A Contrastive Analysis of Pre-Service and In-Service EFL Teachers’ Levels of Technological, Pedagogical, and Content Knowledge
Bibliographic record
Abstract
This study attempted to investigate pre-service and in-service EFL teachers’ levels of knowledge in content, pedagogy, and technology in relation to their gender, Internet access at school, and technology training in Saudi Arabia. The Technological, Pedagogical, and Content Knowledge (TPACK) framework was utilized to (1) examine pre-service and in-service EFL teachers’ levels of TPACK; (2) investigate the differences between pre-service and in-service EFL teachers’ levels of TPACK; (3) scrutinize whether gender, Internet access at school, and technology training had any significant effect on pre-service EFL teachers’ levels of TPACK; and (4) analyze whether gender, Internet access at school, and technology training had any significant effect on in-service EFL teachers’ levels of TPACK. The participants in this study were (111) EFL pre-service teachers and (106) EFL in-service teachers. The descriptive statistical analysis (mean and standard deviation) revealed that the pre-service teachers’ overall level of TPACK was moderate scoring highest in TK, TPK, and TCK and lowest in CK and PK respectively. On the other hand, the in-service teachers’ overall level of TPACK was moderate scoring highest in CK, PK, and PCK and lowest in TK, TPK, and TCK respectively. The inferential statistical analysis (t-test) indicated a statistically significant difference between pre-service and in-service teachers’ levels of TPACK. All the seven sub-domains of TPACK were significant, with pre-service teachers scoring higher in TK, TCK, and TPK while in-service teachers scoring higher in CK, PK, PCK, and TPACK. The inferential analysis also showed that gender, Internet access at school, and technology training had a significant effect on both pre-service and in-service EFL teachers’ levels of TPACK. The study concluded that both pre-service teacher education programs and in-service teacher training courses need to focus on the connections and interactions between content, pedagogy, and technology in order to help EFL teachers integrate technology effectively into their teaching process. The study recommended investigating other factors that might be predictive of teachers’ levels of TPACK.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".