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Record W2167784099 · doi:10.5539/mas.v9n11p144

Personal Moral Philosophy of Undergraduates towards Academic Dishonesty

2015· article· en· W2167784099 on OpenAlexvenueno aff
Jeffrey Lawrence D’Silva, Chan Ling Meng, Jamilah Othman, Zoharah Omar

Bibliographic record

VenueModern Applied Science · 2015
Typearticle
Languageen
FieldDecision Sciences
TopicEthics in Business and Education
Canadian institutionsnot available
FundersUniversiti Putra Malaysia
KeywordsCheatingAcademic dishonestyIdealismRelativismDishonestyPsychologyPerspective (graphical)Social psychologyMoral philosophyMoral developmentEpistemologyPhilosophyComputer science

Abstract

fetched live from OpenAlex

Undeniably moral belief among undergraduates is pertinent since it will provide a better perspective to seek for answers on the possible reasons undergraduates engage in unethical behavior. However, the existing literature showed that only limited studies focused in this specific moral belief development of undergraduates. Hence, the main aim of this study is to identify the level of personal moral philosophy (idealism and relativism) of undergraduates and to examine the relationship between the personal moral philosophy and undergraduates’ academic cheating behavior. Data were collected from 620 undergraduates through questionnaire surveys by employing a simple random sampling. The study found that undergraduates are lately more idealism compared to relativism, which indicated that students are aware with the academic cheating behavior and try to avoid involving in it. Future recommendations are provided to further understand the complexities associated with academic dishonesty.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.999
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.437
GPT teacher head0.434
Teacher spread0.003 · 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 source (direct Gemma or distilled Codex), 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
Published2015
Admission routes1
Has abstractyes

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