PERCEPOLIS: Pervasive Cyberinfrastructure for Personalized Learning and Instructional Support
ABSTRACT
This paper describes PERCEPOLIS, an educational platform that leverages technological advances, in particular in pervasive computing, to facilitate personalized learning in higher education, while supporting a networked curricular model. Fundamental to PERCEPOLIS is the modular approach to course development. Blended instruction, where students are responsible for perusing certain learning objects outside of class, used in conjunction with the cyberinfrastructure will allow the focus of face-to-face meetings to shift from lecture to active learning, interactive problem-solving, and reflective instructional tasks. The novelty of PERCEPOLIS lies in its ability to leverage pervasive and ubiquitous computing and communication through the use of intelligent software agents that use a student’s academic profile and interests, as well as supplemental information such as his or her learning , to customize course content. Assessments that gauge the student’s mastery of concepts are used to allow self-paced progression through the course. Furthermore, the cyberinfrastructure facilitates the collection of data on student performance and learning at a resolution that far exceeds what is currently available. We believe that such an infrastructure will accelerate the acquisition of knowledge and skills critical to professional engineering practice, while facilitating the study of how this acquisition comes about, yielding insights that may lead to significant changes in pedagogy.
This paper describes PERCEPOLIS, an educational platform that leverages technological advances, in particular in pervasive computing, to facilitate personalized learning in higher education, while supporting a networked curricular model. Fundamental to PERCEPOLIS is the modular approach to course development. Blended instruction, where students are responsible for perusing certain learning objects outside of class, used in conjunction with the cyberinfrastructure will allow the focus of face-to-face meetings to shift from lecture to active learning, interactive problem-solving, and reflective instructional tasks. The novelty of PERCEPOLIS lies in its ability to leverage pervasive and ubiquitous computing and communication through the use of intelligent software agents that use a student’s academic profile and interests, as well as supplemental information such as his or her learning , to customize course content. Assessments that gauge the student’s mastery of concepts are used to allow self-paced progression through the course. Furthermore, the cyberinfrastructure facilitates the collection of data on student performance and learning at a resolution that far exceeds what is currently available. We believe that such an infrastructure will accelerate the acquisition of knowledge and skills critical to professional engineering practice, while facilitating the study of how this acquisition comes about, yielding insights that may lead to significant changes in pedagogy.
Cite this paper
nullA. Hurson and S. Sedigh, "PERCEPOLIS: Pervasive Cyberinfrastructure for Personalized Learning and Instructional Support," Intelligent Information Management, Vol. 2 No. 10, 2010, pp. 586-596. doi: 10.4236/iim.2010.210067.
nullA. Hurson and S. Sedigh, "PERCEPOLIS: Pervasive Cyberinfrastructure for Personalized Learning and Instructional Support," Intelligent Information Management, Vol. 2 No. 10, 2010, pp. 586-596. doi: 10.4236/iim.2010.210067.
References
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Satratzemi, “Efficient Authoring of SCORM Courseware Adapted to User Learning Style: The Case of ProPer SAT,” Proceedings of the International Conference on Advances in Web-Based Learning (ICWL ’09), Germany, 2009, pp. 196-205. http://www.springerlink.com/content/7x421jm53n885t53. [25] Advanced Distributed Learning Initiative, “Sharable Content Object Reference Model (SCORM),” http://www.adlnet.org, accessed Apr. 2010. [26] Learning Systems Architecture Laboratory, “SCORM Best Practices Guide For Content Developers,” Technical Report, Carnegie Mellon University, 2005. http://www. jointadlcolab.org/downloads/scormcdg 1edsec7update 20050420.pdf. [27] A. Collins, J. S. Brown and S. E. Newman, “Cognitive apprenticeship: Teaching the Crafts of Reading, Writing, and Mathematics,” Knowing, learning, and instruction: Essays in honor of Robert Glaser, 1989, pp. 453-494. [28] J. S. Brown, A. Collins and P. Duguid, “Situated Cognition and the Culture of Learning,” Educational Researcher, Vol. 18, No. 1, 1989, p. 32. [29] G. Hislop, “The Inevitability of Teaching Online,” Computer, Vol. 42, No. 12, 2009, pp. 94-96. [30] R. Felder and L. Silverman, “Learning and Teaching Styles in Engineering Education,” Engineering education, Vol. 78, No. 7, 1988, pp. 674-681. [31] S. Reisman and W. A. Carr, “Perspectives on Multimedia Systems in Education,” IBM Journal of Research and Development, Vol. 30, No. 3, 1991, pp. 280-295. [32] T. Yager, “Information’s Human Dimension,” Byte Magazine, Vol. 16, No. 13, 1991, pp. 153-160. [33] E. Popescu, “Evaluating the Impact of Adaptation to Learning Styles in a Web-Based Educational System,” in Proceedings of the 8th International Conference on Advances in Web Based Learning (ICWL ’09), Germany, 2009, pp. 343-352. [34] “The Metropolitan Museum of Art,” 2010. http://www. metmuseum.org/works of art, accessed Apr. [35] Y. J. Dori and J. Belcher, “How Does Technology-Enabled Active Learning Affect Undergraduate Students’ Understanding of Electromagnetic Concepts?” Journal of the Learning Sciences, Vol. 14, No. 2, 2005, pp. 243-279.
