MétaCan
Menu
Back to cohort
Record W4328122549 · doi:10.5430/wjel.v13n5p121

Blended Learning in English Language Teaching and Learning: A Focused Study on a Reading and Vocabulary Building Course

2023· article· en· W4328122549 on OpenAlexvenueno aff
Hamood Albatti

Bibliographic record

VenueWorld Journal of English Language · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsnot available
FundersMajmaah University
KeywordsBlended learningComputer scienceVariety (cybernetics)Reading (process)VocabularyMultimediaMathematics educationTeaching methodEducational technologyArtificial intelligencePsychologyLinguistics

Abstract

fetched live from OpenAlex

Blended Learning is a teaching approach that combines traditional face-to-face instruction with technology-mediated activities. It allows students to access course materials and interact with their peers and instructors in physical and virtual learning environments. By incorporating digital tools and resources, blended learning can provide students with more flexible and personalised learning experiences that will impact their English language learning, especially the skills of vocabulary building and reading. It also allows instructors to use a variety of teaching methods and to assess student progress in real-time. While blended learning can offer many benefits, it also requires careful planning and coordination to ensure that it is implemented effectively and meets the needs of all students.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.144
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.012
GPT teacher head0.316
Teacher spread0.304 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueWorld Journal of English LanguageSame topicOnline and Blended LearningFrench-language works237,207