the door open for interpretation on the causal direction of
this relationship: “ is impossible to ascertain whether participation in high-level co-regulation
lead to greater academic performance, or whether higher-performing students had already
developed interactional styles that emphasised high-level co-regulation…” (Volet, Summers et al.,
2009, p. 141).
Only three studies (Janssen et al., 2012; Järvelä et al., 2013; Volet, Summers, et al., 2009)
explored directly whether SSRL produces better learning outcomes, and one additional article
shows indirect evidence about this relationship (Grau & Whitebread, 2012). While two of the
studies found that the groups showing the highest levels of social regulation hence SSRL were
those with higher performance (Janssen et al., 2012; Volet, Summers, et al., 2009) the other
outlined similar results, but without a detailed discussion on the relationship (Järvelä et al., 2013).
The fourth article (Grau & Whitebread, 2012) shows that shared regulation led to higher reflection
on the most important features of the task. In sum, these four studies show a relationship between
higher levels of social regulation SSRL and group performance and learning.
Socially Shared Regulation of Learning 18
Features of SSRL Research
Next, we analyze features of the SSRL research to offer a clearer picture of the field, in
order to answer our fourth research question.
The reviewed empirical studies include participants from primary education (five studies),
middle school (one study), secondary education (one study), and higher education (six studies),
therefore there is evidence of SSRL from a broad range of educational levels. Additionally, a line of
research has focused on analyzing high-achieving students, mainly dyads, and characterizing how
they collaborate (Iiskala et al., 2004, 2011; Vauras et al., 2003).
Subject or Task
The following subjects have been explored: science (one study), business (one study),
veterinary physiological principles (one study), history (one study), interdisciplinary project (one
study) educational psychology (two studies), and mathematics (six studies). Therefore, the
occurrence of SSRL has been explored in relation to a variety of tasks, with a special focus in
mathematics. Nevertheless, there is almost no discussion in the existing research about the
importance of collaboration for those tasks. In other words, it is not stated why/how collaboration is
crucial in those activities, how the collaborative tasks were designed and, therefore, whether SSRL
would be crucial in a real classroom setting. In addition there are a significant number of studies
conducted using CSCL environments.
Method and Type of Data
The reviewed studies show a clear tendency in the SSRL field toward mixed methods using
qualitative data, mostly video-recorded observation data. Only two articles employed a
questionnaire in combination with interview (Järvelä & Järvenoja, 2011; Volet & Mansfield, 2006)
and another article combined questionnaires and a case study (DiDonato, 2013). Since the majority
Socially Shared Regulation of Learning 19
of studies have aimed to characterize SSRL, the methodology is based on observation and analysis
of cases as, through that data, it is possible to identify how SSRL occurs and what its features are.
In terms of the research design, all the studies were descriptive, with most of them using
naturalistic tasks embedded in the curriculum. There were no experiments or quasi-experiments
with control groups. The lack of this type of research is an important flaw, but at the same time,
now that the SSRL phenomena have been characterized it might be time to start aiming for
interventions in either controlled or natural contexts to determine the key factors that promote the
appearance of SSRL.
Data Analysis
The type of data collected aims for analysis of groups’ interactions by means of
sociocultural discourse, verbal transactions, nonverbal communication, and content analysis. The
video data was coded and analyzed, aiming to explore the social aspects of the interactions. One
example can be found in Iiskala et al.’s (2011) study in which they used different interaction
flowcharts and presented two types of arrows, one for interindividual metacognitive actions and
another for interindividual cognitive actions, as mentioned earlier. Another example would be the
study by Volet, Summers, et al. (2009) based on four categories of social interaction: high-level co-
regulation, high-level individual regulation, low-level co-regulation, and low-level individual
regulation. These coding systems are representative of how the different researchers conceptualize
the socially shared regulation phenomenon.
Size of the Groups
One remarkable aspect of SSRL research is the lack of discussion about group size: it has
never been discussed in the reviewed literature why one group size is used and not another, or
whether there is an ideal number of participants for SSRL to occur. Nevertheless, there is a wide
range in the size of the groups in the existing literature (Table 1): dyads (three studies), triads (four),
Socially Shared Regulation of Learning 20
four members (three), six members (one), and non-stated (one). It can be extracted, then, that SSRL
can be identified in the smallest collaboration a dyad up to big groups at least six members.
The aim of this article was to review the empirical evidence on socially shared regulated
learning (SSRL) including socially shared metacognition. We had four research questions: (1) What
are the main characteristics of SSRL, (2) Can different levels of social regulation be identified
(SSRL vs. co-regulation), (3) What the relationship of SSRL and other learning variables is, and (4)
What the salient features of SSRL research are. Next we present our conclusions including
limitations of the existent research, limitations of this review and future lines of work.
