Reference: | [1] ADL Initiative, SCORM Version 1.2 and 1.3, available at http://www.adlnet.org. [2] S. Ainsworth, Tutorial on Evaluation Methods for Learning Environments, in Interna-tional Conference on Artificial Intelligence in Education, 2003. http://www.cs.usyd.edu.au/~aied/Ainsworth_tutorial.pdf [3] M. Alias, T. R. Black, D. E. Gray, “Effect of Instruction on Spatial Visualisation Ability in Civil Engineering Students,” International Educational Journal, Vol. 3, No 1, 2002. [4] A. Aron and E. N. Aron, Statistics for Psychology, 2nd ed., Prentice-Hall, 2000. [5] D. P. Ausubel, J. S. Novak, and H. Hanesian, Educational Psychology: A Cognitive View, Holt, Rinehart & Winston: New York, 1978. [6] R. Baeze-Yates and B Ribeiro-Neto, Modern Information Retrieval, Addison Wesley, 1999. [7] D. Borsboom and G. J. Mellenbergh, “True scores, latent variables, and constructs: A comment on Schmidt and Hunter,” Intelligence, Vol. 30, pp. 505-514, 2002. [8] T. Branoff, P. E. Connolly, “The Addition of Coordinate Axes to the Purdue Spatial Visu-alization Test-Visualization of Rotations: A Study at Two Universities,” in Proc. of ASEE Annual Conference & Exposition, 1999. [9] G. M. Bodner and R. B. Guay, “The Purdue Visualization of Rotations Test,” The Chemical Educator, Vol. 2, No. 4, 1997. [10] P. Brusilovsky, “Methods and Techniques of Adaptive Hypermedia,” User Modeling and User-Adapted Interaction, 6 (2-3), pp. 87-129, 1996. [11] P. Brusilovsky, “Adaptive and Intelligent Technologies for Web-based Education,” Kün-stliche Intelligenz, 4, pp. 19-25, 1999. [12] P. Brusilovsky, “Course Sequencing for Static Courses? Applying ITS Techniques in Large-Scale Web-based Education,” Proc. of International Conference on Intelligent Tutoring Systems, pp. 625-634, 2000. [13] P. Brusilovsky and J. Vassileva, “Course Sequencing techniques for large-scale web-based education,” Int. J. Cont. Engineering Education and Lifelong Learning, 2003. [14] P. Brusilovsky, “Adaptive Hypermedia,” User Modeling and User-Adapted Interaction, 11, pp. 87-110, 2001. [15] B. Carr and I. P. Goldstein, “Overlays: a Theory of Modeling for Computer Aided In-struction,” AI Memo, 1977. [16] C-Y Chang, “The Impact of Different Forms of Multimedia CAI on Students’ Science Achievement,” Innovations in Education and Teaching International (IETI), Vol. 39, Is-sue 4, pp. 280-288, 2002. [17] D. N. Chin, “Empirical Evaluation of User Models and User-Adapted Systems,” User Modeling and User-Adapted Interaction, Vol. 11, pp. 181-194, 2001. [18] J. Cohen, Statistical Power Analysis for the Behavioral Sciences 2nd ed., NJ: Lawrence Erlbaum, 1988. [19] M.T.H. Chi, S. A. Siler, H. Jeong, T. Yamauchi, R. G. Hausmann, “Learning from Hu-man Tutoring,” Cognitive Science, 25, pp. 471-533, 2001. [20] R. E. Clark, “Media will Never Influence Learning,” Educational Technology Research and Development, 42(2), pp. 21-29, 1994. [21] A. T. Corbett and J. R. Anderson, “Locus of Feedback Control in Computer-Based Tu-toring: Impact on Learning Rate, Achievement and Attitudes,” in Proc. of ACM CHI’2001 Conference on Human Factors in Computing Systems, 245-252, 2001. [22] T. H. Cormen, C. E. Leiserson, R. L. Rivest, C. Stein, Introduciton to Algorithms, 2nd Ed., MIT Press, 2001. [23] L. G. Daniel, “Statistical significance testing: a historical overview of misuse and misinterpretation with implication for the editorial policies of educational journals,” Research in the Schools, Vol. 5, pp. 23-32, 1998. [24] P. De Bra, P. Brusilovsky, G. Houben, “Adaptive Hypermedia: From Systems to Frame-work,” ACM Computing Surveys, Vol. 31, No. 4es, Dec. 1999. [25] C. Dede, M. C. Salzman, R. B. Loftin, and D. Sprague, “Multisensory Immersion as a Modeling Environment for Learning Complex Scientific Concepts,” Computer Modeling and Simulation in Science Education, Springer-Verlag, 1999. [26] S. Draper, “Learning Styles notes,” Psychology Department, University of Glasgow, 2003 available at http://www.psy.gla.ac.uk/~steve/lstyles.html [27] Andrea A. diSessa, Changing minds: computer, learning, and literacy, The MIT Press, 2001. [28] J. Eklund