Teacher’s Attitudes towards Educational Technology in English Language Institutes
Bibliographic record
Abstract
The issue of attitude towards technology is not a new one; it has been around since computers were first placed in the classroom. There appears to be a positive attitude towards technology, so researchers aimed to seek out new information in an effort to find the relationship among teachers’ tenure, age, educational level, experience and teachers’ attitude toward technology. The purpose of this study was to investigate the attitude towards technology among teachers working in several institutes in Mazandaran. A total of 100 teachers including 38 males and 62 females, ranging in age from 22 to 50 and 20 to 42 respectively completed a survey. The non-parametric Spearman Rank-Order Correlation was used to find the relationship between the variables. The result of the research questions showed that: (1) there was a statistically significant relationship between teacher experience and attitude toward technology, (2) there was a statistically significant relationship between teacher tenure and attitude towards technology, and (3) there was a statistically significant relationship between teacher age and attitude toward technology.
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 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 | 0.273 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".