Main Characteristics of SSRL
As conclusion, the empirical articles reviewed characterized SSRL as the joint regulation of
cognition, metacognition, motivation, emotion, and behavior. Traces of SSRL can be found in the
collaboration of different size groups (from dyads to six-member groups) in the same just
mentioned processes that the self-regulation field has explored (e.g., Panadero & Alonso-Tapia,
2014; Zimmerman & Moylan, 2009). In that sense the model introduced by Hadwin et al. (2011;
Järvelä & Hadwin, 2013) is a coherent proposal to develop the SSRL field as it comprehends the
same processes.
One important aspect for the SSRL field is the lack of a consistent use of the terminology.
The two most common terms have been socially shared regulation (e.g., Hadwin et al., 2011;
Järvelä et al., 2013) and socially shared metacognition (e.g., Hurme et al., 2009; Iiskala et al.,
2004). In some cases these terms have been used interchangeably, and there is a need to consider
that both might have been used for purposes other than their original theoretical foci. According to
Dinsmore et al. (2008), there are some parallelism between the concepts of self-regulated learning
Socially Shared Regulation of Learning 21
and metacognition: the first one usually emphasizes, in addition to cognition, the importance of the
emotions and motivation, while the second aims more at cognitive processing. Here we propose a
similar use: socially shared metacognition could be used when the study covers exclusively aspects
of cognition and metacognition and socially shared regulated learning (SSRL) when additionally
motivational and emotional aspects are analyzed.
SSRL Versus Co-Regulation
Our second research question addressed the possible distinction of two levels of social
regulation. Is there empirical evidence that differentiates between co-regulation and SSRL, and
what would those differences be? Five of the studies showed direct evidence, and two additional
studies indirect evidence. Therefore, it can be maintained that regulation of learning in collaborative
situations shows different levels and characteristics. Additionally, the reviewed studies show that
there are at least two types of collaborative regulation of learning. First, an unbalanced regulation of
learning usually known as co-regulation in which one or more group members regulate other
member’s activity. Second, a more balanced approach to collaborative learning in which the group
members jointly regulate their shared activity usually known as SSRL or socially shared
metacognition. The differences among both types have been described in great detail in the existent
research in terms of cognitive, metacognitive, motivational, and emotional aspects.
In theory, Hadwin et al. (2011) argue that learners self-regulate, co-regulate, and share their
regulation of learning whenever they work on shared tasks. Instead of investigating co-regulation
and SSRL as different phenomena, the roles of self-regulation, co-regulation and SSRL should be
considered as built into each other (see e.g., Grau & Whitebread, 2012). The idea that we want to
express here is that, even if SSRL seems to have more learning benefits, it can still be the case that
co-regulation occurs also in some periods in groups that mostly socially shared regulate (SSRL).
Socially Shared Regulation of Learning 22
This would be the case as groups progress through different phases on their collaboration and not
always SSRL nor will co-regulation happen in isolation.
A clearer use of the terminology is again needed. The most common has been naming co-
regulation to the less shared balanced type of regulation, and SSRL to the joint one. The field is still
growing, and the terminology could change, but new studies should consider this taxonomy if they
are presenting new categories so that the new ones are easily adapted to the existing framework.
SSRL in Relation to Other Learning Variables
The results from three studies show the tendency for SSRL to increase group performance
and a fourth study indirectly shows evidence also for individual learning. This is a crucial finding,
as use of more learning strategies or self-regulation does not always lead to higher performance
(e.g., Panadero, Alonso-Tapia, & Huertas, 2012; Panadero, Alonso-Tapia, & Reche, 2013), and
therefore SSRL could have counter-effects which would have not yet been identified. Nevertheless,
the number of studies that have explored the effect of SSRL on performance is surprisingly low. We
consider it crucial for the incoming research to provide more evidence on this effect, to establish
whether SSRL promotes higher performance in group tasks. There is then a need to clarify whether
socially shared regulation always benefits learning and/or under what circumstances this happens.
Therefore, our call for is that future research should include measures of performance as a way to
validate the relevance of SSRL for students’ learning.
With regard to the other three learning variables that have been explored (goals, feelings of
difficulty, and content processing) it is precarious to extract conclusions as each of them has only
been studied once. Three aspects seem to us of major importance in the future research. First,
exploring how the individual goals that each member brings to the group affect the occurrence of
SSRL, in line with Volet and Mansfield (2006) research. Second, what type of shared goals groups
construct and if the individual goals taxonomy applies to the group work situations (e.g.,
Socially Shared Regulation of Learning 23
performance, avoidance, and learning). Third, the socioemotional variables seem to have a role in
SSRL (Järvelä et al., 2013), but has not been much investigated.
