Co-regulation Of Learning Research Articles

Learning with Generative Artificial Intelligence Within a Network of Co-Regulation

The emergence of generative artificial intelligence (AI) has created legitimate concerns surrounding academic integrity and the ease with which such technologies might lead to cheating in assessment, in particular. However, fixating solely on potential misconduct is overshadowing a more profound, transformative interaction between learners and machines. This commentary article delves into the relationship between students and AI, aiming to highlight the need for revised pedagogical strategies in the AI age. We argue that the much-discussed approaches that prioritise AI literacy or augmented critical thinking might be inadequate. Instead, we contend that a more holistic approach emphasising self-regulated learning (SRL) and co-regulation of learning is needed. SRL promotes autonomy, adaptability, and a deeper understanding, qualities indispensable for navigating the intricacies of AI-enhanced learning environments. Furthermore, we introduce the notion of a network of co-regulation, which underscores the intertwined learning processes between humans and machines. By positioning the self at the core of this network, we emphasise the indispensable role of individual agency in steering productive human-AI educational interactions. Our contention is that by fostering SRL and understanding co-regulated dynamics, educators can better equip learners for an interconnected AI-driven world.

Effectiveness of a gamified learning analytics dashboard with coregulation mechanism for self-regulated learning in college ethics courses

ABSTRACT It is known that teachers commonly utilize learning platforms equipped with Learning Analytics Dashboards (LAD) to support students in their Self-Regulated Learning (SRL) endeavors. However, students may struggle to effectively employ LAD due to a lack of sufficient metacognitive skills. Co-regulation of learning (CoRL) has been proven to facilitate metacognitive knowledge sharing. However, the implementation of LAD with CoRL mechanisms in self-paced, asynchronous learning environments, aimed at enhancing students' SRL, remains unclear. Investigating how students utilize a LAD with CoRL and how such a system can promote SRL in selfpaced, asynchronous courses is an important topic. This study designed a gamified LAD utilizing a futures trading market interactive interface as the CoRL mechanism. A quasi-experimental design was adopted to assess the effects of the gamified LAD with CoRL on SRL, learning engagement, and academic achievement among 60 students from two Business Ethics classes over the course of a semester. The gamified LAD with CoRL had positive effects on the SRL and learning engagement of the asynchronous learners in the experimental group. Significant differences were observed in the academic achievement of the experimental and control groups. The gamified LAD with CoRL had positive effects on learners in self-paced, asynchronous courses.

Learning with Generative Artificial Intelligence Within a Network of Co-Regulation

The emergence of generative artificial intelligence (AI) has created legitimate concerns surrounding academic integrity and the ease with which such technologies might lead to cheating in assessment, in particular. However, fixating solely on potential misconduct is overshadowing a more profound, transformative interaction between learners and machines. This commentary article delves into the relationship between students and AI, aiming to highlight the need for revised pedagogical strategies in the AI age. We argue that the much-discussed approaches that prioritise AI literacy or augmented critical thinking might be inadequate. Instead, we contend that a more holistic approach emphasising self-regulated learning (SRL) and co-regulation of learning is needed. SRL promotes autonomy, adaptability, and a deeper understanding, qualities indispensable for navigating the intricacies of AI-enhanced learning environments. Furthermore, we introduce the notion of a network of co-regulation, which underscores the intertwined learning processes between humans and machines. By positioning the self at the core of this network, we emphasise the indispensable role of individual agency in steering productive human-AI educational interactions. Our contention is that by fostering SRL and understanding co-regulated dynamics, educators can better equip learners for an interconnected AI-driven world.

Guidelines for teaching with ill-structured real-world engineering problems: insights from a redesigned engineering project management course

ABSTRACT Real-world design settings can be complex, ill-structured, open and typically uncertain and/or ambiguous about their goals and solution paths. This study contributes to understanding how to work with these types of problems in a course project setting. The main objective of the study is to identify, propose and validate a set of practical guidelines for dealing with ill-structured, open-problem project assignments in courses that teach design engineering or design development planning. A literature review identifies key practices for proposing the guidelines, which are then validated by intervening in an engineering project management master’s course. The intervention took place during the COVID-19 lockdown restrictions with 12 project groups created from 105 enrolled students. During the validation, qualitative and quantitative feedback was gathered from the students, and the results provide positive evidence for achieving the objective. Key to this outcome was the combination of the self-regulation of learning, co-regulation of learning and socially shared regulation of learning. In this sense, the proposed guidelines look promising for redesigning university courses that deal with open problems, thus enhancing students’ capacity for handling uncertainty and ambiguity.

