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Collaborative Learning in the Online Environment

2022· book-chapter· en· W4313412502 on OpenAlexaffabout
Elena Rakitskaya

Bibliographic record

VenueAdvances in educational technologies and instructional design book series · 2022
Typebook-chapter
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsYork University
Fundersnot available
KeywordsInstructional designOnline learningRelevance (law)PsychologyOnline courseInterpersonal communicationQualitative researchExploratory researchCollaborative learningMathematics educationFacilitationPedagogyMedical educationComputer scienceMultimediaSociologyMedicine

Abstract

fetched live from OpenAlex

The chapter is based on the qualitative research conducted in a Canadian post-secondary institution. The researcher applied an exploratory case study methodology and a semi-structured interview approach. The participants were students who studied in fully online classes, instructors who delivered online courses, and instructional designers of the online courses. They answered sets of questions about the relevance of interpersonal relationships among online classmates to learning. The respondents also discussed how those relationships could be initiated, developed, and cultivated in an online course by means of instructional design and the implementation of facilitation strategies and techniques. This chapter examines how instructional designers and instructors can design and foster a collaborative learning environment. The research topic is beneficial to adult education instructors, instructional designers, faculty, higher education administrators, educational technologists, students, and scholars who are interested in researching course design for collaborative online learning.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.745
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.284
Teacher spread0.270 · 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.

Study designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations15
Published2022
Admission routes2
Has abstractyes

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