Salient Features of the SSRL Research
The SSRL research has used descriptive data. The existing studies have mainly explored the
existence and characteristics of socially shared regulation, and for that purpose, observing what
groups actually do is a key research method. The aim of these qualitative approaches is to explore
social interactions and exchanges, and that is the type of data that supports those analyses. These
methodological advances to conduct research on interpersonal regulation (see Volet & Vauras,
2013) have potential for unfolding the individual and social interaction processes of regulation in
learning. However, there is a challenge in developing validated instruments and analytical
techniques to move the field forward using methods that could answer research questions other than
those already answered. Future research should conduct experiments or quasi-experiments because
without control groups it is difficult to determine (a) the real learning gains, (b) how to better
differentiate SSRL from co-regulation, and (c) the key factors that trigger SSRL occurrence.
Compared to the traditional self-regulated learning research (Boekaerts & Corno, 2005), a
low number of self-report tools have been applied in SSRL research. Only two questionnaires have
been used in SSRL research so far: SAGA (Volet & Mansfield, 2006) and AIRE (Järvenoja, Volet,
& Järvelä, 2012). Nevertheless, even though self-reports present some limitations when used to
measure students’ strategy use, they could be valuable to add information to the process data which
is the main information collected in SSRL. For example, questionnaires could be used to ask the
students about their collaborative skills perceptions of group work and to explore what aspects they
consider fundamental to engage SSRL. In sum, at this point, self-report data could amplify our
understanding of SSRL and serve to answer new research questions.
Socially Shared Regulation of Learning 24
Limitations of This Review
One limitation is that the SSRL is a new field. The first study dated to 2003. Even if since
2009 there has been a considerable increase in the number of publications, there is still a low
number of studies exploring SSRL. Therefore, our conclusions should be put into context of future
studies to come.
Another limitation is the nature of the empirical evidence available. Most of the studies are
descriptive in essence. This lack of empirical research impedes causal attributions, and when using
correlational data, as the one analyzed here, the conclusions have to be done with care. Therefore,
there is still a need for more research especially using experimental designs to ensure controlled
Practical Implications
The main implication for teaching purposes from this review is that teachers should promote
learning environments leading to SSRL collaborative work. Unfortunately, the environmental and
pedagogical factors that trigger SSRL have not been explored in enough details yet. Nevertheless,
we will present some ideas that could be beneficial for SSRL occurrence. First, teachers should
encourage working groups to have shared responsibility for their actions and equal power
relationships. If one student takes the role of leader with negative consequences (e.g., ordering to
the other group members what to do) there would be less shared decisions. Second, teachers should
provide opportunities for the groups to plan, monitor, and evaluate their work (Järvelä et al., 2014).
This can be done using tools (e.g., rubrics), modeling the groups and allocating time for the groups
to plan and evaluate their work before and after the performance. Third, teachers should point out
that the group processes (e.g., members’ motivation) are also part of the activity. Giving attention to
these types of processes would make them more salient and students would start paying attention
not only to the final outcome but also to the collaboration itself.
Socially Shared Regulation of Learning 25
First General Line of Future Research: Self-Regulation at the Personal Level and Other
Individual Characteristics
As Winne, Hadwin, and Gress (2010) claim, little attention has been paid in the CSCL
research to the resources each group member brings to a collaboration: prior knowledge, task-
relevant information and cognitive processes. This claim is also transferable to the current situation
in SSRL research. The studies analyzed in this review (except for Grau & Whitebread, 2012) do not
explore how different individual variables might promote or disturb the occurrence of SSRL.
Among these, it seems of special relevance to explore how individual self-regulation skills affect
the collaborative work, thus SSRL. For example, can SSRL emerge in groups in which students
have low individual self-regulation? Our claim is that for SSRL to fully emerge, the group members
need to have advanced self-regulation skills, as it is more difficult to regulate at the group level than
at the individual one (Winne et al., 2013). Actually, there are a number of SSRL studies in which
the sample was composed of advanced students (e.g., Vauras et al., 2003), therefore this seems to be
an important area for future research.
Another important individual characteristic for SSRL is the group members’ individual
social skills and how this affects the collaboration. Previous research on the topic has already
pointed out that students perceived as leaders might contribute to different types of group regulation
(Salonen et al., 2005). Also group dynamics of collaboration (Salomon & Globerson, 1989) should
be considered, since if one student feels and is perceived as more of an expert, SSRL might not
happen, as the other group members might consider it better to follow the ‘‘expert’s’’ guidance.
This point was approached theoretically by Salonen et al. (2005) under the name of asymmetry:
‘‘Our study with collaborating peers provides some evidence, but peer relations are different from
teacher-student relations, where there is asymmetry in social status in the group as well as in the
cognitive and motivational background’’ (p. 206).
