Improving Dynamically Personalized E-Learning by Applying a Help-seeking Model

  • Yousef Radi Fares
  • Maizatul Akmar Ismail
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 285)


This paper describes Yourbook, a personalized blended web-based e-learning application being developed in the University of Malaya to assist students completing introductory programming course for undergraduate studies in computer science faculty. The name is inspired by the famous social website Facebook since students are very familiar with the user experience (UX) of this famous website. In our web-based solution we are using Representational State Transfer (REST) software architecture. We are building our services on the back-end using Hypertext Preprocessor (PHP), and front-end using open-source JavaScript library Yahoo! User Interface Library (YUI). We are introducing a new model to enhance the current adaptive e-learning systems by taking in consideration some learning theories which have been introduced many times in educational psychology. Yourbook is mainly considering help-seeking strategy which is identified as a very important strategy in self-regulated learning (SRL). Through the paper we are arguing why we have chosen this specific educational theorem to serve in adaptive systems, and how the system will be designed to achieve our goals in enhancing the educational process.


Adaptive learning Overlay student model Help-seeking Concept network Self-regulated 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Jeremić, Z., J. Jovanović, and D. Gašević. “Student modeling and assessment in intelligent tutoring of software patterns.” Expert Systems with Applications 39.1 (2012): 210-222.Google Scholar
  2. 2.
    Graf, S., and T-C. Liu. “Analysis of learners’ navigational behaviour and their learning styles in an online course.” Journal of Computer Assisted Learning 26.2 (2010): 116-131.Google Scholar
  3. 3.
    Chrysafiadi, Konstantina, and Maria Virvou. “Dynamically Personalized E-Training in Computer Programming and the Language C.” 1-1.Google Scholar
  4. 4.
    Lo, Jia-Jiunn, Ya-Chen Chan, and Shiou-Wen Yeh. “Designing an adaptive web-based learning system based on students’ cognitive styles identified online.”Computers & Education 58.1 (2012): 209-222.Google Scholar
  5. 5.
    Hsiao, I-H., Sergey Sosnovsky, and Peter Brusilovsky. “Guiding students to the right questions: adaptive navigation support in an E-Learning system for Java programming.” Journal of Computer Assisted Learning 26.4 (2010): 270-283Google Scholar
  6. 6.
    Brusilovsky, Peter. “Adaptive hypermedia.” User modeling and user-adapted interaction 11.1-2 (2001): 87-110..Google Scholar
  7. 7.
    De Bra, Paul, Jill Freyne, and Shlomo Berkovsky. “Introduction to the Special Issue on Adaptive Hypermedia.” New Review of Hypermedia and Multimedia 19.2 (2013): 81-83.Google Scholar
  8. 8.
    Gourash, Nancy. “Help-seeking: A review of the literature.” American journal of community psychology 6.5 (1978): 413-423.Google Scholar
  9. 9.
    Gall, Sharon Nelson-Le. “Help-seeking behavior in learning.” Review of research in education 12 (1985): 55-90.Google Scholar
  10. 10.
    Gall, Sharon Nelson-Le. “Help-seeking: An understudied problem-solving skill in children.” Developmental Review 1.3 (1981): 224-246.Google Scholar
  11. 11.
    Schunk, Dale H., and Barry J. Zimmerman. “Social origins of self-regulatory competence.” Educational psychologist 32.4 (1997): 195-208.Google Scholar
  12. 12.
    Ames, Carole. “Classrooms: Goals, structures, and student motivation.”Journal of educational psychology 84.3 (1992): 261-271.Google Scholar
  13. 13.
    Covington, Martin V. Making the grade: A self-worth perspective on motivation and school reform. Cambridge University Press, 1992.Google Scholar
