Dataset from a Quasi-Experimental Study on Enhancing Academic Integrity and Reducing Plagiarism through a Generative AI-Based Paraphrasing Tool in Multilingual Higher Education

This dataset is derived from a quasi-experimental study titled “Enhancing Academic Integrity and Reducing Plagiarism through a Generative AI-Based Paraphrasing Tool: A Quasi-Experimental Study in Multilingual Writing Education.” The study investigated the impact of Languafrasa, a generative AI-based paraphrasing tool specifically designed to support ethical academic writing, on the performance, ethical awareness, and perception of undergraduate students engaged in multilingual education. The study involved 300 undergraduate participants divided equally into experimental and control groups. Over a six-week period, the experimental group utilized the AI tool to complete weekly paraphrasing tasks integrated into a learning management system, while the control group performed the same tasks without access to AI. The dataset includes demographic profiles (age, gender, and field of study), pretest and posttest similarity scores (including gain scores), rubric-based evaluations of paraphrasing quality across five dimensions—semantic fidelity, syntactic transformation, lexical diversity, citation ethics, and clarity—along with measures of engagement and ethical awareness, and student perception survey responses in both Likert and open-ended formats. All statistical procedures were conducted using JASP, including descriptive statistics, assumption testing, paired and independent samples t-tests, one-way ANOVA, MANOVA, and Wilcoxon signed-rank tests. Results are presented in six summary PDF files corresponding to the study’s three research questions. Each file contains structured outputs, effect size calculations, and narrative interpretations. The dataset offers a comprehensive, transparent, and replicable resource for researchers, educators, and instructional designers interested in academic integrity, AI-assisted writing instruction, and multilingual learning environments in higher education.