Behind The Veil Of Silence: An Exploratory Invistigation Into The Silence Of Female Saudi Arabian Learners Of English
Bibliographic record
Abstract
This mixed-methods study investigates the unexplored issue of silence in Saudi female university foreign language (EFL) classroom. Inspired by personal experiences and informed by the complexity approaches to study learner silence, I adopt an approximate replication of King’s (2013b) methodology to perform an extensive investigation of the phenomenon of learner silence in the Saudi female higher education context. To this end, a multi-site study using structured observation methodology was employed to investigate the classroom behaviour of over 500 language learners across three Saudi female universities. To effectively measure the extent of macro-level silence in these research settings, a modified version of the classroom oral participation scheme (King, 2013a,b) was developed. A total of 45 hours of data were collected using a minute-by-minute systematic sampling strategy that uncovered some startling results. Specifically, I found that over 90 % of the total observed lessons time was characterised by the learners’ silence, and an extreme lack of students’ voluntarily participation in the EFL classroom at only less than quarter of a one percent of the total lessons time. This striking quantitative evidence is further corroborated by qualitative results. My analysis of over 100,000-word of transcribed data collected in two types of qualitative interviews provided valuable insights into students’ experiences about remaining silent in their L2 educational context. Specifically, to uncover the process of learners’ thinking and to understand their feelings during silence episodes, I conducted a series of 10 stimulated recall interviews employing an event-specific focus on classroom silence. The final phase of the data collection focused on individual analysis of learners’ perspectives and fundamental beliefs about classroom silence drawing on 14 semi-structured interviews. Applying Complex Dynamic Systems Theory (CDST) as an analytical framework, the investigation moves away from the reductionist approach of generating single cause-effect explanation of the phenomenon of Saudi female EFL learners’ silence. The study uncovered multiple interconnected factors rooted in the Saudi sociocultural and educational contexts. The results highlight the multi-dimensional nature of the seemingly simple act of not speaking and emphasize the need to view Saudi female silence as a potential veil that should be examined from the perspective of the interplay between both individual psychological factors and the environmental influences of the institutional and higher societal levels.
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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 | 0.001 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".