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Record W1621359596 · doi:10.14742/ajet.1087

Assessing laptop use in higher education classrooms: The Laptop Effectiveness Scale (LES)

2010· article· en· W1621359596 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

VenueAustralasian Journal of Educational Technology · 2010
Typearticle
Languageen
FieldComputer Science
TopicMobile Learning in Education
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsLaptopScale (ratio)PsychologyConstruct validityMathematics educationHigher educationComputer scienceMultimediaPsychometricsDevelopmental psychology

Abstract

fetched live from OpenAlex

<span>Considerable research has been conducted examining the use of laptops in higher education, however, a reliable and valid scale to assess in-class use of laptops has yet to be developed. The purpose of the following study was to develop and evaluate the </span><em>Laptop Effectiveness Scale</em><span> (LES). The scale consisted of four constructs: academic use and three areas of non-academic use (communication, watching movies, playing games). Tested on 177 higher education students, the data generated using the LES showed acceptable internal reliability, construct validity, content and convergent validity. Feedback from students suggested that both academic and non-academic constructs assessed by the LES could be expanded to incorporate a wider range of laptop related behaviour</span>

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)0.001
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 score0.344
Threshold uncertainty score0.636

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.024
GPT teacher head0.321
Teacher spread0.297 · 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