and P. Brusilovsky, “The Value of Adaptivity in Hypermedia Learning Envi-ronments: A Short Reiview of Empirical Evidence,” in Proc. of 9th ACM International Hypertext Conference, Pittsburgh, PA, June 1998. [29] R. M. Felder and L. K. Silverman, “Learning and Teaching Styles in Engineering Educa-tion,” Engineering Education, 78(7), pp. 674-681, 1988. [30] R. M. Felder, G. N. Felder, and E. J. Dietz, “The Effects of Personality Type on Engi-neering Student Performance and Attitudes,” Journal of Engineering Education, 9(1), pp. 3-17, 2002. [31] J. E. Gilbert, R. Hubscher and S. Puntambekar Ed., Proc. of Workshop on Assessment Methods in Web-based Learning Environment and Adaptive Hypermedia, affiliated with International Conference on Artificial Intelligence in Education, 2001. available at http://www.eng.auburn.edu/~gilbert/AIED2001/ [32] D. N. M. de Gruijter and L. J. Th. van der Kamp, Statistical Test Theory for Education and Psychology, Graduate School of Education, Universiteit Leiden, Netherlands, 2003. available at http://icloniis.iclon.leidenuniv.nl/gruijter/ [33] J. Han and M. Kamber, Data mining: Concepts and Techniques, Academic Press, 2001. [34] Y. Hijikata, “Implicit User Profiling for On Demand Relevance Feedback,” in Proc. of ACM Intelligent User Interface Conference (IUI 2004), Portugal, January 2004. [35] D. E. Hinkle, W. Wiersma, and S. G. Jurs, Applied Statistics for the Behavioral Sciences, Houghton Mifflin, 1994. [36] B. Hokanson and S. Hooper, “Computers as cognitive media: examining the potential of computers in education,” Computers in Human Behavior, 16:537-552, 2000. [37] P. Holt, S. Dubs, M. Jones and J. Greer, “The State of Student Modeling,” Student Mod-elling: The Key to Individualized Knowledge-Based Instructution, pp. 3-35, Springer-Verlag, 1991. [38] R. Hubscher, “Logical Optimal Curriculum Sequences for Adaptive Hypermedia Sys-tems,” in Proc. of Adaptive Hypermedia, 2000. [39] B. E. Huitema, The Analysis of Covariance and Alternatives, John Wiley & Sons, New York, 1980. [40] Schuyler W. Huck, Reading Statistics and Research, Addison Wesley Longman, 2000. [41] T. Huk, M. Steinke, C. Floto, “The Influence of Visual Spatial Ability on the Attitude of Users towards High-Quality 3D-animations in Hypermedia Learning Environments,” in Proc. of E-Learn’03, 2003. [42] C. Hundhausen, S. Douglas, and J. Stasko, “A Meta-Study of Algorithm Visualization Effectiveness,” Journal of Visual Languages and Computing, Vol. 13, No. 3, pp. 259-290, June 2002. [43] W-Y. Hwang, C-B. Chang and G-J. Chen, “The Relationship of Learning Traits, Motiva-tion and Performance-Learning Response Dynamics,” Computers and Education, Vol. 42, pp. 267-287, 2004. [44] IMS Simple Sequencing Specification 1.0, http://www.imsglobal.org/simplesequencing/index.cfm [45] P. Ji, J. Kurose and B. Woolf, “Student Behavioral Model Based Prefetching in Online Tutoring System,” Technical Report, Department of Computer Science, University of Massachusetts at Amherst, 2001. [46] Judy Kay, “Stereotypes, Student Models and Scrutability,” in Proc. of Intelligent Tutor-ing Systems 2000 (ITS 2000), LNCS 1839, pp. 19-30, 2000. [47] P. K. Koehler, FastScript3D, A Companion to Java 3D, Jet Propulsion Laboratory, Cali-fornia Institute of Technology, 2002. available at http://fastscript3d.jpl.nasa.gov/ [48] S. Lajoie and S. Derry, “A Middle Camp for (Un)Intelligent Instructional Computing: An Introduction,” Computers as Cognitive Tools, pp. 1-11, NJ: Erlbaum., 1993. [49] R. Kozma, "Learning with media," Review of Educational Research, 61(2), pp. 179-212, 1991. [50] J. E. McLean and J. M. Ernest, “The role of statistical significance testing in educational research,” Research in the Schools, Vol. 5, pp. 15-22, 1998. [51] E. Melis, E. Andres, E. Budenbender, A. Frischauf, “ActiveMath: A Generic and Adap-tive Web-based Learning Environment,” International Journal of Artificial Intelligence in Education, 12:385-407, 2001. [52] J. Mohler, “Re-examining 3D Web Technologies for Education,” in Proc. of World Conference on the WWW and Internet, pp. 402-407, 2000 [53] S. Olkun, “Making