Socially Shared Regulation of Learning 26
In conclusion, the main idea that we want to transmit here is that, even if the group is a
separate entity different from the students working in isolation, it is also the sum of all its members
(Dillenbourg, 1999). Looking at the different members’ individual characteristics can be crucial to
better understand how and when SSRL happens. For example, aspects such as friendship, emotional
security, or interdependence, might be crucial for the activation of SSRL strategies within the
groups. Therefore, looking not only at what happens during the collaboration but also what the
students bring to the interaction will help us clarify how to promote SSRL.
Second General Lines of Future Research: The Importance of the Learning Task and
Developing Interventions
There are two other aspects that SSRL researchers could explore in more detail. First, there
is a lack of argumentation regarding why the different tasks were chosen for the studies. Actually,
the tasks used varied from computer-supported collaborative learning to peer learning tasks or
group tasks. It is not clear in these studies whether the task definition was such that the students had
a real need to collaborate and share their ideas (Dillenbourg, 1999). The task type and the degree of
coordination of shared activities (Barron, 2000) is crucial if we want to promote SSRL. Therefore,
argumentation about the type of task chosen is needed in future SSRL research. A second aspect is
the implementation of interventions to enhance SSRL. The current research has characterized the
phenomenon, but there are no studies implementing an intervention to promote SSRL and
comparing with a control group. With the findings from this review in mind, implementing SSRL
interventions would be a positive step to increase groups’ performance. Another step is to conduct
interventions that scaffold and support dynamics that promote SSRL. This has potential especially
in the field of CSCL, since group processes are at the center of CSCL and the opportunities to
support regulatory processes exist in technology that is already available (Järvelä et al., 2014).
Socially Shared Regulation of Learning 27
Third General Line of Research: On the Comparison of SSRL Versus Co-Regulation
Including Developmental Aspects
This review indicates that there are different types of social regulation that occur in
collaborative learning (Hadwin et al., 2011). Future research needs to continue clarifying what are
the characteristics of each SSRL and co-regulation, in addition to the ones presented here. For this
comparison the developmental aspects of the students should be taken into account, not only age but
also the expertise in the task. First, more clarification is needed if and how different group age
students shared their regulation. In the studies reviewed here there is a big range in age groups but
there is not a developmental approach explaining what the role of age is for SSRL. Second, it could
be the case that students need to have some expertise on the task at hands or previous experience in
collaborative tasks for SSRL to occur. Third, more ambitious efforts need to be undertaken to reveal
what could be the impact of individual development of self-regulatory skills on the occurrence of
SSRL when working in teams.
Fourth General Line of Research: A Call for Theoretical Clarification
There are two main areas where more conceptual clarification is needed. First, SSRL
scholars should address in more depth what are the implications of Vygotsky’s and sociocultural
research works for SSRL. Even if this discussion goes beyond the scope of most of SSRL empirical
papers the field would benefit from establishing the connections between SSRL and Vygotsky’s
work. One of the benefits could be a better understanding of the developmental aspects needed for
optimal SSRL. Second, a more thoughtful use of the terms socially shared metacognition and
socially shared regulation would also help on the development of the field as has already been
argued in the Discussion section.
Socially Shared Regulation of Learning 28
General Conclusions
Based on the empirical evidence available our recommendation is that future lines of
research should not focus exclusively on characterizing and describing SSRL but, as explained
above, on advancing the field in three other dimensions: first, exploring the best conditions and
different factors to promote SSRL. We now know how social interactions happen when SSRL
occurs, but there is a need for interventions to promote it so that we can implement it in general
learning contexts (e.g., bigger classroom groups or in computer supported collaborative learning
settings). Promising results have been found regarding the use of technology tools in prompting
self-regulation (Winne et al., 2006) and co-regulation (Azevedo, Cromley, Winters, Moos, &
Greene, 2005), but it is still rare for tools to be leveraged in SSRL regulation support (Järvelä &
Hadwin, 2013; Järvelä et al., 2014).
Second, there is a need to clarify the role of co-regulation in SSRL. The empirical research
shows evidence that co-regulation is built in SSRL (e.g., Grau & Whitebread, 2012), but more is
needed to complete our understanding of the relationship between these two types of regulation. It
seems that instead of being an on/off type of relationship it is more complex and even subordinated.
There may be at least two variables that could explain how groups move between co-regulation and
SSRL: group dynamics and level of expertise (asymmetry). Therefore, future research needs to
address a more in-depth understanding of the dual interaction of co-regulation and SSRL, what are
the benefits of each one and under which circumstances, and what triggers one or the other.
Third, more research is needed on aspects of groups’ characteristics. The current research on
SSRL has not addressed in detail questions regarding size of groups, characteristics of members
(e.g., SRL skills), individual social abilities, etc.
