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Record W2741607424 · doi:10.1186/s41039-017-0054-8

The effectiveness of using in-game cards as reward

2017· article· en· W2741607424 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

VenueResearch and Practice in Technology Enhanced Learning · 2017
Typearticle
Languageen
FieldPsychology
TopicEducational Games and Gamification
Canadian institutionsAthabasca University
Fundersnot available
KeywordsVocabularyOutcome (game theory)PsychologyMathematics educationOrder (exchange)Process (computing)Computer scienceMultimediaBusinessMathematics

Abstract

fetched live from OpenAlex

The research team has developed a web-based multiplayer trading card game to allow teachers choosing cards as rewards for students who actively participate in discussions and classroom activities as well as perform well in terms of doing assignments and writing exams or quizzes. In order to verify the effectiveness of the use of in-game cards as rewards, the research team integrated the trading card game into a web-based English vocabulary learning system. Students can receive cards as rewards every time after they use the learning system. A 6-week experiment had been conducted at an elementary school with 172 fifth-grade students. The results showed that boys have higher intention of getting the in-game cards as rewards. The research also showed that the use of the in-game cards as educational rewards not only motivates students to use the vocabulary learning system but also improves their learning outcome. The research result supported the recommended process for teachers to adopt the trading card game in their courses.

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)0.007
metaresearch head score (Gemma)0.029
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.551
Threshold uncertainty score0.979

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.029
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.078
GPT teacher head0.513
Teacher spread0.435 · 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