Automated Adaptive Mobile Learning System using Shortest Path Algorithm and Learning Style

Authors

  • Ibrahim Alkore Alshalabi Al- Hussein Bin Talal University
  • Samir E Hamada Farmingdale State College
  • Khaled Elleithy University of Bridgeport
  • Ioana Badara University of Bridgeport
  • Saeid Moslehpour University of Hartford

DOI:

https://doi.org/10.3991/ijim.v12i5.8186

Keywords:

Adaptive Learning, m-learning, Learning style, Shortest Path

Abstract


A directed graph represents an accurate picture of course descriptions for online courses through computer-based implementation of various educational systems. E-learning and m-learning systems are modeled as a weighted, directed graph where each node represents a course unit. The Learning Path Graph (LPG) represents and describes the structure of domain knowledge, including the learning goals, and all other available learning paths. In this paper, we propose a system prototype that implements a propose adaptive learning path algorithms that uses the student’s information from their profile and their learning style in order to improve the students’ learning performances through an m-learning system that provides a suitable course content sequence in a personalized manner.

Author Biographies

Ibrahim Alkore Alshalabi, Al- Hussein Bin Talal University

Dr. Ibrahim Alkore Alshalabi received his B.Sc. in Computer Science from Al- Isra Private University, Amman, Jordan in 1997, his Master of Computer Applications (MCA) from Bangalore University, India in 2007, and his PhD in Computer Science and Engineering from the University of Bridgeport, USA in 2016. From 1997-2004 he was Assistant Lecturer at Ma'an Community College, Al-Balqa Applied University, Jordan. From 2007 to 2009 he was an assistant lecturer at Al- Hussein Bin Talal University, Jordan. He is currently an adjunct Professor at Al- Hussein Bin Talal University, College of Information technology, Jordan. His research interests are E-Learning, M-Learning, wireless communications, and networks. He was an active committee member of the International Conference on Engineering Education, instructional technology, Assessment, and E-Learning (EIAE 2010, EIAE 2011). (e-mail: ialkorea@my.bridgeport.edu)

Samir E Hamada, Farmingdale State College

Dr. Samir Hamada received his PhD in Computer Science and Engineering and MS in Computer Science from University of Bridgeport in 2017 and 2001. He, also, received his B.S. in Accounting from Ain Shams University in Egypt. He is currently an Assistant Professor of Computer Systems, School of Business at Farmingdale State College in Farmingdale NY, USA. His research interests include Adaptive Learning, Mobile Learning and the Semantic Web. (e-mail: hamadas@farmingdale.edu)

Khaled Elleithy, University of Bridgeport

Dr. Elleithy is the Associate Vice President for Graduate Studies and Research at the University of Bridgeport. He is a professor of Computer Science and Engineering. He has research interests in the areas of wireless sensor networks, mobile communications, network security, quantum computing, and formal approaches for design and verification. He has published more than three hundreds research papers in international journals and conferences in his areas of expertise.
Dr. Elleithy is the editor or co-editor for 12 books by Springer. He is a member of technical program committees of many international conferences as recognition of his research qualifications. He served as a guest editor for several International Journals. He was the chairperson for the International Conference on Industrial Electronics, Technology & Automation, IETA 2001, 19-21 December 2001, Cairo – Egypt. Also, he is the General Chair of the 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, and 2014 International Joint Conferences on Computer, Information, and Systems Sciences, and Engineering virtual conferences.

Ioana Badara, University of Bridgeport

Dr. Badara holds a Ph.D. (Teacher Preparation/Science Education) from University of Tennessee–Knoxville and an M.Phil. (Microbiology & Immunology) from University of Edinburgh, Scotland. Prior to completing her doctoral work, she has worked as a research scientist in the biomedical field for about ten years, having been affiliated with Weill Medical College of Cornell University and Mount Sinai School of Medicine, in New York City. Her passionate interest in the exploration of connections between scientists’ epistemologies and the teaching of science led her to pursuing doctoral studies in Science Education. She has taught a multitude of core Biology courses for Biology/Pre-Medical undergraduates and mentored student research projects in this field. Dr. Badara is currently a faculty member at University of Bridgeport, where she teaches core research courses in the doctoral (Ed.D.) program, Science Education courses in the Science Teacher Preparation program, and History and Philosophy of Science courses at the undergraduate level. She has been the recipient of several grants for research, including a National Science Foundation grant for conducting research on the teaching of science in urban school districts. She has presented her work at national and international conferences in the field of STEM education.

Saeid Moslehpour, University of Hartford

Dr. Saeid Moslehpour is an Associate Professor and Department Chair in the Electrical and Computer Engineering Department in the College of Engineering, Technology, and Architecture at the University of Hartford. He holds a Ph.D. (1993) from Iowa State University and bachelors of science (1989) and masters of Science (1990) degrees from University of Central Missouri. His research interests include logic design, CPLDs, FPGAs, embedded systems, electronic system testing, and eLearning. Email: moslehpou@hartford.edu.

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Published

2018-09-29

How to Cite

Alkore Alshalabi, I., Hamada, S. E., Elleithy, K., Badara, I., & Moslehpour, S. (2018). Automated Adaptive Mobile Learning System using Shortest Path Algorithm and Learning Style. International Journal of Interactive Mobile Technologies (iJIM), 12(5), pp. 4–27. https://doi.org/10.3991/ijim.v12i5.8186

Issue

Vol. 12 No. 5 (2018)

Section

Papers