Exploratory Factor Analysis for Technostress Among Primary School Teachers
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.
Bibliographic record
Abstract
The aim of this study was to explore and develop instruments for measuring technostress among primary school teachers in Malaysia. The researchers adapted 28 items from previous study and modified the statement to suit current study. Then the items statement was translated into Malay language to suit the local setting. The instruments underwent expert verification for content validity, face validity and criterion validity. The study amended the item statement accordingly based experts’ comment. For pilot study, some 106 school-teachers were selected randomly for data collection. The data were explored and validated through exploratory factor analysis (EFA) procedure. The results of the EFA procedure revealed the 28 items fall into five underlying components. The components are renamed as technical oriented, profession oriented, social oriented, personal oriented and teaching-learning process oriented. The items under these five components explained 71.1% of the total variance. The internal reliability of the technostress construct was 0.95. In addition to adding to the current body of knowledge, the findings provide a reliable source of information for researchers and professional practitioners interested in future research in technostress for educators, particularly primary school teachers.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it