Abstract
This paper presents an in-depth analysis of a nonconventional topic-based personalization approach for adaptive educational systems (AES) that we have explored for a number of years in the context of university programming courses. With this approach both student modeling and adaptation are based on coarse-grained knowledge units that we called topics. Our motivation for the topic-based personalization was to enhance AES transparency for both teachers and students by utilizing typical topic-based course structures as the foundation for designing all aspects of an AES from the domain model to the end-user interface. We illustrate the details of the topic-based personalization technology, with the help of the Web-based educational service QuizGuide—the first system to implement it. QuizGuide applies the topic-based personalization to guide students to the right learning material in the context of an undergraduate C programming course. While having a number of architectural and practical advantages, the suggested coarse-grained personalization approach deviates from the common practices toward knowledge modeling in AES. Therefore, we believe that several aspects of QuizGuide required a detailed evaluation—from modeling accuracy to the effectiveness of adaptation. The paper discusses how this new student modeling approach can be evaluated, and presents our attempts to evaluate it from multiple different prospects. The evaluation of QuizGuide across several consecutive semesters demonstrates that, although topics do not always support precise user modeling, they can provide a basis for successful personalization in AESs.
Similar content being viewed by others
Notes
In the reminder of this paper, whenever possible, we apply independent-samples t-test to compare means of two populations. However, whenever our data do not satisfy the assumptions of parametric statistics (such as here), we use the Mann-Whitney test as a t-test substitute.
The reviewed drawbacks of the original topic-based student modeling formula caused us to replace it with a more cognitively grounded formula in the newer version of topic-based adaptation service Yudelson (2010). However, in this paper, we analyze the exact formula that was used in our QuizGuide studies.
Figure 8 explains why .5 is the maximum level of student per-topic knowledge that results in a change in system adaptation: at this level the topic is annotated with the 3-arrows knowledge icon; any additional (positive) results will not influence the change of the topic annotation.
This is a simplification, as students also take into account the goal-based annotation when choosing topics. However, in order to assess the roles of topic-based and goal-based adaptation separately, we have to simplify this analysis.
There is a ongoing debate in the literature on whether Likert scales produce ordinal or interval data. We have chosen to use a more conservative approach, i.e. treat students’ answers as ordinal data. Based on this assumption and on the fact that students’ responses to all eight questions were not normally distributed around medians, we decided to use one-sample sign tests for this analysis.
References
Ahn, J.-W., Brusilovsky, P., He, D., Grady, J., Li, Q.: Personalized Web Exploration with Task Models. In: Proceedings of the 17th international conference on World Wide Web, WWW ’08, Beijing, China, April 21–25, 2008, ACM, pp. 1–10 (2008)
Anderson, J.R., Corbett, A.T., Koedinger, K.R., Pelletier, R.: Cognitive tutors: lessons learned. J. Learn. Sci. 4(2), 167–207 (1995)
Apted, T., Kay, J., Lum, A.: Supporting metadata creation with an ontology built from an extensible dictionary. In: De Bra, P., Nejdl, W. (eds.) Proceedings of 3rd International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems (AH’2004), pp. 4–13. Springer, Berlin, 23–26 August 2004