  14. 14.
    Dweck, Carol S. “Motivational processes affecting learning.” American psychologist 41.10 (1986): 1040-1048.Google Scholar
  15. 15.
    Wolters, Christopher A., Shirley L. Yu, and Paul R. Pintrich. “The relation between goal orientation and students’ motivational beliefs and self-regulated learning.” Learning and individual differences 8.3 (1996): 211-238.Google Scholar
  16. 16.
    Butler, Ruth, and Orna Neuman. “Effects of task and ego achievement goals on help-seeking behaviors and attitudes.” Journal of Educational Psychology 87.2 (1995): 261-71.Google Scholar
  17. 17.
    Ryan, Allison M., and Paul R. Pintrich. ““ Should I ask for help?” The role of motivation and attitudes in adolescents’ help seeking in math class.” Journal of educational psychology 89.2 (1997): 329.Google Scholar
  18. 18.
    Middleton, Michael J., and Carol Midgley. “Avoiding the demonstration of lack of ability: An underexplored aspect of goal theory.” Journal of educational psychology 89.4 (1997): 710.Google Scholar
  19. 19.
    Mercier, Julien, and Carl H. Frederiksen. “Individual differences in graduate students’ help-seeking process in using a computer coach in problem-based learning.” Learning and Instruction 17.2 (2007): 184-203.Google Scholar
  20. 20.
    Zimmerman, Barry J. “A social cognitive view of self-regulated academic learning.” Journal of educational psychology 81.3 (1989): 329-339.Google Scholar
  21. 21.
    Newman, Richard S. “Adaptive help seeking: A strategy of self-regulated learning.” (1994).Google Scholar
  22. 22.
    Zimmerman, Barry J., and Manuel Martinez-Pons. “Construct validation of a strategy model of student self-regulated learning.” Journal of educational psychology 80.3 (1988): 284-290.Google Scholar
  23. 23.
    Shim, Sungok Serena, Sarah M. Kiefer, and Cen Wang. “Help Seeking Among Peers: The Role of Goal Structure and Peer Climate.” The Journal of Educational Research ahead-of-print (2013).Google Scholar
  24. 24.
    Tsiriga, Victoria, and Maria Virvou. “Evaluation of an Intelligent Web-Based Language Tutor.” Knowledge-Based Intelligent Information and Engineering Systems. Springer Berlin Heidelberg, 2003.Google Scholar
  25. 25.
    Sison, Raymund, and Masamichi Shimura. “Student modeling and machine learning.” International Journal of Artificial Intelligence in Education (IJAIED) 9 (1998): 128-158.Google Scholar
  26. 26.
    Lo, Jia-Jiunn, and Ya-Chen Chan. “Design of adaptive web interfaces with respect to student cognitive styles.” Education and Educational Technology. Springer Berlin Heidelberg, 2012. 331-338.Google Scholar
  27. 27.
    Lazarinis, Fotis, Steve Green, and Elaine Pearson. “Creating personalized assessments based on learner knowledge and objectives in a hypermedia Web testing application.” Computers & Education 55.4 (2010): 1732-1743.Google Scholar
  28. 28.
    Lee, Young-Jin. “Developing an efficient computational method that estimates the ability of students in a Web-based learning environment.” Computers & Education 58.1 (2012): 579-589.Google Scholar
  29. 29.
    Muñoz-Merino, Pedro J., et al. “An adaptive and innovative question-driven competition-based intelligent tutoring system for learning.” Expert Systems with Applications 39.8 (2012): 6932-6948.Google Scholar
  30. 30.
    Pornsawan, Insorn, and Sanrach Charan. “Designing of Adaptive Coaching System to Enhance the Logical Thinking Model in Problem-based Learning.”Procedia-Social and Behavioral Sciences 46 (2012): 5265-5269.Google Scholar

Copyright information

© Springer Science+Business Media Singapore 2014

Authors and Affiliations

  1. 1.Department of Information Systems, Faculty of Computer Science & Information TechnologyUniversity of MalayaKuala LumpurMalaysia

Personalised recommendations