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Scaffolding of Intuitionist Ethical Reasoning with Groupware: Do Students’ Stances Change in Different Countries?

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Collaboration Technologies and Social Computing (CollabTech 2022)

Abstract

Ethics education is essential in business and STEM curricula. For decades up to the present day, a rationalist conception of ethics has been highly influential in its pedagogy. However, in the past twenty years, developments in moral psychology and neuroscience support that moral thought and deliberation are guided by a dual process initiated by intuition. In this research, we present the design of a scaffolding for ethics teaching based on groupware with individual and collaborative activities, informed by the Social Intuitionist Model (SIM) and Moral Foundations Theory (MFT). We conducted an exploratory study based on an original case about academic ethics, involving student samples in five higher education institutions in four countries (N = 249). Results indicate that ethical reasoning, initially guided by intuition, can be influenced by facts, reflective questions, and social interaction. Students regardless of their initial intuitive stance about an eliciting situation, and their moral sensitivity according to MFT, changed their final decision on the situation significantly by the end of the intervention according to a Wilcoxon signed rank test (p < 0.001). About 30% of the sample swung to a stance opposite to what they decided at the outset of the intervention. A question that stems from this research is how students’ ethical thinking could be scaffolded and oriented, both pedagogically and technology-wise, towards identifying and standing for solutions to ethical dilemmas that are based on virtue and bring greater good.

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Correspondence to Claudio Álvarez .

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Álvarez, C. et al. (2022). Scaffolding of Intuitionist Ethical Reasoning with Groupware: Do Students’ Stances Change in Different Countries?. In: Wong, LH., Hayashi, Y., Collazos, C.A., Alvarez, C., Zurita, G., Baloian, N. (eds) Collaboration Technologies and Social Computing. CollabTech 2022. Lecture Notes in Computer Science, vol 13632. Springer, Cham. https://doi.org/10.1007/978-3-031-20218-6_18

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  • DOI: https://doi.org/10.1007/978-3-031-20218-6_18

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