Aroyo, L., Dicheva, D.A.: Concept-based approach to support learning in a Web-based support environment. In: Moore, J.D., Redfield, C.L., Johnson, W.L. (eds.) Proceedings of AI-ED’2001, pp. 1–12. IOS Press, Amsterdam (2001)
Baker, R.S., Corbett, A.T., Aleven, V.: More accurate student modeling through contextual estimation of slip and guess probabilities in Bayesian knowledge tracing. In: Woolf, B., Aïmeur, E., Nkambou, R., Lajoie, S. (eds.) Proceedings of the 9th International Conference on Intelligent Tutoring Systems, Montreal, Canada, pp. 406–415. Springer, Berlin, 23–27 June 2008
Baker, R.S.J.d., Corbett, A.T., Gowda, S.M., Wagner, A.Z., MacLaren, B.A., Kauffman, L.R., Mitchell, A.P., Giguere, S.: Contextual slip and prediction of student performance after use of an intelligent tutor. In: De Bra, P., Kobsa, A., Chin, D. (eds.) Proceedings of 18th International Conference on User Modeling, Adaptation, and Personalization (UMAP 2009), pp. 52–63. Springer, Big Island, HI, 22–24 June 2010
Baker, R.S.J.d., Pardos, Z.A., Gowda, S.M., Nooraei, B.B., Heffernan, N.T.: Ensembling predictions of student knowledge within intelligent tutoring systems. In: Proceedings of 19th International Conference on User Modeling, Adaptation, and Personalization, UMAP 2011, Girona, Spain, pp. 13–24. Springer, 11–15 July 2011
Beck, J., Chang, K.-M., Mostow, J., Corbett, A.: Does help help? Introducing the Bayesian evaluation and assessment methodology. In: Woolf, B., Aïmeur, E., Nkambou, R., Lajoie, S. (eds.) Proceedings of the 9th International Conference on Intelligent Tutoring Systems, Montreal, Canada, pp. 383–394. Springer, Berlin, 23–27 June 2008
Brown, J.S., Burton, R.R.: Diagnostic models for procedural bugs in basic mathematical skills. Cogn. Sci. 2, 155–192 (1978)
Brusilovsky, P.: Adaptive hypermedia. User Model. User Adapt. Interact. 11(1/2), 87–110 (2001)
Brusilovsky, P.: Developing adaptive educational hypermedia systems: from design models to authoring tools. In: Murray, T., Blessing, S., Ainsworth, S. (eds.) Authoring Tools for Advanced Technology Learning Environments: Toward cost-effective adaptive, interactive, and intelligent educational software, pp. 377–409. Kluwer, Dordrecht (2003)
Brusilovsky, P.: Knowledgetree: a distributed architecture for adaptive e-learning. In: Proceedings of 13th International World Wide Web Conference, WWW 2004, pp. 104–113. ACM Press, New York, NY, 17–22 May 2004
Brusilovsky, P.: Adaptive navigation support. In: Brusilovsky, P., Kobsa, A., Neidl, W. (eds.) The Adaptive Web: Methods and Strategies of Web Personalization. Lecture Notes in Computer Science, vol. 4321, pp. 263–290. Springer, Berlin (2007)
Brusilovsky, P.: Adaptive hypermedia for education and training. In: Durlach, P., Lesgold, A. (eds.) Adaptive Technologies for Training and Education, pp. 46–68. Cambridge University Press, Cambridge (2012)
Brusilovsky, P., Cooper, D.W.: Domain, Task, and user models for an adaptive hypermedia performance support system. In: Gil, Y., Leake, D.B. (eds.) Proceedings of 2002 International Conference on Intelligent User Interfaces, pp. 23–30. ACM Press, San Francisco, CA 13–16 January 2002
Brusilovsky, P., Eklund, J.: A study of user-model based link annotation in educational hypermedia. J. Univ. Comput. Sci. 4(4), 429–448 (1998)
Brusilovsky, P., Eklund, J., Schwarz, E.: Web-based education for all: a tool for developing adaptive courseware. In: Ashman, H., Thistewaite, P. (eds.) Proceedings of 7th International World Wide Web Conference, pp. 291–300. Elsevier Science B. V., Brisbane, Australia, 14–18 April 1998
Brusilovsky, P., Karagiannidis, C., Sampson, D.: Layered evaluation of adaptive learning systems. Int. J. Contin. Eng. Educ. Lifelong Learn. 14(4/5), 402–421 (2004)
