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Research into academic integrity (AI) has a long history of extensive work to estimate the prevalence of and predictors for academic misconduct in higher education (HE). In addition, concern about the high prevalence of academic misconduct has justified a proliferation of recommendations for reducing academic misconduct. Scholars have lamented, however, the dearth of research investigating the effectiveness of interventions to prevent academic misconduct. This chapter reports on a review of 97 quantitative studies that investigated the effectiveness of interventions related to academic misconduct in HE. The evidence supports the effectiveness of text-matching software and honor code systems in reducing plagiarism and cheating, respectively. The effectiveness of proctoring examinations, providing instruction about plagiarism, and delivering instruction about AI are not supported by the evidence. Recommendations for future research are suggested.
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Stored only when both papers are in the corpus — 18 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.