The Role of Blended Learning on Moderating Self-Motivation to Mitigate Foreign Language Anxiety among EFL Students
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 purpose of this study is twofold: (1) it looks at how much foreign language anxiety and self-motivation there are among EFL students, and (2) to determine if learning preferences interact with self-motivation to lessen FLA, i.e., moderate this relationship. To do this, 232 EFL students from the 2020–2021 academic year were randomly chosen to participate in a survey method at three universities in central Saudi Arabia: Qassim University, Majmaah University, and Shaqra University. SPSS was used for descriptive analysis, where Macro Process Hayes Plug-In was used for the moderated regression analysis. The findings showed a moderate level of internal and extrinsic goal orientation, control over learning beliefs, self-efficacy, task value, social engagement, instructor support, as well as anxiety related to learning a foreign language. Additionally, it was determined that participant demographic factors had no statistically significant impact on any of the distinct dimensions of self-motivation or anxiety related to learning a foreign language. More significantly, blended learning was found to have a greater negative impact on foreign language classroom anxiety than face-to-face learning and e-learning, indicating that it has a greater impact on increasing self-motivation to lessen classroom anxiety.
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 | 0.000 |
| 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 | 0.000 | 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