Learning Opportunities and Challenges of Sensor Enabled Intelligent Tutoring Systems on Mobile Computing Devices

Authors

  • Luis Vazquez University of Central Florida, USA
  • Michael Proctor University of Central Florida, USA

DOI:

https://doi.org/10.53555/nncse.v3i2.431

Keywords:

intelligent tutoring systems, mobile learning, sensors, tablets, smartphones

Abstract

Long established on stationary devices like traditional personal computers, sensor-enabled intelligent tutoring system (ITS) technology on mobile computing devices (e.g. tablets, smartphones) hope to deliver a personalized tutoring experience tailored to student affect and educational state anywhere, anytime. To achieve these goals, sensor-enabled ITS must overcome technology changes introduced by the mobility of devices such as tablets and smartphones. After a brief contextual presentation and identification of the sensor-enabled ITS technology & research gaps on mobile computing devices, this article discusses opportunities and challenges of the mobile-computing device and proposes a sensor-enabled ITS prototype for mobile devices.

References

Gartner, “Gartner Says Tablet Sales Continue to Be Slow in 2015,” Gartner, 05-Jan-2015. [Online]. Available: http://www.gartner.com/newsroom/id/2954317

A. T. Corbett, K. R. Koedinger, and J. R. Anderson, “Intelligent tutoring systems,” Handb. Humancomputer Interact., pp. 849–874, 1997

W.-H. Wu, Y.-C. Jim Wu, C.-Y. Chen, H.-Y. Kao, C.-H. Lin, and S.-H. Huang, “Review of trends from mobile learning studies: A meta-analysis,”

Comput. Educ., vol. 59, no. 2, pp. 817–827, Sep. 2012

Sottilare and Proctor, “Passively Classifying Student Mood and Performance within Intelligent Tutors.,” Educ. Technol. Soc., vol. 15, no. 2, pp. 101–114, 2012

R. M. Baecker, “TIMELINES Themes in the early history of HCI—some unanswered questions,” interactions, vol. 15, no. 2, pp. 22–27, 2008

T. L. Dimond, “Devices for reading handwritten characters,” in Papers and discussions presented at the December 9-13, 1957, eastern joint computer conference: Computers with deadlines to meet, 1957, pp. 232–237

H. B. Goldberg, “Controller,” 1117184, 17-Nov-1914

F. Lai, R. Luo, L. Zhang, X. Huang, and S. Rozelle, “Does computer-assisted learning improve learning outcomes? Evidence from a randomized experiment in migrant schools in Beijing,” Econ. Educ. Rev., vol. 47, pp. 34–48, Aug. 2015

Y. C. Liu, Y.-A. Huang, and C. Lin, “Organizational factors’ effects on the success of e-learning systems and organizational benefits: An empirical study in Taiwan,” Int. Rev. Res. Open Distrib. Learn., vol. 13, no. 4, pp. 130–151, 2012

Y.-C. Chen, Y.-C. Lin, R. C. Yeh, and S.-J. Lou, “Examining Factors Affecting College Students’ Intention to Use Web-Based Instruction Systems: Towards an Integrated Model.,” Turk. Online J. Educ. Technol.-TOJET, vol. 12, no. 2, pp. 111–121, 2013

J. S. Bruner, Learning and thinking, vol. 29. Harvard Educational Review, 1959

J. S. Bruner, The act of discovery, vol. 31. Harvard Educational Review, 1961

J. S. Bruner, The act of discovery, vol. 31. Harvard Educational Review, 1961.

B. Dalgarno, G. Kennedy, and S. Bennett, “The impact of students’ exploration strategies on discovery learning using computer-based simulations,” Educ. Media Int., vol. 51, no. 4, pp. 310–329, Oct. 2014

M. D. Proctor and Y. Marks, “A survey of exemplar teachers’ perceptions, use, and access of computer-based games and technology for classroom instruction,” Comput. Educ., vol. 62, pp. 171–180, Mar. 2013

J. Schedeen, “The History of the Tablet PC,” IGN, 01-Apr-2010

A. van Dam, “Post-WIMP user interfaces,” Commun. ACM, vol. 40, no. 2, pp. 63–67, Feb. 1997

Microsoft, “Meet Cortana,” 2014. [Online]. Available: http://www.windowsphone.com/en-us/how-to/wp8/cortana/meet-cortana] “iOS - “iOS-Siri - Apple,” Apple, 2016. [Online]. Available: http://www.apple.com/ios/siri/

M. A. Orey and W. A. Nelson, “Development principles for intelligent tutoring systems: Integrating cognitive theory into the development of computerbased instruction,” Educ. Technol. Res. Dev., vol. 41, no. 1, pp. 59–72, 1993

R. Sottilare, A. Graesser, X. Hu, and H. Holden, Eds., Design Recommendations for Intelligent Tutoring Systems, vol. 1. 2013

R. Nkambou, J. Bourdeau, and R. Mizoguchi, Eds., Advances in intelligent tutoring systems. Berlin: Springer, 2010

B. S. Bloom, “The 2 sigma problem: The search for methods of group instruction as effective as one-to-one tutoring,” Educ. Res., vol. 13, no. 6, pp. 4–16, 1984

