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Record W2012021036 · doi:10.1109/icmb-gmr.2010.38

Understanding Student Satisfaction in a Mobile Learning Environment: The Role of Internal and External Facilitators

2010· article· en· W2012021036 on OpenAlexaffabout
Khaled Hassanein, Milena Head, Fang Wang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldDecision Sciences
TopicTechnology Adoption and User Behaviour
Canadian institutionsWilfrid Laurier UniversityMcMaster University
Fundersnot available
KeywordsComputer scienceKnowledge managementField (mathematics)User satisfactionPsychologyDomain (mathematical analysis)Mobile deviceMultimediaHuman–computer interactionWorld Wide WebMathematics

Abstract

fetched live from OpenAlex

This paper presents and empirically validates a model of student satisfaction with mobile learning. The proposed model draws on Optimal Stimulation Theory and Learning Approach Theory from the psychology and education literature, respectively, and integrates them with prior findings from the Information Systems user satisfaction domain. The proposed model is empirically validated using a field survey of MBA students participating in a Blackberry mobile learning pilot project at a major Canadian university. The results confirm the theoretical analysis, suggesting that external facilitating factors within a mobile learner`s environment and internal facilitating factors associated with the mobile learner him/herself influence utilitarian and hedonic antecedents to student satisfaction with mobile learning.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.865

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.066
GPT teacher head0.344
Teacher spread0.279 · 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

Citations10
Published2010
Admission routes2
Has abstractyes

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