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Record W4324140729 · doi:10.2478/eurodl-2023-0001

An analysis of team projects outcomes from student and instructor perspectives in online computing degrees

2023· article· en· W4324140729 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEuropean Journal of Open Distance and E-Learning · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Practises and Engagement
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsPerspective (graphical)Outcome (game theory)Team compositionPsychologyMedical educationKnowledge managementPeer evaluationResistance (ecology)Computer sciencePedagogyHigher educationMedicinePolitical science

Abstract

fetched live from OpenAlex

One of the core aims of higher education degrees is to provide an environment for students to acquire essential skills that will helpthem in the workplace. Team working is one of those essential skill and it is also one that experience and research show is regularlyresisted by students. This resistance can become even more amplified when the degree is delivered online, although some havepointed out that a good team provides much-needed community spirit and support in such environments. The purpose of this studyis to review the delivery of a team assessment format that has been specifically designed for the online environment. The results presented provide insight into the student’s perspective on the delivery as well as the reflections of the instructors involved in thedelivery. The overall outcome is positive for both parties and provides further guidance on implementation to ensure the pedagogicaldesign continues to be viable. This includes insights into team composition, instructor involvement, and peer review scoring formats.

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.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.170
Threshold uncertainty score0.235

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.083
GPT teacher head0.409
Teacher spread0.327 · 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