Improvement of Listening Performance among Undergraduate Learners of English as a Foreign Language (EFL): A Systematic Literature Review
Bibliographic record
Abstract
One of the most significant language skills in learning a foreign language is listening. So far, however, there has been few studies about techniques to improve listening performance among learners of English as a foreign language (EFL). The aim of this study is to conduct a systematic literature review on the improvement of listening performance among EFL undergraduate learners. The review process included five key methodological steps, which are review protocol, formulation of research question, systematic searching strategies, quality appraisal, and data extraction and analysis. The systematic searching strategies consist of identification, screening, and eligibility on five databases: Scopus, Science Direct, SpringerLink, Emerald and Sage. Three main themes were discovered based on the thematic analysis which are 1) factors influencing listening, 2) computer-assisted technology, and 3) instruction approaches. These three themes are divided into 13 sub-themes. Theme one has six subthemes: 1) phonological kownledge, 2) prosodic knowledge, 3) phraseological and syntactic knowledge, 4) aural decoding, 5) metacognitive knowledge, and 6) noise in the conversation environment; theme two has three subthemes: 1) multimedia source, 2) interactive listening software, and 3) learning management systems platform; and theme three has four subthemes: 1) discrete-items instruction approaches, 2) task-based instruction approaches, 3) strategy-based instruction approaches, and 4) integrated instruction approaches. The theoretical implications of this study inform educators and researchers about the challenges that influence EFL learners’ listening and the usefulness of computer-assisted technology and different instruction approaches in improving EFL learners’ listening. Future empirical research is needed to validate the discussed technological applications and instructional approaches to improve listening performance, investigate metacognitive instruction approaches where controversial results have persisted, and explore integrated instruction approaches that could enhance EFL learners' ability to understand and use the target language.
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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 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.013 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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 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".