Conference Learning Analytics and Knowledge, ACM Proceedings
Association for Computing Machinery
The accelerated adoption of digital technologies by people and communities results in a close relation between, on one hand, the state of individual and societal well-being and, on the other hand, the state of the digital technologies that underpin our life experiences. The ethical concerns and questions about the impact of such technologies on human well-being become more crucial when data analytics and intelligent competences are integrated. To investigate how learning technologies could impact human well-being considering the promising and concerning roles of learning analytics, we apply the initial phase of the recently produced IEEE P7010 Well-being Impact Assessment, a methodology and a set of metrics, to allow the digital well-being of a set of educational technologies to be more comprehensively tackled and evaluated. We posit that the use of IEEE P7010 well-being metrics could help identify where educational technologies supported by learning analytics would increase or decrease well-being, providing new routes to future technological innovation in Learning Analytics research.
Hakami, E., Hernández-Leo, D. Investigating the Well-being Impacts of Educational Technologies
Supported by Learning Analytics: An application of IEEE P7010 recommended practice to a set of cases. Dins: Scheffel M, Dowell N, Joksimovic S, Siemens G. Conference Learning Analytics and Knowledge, ACM Proceedings. 1 ed. New York: Association for Computing Machinery; 2021. p. 269-279.