![]() Methods of Information in Medicine 49(3), 207–218 (2010)Ĭytowic, R.E.: Synesthesia: A union of the senses. Luneski, A., Konstantinidis, E., Bamidis, P.D.: Affective medicine: A review of affective computing efforts in medical informatics. ![]() ![]() Picard, R.W., Papert, S., Bender, W., Blumberg, B., Breazeal, C., Cavallo, D., Machover, T., Resnick, M., Roy, D., Strohecker, V.: Affective learning-a manifesto. Krathwohl, D.R., Bloom, B.S., Masia, B.B.: Handbook II: affective domain. David McKay Co Inc., New York (1956)īloom, B.S.: Taxonomy of educational objectives, vol. Special Topic: Assessment in University General Education Program 6(1), 1–44 (2009)īloom, B.S., Engelhart, M.D., Furst, E.J., Hill, W.H., Krathwohl, D.R.: Taxonomy of educational objectives, handbook I: The cognitive domain, vol. Gano-Phillips, S.: Affective learning in general education. The paper concludes with a visionary use case towards affective facilitation of training against medical errors and decision making by intelligent, self-regulated systems that could exploit scenario based learning to augment medical minds for tomorrow’s doctors. Neuroscientific emphasis is placed in the synergy of two perspectives, namely, the detection and recording of emotions from humans and ways to facilitate their elicitation and their subsequent exploitation in the decision-making process. Medical education is borrowed as a domain of reference. In this paper, the concept of affective learning is furnished with case studies where the roles of technologies, neuroscience, learning and education are interwoven. However, measuring and modelling learners’ emotional and affective states remains a difficult task, especially when real-time interactions are envisaged. To cope with personalised learning experiences in such models of learners though, intelligent tutoring systems must now contain “emotion, affect and context”, in analogy to successful human tutors. Having overemphasised the cognitive and relatively neglecting the affective dimension in the past, technology enhanced learning is now enforced by new neuroscience findings that confirmed that affect is complexly intertwined with thinking, and performing important functions that may guide rational behaviour, assist memory retrieval, support decision-making and enhance creativity. In the digital age we live though, affective learning is destined to be technology driven or at least enhanced. Although the issues around emotions and learning are not new, the term affective learning has only recently been defined as the learning that relates to the learner’s interests, attitudes, and motivations.
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