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Record W3164113174 · doi:10.5430/ijfr.v12n4p225

A Systematic Literature Review on Critical Thinking in an Undergraduate Accounting Programme

2021· article· en· W3164113174 on OpenAlexvenueno aff
Lilian Ifunanya Nwosu, Hester H. Vorster

Bibliographic record

VenueInternational Journal of Financial Research · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAccounting Education and Careers
Canadian institutionsnot available
FundersNorth-West University
KeywordsCritical thinkingBackwardnessAccountingMathematics educationPsychologyBusiness

Abstract

fetched live from OpenAlex

The ability of accountancy students to apply critical thinking in solving problems related to modules offered in accountancy undergraduate programme, has remained a concern for many higher institutions. Accountancy students tend to struggle to apply critical thinking to their course work offered in the programme. To be able to apply critical thinking, accountancy students in undergraduate programmes should be able to apply a series of attributes that can enable them to understand questions asked in case study questions or multiple tasks. This study reviewed various ways in which students can apply critical thinking in an undergraduate accounting programme. A systematic literature review was conducted to examine the challenges undergraduate accounting students in South Africa face in applying critical thinking. This study found some of the barriers for applying critical thinking include redundancy, backwardness, application, extent to which preferences are associated to learning, and the ability to engage in real life accountancy practice. Literature reveals that accounting students can use the cube method which includes six steps: describe, compare, associate, analyse, apply, and argue to address the challenges of applying critical thinking. The study however, proposed some strategies that academics can use to ensure that accountancy students are able to apply critical thinking in solving accounting problems. Students are able to apply critical thinking in problem solving. Suggestions for future research were provided.

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)0.005
metaresearch head score (Gemma)0.019
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.682
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0000.001
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 head0.060
GPT teacher head0.402
Teacher spread0.343 · 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 designTheoretical or conceptual
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

Citations3
Published2021
Admission routes1
Has abstractyes

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