Integrating Social Networking Tools into ESL Writing Classroom: Strengths and Weaknesses
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
With the rapid development of world and technology, English learning has become more important. Teachers frequently use teacher-centered pedagogy that leads to lack of interaction with students. This paper aims to investigate the advantages and disadvantages of integrating social networking tools into ESL writing classroom and discuss the ways to plan activities by integrating social networking services (SNSs) into the classroom. Data was collected through an online discussion board from TESL students in a state university in Malaysia. The findings revealed that integrating social networking services in ESL writing classroom could help to broaden students’ knowledge, increase their motivation and build confidence in learning ESL writing. The students’ difficulties for concentrating on the materials when they use computer, lack of enough equipment as well as access to internet, and teachers’ insufficient time to interact with the students were regarded as the main disadvantages of integrating social networking tools into ESL writing classes. Therefore, in this new technological era, it is essential for students and teachers to be equipped with technical skills to be competent for life-long learning and teaching. More studies are needed to explore the teachers’ and students’ attitudes towards using ICT in ESL/EFL contexts. Future quantitative and qualitative studies with more participants are needed to provide deeper insight.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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