Brusilovsky, P., Knapp, J., Gamper, J.: Supporting teachers as content authors in intelligent educational systems. Int. J. Knowl. Learn. 2(3/4), 191–215 (2006)
Brusilovsky, P., Millán, E.: User models for adaptive hypermedia and adaptive educational systems. In: Brusilovsky, P., Kobsa, A., Neidl, W. (eds.) The Adaptive Web: Methods and Strategies of Web Personalization. Lecture Notes in Computer Science, vol. 4321, pp. 3–53. Springer, Berlin (2007)
Brusilovsky, P., Sosnovsky, S.: Engaging students to work with self-assessment questions: a study of two approaches. In: Proceedings of 10th Annual Conference on Innovation and Technology in Computer Science Education, ITiCSE’2005, pp. 251–255. ACM Press, Monte de Caparica, Portugal, 27–29 June 2005a
Brusilovsky, P., Sosnovsky, S.: Individualized exercises for self-assessment of programming knowledge: an evaluation of QuizPACK. ACM Journal on Educational Resources in Computing 5(3): Article no. 6 (2005b)
Brusilovsky, P., Sosnovsky, S., Lee, D., Yudelson, M., Zadorozhny, V., Zhou, X.: Learning SQL programming with interactive tools: from integration to personalization. ACM Transactions on Computing Education 9 (4). Article No. 19, 1–15 (2010)
Brusilovsky, P., Sosnovsky, S., Shcherbinina, O.: User modeling in a distributed e-learning architecture. In: Ardissono, L., Brna, P., Mitrovic, A. (eds.) Proceedings of 10th International User Modeling Conference, pp. 387–391. Springer, Berlin, 24–29 July 2005a
Brusilovsky, P., Sosnovsky, S., Yudelson, M., Chavan, G.: Interactive authoring support for adaptive educational systems. In: Looi, C.-K., McCalla, G., Bredeweg, B., Breuker, J. (eds.) Proceedings of 12th International Conference on Artificial Intelligence in Education, AIED’2005, pp. 96–103. IOS Press, Amsterdam, 18–22 July 2005b
Bull, S.: Supporting learning with open learner models. In: Proceedings of 4th Hellenic Conference on Information and Communication Technologies in Education, pp. 47–61. Athens, Greece, September 29–October 3, 2004
Carbonell, J.R.: AI in CAI: an artificial intelligence approach to computer aided instruction. IEEE Trans. Man-Mach. Syst. MMS 11(4), 190–202 (1970)
Carmona, C., Bueno, D., Guzmán, E., Conejo, R.: SIGUE: making web courses adaptive. In: De Bra, P., Brusilovsky, P., Conejo, R. (eds.) Proceedings of Second International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems (AH’2002), May 29–31, 2002, Springer, Málaga, Spain, pp. 376–379 (2002)
Chin, D.: Empirical evaluations of user models and user-adapted systems. User Model. User Adapt. Interact. 11(1–2), 181–194 (2001)
Conati, C., Gertner, A., Vanlehn, K.: Using Bayesian networks to manage uncertainty in student modeling. User Model. User Adapt. Interact. 12(4), 371–417 (2002)
Conejo, R., Guzman, E., Millán, E.: SIETTE: a web-based tool for adaptive teaching. Int. J. Artif. Intell. Educ. 14(1), 29–61 (2004)
Corbett, A., McLaughlin, M., Scarpinatto, C.: Modeling student knowledge: cognitive tutors in high school and college. User Model. User Adapt. Interact. 10(2–3), 81–108 (2000)
Corbett, A.T., Anderson, J.R.: Student modeling and mastery learning in a computer-based programming tutor. In: Frasson, C., Gauthier, G., McCalla, G. (eds.) Proceedings of Second International Conference on Intelligent Tutoring Systems, ITS’92, pp. 413–420. Springer, Berlin, 10–12 June 1992
Corbett, A.T., Anderson, J.R.: Knowledge tracing: modelling the acquisition of procedural knowledge. User Model. User Adapt. Interact. 4(4), 253–278 (1995)
Corbett, A.T., Anderson, J.R., Carver, V.H., Brancolini, S.A.: Individual differences and predictive validity in student modeling. In: Ram, A., Eiselt, K. (eds.) Proceedings of the 16th Annual Conference of the Cognitive Science Society. pp. 457–464. Lawrence Erlbaum, Edinburgh, 23–27 August 1993a
