Evaluating the Impact of the Curriculum Structure on Group Metacognition During Collaborative Problem-solving Using Educational Robotics

Socratous, Chrysanthos; Ioannou, Andri

doi:10.1007/s11528-022-00738-5

Cited by 10 publications

(4 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…They conclude that Phase 1 and Phase 3 were the most commonly identified in the data, whereas the other phases were either not present at all or were only employed to a minimal extent. A more recent study focusing on children's collaborative problem solving in a science, technology, engineering, and mathematics (STEM) class by Socratous and Ioannou (2018) identifies the occurrence of all KC phases. However, in addition to Phase 1, the participants also actively engaged in Phase 4, which was explained by the learning context applied in the study.…”

Section: Defining and Analyzing Knowledge Construction Using The Inte...mentioning

confidence: 99%

Examining the interplay of knowledge construction and group-level regulation in a computer-supported collaborative learning physics task

Zabolotna

Malmberg

Järvenoja

2023

Computers in Human Behavior

View full text Add to dashboard Cite

Section: Defining and Analyzing Knowledge Construction Using The Inte...mentioning

confidence: 99%

Examining the interplay of knowledge construction and group-level regulation in a computer-supported collaborative learning physics task

Zabolotna

Malmberg

Järvenoja

2023

Computers in Human Behavior

View full text Add to dashboard Cite

“…The group metacognition questionnaire used in this study was adapted from the measure developed by Biasutti and Frate (2018). Previous studies have used it to assess group metacognition for K-12 students (Socratous & Ioannou, 2022). The questionnaire was constructed of 18 items based on four dimensions: knowledge of cognition, planning skill, monitoring skill and evaluation skill (eg, I know how to use the material.).…”

Section: Instrumentmentioning

confidence: 99%

Development of a metacognitive regulation‐based collaborative programming system and its effects on students' learning achievements, computational thinking tendency and group metacognition

Wei

Liu

Tseng

2023

Brit J Educational Tech

View full text Add to dashboard Cite

Collaborative programming helps improve students' computational thinking and increases their confidence in solving programming problems. However, the effect of collaborative learning is not ideal because it is difficult for students to mobilize metacognition to regulate learning spontaneously. To guide students to effectively regulate the learning process when they collaborate to solve programming problems, this study develops a collaborative learning approach and a Collaborative programming System (MR‐CPS) based on metacognitive regulation to support students' collaborative programming learning. A quasi‐experimental study was conducted in a junior high school programming course in Taiwan to assess the effects on students. The impacts of MR‐CPS from both individual and collaborative perspectives were investigated. Students' learning achievement and computational thinking tendencies were examined from an individual perspective. From a collaborative perspective, group self‐efficacy and group metacognition were investigated. Participants were divided into MR‐CPS (n = 115) and No‐MR‐CPS (n = 107). The MR‐CPS group used the collaborative programming approach with metacognitive regulation mechanisms as the experimental group. In contrast, the No‐MR‐CPS group used the collaborative programming approach without metacognitive regulation mechanisms as the control group. The results show that the MR‐CPS group statistically significantly outperformed the No‐MR‐CPS group in learning achievements. It was also found that the MR‐CPS group had statistically significantly better computational thinking tendency, collective efficacy and metacognitive planning and evaluation skills than the No‐MR‐CPS group. This finding suggests that the MR‐CPS has the potential to improve students' learning achievements, computational thinking tendency, group metacognition and collective efficacy. The study results have implications for the design of collaborative programming systems consistent with metacognitive regulation.

show abstract

“…Collaborative programming requires students utilize their cognitive, affective and social competencies to facilitate the group's social interactions, decision-making and problem-solving process in order to construct programming and assess the outcomes (Clark & Sengupta, 2020;Lai & Wong, 2022;Lavonen et al, 2002). Therefore, instructor scaffolding is a necessity during collaborative programming, that have been showed positive influences on groups' collaborative learning (Socratous & Ioannou, 2022).…”

Section: Literature Reviewmentioning

confidence: 99%

Applying multimodal learning analytics to examine the immediate and delayed effects of instructor scaffoldings on small groups’ collaborative programming

2022

View full text Add to dashboard Cite

Background Instructor scaffolding is proved to be an effective means to improve collaborative learning quality, but empirical research indicates discrepancies about the effect of instructor scaffoldings on collaborative programming. Few studies have used multimodal learning analytics (MMLA) to comprehensively analyze the collaborative programming processes from a process-oriented perspective. This research conducts a MMLA research to examine the immediate and delayed effects of instructor scaffoldings on small groups’ collaborative programming in K-12 education context with an aim to provide research, analytics, and pedagogical implications. Results The results indicated that the instructor provided five types of scaffoldings from the social, cognitive, and metacognitive dimensions, and groups had seven types of responses (i.e., immediate uptake and delayed use) to five instructor scaffoldings, ranging from the low-to-medium and high level of cognitive engagement. After the scaffolding was faded, groups used the content from the high-control cognitive scaffolding frequently to solve problems in a delayed way, but groups did not use the instructor’s scaffolding content from the social and low-control cognitive scaffoldings from the pedagogical perspective, instructors should consider scaffolding types, group states and characteristics, as well as the timing of scaffolding to better design and facilitate collaborative programming. From an analytical perspective, MMLA was proved to be conducive to understand collaborative learning from social, cognitive, behavioral, and micro-level dimensions, such that instructors can better understand and reflect on the process of collaborative learning, and use scaffoldings more skillfully to support collaborative learning. Conclusions Collaborative programming is encouraged to be integrated in STEM education to transform education from the instructor-directed lecturing to the learner-centered learning. Using MMLA methods, this research provided a deep understanding of the immediate and delayed effects of instructor scaffoldings on small groups’ collaborative programming in K-12 STEM education from a process-oriented perspective. The results showed that various instructor scaffoldings have been used to promote groups’ social and cognitive engagement. Instructor scaffoldings have delayed effects on promoting collaborative programming qualities. It is highly suggested that instructors should integrate scaffoldings to facilitate computer programming education and relevant research should apply MMLA to reveal details of the process of collaboration.

show abstract

Evaluating the Impact of the Curriculum Structure on Group Metacognition During Collaborative Problem-solving Using Educational Robotics

Cited by 10 publications

References 35 publications

Examining the interplay of knowledge construction and group-level regulation in a computer-supported collaborative learning physics task

Examining the interplay of knowledge construction and group-level regulation in a computer-supported collaborative learning physics task

Development of a metacognitive regulation‐based collaborative programming system and its effects on students' learning achievements, computational thinking tendency and group metacognition

Applying multimodal learning analytics to examine the immediate and delayed effects of instructor scaffoldings on small groups’ collaborative programming

Contact Info

Product

Resources

About