Abstract
Increasing usage of mobile apps encourages the mobile application developers to add more services through specialized mobile applications. One of such service is m-leaning (mobile learning) application. Learning through mobile provides unique experience to the learners to learn course/subject at anywhere and at any time. To increase the learning interest and success of learning is relying on the learners need and the learning environment. This requirement brings new research direction called context-aware personalized learning. This paper proposes the new m-learning system which organizes the course content, accommodating the dynamic nature of learner’s preferences and state. Learners’ preferences are identified through ILS (index of learning styles) test and subsequently updated based on learners activity log using apriori algorithm. The system finally will adopt the content based on the learner’s environment context such as network and surrounding light.
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References
Dey, A.K.: Understanding and Using Context, Personal and Ubiquitous Computing, vol. 5 issue 1, pp. 4–7. Springer, Berlin (2001)
Schilit, B., Adams, N., Want, R.: Context-aware computing applications. In: Mobile Computing Systems and Applications, pp. 85–90. WMCSA (1994)
Dey, A.K., Abowd, G.D., Salber, D.: A conceptual framework and a toolkit for supporting the rapid prototyping of context-aware applications. Hum. Comput. Interact. 16, 97–166 (2001)
Wang, Y.: Context awareness and adaptation in mobile learning. In: Workshop on Wireless and Mobile Technologies in Education (2004)
Zervas, P., Gómez, S., Fabregat, R., Sampson, D.: Tools for context-aware learning design and mobile delivery. In: Proceedings 11th IEEE International Conference on Advanced Learning Technologies (ICALT), pp. 534–535 (2011)
Benlamri, R., Zhang, X.: Context-aware recommender for mobile learners. Hum. Centric Comput. Inf. Sci. (2014)
Triantafillou, E., Pomportsis, A., Demetriadis, S., Georgiadou, E.: The value of adaptivity based on cognitive style: an empirical study. Br. J. Edu. Technol. 35(1), 95–106 (2004)
El Guabassi, I., Al Achhab, M., Jellouli, I., El Mohajir, B.E.: Personalized ubiquitous learning via an adaptive engine. J. Emerg. Technol. Learn. 13 (2018) (Elsevier B.V.)
Curum, B., Chellapermal, N., Khedo, K.K.: A Context-aware mobile learning system using dynamic content adaptation for personalized learning. Emerging Trends in Electrical, Electronic and Communications Engineering, Lecture Notes in Electrical Engineering, vol. 416, Springer, Berlin (2017)
Tortorella, R.A.W., Graf, S.: Considering learning styles and context-awareness for mobile adaptive learning. Educ. Inf. Technol. 22(1), 297–315 (2017) (Springer)
Tortorella, R.A.W., Graf, S.: Personalized mobile learning via an adaptive engine. In: IEEE Conference on Advanced Learning Technologies (2012)
Kazanidis, I., Satratzemi, M.: Adaptivity in ProPer: an adaptive SCORM compliant LMS. J. Distance Educ. Technol. 7(2), 44–62 (2009)
Premlatha, K.R., Dharani, B., Geetha, T.V.: Dynamic learner profiling and automatic learner classification for adaptive e-learning environment. Interact. Learn. Environ. 24(6) (2016)
Schmidt, A., Winterhalter, C.: User context aware delivery of elearning material: approach and architecture. J. Univ. Comput. Sci. 10(1), 38–46 (2004)
Kolekar, S.V., Pai, R.M., Manohara Pai, M.M.: Modified literature based approach to identify learning styles in adaptive E-learning. Adv. Comput. Netw. Informat. 1, 555–564 (2014) (Springer)
Felder, R.M., Silverman, L.K.: Learning and teaching styles in engineering education. Eng. Educ. 78, 674–681 (1988)
Briggs Myers, I.: Manual: The Myers-Briggs Type Indicator. Consulting Psychologists Press, Palo Alto, CA (1962)
Kolb, D.A.: Experiential Learning: Experience as the Source of Learning and Development. Prentice-Hall, Englewood Cliffs, NJ (1984)
Pask, G.: Styles and strategies of learning. Br. J. Educ. Psychol. 46, 128–148 (1976)
Honey, P., Mumford, A.: The manual of learning styles. Peter Honey, Maidenhead (1982)
Carver, C.A., Howardl, R.A., Lane, W.D.: Addressing different learning styles through course hypermedia. IEEE Trans. Educ. 42, 33–38 (1999)
Saleem Raja, A., George, E.: Compact bitTable based adaptive association rule mining using mobile agent framework. J. Comput. Sci. Softw. Eng. 4(9), 224–229 (2015)
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Madhubala, R., Akila (2020). Context-Aware Personalized Mobile Learning. In: Bhateja, V., Satapathy, S., Zhang, YD., Aradhya, V. (eds) Intelligent Computing and Communication. ICICC 2019. Advances in Intelligent Systems and Computing, vol 1034. Springer, Singapore. https://doi.org/10.1007/978-981-15-1084-7_45
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DOI: https://doi.org/10.1007/978-981-15-1084-7_45
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