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Record W2972021026

Extend of TAM Model with Technology anxiety and Self-Efficacy to Accept Course websites at University Canada West

2019· article· en· W2972021026 on OpenAlexaboutno aff
Saleh Ali NuriAbdalla

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldDecision Sciences
TopicTechnology Adoption and User Behaviour
Canadian institutionsnot available
Fundersnot available
KeywordsTechnology acceptance modelPsychologyUsabilityVariablesAnxietyDistance educationSocial psychologySelf-efficacyMedical educationApplied psychologyMathematics educationComputer scienceStatisticsMathematicsMedicine
DOInot available

Abstract

fetched live from OpenAlex

Learning technology is the use of technology to support the learning process - widely known as e-learning. In higher education, this term refers to educational web sites such as online courses. The acceptance of technology in the learning process depends on some crucial factors. This research paper investigated the relationship among several variables that are related to educational technology performance based on the technology acceptance modal (TAM).  The respondents were 61 students who are studying in the University Canada West (both undergraduate and postgraduate). Descriptive, correlation and multiple regressions were conducted to date. The results of the investigation showed that there was a positive correlation relationship among variables except of one variable, technology anxiety that was not correlated with the others. The multiple regressions resulted that two of independent variables, perceived of ease and self-efficacy, had a significant positive effect on the intention of use.

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)0.000
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 score0.239
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.022
GPT teacher head0.283
Teacher spread0.261 · 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

Citations5
Published2019
Admission routes1
Has abstractyes

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