Publications

Theoretical Framework of Self-Regulation, Co-Regulation, and Socially Shared Regulation

Selected Publications:

Hadwin, A. F., Järvelä., S., & Miller, M. (2018). Self-regulation, co-regulation, and shared regulation in collaborative learning environments. In D. H. Schunk, & J. A. Greene, (Eds.). Handbook of self-regulation of learning and performance (2nd ed.). New York: Routledge.

This chapter revisits and updates our earlier conceptualizations of social modes of regulation in collaboration (Hadwin et al., 2011) with the aim of: (a) summarizing relevant theoretical ideas, (b) grounding these constructs in their educational psychology foundations, (c) highlighting contemporary research evidence bearing on these ideas, (d) offering directions for future research, and (e) discussing implications for practice.

 

Scripting and Visualization to Support Regulation 

Selected Publications and Presentations:

Miller, M., Hadwin, A.F., & Starcheski, S. (2017, August). Promoting socially shared regulation in collaboration: Implicit guidance of strategic planning. Effects of explicit and implicit guidance on external and self- regulation through conflict awareness. Symposium conducted at the meeting of European Association for Research on Learning and Instruction. Tampere, Finland.

Shared planning is a critical, but challenging, aspect of successfully regulating collaboration. Although explicit guidance can support planning, effects may not extend to performance. As such, this study examined the effect of different types of implicit guidance on groups’ shared planning for a collaborative task. By providing groups with visualizations of their members’ individual plans, we aimed to help groups become aware of differences and interact more meaningfully with planning scripts. Groups were assigned to one of three implicit guidance conditions (numeric, non-numeric, or no-visualization). The effect of condition was examined for (a) accuracy of shared task perceptions, (b) discussion quality, and (c) collaborative task performance. Results indicated groups provided with non-numeric visualizations engaged in more transactive planning discussion and constructed more accurate shared task perceptions than groups provided with numeric or no visualization. Group performance did not significantly differ across condition. Implications for guidance of regulation is discussed.

Hadwin, A.F., Bakhtiar, A., Miller, M. (2017, May). Challenges in an online collaboration: Effects of scripting shared task perceptions. Paper presented as part of a symposium titled Promoting Adaptive Regulation, Annual Meeting of the Canadian Society for the Study of Education, Toronto, ON

The mark of successful regulation is strategic adaptation in response to challenging situations. In group work, the research to date points to at least five broad types of challenges experienced by groups across a variety of settings: motivational, socio-emotional, cognitive, metacognitive, and environmental (e.g., Blumenfeld, Marx, Soloway, & Krajcik, 1996; Järvenoja & Järvelä, 2009). Self-regulated learning theory posits that planning, especially having shared perceptions about the collaborative task, is critical in ameliorating group work challenges. Hence, the purpose of this study was to examine the effects of providing different types of planning supports in the form of awareness visualizations of group members’ task perceptions on reported challenges. Findings revealed dominant differences across support conditions. Individuals in the no visualization condition (a) rated planning as more problematic for their groups than individuals in either of the two visualization conditions, and (b) reported the degree of challenges in doing the task, checking progress, and engaging in group work to be strongly positively correlated with planning challenges, (c) reported more Time and Planning main challenges compared to Doing and Group work challenges, and (d) reported that planning strategies (adopted together as a team) were most effective for addressing planning challenges they encountered, followed by teamwork strategies which were less effective. In contrast, individuals belonging to groups who received one of the two planning visualization supports  (a) reported both planning and teamwork strategies to be equally effective for addressing planning challenges, and (b) reported higher levels of success with their strategies than groups without a planning support. Findings attest to the need to support awareness of group processes for collaborative team planning.

 

Starcheski, S., Davis, S.K., Bakhtiar, A., Webster, E., Miller, M., & Hadwin, A.F. (2017, May). Processes and targets of regulation in online collaborative assessments. Paper presented as part of a symposium titled Promoting Adaptive Regulation, Annual Meeting of the Canadian Society for the Study of Education, Toronto, ON.

