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Case Studies in Pediatric Psychiatry: An Approach to Deep Learning and Experience Acquisition.
Publication year - 2020
Language(s) - English
DOI - 10.46940/sjpmh.01.1004
Subject(s) - comprehension , deep learning , field (mathematics) , curriculum , psychology , medical education , artificial intelligence , medicine , computer science , pedagogy , mathematics , pure mathematics , programming language
It has been disturbingly observed that many learners in the field of medicine, both undergraduate and postgraduate levels may have satisfactory information acquisition in their fields of study, but fail to use it appropriately when it comes to clinical practice. One of the important roles of instructors and professional trainers in the field of medicine is to encourage learners to adopt deep learning approaches by making the studied materials interesting and design a curriculum and assessment methods that encourage understanding which help in establishing and creating experience. Deep learning is mostly motivated by the interest in understanding the studied materials and the need to interpret the presented knowledge during the course. Comprehension is the main intention and focus of the learners adopting deep learning [1-3]. This special article presents authentic real case studies in child psychiatry aiming at encouraging the learners of this field to adopt deep learning by making these cases interesting with real patients’ photos. These cases which represents major referrals in at the pediatric psychiatry clinic are designed to make comprehension is the essential outcome of learning.

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