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Record W1686658427 · doi:10.1111/jcal.12036

Learning in a mobile age: an investigation of student motivation

2013· article· en· W1686658427 on OpenAlexaff
Katia Ciampa

Bibliographic record

VenueJournal of Computer Assisted Learning · 2013
Typearticle
Languageen
FieldComputer Science
TopicMobile Learning in Education
Canadian institutionsBrock University
Fundersnot available
KeywordsAffordanceCuriosityPsychologyMobile deviceIntrinsic motivationPerceptionMathematics educationM-learningEducational technologyPedagogySocial psychologyComputer scienceCognitive psychologyWorld Wide Web

Abstract

fetched live from OpenAlex

Abstract The purpose of this single‐case study was to explore the lived experiences of a grade 6 teacher and students who used tablets as part of their classroom instruction. M alone and L epper's taxonomy of intrinsic motivations for learning is used as a framework for examining whether and how this particular theory of motivation applies equally well for mobile learning. This study reports on the grade 6 teacher's and students' perceptions regarding the motivational affordances of using these mobile devices for learning. The findings are consistent with those of M alone and L epper that motivation can be enhanced through challenge, curiosity, control, recognition, competition and cooperation. This model is helpful in informing our understanding of the motivating features of using mobile devices for learning and how mobile technologies can be used to enhance learners' motivation.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0040.002
Scholarly communication0.0050.002
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.023
GPT teacher head0.285
Teacher spread0.262 · 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 source (direct Gemma or distilled Codex), 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

Citations388
Published2013
Admission routes1
Has abstractyes

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