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Using Interactive Exercise in Mobile Devices to Support Evidence-based Teaching and Learning

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Published:11 July 2016Publication History

ABSTRACT

To improve student's class experience, the use of mobile devices has been steadily increasing. However, such use of mobile learning environments in the class is mostly static in nature through content delivery or multiple choice and true/false quiz taking. In CS courses, we need learning environments where students can interact with the problem in a hands-on-approach and instructor can assess their learning skills in real-time with problems having different degree of difficulty. To facilitate such interactive problem solving and real-time assessment using mobile devices, a comprehensive backend system is necessary. This paper presents one such system, named Mobile Response System (MRS) software, associated interactive problem-solving activities, and lessons learned by using it in the CS classrooms. MRS provides instructor with the opportunity of evidence-based teaching by allowing students to perform interactive exercises in their mobile devices with different learning outcomes and by getting an instant feedback on their performance and mental models. MRS is easy-to-use, extensible and can render interactive exercises developed by third-party developers. The student performance data shows its effectiveness in increasing student understanding of difficult concepts and the overall perception of using the software was very positive.

References

  1. D. Perry, How The Brain Learns Best, Instructor Magazine, 11: 34--37, 2000.Google ScholarGoogle Scholar
  2. T. L. Naps, G. Rößling, V. Almstrum, W. Dann, R. Fleischer, C. Hundhausen, A. Korhonen, L. Malmi, M. McNally, S. Rodger, and J. A. Velázquez-Iturbide. Exploring the role of visualization and engagement in computer science education. In Working group reports from ITiCSE'02 on Innovation and technology in computer science education, 131--152, 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. M. Cometa, Use of Technology-Rich Learning Environment Reveals Improved Retention Rates, Rochester University of Technology, Nov 16, 2011 http://www.rit.edu/news/ story.php?id=48699.Google ScholarGoogle Scholar
  4. C. A. Romney, Tablet PC use in freshman mathematics classes promotes STEM retention, Frontiers in Education Conference (FIE), F1J-1 - F1J-7, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Z. Avery, M. Castillo, H. Guo, J. Guo, N. Warter-Perez, D. S. Won, J. Dong, Implementing Collaborative Project-Based Learning using the Tablet PC to enhance student learning in engineering and computer science courses, Frontiers in Education Conference, F1E-1-F1E-7, 2010.Google ScholarGoogle Scholar
  6. R. J. Young, Mobile College App: Turning iPhones Into "Super-Clickers" for Classroom Feedback, Chronicle of higher education, 2008.Google ScholarGoogle Scholar
  7. D. Berque, An evaluation of a broad deployment of DyKnow software to support note taking and interaction using pen-based computers. Journal of Computing Sciences in Colleges, 21(6): 204--216, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. J. Hattie, Visible learning: A synthesis of over 800 meta-analyses relating to achievement. Routledge, 2000.Google ScholarGoogle Scholar
  9. G. Wiggins, Seven keys to effective feedback. Educational Leadership, 70: 10--16, 2012.Google ScholarGoogle Scholar
  10. M. M. Fuad, D. Deb, J. Etim, and C. Gloster, Mobile Response System: A Novel Approach to Deliver Interactive and Hands-on Activity in the Classroom, Journal of Educational Technology Research and Development, Springer, Under revision, 2016.Google ScholarGoogle Scholar
  11. D. Deb, M. M. Fuad and W. Farag, Developing Interactive Classroom Exercises for use with Mobile Devices to Enhance Class Engagement and Problem-solving Skills, IEEE Frontier's of Education Conference, IEEE Press, 343--346, Madrid, Spain, October 22-25, 2014.Google ScholarGoogle Scholar
  12. M. M. Fuad, D. Deb. and J. Etim, An Evidence Based Learning and Teaching Strategy for Computer Science Classrooms and its Extension into a Mobile Classroom Response System, Proceedings of the 14th IEEE International Conference on Advanced Learning Technologies (ICALT), IEEE Press, 149--153, Athens, Greece, July 7-9, 2014. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. T. Postmes, R. Spears, K. Sakhel, and D.De Groot, Social influence in computer-mediated communication: The effects of anonymity on group behavior, Personality and Social Psychology Bulletin, 27: 1243--1254, 2001.Google ScholarGoogle ScholarCross RefCross Ref
  14. M.-T. Félix, C.-O. Jesús, G.-J. Luis, Anonymity effects in computer-mediated communication in the case of minority influence, Computers in Human Behavior, 23:1660--1674, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. J. E. Caldwell, Clickers in the Large Classroom: Current Research and Best-Practice Tips, CBE? Life Sciences Education, 6(1): 9--20, 2007.Google ScholarGoogle ScholarCross RefCross Ref
  16. J. K. Knight and W. B. Wood, Teaching more by lecturing less, Cell biology education, 4(4): 298--310, 2005.Google ScholarGoogle Scholar
  17. E. E. Fredericksen and M. Ames, Can a $30 Piece of Plastic Improve Learning? An Evaluation of Personal Responses Systems in Large Classroom Settings, EDUCAUSE, 2009.Google ScholarGoogle Scholar
  18. L. Malmi, V. Karavirta, A. Korhonen, J. Nikander, O. Seppa'la', and P. Silvasti. Visual algorithm simulation exercise system with automatic assessment: TRAKLA2. Informatics in Education, 3(2):267--288, 2004.Google ScholarGoogle ScholarCross RefCross Ref
  19. T. L. Naps, Jhavé: Supporting algorithm visualization, Computer Graphics and Applications, IEEE, 25(5):49--55, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. V. Karavirta and C. A. Shaffer, Creating Engaging Online Learning Material with the JSAV JavaScript Algorithm Visualization Library, in Learning Technologies, IEEE Transactions on, PP(99): 1--1, 2015.Google ScholarGoogle Scholar
  21. Mobile Response System, http://compsci.wssu.edu/MRS, 2016.Google ScholarGoogle Scholar

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        cover image ACM Conferences
        ITiCSE '16: Proceedings of the 2016 ACM Conference on Innovation and Technology in Computer Science Education
        July 2016
        394 pages
        ISBN:9781450342315
        DOI:10.1145/2899415

        Copyright © 2016 ACM

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        Publication History

        • Published: 11 July 2016

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        ITiCSE '16 Paper Acceptance Rate56of147submissions,38%Overall Acceptance Rate552of1,613submissions,34%

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