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Record W2909475816 · doi:10.1002/pits.22225

The use of touch devices for enhancing academic achievement: A meta‐analysis

2019· article· en· W2909475816 on OpenAlex
Shawna Petersen‐Brown, Erin E. C. Henze, David A. Klingbeil, Jennifer L. Reynolds, Rachel C. Weber, Robin S. Codding

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

VenuePsychology in the Schools · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMeta-analysisPsychologyAcademic achievementIntervention (counseling)Research designMathematics educationApplied psychologyMedical educationMedicine

Abstract

fetched live from OpenAlex

Abstract Touch devices such as tablets and smartphones are widely adopted in educational settings and have many desirable features. However, research supporting the use of touch devices to improve academic achievement is emergent and has not been evaluated through a meta‐analysis. We conducted a meta‐analysis of 65 group and single case design research studies, published 2010–2018, to evaluate the effects of touch device implementation on academic achievement. The overall mean effect sizes were moderate for group design and single case design studies. Participant, intervention, and study attributes were also evaluated to describe the research and how these attributes may moderate the results. Overall, results suggest that touch devices may be an effective tool for enhancing academic achievement. The need to conduct additional, rigorous research on the use of touch devices as well as implications for researchers and practitioners are discussed.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.719
Threshold uncertainty score0.253

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 science0.0010.000
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 head0.136
GPT teacher head0.405
Teacher spread0.269 · 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