Current perspectives suggest deliberate regulation is a key aspect of successful collaboration (Hadwin, Järvelä, & Miller, 2011, in press). Thus understanding how groups regulate across different phases of regulation (i.e., planning, enacting, monitoring, adapting) to take control of their cognition, behaviour, and affect is essential to designing effective supports for this process. In this paper, a multi-level coding approach was used to disentangle groups’ regulatory processes. Specifically, in two separate waves, we identified processes and targets of regulation in groups’ discourse data obtained from two group planning sessions and two online collaborative task-work sessions. Groups varied in the support they received at planning: scripting support augmented with numeric or non-numeric graphic visualizations of each team members’ individual planning perceptions (Numeric-Vis; Non-numeric-Vis), or scripting support with no visualization information (No-Vis). Due to the exploratory and complex nature of the data, patterns of group conditions were examined. Findings revealed differences in all four processes: planning, enacting, monitoring, and adapting, as well as with the targets of behaviour-strategy and cognition. Groups with graphic visualizations of team members planning perceptions were more active at planning than groups who had no visualization information (No-Vis). This finding indicates that graphic visualizations of individual planning stimulate active planning, perhaps by increasing group awareness of similarities and differences in task perceptions amongst group members. However, the type of visualizations presented to the group did not seem to matter.

Miller, M., Hadwin, A.F., & Starcheski, S., (2017, May). Examining group awareness supports for strategic planning in collaboration. Paper presented as part of a symposium titled: Promoting adaptive regulation in collaborative learning. Canadian Society for the Study of Education. Toronto, Canada

Shared planning is a challenging, but vital aspect of successful regulation of collaboration. While group awareness tools can support collaboration by visualizing intra-group differences, their potential to support shared regulatory processes has been underexamined. As such, this study examined the effects of group awareness visualizations on groups’ construction of shared task perceptions. By visualizing group members’ individual plans, we aimed to help groups become aware of differences and engage in more meaningful planning. Groups were assigned to one of three visualization conditions (numeric, non-numeric, or no-visualization). The effect of condition was examined for (a) accuracy of shared task perceptions, (b) discussion quality, and (c) collaborative task performance. Results indicated that, compared to groups with no visualizations, groups with Non-numerical visualizations constructed more accurate shared task perceptions and engaged in more transactive discussion of explicit task features. Furthermore, groups with numerical or non-numerical visualizations engaged in more transactive discussion of implicit task features. Group performance did not significantly differ across condition Implications for guidance of regulation is discussed.

Miller, M., Hadwin, A. F. (2015). Scripting and awareness tools for regulating collaborative learning: Changing the landscape of support in CSCL. Computers in Human Behaviour, 52, 573-588.

This conceptual paper addresses the need to design tools for supporting regulation in computer supported collaborative learning (CSCL). First, we extend previous work articulating the important role of self-regulation, co-regulation, and shared-regulation in successful collaboration (Hadwin, Järvelä, & Miller, 2011; Järvelä & Hadwin, 2013). Second, we draw on this theoretical framework to address the capacity of CSCL environments to support regulation of collaboration in the form of two types of tools:

(a) Scripting tools that structure and sequence collaborative interactions, and (b) group awareness tools that collect, aggregate and reflect information back to learners to facilitate collaboration. Finally, directions for future research of regulation of collaboration and CSCL regulation tools are discussed.