In conclusion, the empirical evidence accumulated shows that SSRL is a real phenomenon
that occurs within collaborative groups in joint learning situations. Even though the field is young
and growing a number of important features of SSRL have been already explored. Nevertheless,
Socially Shared Regulation of Learning 29
there is still a long road ahead to continue discovering aspects of SSRL and how to create the best
learning environments to promote SSRL in collaborative learning situations.
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Socially Shared Regulation of Learning 36
Table 1
Summary studies on shared regulation
(& country)
Type of data
Main conclusion
Vauras, Iiskala,
Kajamies, Kinnunen
& Lehtinen (2003)
One pair high-
achieving 4th
Observational data
Explored the main features of SSRL in a high-achieving
pair of 4th graders.
Iiskala, Vauras &
Lehtinen (2004)
Four 4th grade
Mathematics (Quest of the
Silver Owl)
Observational data
Studied shared metacognition adding the idea of mutuality,
simultaneity and sharing.
Salonen, Vauras &
Efklides (2005)
Two studies
conducted on the
Theoretical reflection
Different aspects of socially shared metacognition are
presented: scaffolding and how to make it optimal,
perceptions of students’ metacognitive experiences, among
Volet & Mansfield
Eighteen 3rd year
Business students.
Unknown members
per group
Business small group
Interview and
Explored the role of different goals and their effects on co-
regulation vs. SSRL.
Hurme, Merenluoto
& Järvelä (2009)
Two triads of pre-
service primary
Descriptive. Through
the interactions in
WorkMate (a CSCL
Characterization of the SSRL in combination with feelings
of difficulty.
Volet, Summers &
Thurman (2009)
18 second-year
veterinary science
students’ (groups of
Physiological principles
applied to veterinary cases.
Case study
embedded in real
classrooms. Video
data collection and
Explored different levels of collaborative work based in
four-pole axis matrix: social regulation (SSRL vs. co-
regulation) and content processing (low-level knowledge
acquisition vs. high-level construct meaning).
Volet, Vauras &
Salonen (2009)
Co-regulation theories
Narrative review
Compared different traditions’ views on interactions
during joint activity. Analysis of the origin of the shared
regulation term. Future lines of research especially on
clarifying other-regulation and co-regulation.
Socially Shared Regulation of Learning 37
Castelló, Bañales &
Vega-López (2010)
Different theories driven
interventions on the writing
Narrative review
Identified four approaches to the study of the writing
process: (a) cognitive perspective starting with Hayes and
Flower work; (b) Socio-cognitive perspective: ideas from
Zimmerman including motivation and emotion; (c)
Sociocultural perspective: writing is a social process that
develops within a community; and (d) Socially shared
perspective: taking ideas from Hadwin and Järvelä.
Iiskala, Vauras,
Lehtinen & Salonen
Four high-
achieving dyads
Mathematical word problems
Observational data
from case studies.
Presented data clarifying the features of SSMetacognition.
Hadwin, Järvelä &
Miller (2011)
Theoretical reflection
Outlined the differences between individual SRL, co-
regulation, and socially shared regulation. The key feature
that distinguishes SSRL from co-regulation is that the
group, as a unit, shares convergent regulation of the team
activity through planning, monitoring, evaluation, and
regulating the motivation, emotion, cognition, and
Järvelä & Järvenoja
Sixteen first year
graduate from an
educational course.
Four members
Educational psychology
Observational data
(video), interviews
and self-report
Presented evidence that SSRL emerges when students
collaborate and make efforts to regulate their learning and
Rogat &
Six four-member
groups of sixth-
Observational data
Explored different levels of social regulation linked to co-
regulation and SSRL.
Grau & Whitebread
8 third grade
working in four-
members groups.
Science subject.
Case study
embedded in real
classrooms. Video
data collection and
Compared SSRL vs. co-regulation presenting the most
salient features of both.
Socially Shared Regulation of Learning 38
Janssen, Erkens,
Kirschner, &
Kanselaar, (2012)
310 secondary
education students
(15-18 years). 5th
year of the pre-
university track.
Mostly triads but
also pairs and four-
member groups.
History tasks. Virtual
Collaborative Research
Institute (VCRI) tool
Cases studies
It was found that groups regulated their task performance
on a regular basis mostly planning the task (19.51%) and
monitoring task progress (14.03). Discussing information
and regulation of task-related activities did not predict
group performance. There is a positive effect of regulation
of social activities on group performance.
DiDonato (2013)
64 middle school
students (Ages 12-
14). Unknown
group number.
Interdisciplinary project
questionnaires &
qualitative: case
Co-regulation as measured by the questionnaire mediated
the use of SRL in the group. The case study data showed
that the group had strong other-regulation that most
probably helped to achieve the task goals. There was also
shared regulation but less frequently.
