Hardika Dwi Hermawan, Ratna Wardani, Julian Chu, Arum Darmawati, Muhammetmyrat Yarmatov
Adaptive mobile learning is necessary platform in supporting students to understand the lesson because the system can adapt to the different learning skills and characteristics of learners. This paper focuses on the application of adaptive learning in nearby wisdom app that are being developed; nearby wisdom is a mobile learning platform that provides a variety of learning features that support self-directed learning, collaborative learning, gamification and adaptive learning. Implementation of adaptive learning in the app divided into three types, 1) adaptive content, 2) adaptive assessment, and 3) adaptive sequence. The paper tries to illustrate and compare these types of adaptive learning, the workflow and differences in input and output generated. In the end, the paper provides some recommendations on the common factors in building adaptive mobile learning that is 1) user, 2) content, 3) skill or difficulty level and 4) performance. However, developing adaptive mobile learning that implement all types of adaptive learning requires systematic thinking skills and sophisticated algorithms, especially for adaptive sequences. © 2018 IEEE.
Information and Technology Studies, Faculty of Education, University of Hong Kong, Hong Kong, Hong Kong; Electronics and Informatics Engineering Education, Postgraduate School, Yogyakarta State University, Indonesia; St. Paul Co-educational College, Hong Kong; Department of Management, Faculty of Economics, Yogyakarta State University, Indonesia; Ulsan National Institute of Science and Technology, South Korea