Järvelä, S., Kirschner, P. A., Hadwin, A., Järvenoja, Hl., Malmberg, J., Miller, M., & Laru, J. (2016). Socially shared regulation of learning in CSCL: Understanding and prompting individual and group level shared regulatory activities. International journal of computer-supported collaborative learning, 11 (3), 263-280. DOI: 10.1007/s11412-016-9238-2

The field of computer supported collaborative learning (CSCL) is progressing instrumentally and theoretically. Nevertheless, few studies examine the effectiveness and efficiency of CSCL with respect to cognitive, motivational, emotional, and social issues, despite the fact that the role of regulatory processes is critical for the quality of students’ engagement in collaborative learning settings. We review the four earlier lines in developing support in CSCL and show how there has been a lack of work to support individuals in groups to engage in, sustain, and productively regulate their own and the group’s collaborative processes. Our aim is to discuss how our conceptual work in socially shared regulation of learning (SSRL) contributes to effective and efficient CSCL, what tools are presently available, and what the implications of research on these tools are for future tool development.

Hadwin, A. F., Bakhtiar, A., & Miller, M., (2017). Challenges in an Online Collaboration: Comparing Shared Planning Supports. Paper presented at the Canadian Society for the Study of Education. Toronto, Canada.

The mark of successful regulation is strategic adaptation in response to challenging situations. In group work, the research to date points to at least five broad types of challenges experienced by groups across a variety of settings: motivational, socio- emotional, cognitive, metacognitive, and environmental (e.g., Blumenfeld, Marx, Soloway, & Krajcik, 1996; Järvenoja & Järvelä, 2009). Self-regulated learning theory posits that planning, especially having shared perceptions about the collaborative task, is critical in ameliorating group work challenges. Hence, the purpose of this study was to examine the effects of providing different types of planning supports in the form of awareness visualizations of group members’ task perceptions on reported challenges. Findings revealed dominant differences across support conditions. Individuals in the no visualization condition (a) rated planning as more problematic for their groups than individuals in either of the two visualization conditions, and (b) reported the degree of challenges in doing the task, checking progress, and engaging in group work to be strongly positively correlated with planning challenges, (c) reported more Time and Planning main challenges compared to Doing and Group work challenges, and (d) reported that planning strategies (adopted together as a team) were most effective for addressing planning challenges they encountered, followed by teamwork strategies which were less effective. In contrast, individuals belonging to groups who received one of the two planning visualization supports (a) reported both planning and teamwork strategies to be equally effective for addressing planning challenges, and (b) reported higher levels of success with their strategies than groups without a planning support. Findings attest to the need to support awareness of group processes for collaborative team planning.

Adaptive Regulation and Student Success

Selected Publications and Presentations:

Hadwin, A.F., Bakhtiar, A., & Davis, S.K. (2018, April). Promoting & researching SRL: Strategic and adaptive responses to new situations and challenges. Paper presented as a part of a symposium titled An Integrative and Comparative Analysis of Approaches to Developing Undergraduates’ Learning Skills at the Annual Meeting of the American Educational Research Association. New York, NY.

This contribution to the symposium focuses on our approach to support the development of self-regulated learning (SRL) expertise through a large first-year undergraduate course titled Learning Strategies for University Success. This SRL approach extends beyond teaching strategies to encourage the development of a growth mindset wherein academic challenges create opportunities to strategically take control of learning. Challenges provide opportunities for learners to engage in deliberate self-regulation and for researchers to study it in situ (Hadwin, Järvelä, & Miller, 2011). Our approach has been to support SRL processes related to students’ academic work by drawing from and reinforcing Winne and Hadwin’s (1998) cyclical model of SRL. Therefore, all data collection serves dual purposes by: (a) increasing students’ metacognitive knowledge, awareness, and control in response to learning conditions and challenges they experience while (b) examining students’ regulatory actions and adaptations across tasks and time. Academic challenges affect regulation across SRL phases, however they become particularly salient when goal progress is disrupted. Detecting disruptions in goal progress, relies on self-monitoring. This metacognitive exercise invites regulatory action: choosing, using, and adapting a strategy, or adapting something in another
SRL phase. From this perspective, examining the challenges students encounter and the ways they strive to overcome them reveals information about their SRL as a process.

Davis, S.K., Edwards, R., Hadwin, A.F., & Milford, T. (2017, August) Exploring factors in student engagement that predict low versus high academic performance. Paper presented at the meeting of European Association for Research on Learning and Instruction. Tampere, Finland.

