Title of article :
Phy-Antastic Teaching: An Innovative Landscape for Malaysian Anatomical Education
Author/Authors :
yeoh, boon seng universiti sains malaysia - school of medical sciences - department of physiology, MALAYSIA , hadie, siti nurma hanim universiti sains malaysia - school of medical sciences - department of anatomy, MALAYSIA , omar, norsuhana universiti sains malaysia - school of medical sciences - department of physiology, MALAYSIA
Abstract :
Phy-Antastic is the pioneering horizontally-integrated pedagogy that adopts physiology-oriented anatomy teaching. A decline in time allocation for basic medical sciences (BMS) modules triggers the conflict of interests among educators. “Physiology-then-Anatomy” temporal synchronisation (and therefore Phy-Antastic) facilitates deep learning. The five highlighted features of Phy-Antastic are: (i) explicit declaration of learning outcomes and prerequisite knowledge as groundwork for the forthcoming topics; (ii) explanation of subject-related glossary to improve comprehension; (iii) elucidation of the related physiological mechanism to calibrate the learners into appreciating the cardinal anatomical features; (iv) the creative utilisation of multimodal teaching aids to simulate consolidated learning experience; (v) lesson was concluded by revisiting learning objectives, reflection on principal inquiry questions and recapitulating fundamental elements. The strength of Phy- Antastic depends on homeostatic teaching with rigorous educational outcome set-point and interdisciplinary feedback mechanisms. Small group discussion, problem-based learning and technology-assisted teaching can easily incorporate Phy-Antastic. Inertia among BMS educators in embracing interdisciplinary collaborative teaching remains the institutional barrier to the implementation of Phy-Antastic. This article proposes a prospective advancement in anatomical education for the contemplation of educators.
Keywords :
Integrated medical curriculum , Outcome , based education , Interdisciplinary teaching , Deep learning
Journal title :
Education in Medicine Journal(EIMJ)
Journal title :
Education in Medicine Journal(EIMJ)