Mitigating academic cheating through innovations in interdisciplinary and transdisciplinary teaching and peer assessment in digital educational environments
Thuy Thi Bich Vo et al.
What the paper says
Purpose Academic cheating, particularly in unsupervised digital environments, is a persistent challenge. This study examines the effectiveness of interdisciplinary and transdisciplinary teaching approaches combined with peer assessment in mitigating academic dishonesty. Design/methodology/approach Over one semester, an experimental group ( N = 111) applied the proposed methods, while a control group ( N = 55) followed traditional practices. Peer assessment was integrated after midterm assignments to evaluate dishonesty levels and work replicability using a reliable scale. Surveys compared dishonest behaviors between the two groups. Findings ANOVA results reveal that (1) academic dishonesty was significantly lower in the experimental group. (2) Peer assessment showed that experimental group students demonstrated greater creativity, synthesis and citation accuracy. (3) Statistical analysis confirmed significant differences between groups (Sig. < 0.05). Practical implications This study offers valuable insights for educators and higher education institutions to enhance academic integrity in digital learning through innovative teaching and assessment strategies, supporting policy improvements in digital education. Social implications A significant implication is the need to innovate teaching and assessment practices by integrating interdisciplinary and transdisciplinary teaching and peer assessment solutions. Originality/value This research presents a novel experimental approach to reducing academic dishonesty in unsupervised digital environments, offering practical, resource-efficient solutions that promote transparency, self-monitoring and mutual accountability.
1 citation
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.16 × 0.4 = 0.06 |
| M · momentum | 0.53 × 0.15 = 0.08 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.