Open Access Repository

IoTFLiP: IoT-based flipped learning platform for medical education


Downloads per month over past year

Ali, M, Bilal, HSM, Razzaq, MA, Khan, J, Lee, S, Idris, M, Aazam, M, Choi, T, Han, SC ORCID: 0000-0002-1948-6819 and Kang, BH ORCID: 0000-0003-3476-8838 2017 , 'IoTFLiP: IoT-based flipped learning platform for medical education' , Digital Communications and Networks, vol. 3, no. 3 , pp. 188-194 , doi: 10.1016/j.dcan.2017.03.002.

117870.pdf | Download (1MB)

| Preview


Case-Based Learning (CBL) has become an effective pedagogy for student-centered learning in medical education, which is founded on persistent patient cases. Flippped learning and Internet of Things (IoTs) concepts have gained significant attention in recent years. Using these concepts in conjunction with CBL can improve learning ability by providing real evolutionary medical cases. It also enables students to build confidence in their decision making, and efficiently enhances teamwork in the learing environment. We propose an IoT-based Flip Learning Platform, called IoTFLiP, where an IoT infrastructure is exploited to support flipped case-based learning in a cloud environment with state of the art security and privacy measures for personalized medical data. It also provides support for application delivery in private, public, and hybrid approaches. The proposed platform is an extension of our Interactive Case-Based Flipped Learning Tool (ICBFLT), which has been developed based on current CBL practices. ICBFLT formulates summaries of CBL cases through synergy between students' and medical expert knowledge. The low cost and reduced size of sensor device, support of IoTs, and recent flipped learning advancements can enhance medical students' academic and practical experiences. In order to demonstrate a working scenario for the proposed IoTFLiP platform, real-time data from IoTs gadgets is collected to generate a real-world case for a medical student using ICBFLT.

Item Type: Article
Authors/Creators:Ali, M and Bilal, HSM and Razzaq, MA and Khan, J and Lee, S and Idris, M and Aazam, M and Choi, T and Han, SC and Kang, BH
Keywords: internet of things, cloud environment, flipped learning, case-based learning, medical education
Journal or Publication Title: Digital Communications and Networks
Publisher: Elsevier BV
ISSN: 2352-8648
DOI / ID Number: 10.1016/j.dcan.2017.03.002
Copyright Information:

Copyright 2017 Chongqing University of Posts and Telecommunications. Licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)

Related URLs:
Item Statistics: View statistics for this item

Actions (login required)

Item Control Page Item Control Page