Developing and Assessing a Digital Platform for Teaching Ethical Decision-Making

Thesis Abstract

The increasing complexity of ethical dilemmas faced by professionals across various sectors necessitates innovative pedagogical approaches to effectively teach ethical decision-making. Traditional methods such as lectures and case study discussions often lack immersive engagement and practical applicability, thereby limiting students’ readiness to navigate real-world ethical challenges. This study aims to develop, implement, and assess a digital learning platform specifically designed to enhance ethical decision-making skills among postgraduate students in philosophy and ethics programs. The specific objectives include designing the platform based on established ethical decision-making models, evaluating its usability and pedagogical efficacy, and analyzing its impact on learners' ethical reasoning and decision-making competence. Adopting a mixed-methods research design, the study integrates quantitative and qualitative approaches to facilitate a comprehensive evaluation of the platform. The quantitative component employs a quasi-experimental pretest-posttest control group design involving 200 postgraduate students from a leading university’s philosophy department. Participants are randomly assigned into an experimental group, which utilizes the digital platform, and a control group, which receives traditional instruction. Data collection instruments comprise validated ethical reasoning assessments, user satisfaction surveys, and platform usability questionnaires, all subjected to validity and reliability testing through Cronbach's alpha and confirmatory factor analysis. Qualitative data, gathered via focus group discussions and semi-structured interviews with 20 participants, are analyzed through thematic analysis to explore user experiences and perceived learning outcomes. Data analysis involves descriptive statistics to characterize participant responses, inferential statistics including paired t-tests and ANOVA to determine statistically significant differences between control and experimental groups, and multiple regression analysis to identify predictors of ethical decision-making improvement. Thematic analysis is applied to qualitative data to identify recurrent themes related to platform usability, engagement, and pedagogical effectiveness. The study also adopts Kohlberg’s stages of moral development and Rest’s Four Component Model as theoretical frameworks to guide the platform’s design and interpretive analysis. Anticipated findings suggest that the digital platform significantly enhances students’ ethical reasoning abilities, as evidenced by higher post-intervention scores compared to the control group, with effect sizes indicating moderate to substantial gains. User feedback is expected to reflect high levels of engagement, perceived relevance, and usability, supporting the platform’s pedagogical value. The integration of visual simulations, interactive scenarios, and immediate feedback mechanisms is projected to foster deeper moral reflection and practical ethical judgment skills, aligning with cognitive engagement theories. This research contributes novel empirical evidence to the field of ethics education by demonstrating that well-designed digital platforms can effectively complement traditional instructional methods, fostering advanced ethical reasoning in postgraduate learners. It advances knowledge on the application of technology-enhanced learning in moral education, offering evidence-based guidelines for future integration of digital tools in ethics curricula. The study concludes that digital platforms constitute a viable and scalable means to improve ethical decision-making competencies, and recommends their adoption in academic and professional training programs. Further research should explore longitudinal impacts, platform customization for specific professional contexts, and the integration of artificial intelligence to personalise ethical dilemmas, ensuring continuous improvement in ethics pedagogy.