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Record W4283657391 · doi:10.5539/jedp.v12n2p43

Large Class Management throughout Learning and Teaching of Speaking Skill: Case study of the University of Burundi

2022· article· en· W4283657391 on OpenAlexvenueno aff
Sinai Bakanibona

Bibliographic record

VenueJournal of Educational and Developmental Psychology · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsnot available
Fundersnot available
KeywordsSeriousnessClass (philosophy)Simple random samplePsychologyMathematics educationCase study researchQualitative researchPopulationMedical educationPedagogySociologyComputer scienceMedicinePolitical science

Abstract

fetched live from OpenAlex

The objective of this study was to discuss challenges encountered by lecturers and students in the management of large classes while teaching and learning the speaking skill in English. The work was motivated by the fact that First Year students, even though they use English as medium of instruction, are not good at speaking English. The study enthralled on the use of appropriate methods, approaches and techniques to manage large classes. The purpose of the study was to examine the category and seriousness of the challenges faced by the subjects and suggest the use of appropriate methods, techniques and approaches in a large class of more than a hundred students. The case study was conducted at the Institute for Applied Pedagogy of the University of Burundi. Simple random sampling was adopted to select students, lecturers and administrators concerned as the study population. A written questionnaire, interview and participant observation were used during the study through the qualitative analysis.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.160
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.301
Teacher spread0.279 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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