The Impacts of Blended Learning on English Language Proficiency in Higher Education: A Systematic Literature Review
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
Blended learning, integrating traditional and online instruction, has emerged as a significant approach to enhancing English proficiency (listening, speaking, reading, writing) among non-native university students. This study conducted a PRISMA 2020-guided systematic review of 52 articles (2020-2024) from Web of Science, Scopus, EBSCOhost, and ERIC, with 30 meeting MMAT quality criteria. Using the PICO framework, it analyzed blended learning’s impact on language skills. Findings indicated notable improvements across all four competencies, attributed to methods like timely feedback, task/project-based learning, and self-paced modules, alongside strategies such as flipped classrooms, multimodal resources, mobile technologies, and collaborative activities. These approaches enhanced flexibility, interactivity, and personalized learning while providing rich resources. The integration of online and offline phases, combined with structured peer/instructor interaction, was critical for skill development. Results underscore blended learning’s potential to inform instructional design, policy-making, and quality improvements in higher education language programs, addressing globalization-driven demands for advanced English proficiency.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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