An informal Facebook group for English language interaction : a study of Malaysian university students' perceptions, experiences and behaviours
Bibliographic record
Abstract
This study looks at a group of Malaysian university students’ perceptions, experiences and behaviours when presented with an informal, participatory Facebook interaction group for English language practice. Three methods of data collection, namely questionnaire, LMT100 Facebook interaction group, and semi-structured interview were employed in stages. \n \nThe findings show a discrepancy between the participants’ perceptions of using Facebook for English language learning (ELL), and their experiences and behaviours when presented with the interaction group. Only a quarter of the participants used the group actively by initiating interaction threads, and communicating with each other. A huge majority acted passively by making their participation visible just once or repeatedly through the means of likes and short comments. The rest of the members were silent readers who never made their involvement visible over the period of six weeks. \n \nThe students showed higher participation rate when presented with three topics; entertainment-based, grammar quizzes, and university-related inquiries. This was discussed as students’ selective interests and preferences in learning. The types of online content suitable for English language learning was also addressed. More passive interviewees reported small improvements in their communicative competence from the interaction activity. The active interviewees however only felt a boost in their confidence to use English publicly rather than experience enhanced English language ability. \n \nThe discrepancy between the students’ perceptions and behaviours are discussed from three levels of sociocultural influences which are personal, institutional, and societal. The students’ prior English language learning experience within an education system that privileges examinations may have influenced their (non)participation in the LMT100 group. The interviewees also indicated the existence of sentiments in racial, political, and religious issues, which may have influenced their learning experience at the university. \n \nThe findings indicate that the informal, unstructured English language interaction platform on Facebook as having great potentials, although not tremendously successful in this study. Several implications are presented as strategies that may assist the integration of Facebook for English language learning in the future. \n
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".