Corbett, A.T., Anderson, J.R., O’Brien, A.T.: The predictive validity of student modeling in the ACT programming tutor. In: Brna, P., Ohlsson, S., Pain, H. (eds.) Proceedings of AI-ED’93, World Conference on Artificial Intelligence in Education, pp. 457–464. AACE, Charlottesville, Edinburgh, 23–27 August 1993b
Cristea, A., Aroyo, L.: Adaptive authoring of adaptive educational hypermedia. In: De Bra, P., Brusilovsky, P., Conejo, R. (eds.) Proceedings of Second International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems (AH’2002), pp. 122–132. Springer, Berlin, 29–31 May 2002
Davidovic, A., Warren, J., Trichina, E.: Learning benefits of structural example-based adaptive tutoring systems. IEEE Trans. Educ. 46(2), 241–251 (2003)
De Bra, P.: Pros and cons of adaptive hypermedia in web-based education. J. CyberPsychol. Behav. 3(1), 71–77 (2000)
De Bra, P., Aerts, A., Berden, B., de Lange, B., Rousseau, B., Santic, T., Smits, D., Stash, N.: AHA! The adaptive hypermedia architecture. In: Proceedings of the 14th ACM Conference on Hypertext and Hypermedia, pp. 81–84. Nottingham, UK, ACM (2003)
De Bra, P., Ruiter, J.-P.: AHA! Adaptive hypermedia for all. In: Fowler, W., Hasebrook, J. (eds.) Proceedings of WebNet’2001, World Conference of the WWW and Internet, pp. 262–268. AACE, Orlando, FL, 23–27 October 2001
De Bra, P., Smits, D., van der Sluijs, K., Cristea, A., Foss, J., Glahn, C., Steiner, C.: GRAPPLE: learning management systems meet adaptive learning environments. In: Peña-Ayala, A. (ed.) Intelligent and Adaptive Educational-Learning Systems, vol. 17, pp. 133–160. Springer, Berlin (2013)
Eliot, C., Neiman, D., Lamar, M.: Medtec: A Web-based intelligent tutor for basic anatomy. In: Lobodzinski, S., Tomek, I. (eds.) Proceedings of WebNet’97, World Conference of the WWW, Internet and Intranet, pp. 161–165. AACE, Toronto, Canada, 1–5 November 1997
Falakmasir, M.H., Pardos, Z.A., Gordon, G.J., Brusilovsky, P.: A spectral learning approach to knowledge tracing. In: D’Mello, S.K., Calvo, R.A., Olney, A. (eds.) Proceedings of the 6th International Conference on Educational Data Mining (EDM 2010), pp. 28–34. Memphis, TN, USA, 6–9 July 2013
Farzan, R., Brusilovsky, P.: AnnotatEd: a social navigation and annotation service for web-based educational resources. New Rev. Hypermedia Multimed 14(1), 3–32 (2008)
Fogarty, J., Baker, R., Hudson, S.: Case studies in the use of ROC curve analysis for sensor-based estimates in human computer interaction. Proc. Grap. Interface 2005, 129–136 (2005)
Gena, C. Weibelzahl, S.: Usability engineering for the adaptive web. In: Brusilovsky, P., Kobsa, A., Neidl, W. (eds.): The Adaptive Web: Methods and Strategies of Web Personalization. Lecture Notes in Computer Science, Vol. 4321, pp. 720–762. Springer, Berlin (2007)
Goldstein, I.P.: The genetic graph: a representation for the evolutionof procedural knowledge. Int. J. Man-Mach. Stud. 11(1), 51–77 (1979)
Goldstein, I.P., Carr, B.: The computer as coach: an athletic paradigm for intelligent education. In: Proceedings of 1977 Annual ACM Conference, Seatle, pp. 227–233. October (1977)
González-Brenes, J.P., Huang, Y., Brusilovsky, P.: General features in knowledge tracing to model multiple subskills, temporal item response theory, and expert knowledge. In: Stamper, J., Pardos, Z., Mavrikis, M., McLaren, B.M. (eds.) Proceedings of the 7th International Conference on Educational Data Mining (EDM 2014), London, UK, pp. 84–91. 4–7 July 2014
Hatala, M., Gasevic, D., Siadaty, M., Jovanovic, J., Torniai, C.: Can educators develop ontologies using ontology extraction tools: an end-user study. In: Cress, U., Dimitrova, V., Specht, M. (eds.) Proceedings of 4th European Conference on Technology Enhanced Learning (ECTEL 2009), Nice, France, pp. 127–139. Springer, Berlin, 29 September–2 October 2009
