MétaCan
Menu
Back to cohort
Record W3131816710 · doi:10.29173/isotl520

Role-Playing Gamification Technologies with Adult Learners

2021· article· en· W3131816710 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.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueImagining SoTL · 2021
Typearticle
Languageen
FieldPsychology
TopicEducational Games and Gamification
Canadian institutionsLethbridge College
Fundersnot available
KeywordsScholarship of Teaching and LearningContext (archaeology)PsychologyTeamworkLikert scaleScholarshipInstitutionPedagogyStyle (visual arts)Mathematics educationTeaching methodSociologyTeaching and learning centerManagementPolitical scienceSocial science

Abstract

fetched live from OpenAlex

The purpose of this quantitative scholarship of teaching and learning (SoTL) research study was to examine the impact Classcraft had on adult criminal justice students in a face-to-face context in a western-Canadian institution. Specifically, the role-playing digital game was integrated into a first-year applied English and investigative writing course; learners earned points, received “real world” prizes, and completed random, content-related challenges with their teams. Using a survey with Likert-style and open-ended questions, it was determined that most elements of Classcraft motivated and engaged participants. The most impactful finding was that Classcraft promoted teamwork and problem-solving abilities. While little research has been conducted in adult post-secondary settings related to the implementation of Classcraft, it is evident more research is required in other post-secondary learning contexts.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.371
Threshold uncertainty score0.449

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 studies0.0000.000
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 head0.016
GPT teacher head0.305
Teacher spread0.289 · 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