Shared Metacognition in a Community of Inquiry

Garrison, Randy

doi:10.24059/olj.v26i1.3023

Cited by 40 publications

(59 citation statements)

References 10 publications

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“…topics (Murphy et al, 2005;Stein et al, 2013). Thus, coaching is promising for promoting participants' metacognition, which enables them to lead and shape the inquiry process (Garrison, 2022). The quality of coaching depends on how well instructors can identify and interpret the cognitive patterns in discussion transcripts (Dudek et al, 2019).…”

Section: Practitioner Notesmentioning

confidence: 99%

Assessing cognitive presence in online inquiry‐based discussion through text classification and epistemic network analysis

Stein

et al. 2022

Brit J Educational Tech

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Providing coaching to participants in inquiry‐based online discussions contributes to developing cognitive presence (CP) and higher‐order thinking. However, a primary issue limiting quality and timely coaching is instructors' lack of tools to efficiently identify CP phases in massive discussion transcripts and effectively assess learners' cognitive development. This study examined a computational approach integrating text mining and co‐occurrence analysis for assessing CP and cognitive development in online discussions based on the community of inquiry (CoI) framework. First, text classifiers trained on different language models were evaluated for identifying and coding the CP phases. Second, epistemic network analysis (ENA) was employed to model cognitive patterns reflected by co‐occurrences between the coding elements. Results indicated that text classifiers trained on the state‐of‐the‐art language model Bidirectional Encoder Representations from Transformers (BERT) can address the efficiency issue in coding CP phases in discussion transcripts and obtain substantial agreements (Cohen's k = 0.76) with humans, which outperformed other baseline classifiers. Furthermore, compared to traditional quantitative content analysis, ENA can effectively model the temporal characteristics of online discourse and detect fine‐grained cognitive patterns. Overall, the findings suggest a feasible path for applying learning analytics to tracking learning progression and informing theory‐based assessments. What is already known about this topic Cognitive presence is an important construct describing the progression of thinking in online inquiry‐based discussions. Most studies used self‐report instruments or quantitative content analysis to measure and assess cognitive presence. More efficient and effective approaches were needed by instructors to support assessment of cognitive development and determine coaching strategies. What this paper adds An integrated computational approach for the developmental and formative assessment of cognitive presence was proposed and evaluated. A BERT‐based text classification model could efficiently code massive transcripts and achieve substantial agreements with human coders. Epistemic network analysis effectively revealed the process of cognitive development and identified representative discussion patterns and behaviours. Implications for practice and/or policy The proposed approach can considerably reduce the pressure on instructors, enabling them to focus on quality coaching and feedback. Compared to frequencies of individual codes, the connective features between codes carry more insights for assessing cognitive patterns. Learners in a discussion group play different roles and produce diverse paths of cognitive development.

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Section: Practitioner Notesmentioning

confidence: 99%

Assessing cognitive presence in online inquiry‐based discussion through text classification and epistemic network analysis

Stein

et al. 2022

Brit J Educational Tech

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“…Self-regulated learning denotes one's ability to understand and control one's goal setting, selfinstruction, self-monitoring, and self-reinforcement, which is an important skill in the online learning environment (De Backer et al, 2022). Self-regulation is associated with metacognition (De Backer et al, 2022;Garrison, 2022). Metacognition refers to growing awareness of the learning process and taking responsibility of implementing strategies to manage the learning process (Garrison, 2022).…”

Section: Benefits Of Collaborative Learningmentioning

confidence: 99%

“…Self-regulation is associated with metacognition (De Backer et al, 2022;Garrison, 2022). Metacognition refers to growing awareness of the learning process and taking responsibility of implementing strategies to manage the learning process (Garrison, 2022). Metacognition is crucial to any form of learning (Dindar et.…”

Section: Benefits Of Collaborative Learningmentioning

confidence: 99%

“…Selfregulated learners with metacognitive skills are proactive in the learning processes; they are aware of their knowledge and competencies for organizing, guiding, and controlling their own thinking and actions (Sumadyo et al, 2021). Garrison (2022) described shared metacognition as an understanding of one's learning in the processes of creating meaning and building comprehensions related self with others. In collaborative learning, it is necessary to initate regulation strategies by various team members who jointly take part in controlling and regulating the team's learning at the behavioral, cognitive, contextual, and motivational level (De Backer et alm, 2022;Zhao & Ye, 2020), which is referred to as socially shared regulation (Hadwin et al, 2017).…”

Section: Benefits Of Collaborative Learningmentioning

confidence: 99%

“…For that reason, the instructor needs to take on several roles, for instance facilitator, guide, and helper, to ensure the collaborative learning process goes as intended. The instructor's presence is the essence of collaborative learning (Garrison, 2022). The instructor should facilitate the learning processes in which students are encouraged to self-regulate and take responsibility of their learning (Brannen et al, 2021).…”

Section: Solutionsmentioning

confidence: 99%

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The Role of Collaborative Learning in the Online Education

Lu¹,

Smiles²

2022

IJEBMR

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Collaboration or teamwork is indispensable in today’s workplace. The continual and increasingly rapid change in the external environment requires professionals equipped with unique skill sets to work together and solve problems collaboratively. It is the higher education institution’s responsibility to prepare students for the necessary skills expected by the employers. Collaborative learning is an active learning approach that two or more students team up toward common goals. The knowledge and product are created through the active, social, and engaging process. Students develop communication, interpersonal, metacognitive thinking, and problemsolving skills, as well as their understanding of the diverse perspectives for real-world profession-related situations. Furthermore, working in a team could reduce student’s feelings of isolation in the online learning environment. As such more and more online programs incorporate collaborative learning into their curricula. In this paper, the benefits, challenges, and solutions to challenges in collaborative learning are presented and discussed.

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Grebennikova,

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et al. 2024

Sustainable Development

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This paper scrutinizes how adaptive learning technologies and artificial intelligence (AI) are transforming today's education by making it personalized, accessible, and efficient as well as leading people to accepting, addressing, and mitigating sustainable development. Recently, education witnessed a remarkable technological surge driven by various advances in technology, which can be demonstrated by the increase of the number of scientific publications on this topic from just 1 in 1990 to 636 in 2023. Ongoing digitalization and technological revolution in education together with the novel approach to respect each student's unique learning style and abilities paved the way for adaptive learning technologies represented by the innovative tools that personalize educational experiences to cater to individual learners. All of that contributes to preparing more educated and informed citizens, drives innovation, and supports economic growth necessary for achieving a sustainable future. Our bibliographic study employs VOSviewer to conduct a bibliometric analysis of a total number of 3518 selected publications using the keywords “adaptive learning” and “AI” (represented by articles, proceeding papers, and book chapters) indexed in the Web of Science (WoS) database from 1990 to 2024. Our results demonstrate that recent technological changes played a key role in transforming adaptive learning, which was rather reinforced by the “digital surge” in education brought about by the COVID‐19 pandemic. Our findings can be useful for further development in the field of adaptive education where they can be employed by the relevant stakeholders and policymakers as well as by the scholars and researchers.

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Shared Metacognition in a Community of Inquiry

Cited by 40 publications

References 10 publications

Assessing cognitive presence in online inquiry‐based discussion through text classification and epistemic network analysis

Assessing cognitive presence in online inquiry‐based discussion through text classification and epistemic network analysis

The Role of Collaborative Learning in the Online Education

AI‐driven adaptive learning for sustainable educational transformation

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