The Elementary School Teachers Adoption of Learning Management System: A UTAUT Model Analysis
Bibliographic record
Abstract
This study investigates how primary school teachers are integrating Learning Management Systems (LMS) using the Unified Theory of Acceptance and Use of Technology (UTAUT) approach.A four-point Likert scale questionnaire including characteristics like Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Conditions, Hedonic Motivation, Price Value, and Habit was used in this study, which involved 426 instructors from 84 public and private primary schools.Google Forms was used to collect the data, and structural equation modeling (SEM) was used to analyze it.The results of the study show that these factors have a strong correlation with teachers' behavioral intentions and user behavior with reference to LMS, demonstrating excellent reliability and validity.These results align with the UTAUT model, contributing to the understanding of factors influencing LMS adoption among elementary school teachers.The implications suggest that policymakers and practitioners can utilise these findings to design more effective strategies for enhancing technology adoption in future educational contexts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".