Teaching Approaches Compatible with First-Year Accounting Student Teachers’ Learning Styles: Theoretical and Phenomenological Perspectives
Bibliographic record
Abstract
Premised on the theoretical assumptions of social constructivism and multiple intelligences, the purpose of this conceptual study was to investigate teaching approaches which are compatible with the learning styles of first-year accounting student teachers from a theoretical perspective. Being a conceptual study in nature, data was collected from a host of sources on learning styles, teaching approaches, social constructivism and multiple intelligences. The study established that while not all first-year accounting student teachers are able or do not prefer to learn everything in the same way, social constructivist centred approaches are highly compatible with most of the students’ learning styles. Based on literature verdicts, the study recommends the application of the principles of social constructivism in accounting lesson presentations. It is also recommended that accounting lecturers should orchestrate all teaching and learning activities around student needs and their learning styles. Furthermore, the findings from literature review provide a sound basis to recommend that students must always be at the centre of all teaching and learning, regardless of the pedagogical beliefs and preferred teaching approaches of the accounting lecturer.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".