Editorial: Classroom assessment as the co-regulation of learning

EDITORIAL article Front. Educ., 04 January 2023Sec. Educational Psychology Volume 7 - 2022 | https://doi.org/10.3389/feduc.2022.1063123

Student-centred learning environments supporting undergraduate mathematics students to apply regulated learning: A mixed-methods approach

The importance of students’ regulation of learning in university mathematics is widely acknowledged, but research approaching regulation of learning from the perspective of learning environments is scarce. The aim of the present study is to deepen our understanding of how mathematics learning environments can promote regulated learning by investigating the same students in two parallel but pedagogically different student-centred learning environments. The quantitative measurement of students’ course-level self-regulation of learning (N = 91) is accompanied with a qualitative analysis of student interviews (N = 16). The results indicate that the learning environments are distinguished by the factor measuring lack of regulation, and that unregulated learning is created by out-of-reach teaching and -tasks causing challenges in goal setting and motivation. In contrast, co-regulation of learning in the form of scaffolding and a positive social environment has a central role in supporting regulated learning. Practical implications for how to support students’ regulated learning are discussed.

Learning Scenario to Promote Comprehension of the Meaning of Subtraction

The integration of virtual manipulatives in classroom practices facilitates student learning processes. For this, the teacher must understand how to support students in establishing mathematical connections between the manipulation and their interpretations of the representations. We present a learning scenario that integrates the use of virtual manipulatives in mathematical modelling tasks. It was designed and implemented during initial teacher training, with the aim of helping a group of first-year elementary school students to overcome difficulties identified in their comprehension of the meaning of subtraction. The research, following the principles of design-based research, included three distinct moments: an individual written pre-test, an intervention phase with six micro-cycles, and an individual written post-test. The analysis of the collected data—audio, screen recordings, and written productions—allowed us to identify the most influential structural characteristics of the learning scenario: mathematical communication, collaborative learning, self-regulation, and co-regulation of learning. Our results suggest that differentiated instruction, minimal guidance, and scaffolding played an important role in the support provided by the pre-service teacher to students in the mathematical modelling activities that integrated virtual manipulatives.

Learning to be expert writers: feedback in secondary English

ABSTRACT Feedback is a cultural tool through which English teachers can facilitate secondary students’ evaluative expertise in their writing development. While there is increased concern to use feedback to enhance learning at all educational levels, there is currently little empirical knowledge of how secondary teachers of English design feedback for complex appraisal. Using data from two qualitative studies, this paper explores practices drawing on Anglophone cultures of secondary schooling for subject English. Observation, artefact and interview data are analysed using a socio-cultural theoretical lens. Cultural tools including student planners, peer feedback and discussion linked students’ self-regulated learning to community norms for evaluating written texts. Two distinctive feedback conditions for written texts in the school subject of English are identified: the disciplinary practices of evaluation of texts within community cultural values, and the role of cultural tools in co-regulation of learning in the classroom context.

Teacher Support of Co- and Socially-Shared Regulation of Learning in Middle School Mathematics Classrooms

Social influences on classroom learning have a long research tradition (e.g., Bandura, 1977; Vygotsky, 1978) and are critical components of self-regulated learning theories (Zimmerman, 2008). More recently, researchers have explored the social influences of self-regulated learning in cooperative learning contexts. In these settings, co-regulation of learning and socially-shared regulation of learning strategies have been aligned with self-regulated learning theory (Hadwin et al., 2018; Khosa & Volet, 2014; Molenar et al., 2014). However, without specific training or structure, teachers are not likely to explicitly integrate SRL strategies into their teaching (Spruce & Bol, 2014). We use case studies to better understand how Zimmerman’s theory of self-regulated learning (2008) and Hadwin’s conceptual framework of socially-shared regulation of learning (2018) emerge from teachers’ support of student-centered instruction. We purposely selected two proficient teachers for more extensive observations focused on student behaviors in teams. The observation instruments afford us a means of advancing research and practice with respect to how teamwork may elicit self- and socially-shared regulation of learning strategies. Consistent with previous findings (Spruce & Bol, 2014), the teachers we observed seem to have made many pedagogical moves to explicitly prompt self- and team monitoring of learning during engagement with course content yet provided fewer opportunities for students to think through the planning and evaluation processes. These findings suggest the cooperative learning model implemented in these classrooms provides support for students’ co- and socially-shared regulation of learning.