[1] B. York, A. van Dam, J. Ullman, E. Soloway, J. Pollack, A. Kay and T. Kalil, “A Teacher for Every Learner: Scalable Learner-Centered Systems,” 2010. http://www. nesc.ac.uk/esi/events/Grand_Challenges/usa/education.pdf. [2] S. D. Sheppard, K. Macatangay, A. Colby and W. M. Sullivan, “Educating Engineers: Designing for the Future of the Field,” Carnegie Foundation for the Advancement of Teaching, Jossey-Bass, USA, 2009. [3] National Academy of Engineering, “Grand Challenges for Engineering,” http://www.engineeringchallenges.org, accessed Jan. 2010. [4] M. Satyanarayanan, “Pervasive Computing: Vision and Challenges,” IEEE Personal Communications, Vol. 8, No. 4, 2001, pp. 10-17. [5] G. Banavar and A. Bernstein, “Software Infrastructure and Design Challenges for Ubiquitous Computing Applications,” Communications of the ACM, Vol. 45, No. 12, 2002, pp. 92-96. [6] D. Lange and M. Oshima, “Programming and Developing Java Mobile Agents with Aglets,” Addison-Wesley, New York, 1998. [7] R. Gray, D. Kotz, G. Cybenko and D. Rus, “Mobile Agents: Motivations and State-of-the-Art Systems,” In: J. Bradshaw, Ed., Handbook of Agent Technology, AAAI/ MIT Press, Cambridge, 2002, pp. 1-30. [8] A. R. Hurson, E. Jean, M. Ongtang, X. Gao, Y. Jiao and T. E. Potok, “Recent Advances in Mobile Agent-Oriented Applications,” In: L. Yang and A. B. Waluyo, Eds., Mobile Intelligence: When Computational Intelligence Meets Mobile Paradigm, John Wiley & Sons, New York, 2009, pp. 106-139. [9] Y. Jiao and A. Hurson, “Performance Analysis of Mobile Agents in Heterogeneous Mobile Database Systems,” Proceedings of the IEEE International Conference on Emerging Technologies (ICET’03), Minneapolis, USA, 2003. [10] Y. Jiao and A. R. Hurson, “Mobile Agents in Mobile Data Access Systems,” Proceedings of the 10th International Conference on Cooperative Information Systems (COOPIS), Irvine, 2002, pp. 144-162. [11] E. Jean, Y. Jiao and A. R. Hurson, “Addressing Mobile Agent Security through Agent Collaboration,” Journal of Information Processing Systems, Vol. 3, No. 2, 2008, pp. 43-53. [12] M. Ongtang, A. R. Hurson and Y. Jiao, “Agent-Based Infrastructure for Data and Transaction Management in Mobile Heterogeneous Environment,” Proceedings of the WRI International Conference on Communications and Mobile Computing (CMC’09), Yunnan, 2009, pp. 314- 318. [13] E. Jean, R. T. Collins, A. R. Hurson, S. Sedigh and Y. Jiao, “Pushing Sensor Network Computation to the Edge,” Proceedings of the 5th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM ’09), Beijing, China, 2009, pp. 1-4. [14] S. Sedigh, A. R. Hurson and B. Shirazi, “Tools and Techniques for Interoperability and Dynamic Reconfiguration of Pervasive Systems,” In: M. Denko and M. S. Obaidat, Eds.Pervasive Computing and Networking, John Wiley & Sons, New York, 2010. [15] M. W. Bright, A. R. Hurson and S. H. Pakzad, “A Taxonomy and Current Issues in Multidatabase Systems,” Computer, Vol. 25, No. 3, 1992, pp. 50-60. [16] M. W. Bright, A. R. Hurson and S. H. Pakzad, “Automated Resolution of Semantic Heterogeneity in Multidatabases,” ACM Transactions on Database Systems, Vol. 19, No. 2, 1994, pp. 212-253. [17] M. W. Bright, A. R. Hurson, S. Pakzad and H. Sarma, “The Summary Schemas Model-An Approach for Handling Multidatabases: Concept and Performance Analysis,” Multidatabase