A Concept Map Approach to Supporting Diagnostic and Remedial Learning Activities
Due to rapid advancement in the field of computer communication there has been a lot of research in development of Intelligent Tutoring System (ITS). However ITS fails to pinpoint the exact concept the student is deficient in. We propose the development of an Intelligent Diagnostic and Remedial learning system which aims to diagnose the exact concept the student is deficient in. The proposed system composed of three modules is derived from David Ausubel’s theory of meaningful learning which consists of three learning elements. The system is implemented in mobile environment using Android Emulator. Finally an experiment was conducted with a set of 60 students majoring in computer science. Experimental results clearly show that the system improves the performance of the learners for whom they are intended.
KeywordsTheory of Meaningful Learning Remedial Learning M-Learning Concept Mapping Android Emulator t-test
Unable to display preview. Download preview PDF.
- 1.Novak, J.D., Alberto, C.J.: Theoretical Origins of Concept Map, How to construct them and their used in Education. Reflecting Education 3(1), 29–42 (2007)Google Scholar
- 2.Pendidican, F.: Learning Theories. Mathematika dan IInam Alam, Universitas Pendidikan IndonesiaGoogle Scholar
- 3.Hwang, G.: A conceptual map model for developing Intelligent Tutoring Systems. Computers and Education, 217–235 (2003)Google Scholar
- 4.Hwang, G.: A computer assisted approach to diagnosing student learning problems in science courses. Journal of Information Science and Engineering, 229–248 (2007)Google Scholar
- 5.Pocatilu, P.: Developing mobile learning applications for Android using web services. Informatica Economica 14(3) (2010)Google Scholar
- 7.Virvou, M., Alepis, E.: Mobile Education features in authoring tools for personalized tutoring. Computers and Education, 53–68 (2005)Google Scholar
- 8.Kazi, S.: Voca Test: An intelligent Tutoring System for vocabulary learning using M-Learning Approach (2006)Google Scholar
- 9.Thompson, T.: The learning theories of David P Ausubel. The importance of meaningful and reception learningGoogle Scholar
- 10.Johnson, W.B., Neste, L.O., Duncan, P.C.: An authoring environment for intelligent tutoring systems. In: IEEE International Conference on Systems, Man and Cybernetics, pp. 761–765 (1989)Google Scholar
- 11.Vasandani, V., Govindaraj, T., Mitchell, C.M.: An intelligent tutor for diagnostic problem solving in complex dynamic systems. In: IEEE International Conference on Systems, Man and Cybernetics, pp. 772–777 (1989)Google Scholar
- 12.Psotka, J., Mutter, S.A.: Intelligent Tutoring Systems: Lessons Learned. Lawrence Erlbaum Associates (1998)Google Scholar
- 13.Sai, C.: Data Mining Techniques for Identifying students at risk of failing a computer proficiency test required for graduation. Australasian Journal of Educational Technology 27(3), 481–498 (2012)Google Scholar