Järvelä, Järvenoja,
Malmberg & Hadwin
18 graduate
students in a
Master's program
working in triads
Educational pysch. course
Quantitative data
using nStudy
Identified three types of SSR: strong, progressive, and
weak. They also explored the relationship of SSR and
performance, resulting in three levels of performance
(strong, improvers, and weak).
Hurme, Merenluoto,
Salonen & Järvelä
(sent for publication)
45 pre-service
primary teachers
(working in triads)
Descriptive. Through
the interactions in
WorkMate (a CSCL
tool). And
quantitative using
Characterization of the socially shared metacognition
... La revue de Isohätälä et al. (2018) confirmaient justement que la majorité des études empiriques sur l'apprentissage en groupe est axée sur les processus cognitifs et que ce n'est que récemment que des études ont abordé plus explicitement les processus socioémotionnels qui s'entrecroisent avec les processus cognitifs. Seuls quelques auteurs se sont donc intéressés à la régulation partagée de la motivation et des émotions (Panadero et Järvelä, 2015). Leurs recherches portent soit sur le seul aspect de la motivation (Järvelä et Järvenoja, 2011) (Senge, 1990;Zaccaro et al., 2008). ...
... Des recherches de Zimmerman ont notamment porté sur l'autorégulation des apprentissages musicaux et sportifs (Zimmerman, 1998;Zimmerman, 2008;Zimmerman et Kitsantas, 1997), ainsi que sur l'autorégulation de l'activité d'écriture chez des écrivains (Zimmerman et Risemberg, 1997 La perspective de la régulation socialement partagée, qui se déroule au sein de l'accomplissement de tâches coopératives ou collaboratives, permet d'appliquer l'apprentissage autorégulé au contexte du partenariat multipartite. Toutefois, même si la recherche sur la régulation socialement partagée a augmenté dans les dernières années, elle demeure limitée en comparaison avec les autres concepts associés à la régulation tels que l'autorégulation ou la corégulation (Panadero et Järvelä, 2015). De plus, outre les phases qui sont reconnues, peu d'études développent les processus utilisés dans les différentes phases . ...
... À cet effet, Isohätälä et al. (2018) affirmaient que la majorité des études étaient axées sur les processus cognitifs et que ce n'est que récemment que des études avaient abordé plus explicitement les processus socioémotionnels qui s'entrecroisent avec les processus cognitifs. Seuls quelques auteurs se sont donc intéressés à la régulation partagée de la motivation et des émotions (Panadero et Järvelä, 2015) et aucune de ces recherches abordent le conflit (Cosnefroy, 2010), aspect incontournable des relations au sein d'un groupe. La littérature sur le travail en équipe apporte ici un complément pertinent aux quelques recherches qui ont traité des aspects socioémotionnels (Isohätälä et al., 2018;Järvelä et Järvenoja, 2011;Ucan et Webb, 2015). ...
... To close this gap, we propose extending previous theories on routines by introducing theories on self-regulated and collectively regulated learning as a new theoretical lens. We consider these theories to be a beneficial complement because of their broad theoretical, methodological, and empirical research base (Hadwin et al., 2018;Panadero, 2017;Panadero & Järvelä, 2015). Most importantly, theories on regulated learning are framed by a socioconstructivist understanding of learning (Vygotsky, 1978) and will aid identification of the conditions and analysis of teachers' and school teams' adaptation of routines in a concrete challenging situation by applying cognitive, metacognitive, and motivational regulation strategies (Winne & Hadwin, 1998. ...
... Most importantly, theories on regulated learning are framed by a socioconstructivist understanding of learning (Vygotsky, 1978) and will aid identification of the conditions and analysis of teachers' and school teams' adaptation of routines in a concrete challenging situation by applying cognitive, metacognitive, and motivational regulation strategies (Winne & Hadwin, 1998. Further, theories on regulated learning analyze not only individual but also collective learning processes (Bakhtiar & Hadwin, 2020;Hadwin et al., 2011;Hadwin et al., 2018;Panadero & Järvelä, 2015). This is most important, as schools, as loosely coupled systems (Weick, 1976), have a highly complex social structure, and the handling of challenging situations is undertaken not only by individual teachers but also by school teams or the whole school (Mitchell & Sackney, 2011;Stoll & Louis, 2007). ...
