Bridging Intuition and Reason: Exploring Ethical Decision-Making Through Instructional Design in Case-Based Learning

This dataset accompanies the article "Bridging Intuition and Reason: Exploring Ethical Decision-Making Through Instructional Design in Case-Based Learning" (Alvarez, Zurita & Farías), accepted for publication in The International Journal of Management Education (Elsevier). Please cite the article when using this dataset. The data were collected between April 2021 and June 2022 from undergraduate students at two Chilean universities, and comprise two linked components: 1. EthicApp case-based ethics activity (ethicapp_wide.csv, 798 participants). Students judged an academic-integrity dilemma — a friend asking for help to cheat on an exam — across seven successive phases of a collaborative activity supported by EthicApp, a Computer-Supported Collaborative Learning (CSCL) system. The phases comprised individual judgments, exposure to peers' responses, and small-team deliberation. Each row contains one participant's judgments on a 7-point semantic differential scale (1 = "Help him with the exam" … 7 = "Do not help him with the exam") for each phase, together with the written justifications provided by the student (free text, in Spanish), plus gender, course section, seniority (freshman/senior), and team membership. 2. Moral Foundations Questionnaire (mfq_raw.csv, 789 respondents). Raw item-level responses to the MFQ-30 (Graham et al., 2011), administered in Spanish, including the 30 substantive items and the 2 standard attention-check items (32 items total, 0–5 response scale), plus gender and seniority. Both files share an anonymous participant key (anon_id); 571 participants appear in both components. All direct identifiers (names, national ID numbers, e-mail addresses) were removed; participant, team, and course-section codes were recoded to anonymous labels; timestamps were excluded; and all written comments were screened for personal names. Data are exported without imputation or careless-responding exclusions, so that all screening decisions reported in the article can be reproduced from the published files; sample sizes in the article are therefore obtained after applying the analysis code. A README file included in the deposit documents the data dictionaries, variable codings, linkage between files, anonymization procedure, and known limitations.