Student engagement has been identified as an important factor in academic performance, but research has not typically addressed the multidimensional aspects of engagement. The purpose of this mixed method case study is to explore specific engagement characteristics distinguishing students in a first year university class who entered with low prior academic achievement and remain in the low achievement group versus those who enter with low achievement levels and move into higher achievement groups. For this study, engagement data comprised two primary sources: (a) learning analytics collected in activity and access logs gathered via the course management system and (b) quality of “non-graded” Self Regulated Learning (SRL) engagement in course learning activities. Data sources were organized into five indicators of (a) behavioral engagement, (b) cognitive engagement, (c) emotions experienced during learning, (d) agency or proactive approaches to studying, and (e) overall engagement. Findings indicated that students who moved achievement groups showed higher levels of behavioral engagement, cognitive engagement, agency or proactive approaches to studying and overall engagement and students who remained in the low achievement group showed higher levels of positive deactivating emotions. Implications for future research on student engagement are discussed.

McCardle, L., & Hadwin, A.F. (2017, August). Standards in calibration: Students’ perceptions of conditions for creating performance standards. Paper presented at the meeting of European Association for Research on Learning and Instruction. Tampere, Finland.

Models of self-regulated learning suggest that learners base metacognitive evaluations on personal standards. Calibration research typically focuses on alignment between confidence judgments and performance, largely ignoring standards against which students make confidence judgments. Framed in Winne and Hadwin’s (1998) COPES model of self-regulated learning, our aim was to explore the conditions learners identify as salient for choosing a performance standard and to compare conditions considered by students demonstrating accurate, overconfident, and underconfident calibration and selecting high versus low standards. Participants (n = 195) completed a reflection after each exam in a course on self-regulated learning. They reported what they considered in determining a grade-standard of doing “well” on each exam. Responses were coded inductively drawing flexibly on a priori categories. Findings indicated students considered a wide range of conditions, often focusing on how they students studied, such as how much time and effort were put into studying. Conditions were more course specific at the final than at the midterm. No differences were found between students with accurate versus inaccurate calibration, but when students chose high standards they had more positive valence in the conditions considered. Findings suggest confidence and standards have a reciprocal relation and that learners update conditions, and therefore standards, based on past experiences.

Bakhtiar, A., Hadwin, A.F., Milford, T., & Edwards, R. (2017, August). Measuring collaboration challenges and We-I dimension using a collaborative assessment tool. Paper presented at the meeting of European Association for Research on Learning and Instruction. Tampere, Finland.

Given its complex structure, group work or collaboration is posed with multitudes of challenges (e.g., Barron, 2003). However, methods of assessing and identifying those varied challenges are still underdeveloped, consequently reducing the effectiveness of efforts at supporting learners’ regulation of those challenges. The purpose of this study was to (a) explore the types of challenges learners encountered in a collaborative task by (b) identifying activities that were perceived as either performed more collectively (WE-focused) or more individually (I-focused). A Collaborative Assessment Tool was used as a contemporary method for tapping into challenge areas in collaboration, and its validity and reliability will be analyzed in this paper. Findings, thus far, indicate that learners were more successful at harnessing group effort in communication, followed by motivation and socio-emotional climate. Activities pertaining to planning, strategic engagement, and using appropriate task knowledge were less WE-focused. Implications for supporting regulation in collaboration are discussed.

Davis, S.K., Edwards, R.L., Hadwin, A.F., & Milford, T.M. (2017, May). An exploratory study of a trimodal distribution of student achievement in an undergraduate self-regulated learning course. Paper presented at the Annual Meeting of the Canadian Society for the Study of Education, Toronto, Ontario.