... To address these gaps, we propose focusing on short-term adaptation of existing performed routines and extending previous theories on routines by considering theories on selfregulated and collectively regulated learning. Currently, theories on regulated learning (Boekaerts, 1999;Efklides, 2011;Hadwin et al., 2011;McClelland et al., 2018;Panadero, 2017;Winne & Hadwin, 1998;Zimmerman, 1986) are used not only to analyze students' self-regulated learning but also to investigate students' collective learning processes (Bakhtiar & Hadwin, 2020;Hadwin et al., 2011;Hadwin et al., 2018;Panadero & Järvelä, 2015). In the following, we argue that theories on regulated learning have the potential to yield a better understanding of the adapting of the routines of teachers, school teams, and the whole school. ...
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Routines play a major role in educational change in schools. But what happens if the routines performed by school staff fail to deal successfully with current challenges? What strategies aid adaptation of the routines in a specific situation? Up to now, there exists no comprehensive concept for understanding why and at what points the adapting of routines in schools in a specific situation takes a favorable or unfavorable direction. To address this gap, we propose extending theories on routines by considering theories on self-regulated and collectively regulated learning. We consider these theories to be a beneficial complement because of their broad theoretical, methodological, and empirical research base. We argue that these theories enhance the understanding of adapting routines to specific challenging situations in schools. We present a newly developed theoretical framework for dealing with specific challenging situations in schools as an interplay between routines and regulation processes. Finally, important research questions regarding the suggested approach are discussed.
Des études ont montré que la présence d'illustrations dans des documents multimédias n'amélioraient pas toujours l'apprentissage car elles peuvent faire l'objet d'un traitement superficiel. Demander aux apprenants de générer des schémas pourrait les engager dans un traitement plus actif du document. Toutefois, les effets de la génération de schémas apparaissent mitigés et dépendent du niveau de support fourni pendant l'activité. Pour mieux comprendre les conditions d'efficacité de cette activité sur l'apprentissage de collégiens, deux démarches complémentaires ont été adoptées. Dans un premier temps, une démarche de co-conception d'une application de génération de schémas sur tablette a été mise en place. La seconde démarche était basée sur une méthode expérimentale et avait pour objectif d'étudier les effets de la génération de schémas sur l'apprentissage de notions scientifiques chez des élèves de cinquième. Deux premières études ont testé les effets de la génération de schémas et de sa facilitation par des guidages (fournir aux élèves une illustration pendant l'activité générative ou mettre en saillance les éléments à générer). Les résultats n'ont pas mis en évidence d'effets bénéfiques de la génération de schémas sur l'apprentissage, qu'elle soit guidée ou non. La troisième étude visait à examiner les effets d'un travail collaboratif entre élèves lors de la génération de schémas, et montre qu'il n'a pas amélioré leur apprentissage par rapport à un travail individuel. Ces résultats suggèrent qu'il faut étudier d'autres types de supports de la génération de schémas pour améliorer l'apprentissage des élèves.
Purpose This study explores a conceptual framework that addresses a school principal's self-regulated learning (SPSRL) as well as possible avenues for future conceptualization of, and research into this issue. Design/methodology/approach The conceptual framework of SPSRL is based on an extensive literature review of the research on student’s and teacher’s self-regulated learning models. Findings A novel conceptual and practical SPSRL framework for planning, performing, monitoring and self-reflection is elaborated. Research limitations/implications This novel SPSRL conceptual framework provides school principals with a means to shape and develop processes, strategies and structures to monitor and evaluate their learning, enabling them to react effectively in uncertain and dynamic environments. This framework may open the way to future research into possible contributions of the SPSRL construct with other variables related to principal effectiveness. The suggested framework should be examined empirically in various sociocultural contexts, possibly substantiating its conceptual validity. Originality/value The SPSRL conceptual framework can improve school learning, which might connect the individual (the school principal) and organizational (teachers) learning levels.
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Socially shared metacognition is important for effective collaborative problem solving in virtual laboratory settings, A holistic account of socially shared metacognition in virtual laboratory settings is needed to advance our understanding, but previous studies have only focused on the isolated effect of each dimension on problem solving. This study thus applied learning analytics techniques to develop a comprehensive understanding of socially shared metacognition during collaborative problem solving in virtual laboratories. We manually coded 126 collaborative problem-solving scenarios in a virtual physics laboratory and then employed K-Means clustering analysis to identify patterns of socially shared metacognition. Four clusters were discovered. Statistical analysis was performed to investigate how the clusters were associated with the outcome of collaborative problem solving and also how they related to the difficulty level of problems. The findings of this study provided theoretical implications to advance the understanding of socially shared metacognition in virtual laboratory settings and also practical implications to foster effective collaborative problem solving in those settings.