A framework for classroom assessment, learning, and self-regulation

ABSTRACT We present a conceptual framework that leverages synergies between classroom assessment (CA) practices and self-regulated learning (SRL) theory to support academic growth and instruction. We articulate the processes shared by CA and SRL, drawing on a model of SRL with three phases: forethought, performance, and self-reflection. We blend this SRL model with CA to create the CA:SRL framework in four stages: (1) pre-assessment, (2) the cycle of learning, doing, and assessing, (3) formal assessment, and (4) summarizing assessment evidence. We elucidate how SRL processes are involved at each stage and can be drawn on to support learning development and teacher understanding and co-regulation of learning. This framework is important in that it depicts how assessment and learning processes interact dynamically for both teachers and students in classrooms, and demonstrates that such interactions encompass the full breadth of purposes in CA, from planning through summation of evidence.

Assessment and the co-regulation of learning in the classroom

ABSTRACT This paper examines the processes of regulation of student learning that are associated with formative assessment in the classroom. It discusses the concept of co-regulation and presents a model of co-regulation developed in a situated perspective on classroom learning. This model conceptualises co-regulated learning as resulting from the joint influence of student self-regulation and of sources of regulation in the learning environment: namely, the structure of the teaching/learning situation, the teacher’s interventions and interactions with students, the interactions between students, and the tools used for instruction and for assessment. Examples of research showing how co-regulation functions are discussed, in particular students’ use of tools for self-assessment and peer assessment, and the role of teacher–student interactions that encourage active student participation in formative assessment.

Classroom assessment as the co-regulation of learning

ABSTRACT Until recently, the classroom assessment literature has emphasized the role of teachers and tests, for example investigating teachers’ assessment practices or the quality of classroom tests and other assessments. In contrast, current understandings of teaching and learning emphasize the role of students, as well as the complex interactions between teachers, students, and contexts. We use the literature review method to give substance to a theory of classroom assessment as the co-regulation of learning by teachers, students, instructional materials, and contexts. We organize the literature using a version of Pintrich and Zusho’s theory of the phases and areas of the self-regulation of learning, expanded to include the co-regulation of learning, in order to demonstrate how classroom assessment is related to all aspects of the regulation of learning. We conclude that this is a useful expansion for the field.

Using formative assessment to influence self- and co-regulated learning: the role of evaluative judgement

Recently, the concept of evaluative judgement has gained attention as a pedagogical approach to classroom formative assessment practices. Evaluative judgement is the capacity to be able to judge the work of oneself and that of others, which implies developing knowledge about one’s own assessment capability. A focus on evaluative judgement helps us to better understand what is the influence of assessment practices in the regulation of learning. In this paper, we link evaluative judgement to two self-regulated learning models (Zimmerman and Winne) and present a model on the effects on co-regulation of learning. The models help us to understand how students can be self-regulated through developing their evaluative judgement. The co-regulation model visualises how the learner can become more strategic in this process through teacher and peer assessment in which assessment knowledge and regulation strategies are shared with the learner. The connections we make here are crucial to strengthening our understanding of the influence of assessment practices on students’ learning.

Student teachers’ emotional landscapes in self- and co-regulated learning

Self- and co-regulation are central elements in skillful student-teacher learning. Studies have confirmed the interrelation between positive academic emotions and student engagement in self-regulated learning. There are also indicators of student-teachers experiencing co-regulative learning activities as highly significant. Yet, we know surprisingly little about the emotional landscape of the self- and co-regulation of learning among student-teachers. Hence, in this study, we explore the kinds of academic emotions that primary school student-teachers experience during self- and co-regulated learning. Altogether 19 Finnish primary school student-teachers were interviewed. The data were qualitatively content analyzed. The results showed that both self- and co-regulated learning experiences were emotionally activating. Student-teachers reported primarily positive emotions (80%) in self- and co-regulated learning. The results also showed that positive activating emotions, such as enthusiasm, were emphasized in all regulatory phases: goal setting and task analysis, strategy use and monitoring, and reflection. Our findings on the high frequency of various positive emotions embedded in self- and co-regulated learning confirmed that positive activating emotions are essential elements in student-teachers self- and co-regulated learning. The findings imply that self- and co-regulated learning can trigger a positive cycle in student-teacher learning in terms of both emotions and productive learning.