Systems: An Advanced Solution for Global Information Sharing, 1999, pp. 199-216. [18] B. Yang and A. R. Hurson, “Semantic-Aware and QoS-Aware Image Caching in Ad Hoc Networks,” IEEE Transactions on Knowledge and Data Engineering, Vol. 19, No. 12, pp. 1694-1707, 2007. [19] J. B. Lim, A. R. Hurson and Y. Jiao, “Transaction Processing in Mobile, Heterogeneous Database Systems,” Encyclopedia of Computer Science and Engineering, Vol. 5, 2008, pp. 2922-2930. [20] K. Dash, A. Hurson, S. Phoha and C. Chehadeh, “Summary Schemas Model: A Scheme for Handling Global Information Sharing,” Proceedings of the International Conference on Intelligent Information Management Systems, 1994, pp. 47-51. [21] L. Smith and A. Hurson, “A Search Engine Selection Methodology,” Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC’03), Washington, DC, 2003, pp. 122-129. [22] A. R. Hurson and M. W. Bright, “Multidatabase Systems: An Advanced Concept in Handling Distributed Data,” Advances in Computers, Las Vegas, Vol. 32, 1991, pp. 149-200. [23] J. B. Lim and A. R. Hurson, “Transaction Processing in Mobile, Heterogeneous Database Systems,” IEEE Transactions on Knowledge and Data Engineering, Vol. 14, No. 6, 2002, pp. 1330-1346. [24] I. Kazanidis and M. Satratzemi, “Efficient Authoring of SCORM Courseware Adapted to User Learning Style: The Case of ProPer SAT,” Proceedings of the International Conference on Advances in Web-Based Learning (ICWL ’09), Germany, 2009, pp. 196-205. http://www.springerlink.com/content/7x421jm53n885t53. [25] Advanced Distributed Learning Initiative, “Sharable Content Object Reference Model (SCORM),” http://www.adlnet.org, accessed Apr. 2010. [26] Learning Systems Architecture Laboratory, “SCORM Best Practices Guide For Content Developers,” Technical Report, Carnegie Mellon University, 2005. http://www. jointadlcolab.org/downloads/scormcdg 1edsec7update 20050420.pdf. [27] A. Collins, J. S. Brown and S. E. Newman, “Cognitive apprenticeship: Teaching the Crafts of Reading, Writing, and Mathematics,” Knowing, learning, and instruction: Essays in honor of Robert Glaser, 1989, pp. 453-494. [28] J. S. Brown, A. Collins and P. Duguid, “Situated Cognition and the Culture of Learning,” Educational Researcher, Vol. 18, No. 1, 1989, p. 32. [29] G. Hislop, “The Inevitability of Teaching Online,” Computer, Vol. 42, No. 12, 2009, pp. 94-96. [30] R. Felder and L. Silverman, “Learning and Teaching Styles in Engineering Education,” Engineering education, Vol. 78, No. 7, 1988, pp. 674-681. [31] S. Reisman and W. A. Carr, “Perspectives on Multimedia Systems in Education,” IBM Journal of Research and Development, Vol. 30, No. 3, 1991, pp. 280-295. [32] T. Yager, “Information’s Human Dimension,” Byte Magazine, Vol. 16, No. 13, 1991, pp. 153-160. [33] E. Popescu, “Evaluating the Impact of Adaptation to Learning Styles in a Web-Based Educational System,” in Proceedings of the 8th International Conference on Advances in Web Based Learning (ICWL ’09), Germany, 2009, pp. 343-352. [34] “The Metropolitan Museum of Art,” 2010. http://www. metmuseum.org/works of art, accessed Apr. [35] Y. J. Dori and J. Belcher, “How Does Technology-Enabled Active Learning Affect Undergraduate Students’ Understanding of Electromagnetic Concepts?” Journal of the Learning Sciences, Vol. 14, No. 2, 2005, pp. 243-279.