A Systematic Literature Review of Emotional Scaffolding in EFL Pedagogy
Bibliographic record
Abstract
While Emotional Scaffolding has received encouraging research interest due to increase students’ engagement, academic performance, and well-being, there is scant synthesis and review study in the field of higher education and EFL teaching. Based on PRISMA (2021) principle, the present literature review has selected 33 peer-reviewed journal articles from 4 popular databases (which are Scopus, WOS, Eric, and ProQuest Education database). Through a thematic analysis of them, the review indicated 5 main categories (integrating emotional themes, emotional climate design, use of humour/storytelling, verbal affirmations/positive reinforcement, and technology medicated support) in EFL pedagogy using Emotional Scaffolding, which have received outcomes in enhancing student engagement, well-being, and language proficiency. It also addresses 3 emotional factors correlated with teaching. This study synthesizes current evidence for understanding Emotional Scaffolding in higher education EFL teaching. This review provides some implications for teachers, administrators, and other stakeholders and calls for more practical studies on higher education as well as higher vocational education level with more insights on teacher training and curriculum development.
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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 | 0.015 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.020 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".