University students' self- and co-regulation of learning and processes of understanding: A person-oriented approach

The study used a person-oriented approach to identify different profiles relating to the self- and co-regulation of learning as well as university students' processes of understanding. Altogether 33 participating university students were interviewed. The data were analysed using qualitative inductive and deductive content analysis. Three student profiles were identified: 1) self-regulated students not using co-regulation, 2) actively co-regulating students with average self-regulation skills, and 3) students with self-regulation problems relying on co-regulation. Self-regulated students not using co-regulation showed evidence of excellent self-regulation skills and deep-level processing, whereas actively co-regulating students with average self-regulation skills showed an active use of co-regulation of learning, some problems in self-regulation, and challenges in deep processing. Students with self-regulation problems relying on co-regulation emphasised other students' support when studying, and exhibited surface-level processing. The results imply that by recognising the profiles of university students it is possible to identify those who may be at risk and in need of more support in their studying.

Student teachers’ self- and co-regulation of learning during teacher education

Self-regulative learning skills are extremely important contributors in student teacher learning. Also, interest in co-regulation in learning as a facilitator for pupils’ self-regulation skills and an ability to learn how to support peers’ regulated learning has increased significantly during the past decade. Still, our understanding of student teachers’ co- and self-regulative learning during their studies is shallow. This study aims to explore student teachers’ self- and co-regulation of learning, including their elements and qualities embedded in various contexts of teacher education. In this study 19 primary school student teachers from a large research-based Finnish university were interviewed. The data were content analysed by applying an abductive strategy. The results showed that student teachers applied self-regulated learning more often than co-regulated learning, and that teaching practice provided a primary arena for regulative learning. Further investigation revealed that although self- and co-regulation had the same components, they differed in terms of the quality of regulation. Our findings suggest that co-regulated learning activities that involve peers and teacher educators reached a more profound and meaningful level when learning to become a teacher than learning activities involving self-regulated activities.

Re-evaluation of community of inquiry model with its metacognitive presence construct

Among the discussion-content analytical tools in the field of e-learning research, the community of inquiry (CoI) model is extensively applied and continuously improved by its users. This model investigates the types of elements that are manifested through inquiry-based learning processes in online discussions. They are social, cognitive, teaching and metacognitive presences. These elements are essential for meaningful student interactions to take place in online learning environments. In particular, the metacognitive presence construct of the CoI model discovers the students’ ability of self and co-regulation of learning in an online learning environment. However, the metacognitive presence construct of the CoI model has not been evaluated along with the other components of the model. Therefore, in this paper the CoI model was re-evaluated to determine its reliability in analysing discussions in online courses on information technology related subjects. The evaluation is conducted with four online courses designed and developed for a distance learning programme in Sri Lanka. The paper discusses the modifications that were needed to make the model more applicable for conducting discussion-content analysis in similar types of online learning environments, and reports on the results of the final evaluation. Furthermore, the findings of the study imply that the theoretical framework of the CoI model needs to be improved to properly enclose the metacognitive presence component. In spite of this, the study adds points to the CoI model supporting for its well applicability and reliability in analysing online discussion content in information technology related courses. DOI: http://dx.doi.org/10.4038/icter.v5i4.6095 International Journal on Advances in ICT for Emerging Regions 2012 5(4) 1-13

Pedagogy, didactics and the co-regulation of learning: a perspective from the French-language world of educational research

Since pedagogy is a key term in the Teaching and Learning Research Programme (TLRP) principles, it is of interest to examine the evolution of the concept of pedagogy in the French-language world of education, as well as the emergence of a new field of research called ‘didactics’. Work on situated cognition provides a framework for defining co-regulation of learning in the classroom as resulting from the joint influence of student self-regulation and of regulation from other sources (teachers, peers, curriculum materials, assessment instruments, etc.). Several examples of research on this topic are mentioned. In conclusion, it is argued that the concept of co-regulation of learning can be seen as a way of linking the TLRP principles of scaffolding and of student engagement.

Editorial

Editorial

Social Interaction - What Can It Tell Us about Metacognition and Coregulation in Learning?

Abstract. This article brings to the fore the sociocognitive aspect of metacognition and processes involved in coregulation. We argue that coregulation in a learning situation that involves the interaction of teachers and students or peers is based on awareness of the partners' cognition, metacognition, affect, and motivation, as well as interpersonal perception processes and/or interpersonal relational control processes. One aspect of metacognition, particularly relevant to coregulation of learning, is metacognitive experience, i.e., how the interacting partners feel and what they think about the task at hand. Awareness of one's own and the other's cognition and of metacognitive experiences is necessary for metacommunication control processes. Evidence from two independent studies suggests that there can be misperception of the interacting partners' metacognitive experiences because of “theory-driven” conceptions of the other person or lack of metacognitive coregulation because of the prevalence of relational control processes. We suggest that this may lead to scaffolding mismatch in instruction, failure in coregulation, and negative feelings and behaviors of the interacting partners in certain learning situations.