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Record W2081088072 · doi:10.5121/ijite.2014.3401

A Study of The Interface Usability Issues of Mobile Learning Applications for Smart Phones from the User’s Perspective

2014· article· en· W2081088072 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

VenueInternational Journal on Integrating Technology in Education · 2014
Typearticle
Languageen
FieldComputer Science
TopicMobile Learning in Education
Canadian institutionsWestern University
Fundersnot available
KeywordsUsabilityAndroid (operating system)User interfaceCognitive walkthroughUsability engineeringMobile devicePluralistic walkthroughUsability labUsability inspection

Abstract

fetched live from OpenAlex

A conceptual framework for measuring the usability characteristics of mobile learning (m-Learning) application has been developed. Furthermore, a software prototype for smartphones to assess usability issues of m-Learning applications has also been designed and implemented. This prototype has been developed, using Java language and the Android Software Development Kit, based on the recommended guidelines of the proposed conceptual framework. The usability of the proposed model was compared to a generally available similar mobile application (based on the Blackboard) by conducting a questionnairebased survey at Western University. The two models were evaluated in terms of ease of use, user satisfaction, attractiveness, and learnability. The results of the questionnaire showed that the participants considered the user interface based on our proposed framework more user-friendly as compared to the Blackboard-based user interface.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.302
Threshold uncertainty score0.415

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
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 science0.0020.000
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 head0.011
GPT teacher head0.352
Teacher spread0.341 · 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