K. Porayska-Pomsta, M. Mavrikis, and H. Pain, “Diagnosing and acting on student affect: the tutor’s perspective,” User Model. User-Adapt. Interact., vol. 18, no. 1–2, pp. 125–173, Feb. 2008

B. Woolf, W. Burelson, and I. Arroyo, “Emotional intelligence for computer tutors,” in Workshop on Modeling and Scaffolding Affective Experiences to Impact Learning at 13th International Conference on Artificial Intelligence in Education, 2007, pp. 6–15

B. Woolf, W. Burleson, I. Arroyo, T. Dragon, D. Cooper, and R. Picard, “Affect-aware tutors: recognising and responding to student affect,” Int. J. Learn. Technol., vol. 4, no. 3, pp. 129–164, 2009

K. Forbes-Riley, M. Rotaru, and D. J. Litman, “The relative impact of student affect on performance models in a spoken dialogue tutoring system,” User Model. User-Adapt. Interact., vol. 18, no. 1–2, pp. 11–43, 2008

B. Laurel, Computers as theatre. Reading, Mass: Addison-Wesley Pub. Co, 1993

H. L. O’Brien and E. G. Toms, “What is user engagement? A conceptual framework for defining user engagement with technology,” J. Am. Soc. Inf. Sci. Technol., vol. 59, no. 6, pp. 938–955, Apr. 2008

S. D’Mello, A. Graesser, and R. Picard, “Toward an affect-sensitive AutoTutor,” Intelligent Systems, IEEE, vol. 22, no. Intelligent Systems, IEEE, pp.53–61, 2007

S. D’Mello, A. Olney, C. Williams, and P. Hays, “Gaze tutor: A gaze-reactive intelligent tutoring system,” Int. J. Hum.-Comput. Stud., vol. 70, no. 5, pp. 377–398, May 2012

D. H. Shanabrook, I. Arroyo, and B. P. Woolf, “Using touch as a predictor of effort: what the ipad can tell us about user affective state,” in User Modeling, Adaptation, and Personalization, Springer, 2012, pp. 322–327

L. Anthony, J. Yang, and K. R. Koedinger, “A paradigm for handwriting-based intelligent tutors,” Int. J. Hum.-Comput. Stud., vol. 70, no. 11, pp. 866–887, Nov. 2012

“Evidence That Tutoring Works.” Department of Education, Washington, DC. Planning and Evaluation Service.; Corporation for National Service, Washington, DC, 2001

R. W. Picard, S. Papert, W. Bender, B. Blumberg, C. Breazeal, D. Cavallo, T. Machover, M. Resnick, D. Roy, and C. Strohecker, “Affective learning—a manifesto,” BT Technol. J., vol. 22, no. 4, pp. 253–269, 2004

K. VanLEHN, “The Relative Effectiveness of Human Tutoring, Intelligent Tutoring Systems, and Other Tutoring Systems,” Educ. Psychol., vol. 46, no.4, pp. 197–221, Oct. 2011

Proctor, T. Lucario, and C. Wiley, “Are Officers More Reticent of Games for Serious Training than Enlisted Soldiers?,” J. Def. Model. Simul. Appl. Methodol. Technol., vol. 5, no. 3, pp. 179–196, Jul. 2008

H. K. Saleh, “Computer self-efficacy of university faculty in Lebanon,” Educ. Technol. Res. Dev., vol. 56, no. 2, pp. 229–240, Apr. 2008

E. M. Rogers, Diffusion of innovations, 4th ed. New York: Free Press, 1995

J. P. San Diego, J. C. Aczel, B. K. Hodgson, and E. Scanlon, “Digital approaches to researching learners’ computer interactions using gazes, actions, utterances and sketches,” Educ. Technol. Res. Dev., vol. 60, no. 5, pp. 859–881, Oct. 2012

L. Shen, M. Wang, and R. Shen, “Affective e-Learning: Using‘ Emotional’ Data to Improve Learning in Pervasive Learning Environment.,” Educ. Technol. Soc., vol. 12, no. 2, pp. 176–189, 2009

C. Frasson and P. Chalfoun, “Managing Learner’s Affective States in Intelligent Tutoring Systems,” in Advances in Intelligent Tutoring Systems, Springer, 2010, pp. 339–358

K. Bahreini, R. Nadolski, and W. Westera, “Towards multimodal emotion recognition in e-learning environments,” Interact. Learn. Environ., pp. 1–16, May 2014

H. Ashtankar, P. Nagrale, Y. Timande, and I. Mandwi, “Mouse control using head movement,” J. Int. Assoc. Adv. Technol. Sci., vol. 16, no. 4, p. 6, Mar. 2015

Downloads

Published

2016-02-29

How to Cite

Vazquez, L., & Proctor, M. (2016). Learning Opportunities and Challenges of Sensor Enabled Intelligent Tutoring Systems on Mobile Computing Devices. Journal of Advance Research in Computer Science & Engineering (ISSN 2456-3552), 3(2), 01-08. https://doi.org/10.53555/nncse.v3i2.431