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Record W4288048890 · doi:10.4018/ijopcd.305728

Enhancing Student Engagement and Structured Learning in Online Discussion Forums

2022· article· en· W4288048890 on OpenAlexaff
Agnès Whitfield, Vanessa Evans, Breanna E. M. Simpson

Bibliographic record

VenueInternational Journal of Online Pedagogy and Course Design · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsYork University
Fundersnot available
KeywordsWorksheetOnline discussionStudent engagementReading (process)Mathematics educationPsychologyTask (project management)PedagogyComputer scienceWorld Wide WebEngineering

Abstract

fetched live from OpenAlex

Discussion forums remain an important component in student engagement and learning in many online courses, but current research suggests that refining their pedagogical design could significantly enhance their effectiveness. The Worksheet Video Walk Formula offers one such option. Drawing on scaffolding and question techniques, the worksheet structures the interactive learning tasks closely around the concepts and skills to be learned, while the video walk reinforces students’ connection and engagement with the task activities. This article discusses the pedagogical challenges in designing and implementing the Formula in a large (104 students) second-year English literature course on the short story. The impact of the Formula on the quality of student interaction with concepts and texts as well as their development of close reading and critical thinking skills is assessed, and future applications are explored. This study has implications for teacher presence in discussion forums, learning outcomes, student satisfaction, and online pedagogy in large classes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.857
Threshold uncertainty score0.332

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.036
GPT teacher head0.409
Teacher spread0.372 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2022
Admission routes1
Has abstractyes

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