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Record W2588869662 · doi:10.1564/tme_v23.1.03

Secondary Students Learning Mathematics Through Digital Game Building: A Study Of The Effects And Students’ Perceptions

2016· article· en· W2588869662 on OpenAlexaff
Qing Li, Elise Vandermeiden, Collette Lemieux, Shahista Nathoo

Bibliographic record

VenueInternational Journal for Technology in Mathematics Education · 2016
Typearticle
Languageen
FieldPsychology
TopicEducational Games and Gamification
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMathematics educationPerceptionGame based learningPsychologyComputer science

Abstract

fetched live from OpenAlex

This study explored secondary students’ learning experiences in mathematics through digital game building. In this study, students were asked to become designers and builders in order to coauthor their own mathematics learning. Grounded in enactivism, this study examined the impact of game building on students’ achievement. In addition, it explored students’ perceptions about their game building experience. Forty secondary students participated either in a treatment or control group. Results showed that the treatment group experienced significant achievement gains. The analysis of the qualitative data revealed that the students perceived that game building experiences afforded them a chance to see math in a new light: math learning became fun, exciting, creative, and contextualized shared actions. Further discussion and implications are detailed.

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)0.001
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 score0.302
Threshold uncertainty score0.426

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.000
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 head0.395
Teacher spread0.379 · 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 designObservational
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

Citations5
Published2016
Admission routes1
Has abstractyes

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