An Investigation of the Perceptions and Experiences of the EFL Teachers and Learners About the Effectiveness of Blended Learning at Taif University
Bibliographic record
Abstract
The traditional face-to-face teaching, despite being constantly criticized by the methodologists and ever-emerging modern approaches, has never lost its scope in the (EFL) English as a Foreign Language context. Researchers and pedagogues, in order to get the both ends meet, have converged traditional face-to-face instructions and online activities into the concept of blended learning. By establishing on previous works and contexts, the present study aims at investigating Taif University’s EFL teachers and learners’ positive and negative perceptions and experiences towards the effectiveness of online (CLMS) Cambridge Learning Management System and on-site learning environments. The work utilized triangulation in the use of research methods, i.e., both qualitative and quantitative methods overlap each other: (i) structured interview of experienced EFL (4 male and 4 female) teachers of Taif University, with maximum open ended questions, exhibit qualitative dimensions of the study; (ii) an opinionnaire developed with closed ended questions by employing Likert’s five point scale to collect the data from 100 male and 100 female EFL learners of Taif University, represents quantitative perspective of the work. The opinionnaire includes 22 items and has been developed to measure the four subscales; learners’ beliefs and attitudes, promising strands that help develop learners’ confidence and language coupled with the perils that impede their creativity and motivation to learn. The findings of the study indicate that the level of strengths of blended learning is higher than its limitations. Learners found themselves satisfied being more exposed to the target language through vivid images, videos, audios, reading texts, chatting and discussion forums and acknowledged that (BLE) blended learning environment enhanced their language proficiency.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".