Integrating Technology in English Language Teaching: Global Experiences and Lessons for Indonesia
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 integration of Information and Communication Technology (ICT) in English language educational settings often improves teaching and learning (Tinio, 2016). English language teaching and technology have been seen as interesting new research era. This article reviewed studies on ICT integration in teaching from ten different countries. The aim of this review is to analyze cross cultural findings in order to determine what factors might be best applied to the Indonesia situation to improve English language learning and teaching as well as types of technology might be best adopted for ELT improvement. The articles for the study were found through internet search engine, Google scholar and ERIC in the area of technology integration and technology tools in English language teaching. Thus, the data taken is carefully investigated using inclusion and exclusion criteria. The result of analysis showed that the integration of technology in teaching can improve the experience for students and teachers and improve learning for students.
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 | 0.137 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it