Fredricks, Blumenfeld, and Paris (2004) outline three dimensions of student engagement (behavioural, emotional and cognitive) that could explain individual differences in course performance. Examining differences in student engagement allows us to further understand differences across student achievement. Prior research on the prediction of student achievement has divided students into two groups (pass or fail). Discovery of a trimodal distribution of final course grades in an undergraduate self-regulated learning course resulted in three performance groups: low, middle, and high. A logistic regression analysis using student engagement measures showed the low group demonstrated less behavioral engagement than the middle group and the middle group demonstrated less agentic engagement than the high group. These results support Reeve (2016)’s assertion that emotional engagement should be replaced with agentic engagement. These results suggest that students at different performance levels need to focus their efforts on different aspects of student engagement.

McCardle, L.D., Davis, S.K., & Hadwin, A.F. (2017, May). Self-regulated learning in response to challenge: Between-person differences in authentic tasks. Paper presented at the Annual Meeting of the Canadian Society for the Study of Education, Toronto, Ontario.

Although adaptation is conceptually critical in self-regulation (SRL), research has not addressed learners’ engagement of self-regulatory processes in response to particular challenges. Our purposes were (a) to describe learners’ academic challenges and responses, and (b) to compare SRL responses for learners’ who reported facing different challenges. In this study, undergraduate students (n = 663) completed the Regulation of Learning Questionnaire (RLQ; McCardle & Hadwin, 2015), an event-based, self-report with five subscales based on Winne and Hadwin’s (1998) model of SRL. On the RLQ, learners reported the course, the task, and the challenge they faced in one study episode. We emphasize two key findings: (a) students faced a range of academic challenges in a variety of tasks, and (b) intent and engagement of SRL processes did not effectively differ depending on type of challenge. Future research should examine students’ responses to challenges in situ and use of the RLQ as an intervention.

Huang, Y., & Hadwin, A.F. (2017, May). Transition to university: Canadian students’ and Chinese-international students’ academic adjustment. Paper presented at the Annual Meeting of the Canadian Society for the Study of Education, Toronto, Ontario.

Undergraduate students face a number of stressors throughout university (J. Parker, Duffy, Wood, Bond, & Hogan, 2005; J. D. Parker, Summerfeldt, Hogan, &Majeski, 2004). International students encounter even more challenges to their study (Mendelsohn, 2002). The purpose of this study was to examine challenges encountered by Chinese international students transitioning to university courses in Canada and compare them to challenges experienced by domestic students. Participants included 38 Chinese international students and 112 Canadian students studied in a self-regulated learning (SRL) strategies learning course. Weekly over 10 weeks, participants (a) rated their experiences with a list of possible challenges, (b) identified their biggest challenges from a list, and (c) identified one possible strategy for addressing the biggest challenge. Findings indicated that Chinese-international students reported higher frequency of challenges related to social-cultural challenges, whereas domestic students reported higher proportional frequency of motivation challenges. From the perspective of strategy use, domestic participants reported persisting strategies more often, but Chinese-international students more frequently reported social-regulation strategies. Findings from this study will inform policy and practice in the area of global education and intercultural learning by identifying specific challenges to be addressed in supporting Chinese international students.

Davis, S.K., Edwards, R., Hadwin, A.F., & Milford, T. (2017). Exploring Student Engagement to Understand a Trimodal Distribution of Student Achievement in an Undergraduate Learning to Learn Course. Paper presented at the Canadian Society for the Study of Education. Toronto, Canada.

Fredricks, Blumenfeld, and Paris (2004) outline three dimensions of student engagement (behavioural, emotional and cognitive) that could explain individual differences in course performance. Examining differences in student engagement allows us to further understand differences across student achievement. Prior research on the prediction of student achievement has divided students into two groups (pass or fail). Discovery of a trimodal distribution of final course grades in an undergraduate self-regulated learning course resulted in three performance groups: low, middle, and high. A logistic regression analysis using student engagement measures showed the low group demonstrated less behavioral engagement than the middle group and the middle group demonstrated less agentic engagement than the high group. These results support Reeve (2016)’s assertion that emotional engagement should be replaced with agentic engagement. These results suggest that students at different performance levels need to focus their efforts on different aspects of student engagement.