Heathcote, A., Brown, S., Mewhort, D.J.K.: The power law repealed: the case for an exponential law of practice. Psychon. Bull. Rev. 7(2), 185–207 (2000)
Henze, N., Naceur, K., Nejdl, W., Wolpers, M.: Adaptive hyperbooks for constructivist teaching. Künstliche Intell. 4, 26–31 (1999)
Henze, N., Nejdl, W.: Student modeling for KBS Hyperbook system using Bayesian networks, Technical report, Report, University of Hannover (1999)
Hothi, J., Hall, W., Sly, T.: A study comparing the use of shaded text and adaptive navigation support in adaptive hypermedia. In: Brusilovsky, P., Stock, O., Strapparava, C. (eds.) Proceedings of Adaptive Hypermedia and Adaptive Web-based systems, pp. 335–342. Springer, Berlin, 28–30 August 2000
Hovland, C.I., Lumsdaine, A.A., Sheffield, F.D.: A baseline for measurement of percentage change. In: Hovland, C.I., Lumsdaine, A.A., Sheffield, F.D. (eds.) Experiments on Mass Communication. Wiley, New York (1949)
Hsiao, I.-H., Sosnovsky, S., Brusilovsky, P.: Guiding students to the right questions: adaptive navigation support in an E-Learning system for Java programming. J. Comput. Assist. Learn. 26(4), 270–283 (2010)
Jameson, A.: Numerical uncertainty management in user and student modeling: an overview of systems and issues. User Model. User Adapt. Interact. 5(3–4), 193–251 (1996)
Jameson, A.: Modeling both the context and the user. Pers. Technol. 5(1), 29–33 (2001)
Karagiannidis, C., Sampson, D.G.: Layered evaluation of adaptive applications and servers. In: Brusilovsky, P., Stock, O., Strapparava, C. (eds.) Proceedings of Adaptive Hypermedia and Adaptive Web-based systens, pp. 343–346. Springer, Berlin, 28–30 August 2000
Käser, T., Koedinger, K.R., Gross, M.: Different parameters - same prediction: An analysis of learning curves. In: Stamper, J., Pardos, Z., Mavrikis, M., McLaren, B.M. (eds.) Proceedings of the 7th International Conference on Educational Data Mining (EDM 2014), London, UK, pp. 52–59. 4–7 July 2014
Kavcic, A.: Fuzzy user modeling for adaptation in educational hypermedia. IEEE Trans. Syst. Man Cybern. 34(4), 439–449 (2004)
Keane, M., O’Brien, M., Smyth, B.: Are people biased in their use of search engines? Commun. ACM 51(2), 49–52 (2008)
Knutov, E., De Bra, P., Pechenizkiy, M.: AH 12 years later: a comprehensive survey of adaptive hypermedia methods and techniques. New Rev. Hypermed. Multimed. 15(1), 5–38 (2009)
Koedinger, K., Mathan, S.: Distinguishing qualitatively different kinds of learning using log files and learning curves. In: Mostow, J., Tedesco, P. (eds.) Proceedings of TS 2004 Log Analysis Workshop, pp. 39–46. Maceio, Brazi (2004)
Koedinger, K.R., Anderson, J.R., Hadley, W.H., Mark, M.A.: Intelligent tutoring goes to school in the big city. Int. J. Artif. Intell. Educ. 8, 30–43 (1997)
Koedinger, K.R., McLaughlin, E.A., Stamper, J.: Automated Student Model Improvement. In: Yacef, K., Zaïane, O., Hershkovitz, H., Yudelson, M., Stamper, J. (eds.) Proceedings of the 5th International Conference on Educational Data Mining, pp. 17–24. Chania, Greece (2012)
Lawless, S., Hederman, L., Wade, V.: Enhancing Access to Open Corpus Educational Content: Learning in the Wild. In: Proceedings of the 19th ACM Conference on Hypertext & Hypermedia, Pittsburgh, Pennsylvania, USA, pp. 167–174 (2008)
Martin, B., Koedinger, K.R., Mitrovic, A., Mathan, S.: On using learning curves to evaluate ITS. In: Looi, C.-K., McCalla, G., Bredeweg, B., Breuker, J. (eds.) Proceedings of 12th International Conference on Artificial Intelligence in Education, AIED’2005, pp. 419–426. IOS Press, Amsterdam, July 18–22, 2005
