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Record W4391173697 · doi:10.21083/ajote.v13i1.7218

Developing interactive pedagogies: A case of accounting pre-service teachers from Ghana

2024· article· en· W4391173697 on OpenAlexvenueno aff
Bernard Fentim Darkwa, Douglas Darko Agyei, Joseph Tufuor Kwarteng

Bibliographic record

VenueAfrican Journal of Teacher Education · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsnot available
Fundersnot available
KeywordsService (business)AccountingMathematics educationSociologyPsychologyBusinessMarketing

Abstract

fetched live from OpenAlex

This is a study of how eight pre-service teachers developed their skills in developing interactive lessons to teach concepts in Accounting in Senior High Schools in Ghana. Sequential multiple case study design was employed to observe two cohorts of four pre-service teachers who worked in two phases of a professional development scenario to design and enact interactive Accounting lessons. Data for the study were collected through observation, interviews, lesson documents and questionnaires. Pictures, content and thematic analysis procedures were used to analyse the qualitative data, whilst means and standard deviation were used to analyse the quantitative data. It emerged from the results that the interactive lessons developed and implemented by the pre-service teachers were effective in promoting participation in the classroom. The study also brought to light that interactive teaching promotes collaboration among students through solving problems in groups which helps to strengthen the bond between students. The study thus, advocates the need for teacher training institutions to focus on training teachers to acquire the skills in designing and enacting lessons interactively to promote students’ participation in the classroom.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.532
Threshold uncertainty score0.922

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.039
GPT teacher head0.402
Teacher spread0.362 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2024
Admission routes1
Has abstractyes

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