Lernen mit digitalen Medien ist ein zwar junges aber weit erforschtes Feld der psychologischen Forschung. Ein Großteil der Forschung widmete sich dabei der Erforschung kognitiver Prozesse bei der Selektion und Verarbeitung sowie der Speicherung und dem Abruf von Informationen. Erst in den letzten 20 Jahren wurden verstärkt begleitende psychische Prozesse wie der Motivation, der Emotion, sozialer Prozesse sowie der Metakognition untersucht. Dieser Beitrag gibt einen Überblick über grundlegende und um zusätzliche Prozesse erweiterte Theorien zum Lernen mit digital präsentierten Lernmaterialien. Darüber hinaus werden alle Prozessarten, die am Lernvorgang beteiligt sein können, näher beleuchtet um ein ganzheitliches Bild des Lernens mit digitalen Medien zu zeichnen. Gleichzeitig wird anhand aktueller Forschung aufgezeigt, in welchen Bereichen noch bestehende Forschungslücken herrschen.
The quasi-experimental study explored the effects of collaborative reading during prediction-confirmation reading cycles in an EFL classroom through quantitative and qualitative analysis. The quantitative investigation was undertaken to compare the efficacy of the prediction-confirmation instructional approach when applied to individualistic vs. collaborative learning contexts. The data indicated the instructions were more facilitative to reading comprehension and retention in collaborative learning than in individualistic learning contexts. On the other hand, the qualitative analysis utilized interactive dialogues and semi-structured interviews of three selected focus groups in an attempt to understand how peer-mediated learning occurred. The qualitative data revealed that three modes of regulation—self-regulation, co-regulation, and shared-regulation—emerged as a basis of successful collaborative learning. Another finding was that co-regulation served as resource to resolve lower-level language-related problems, whereas shared-regulation manifested in higher-level skills of reading.
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Self-regulated learning includes the cognitive, metacognitive, behavioral, motivational, and affective aspects of learning. The conceptualization of self and socially regulated learning has recently received much attention and peer assessment has been found to increase the use of metacognitive activity. The present exploratory qualitative study aimed to identify self-, co-, and socially shared regulatory processes in an oral English as a Foreign Language task. The regulatory activity deployed by 10 learners was studied within the context of a peer assessment task using an assessment form paired with video feedback in the context of an English language classroom at a French university. These interactions were filmed and discussed in individual self-confrontation interviews which were analyzed through inductive coding. Specific findings from the classroom setting shed light on existing gaps in the literature. First, students can gain confidence in their own skills through assessing their peers and activating regulatory processes both individually and as a group. Second, appropriate tools can increase co-regulated and socially regulated learning through the structuring of cooperative regulatory behaviors. Third, psychological safety appeared to be a propitious social context for supporting regulated learning (SRL, CoRL, and SSRL). We also shed light on the fact that adaptive regulatory strategies are present in oral (as well as written) English as a Foreign Language tasks. These results indicate the potential for learning situations based on video feedback used in conjunction with peer assessment and collaborative learning in order to develop regulatory behaviors in language learners.
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For effective computer supported collaborative learning (CSCL), socially shared regulation of learning (SSRL) is necessary. To this end, this article extends the idea first posited by Järvelä and Hadwin (Educ Psychol 48(1):25–39, 2013) that successful collaboration in CSCL contexts requires targeted support for promoting individual selfregulatory skills and strategies, peer support, facilitation of self-regulatory competence within the group, and SSRL. These (meta)cognitive, social, motivational, and emotional aspects related to being/becoming aware of how one learns alone and with others are for the most part neglected in traditional CSCL support. Based upon a review of theoretical and empirical studies on the potential of and challenges to collaboration, three design principles for supporting SSRL are introduced: (1) increasing learner awareness of their own and others’ learning processes, (2) supporting externalization of one’s own and others’ learning process and helping to share and interact, and (3) prompting acquisition and activation of regulatory processes. Finally, an illustrative example is presented for how these principles are applied in a technological tool for supporting SSRL.
Although research in collaborative learning has a fairly long history, dating back at least to the early work of Piaget and Vygotsky, it is only recently that workers have begun to apply some of its findings to the design of computer based learning systems. The early generation of the!le systems focused on their potential for supporting individual learning: learning could be self­ paced; teaching could be adapted to individual learners' needs. This was certainly the promise of the later generation of intelligent tutoring systems. However, this promise has yet to be realised. Not only are there still some very difficult research problems to solve in providing adaptive learning systems, but there are also some very real practical constraints on the widespread take up of individualised computer based instruction. Reseachers soon began to realise that the organisational, cultural and social contexts of the classroom have to be taken into account in designing systems to promote effective learning. Much of the work that goes on in classrooms is collaborative, whether by design or not. Teachers also need to be able to adapt the technology to their varying needs. Developments in technology, such as networking, have also contributed to changes in the way in which computers may be envisaged to support learning. In September 1989, a group of researchers met in Maratea, Italy, for a NATO-sponsored workshop on "Computer supported collaborative . learning". A total of 20 researchers from Europe (Belgium.