McCardle, L, Webster, E. A., Haffey, A., & Hadwin, A. F. (2015). Examining students’ self-set goals for self regulated learning: Goal properties and patterns, Studies in Higher Education, 1-17. http://dx.doi.org/10.1080/03075079.2015.1135117

Task-specific goals play a critical role in self-regulated learning, yet little research has examined students’ self-set goals for authentic study sessions. We propose high-quality goals that are useful for guiding task engagement and evaluating progress are specific about (a) time, (b) actions, (c) standards, and (d) content. In Study 1, we examined characteristics of students’ self-set goals. Five categories were created to describe students’ goals relative to the features of a high-quality goal. Students rarely included specific information regarding actions, standards, or content. In Study 2, we examined patterns of change in quality of self-set goals across a semester in which students were in a learning-to-learn course. Improvements in goal quality were either inconsistent or non-existent. Implications of vague goals for regulating learning are discussed.

Regulation of Motivation and Emotion

Selected Publications and Pressentations:

Bakhtiar, A., Webster, E., & Hadwin, A.F. (2017). Regulation and socio-emotional interactions in a positive and a negative group climate. Metacognition and Learning, 1-34, doi: 10.1007/s11409-017-9178-x.

Collaboration in an online environment can be a socially and emotionally demanding task. It requires group members to engage in a great deal of regulation, where favourable emotions need to be sustained for the group’s productive functioning. The purpose of this cross-case analysis was to examine the interplay of two groups’ regulatory processes, regulatory modes, and socio-emotional interactions that contribute to or are influenced by emotions and socio-emotional climate perceived in the group. Specifically, this study compared a group of 4 students unanimously reporting a positive climate to  a group of 4 students unanimously reporting a negative climate after completing a 90-minute online text-based collaborative assignment. By drawing on two data channels (i.e., observed regulatory actions and socio-emotional interactions during collaboration and self-reported data about emotional beliefs and perceptions), four contrasting group features emerged: (a) incoming conditions served as a foundation for creating a positive collaborative experience, (b) regulation of emotions during initial planning, (c) negative emotions served as a constraint for shared adaptation in the face of a challenge, and (d) encouragement and motivational statements served as effective strategies for creating a positive climate. Implications for researching and supporting emotion regulation in collaborative learning are discussed.

Bakhtiar, A., Hadwin, A.F., Milford, T., & Fior, M. (2017). Self and team efficacy beliefs as predictors of collaborative task participation in a computer-supported collaborative learning environment. Paper presented at the Canadian Society for the Study of Education. Toronto, Canada.

Three efficacy beliefs may be important for examining task engagement in Computer Supported Collaborative Learning (CSCL) environments: self-efficacy, proxy efficacy, and collective efficacy (e.g., Wang & Hwang, 2012). In particular, regulating task engagement in CSCL requires learners to not only consider the degree to which they feel confident to collaborate on the task (self- efficacy), but also the degree to which they feel confident in other members’ ability (proxy efficacy) and the team’s ability as a whole (collective efficacy). In this study, we (a) focused our examination on self- and proxy efficacy and examined their influences on individual task participation during two online collaborative tasks, and (b) whether the links between efficacy and participation changed depending on the types of visualization supports provided during shared planning. Findings indicated that self-efficacy positively influence the amount of effort put towards the task, even beyond knowledge mastery. A path model described the importance of collaboration experience, not grades, in influencing self-efficacy and in turn individual participation in the next collaboration. Although high proxy efficacy is associated with reduced effort, this effect was removed with group experience. The differences in predictive strengths found between the two tasks, especially for proxy efficacy, showed the evolving nature of learners’ strategic approach from one task to another. Findings demonstrate the need to follow collaborating students across multiple learning sessions to understand the role each type of efficacy belief play in shaping task engagement in collaboration; therefore, develop a more effective CSCL tools to support that process.

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