Connections: Improving Spatial Abilities with Engineering Drawing Activities,” International Journal of Mathematics Teaching and Learning, April, 2003. [54] R. Parent, Computer Animation: Algorithms and Techniques, Academic Press, 2002. [55] B. R. Preiss, Data Structures and Algorithms with Object-Oriented Design Patterns in C++, John Wiley & Sons, 1999. [56] M. Recker and A. Ram, “Cognitive Media Types as Indices for Hypermedia Learning Environments,” in Proc. of the AAAI-94 Workshop on Indexing and Reuse in Multimedia Systems, Seattle, WA, 1994. [57] E. Rich, “User Modeling via Stereotypes,” Cognitive Sciences, Vol. 3, pp.355-366, 1979. [58] J. Rieman, M. Franzke and D. Redmiles, “Usability Evaluation with the Cognitive Walk-through,” in Proc. of ACM Annual Conference on CHI (CHI’95), 1995. [59] J.A. Self. “Bypassing the intractable problem of student modelling,” Intelligent Tutoring Systems: at the Crossroads of Artificial Intelligence and Education, pages 107--123, Norwood, NJ, 1990. [60] V. J. Shute, “A Comparison of Learning Environments: All That Glitters…”Computers as Cognitive Tools, pp. 47-73, NJ: Erlbaum., 1993. [61] B. A. Soloman and R. M. Felder, Index of Learning Styles Questionnaire, available at http://www.engr.ncsu.edu/learningstyles/ilsweb.html [62] N. Stach, A. Cristea and P. De Bra, “Authoring of Learning Styles in Adaptive Hyperme-dia,” in Proc. of WWW Conference, NY, USA, 2004. [63] M. K. Stern and B. P. Woolf, “Adaptive Content in an Online Lecture System,” in Proc. of Adaptive Hypermedia 2000, LNCS 1892, pp. 227-238, 2000. [64] J. Stevens, Applied Multivariate Statistics for the Social Science 3rd ed., NJ: Lawrence Erlbaum, 1996. [65] A. Strehl, Relationship-based Clustering and Cluster Ensembles for High-dimensional Data Mining, Doctorial Dissertation, The University of Texas at Austin, May 2002. [66] E. Triantafillou, A. Pomportsis, S. Demetriadis and E. Georgiadou, “The Value of Adap-tivity based on Cognitive Style: An Empirical Study,” British Journal of Educational Technology, Vol. 35, No. 1, pp. 95-106, 2004. [67] A. Tretiakov, Kinshuk, T. Tretiakov, “Designing Multimedia Support for Situated Learn-ing,” Proc. of IEEE International Conference on Advanced Learning Technologies, 2003. [68] V. Tsiriga and M. Virvou, “Initializing the Student Model using Stereotypes and Machine Learning,” in Proc. of IEEE International Conference on Systems, Man and Cybernetics, 2002. [69] NASA Johnson Space Center, The Virtual Astronaut Website Project, available at http://virtualastronaut.jsc.nasa.gov. [70] NASA Science@NASA website, “Whatever happened to Virtual Reality,” available at http://science.nasa.gov/headlines/y2004/21jun_vr.htm [71] J. Rickel and W. L. Johnson, “Animated Agents for Procedural Training in Virtual Real-ity: Perception, Cognition, and Motor Control,” Applied Artificial Intelligence, 13:343-382, 1999. [72] F. L. Schmidt and J. E. Hunter, “Theory Testing and Measurement Error,” Intelligence, 27(3), pp.183-198. 1999. [73] B. J. Underwood and J. J. Shaughnessy, Experimentation in Psychology, John Wiley&Sons, New York, 1975. [74] J. Vassileva, “Instructional Planning Approaches: from Tutoring towards Free Learning,” in Proc. of Euro-AIED, 1996. [75] H-C. Wang, T-Y. Li, "Considering Model-based Adaptivity for Learning Objects," Learning Technology newsletter, Vol. 6, Issue 2, April 2004. [76] R. Wolfe, “A Syllabus Survey: Examining the State of Current Practice in Introductory Computer Graphics Courses,” ACM SIGGRAPH Computer Graphics, Volume 33, Issue 1, 1999. [77] B. Woolf, M. Romoser, D. Bergeron, D. Fisher, “Tutoring 3-Dimensional Visual Skills: Dynamic Adaptation to Cognitive Skill,” in Proc. of Artificial Intelligence in Education, 2003. [78] C. H. Yu, B. Onlund, S. DiGangi and A. Jannasch-Pennell, “Estimating the Reliability of Self-reported Data for Web-based Instruction,” AECT’s Annual International Convention, Long Beach, California, 2000. [79] B. Zayas, “Learning from 3D VR representations: learners-centered design, realism and interactivity,” in Proc. of Workshop on External Representations in AIED, May 2001. |