Martin, B., Mitrovic, A., Koedinger, K., Mathan, S.: Evaluating and improving adaptive educational systems with learning curves. User Model. User Adapt. Interact. 21(3), 249–283 (2011)
Mitrovic, A.: An intelligent SQL tutor on the web. Int. J. Artif. Intell. Educ. 13(2–4), 173–197 (2003)
Mitrovic, A., Ohlsson, S.: Evaluation of a constraint-based tutor for a database language. Int. J. Artif. Intell. Educ. 10(304), 238–256 (1999)
Murre, J., Chessa, A.: Power laws from individual differences in learning and forgetting: mathematical analyses. Psychon. Bull. Rev. 18(3), 592–597 (2011)
Newell, A., Rosenbloom, P.S.: Mechanisms of skill acquisition and the law of practice. In: Anderson, J.R. (ed.) Cognitive Skills and their Acquisition, pp. 1–51. Lawrence Erlbaum Associates Inc, Hillsdale, NJ (1981)
Oberlander, J., O’Donell, M., Mellish, C., Knott, A.: Conversation in the museum: experiments in dynamic hypermedia with the intelligent labeling explorer. New Rev. Multimed. Hypermed. 4, 11–32 (1998)
Ohlsson, S.: Constraint-based student modeling. J. Artif. Intell. Educ. 3(4), 429–447 (1992)
Olston, C., Chi, E.H.: ScentTrails: integrating browsing and searching on the Web. ACM Trans. Comput. Hum. Interact. 10(3), 177–197 (2003)
Papanikolaou, K.A., Grigoriadou, M., Kornilakis, H., Magoulas, G.D.: Personalising the interaction in a web-based educational hypermedia system: the case of inspire. User Model. User Adapt. Interact. 13(3), 213–267 (2003)
Paramythis, A., Weibelzahl, S.: A decomposition model for the layered evaluation of interactive adaptive systems. In: Ardissono, L., Brna, P., Mitrovic, A. (eds.) Proceedings of 10th International User Modeling Conference, pp. 438–442. Springer, Edinburgh, UK, 24–29 July 2005
Pardos, Z.A., Heffernan, N.: KT-IDEM: introducing item difficulty to the knowledge tracing model. In: Konstan, J., Conejo, R., Marzo, J., Oliver, N. (eds.) Proceedings of 19th International Conference on User Modeling, Adaptation, and Personalization, UMAP 2011, pp. 243–254. Springer, Girona, Spain, 11–15 July 2011
Pavlik Jr, P.I., Cen, H., Koedinger, K.R.: Performance factors analysis-a new alternative to knowledge tracing. In: Proceedings of 14th International Conference on Artificial Intelligence in Education (AIED 2009), pp. 531–538. Brighton, UK, 6–10 July 2009
Pirolli, P., Kairam, S.: A knowledge-tracing model of learning from a social tagging system. User Model. User Adapt. Interact. 23(2–3), 139–168 (2013)
Prentzas, J., Hatzilygeroudis, I., Garofalakis, J.: A Web-based intelligent tutoring systems using hybrid rules as its representation basis. In: Cerri, S.A., Gouardères, G., Paraguaçu, F. (eds.) Proceedings of 6th International Conference on Intelligent Tutoring Systems (ITS’2002), pp. 119–128. Springer, Berlin, 2–7 June 2002
Ritter, S.: PAT Online: A Model-tracing tutor on the World-wide Web. In: P. Brusilovsky, K. Nakabayashi and S. Ritter (eds.) Proceedings of Workshop ”Intelligent Educational Systems on the World Wide Web” at AI-ED’97, 8th World Conference on Artificial Intelligence in Education, Kobe, Japan, 18 August 1997, ISIR, pp. 11–17, also available at http://www.contrib.andrew.cmu.edu/~plb/AIED97_workshop/Ritter/Ritter.html (1997)
Schneider-Hufschmidt, M., Kühme, T., Malinowski, U. (eds.): Adaptive user Interfaces: Principles and Practice. Human factors in information technology. North-Holland, Amsterdam (1993)
Schultz, S., Arroyo, I.: Tracing Knowledge and Engagement in Parallel in an Intelligent Tutoring System. In: Stamper, J., Pardos, Z., Mavrikis, M., McLaren, B.M. (eds.) Proceedings of the 7th International Conference on Educational Data Mining (EDM 2014), pp. 312–315. London, UK, 4–7 July 2014
Self, J.: Student models in computer-aided instruction. Int. J. Man-Mach. Stud. 6, 261–276 (1974)
Self, J.: Bypassing the intractable problem of student modelling. In: Frasson, C., Gauthier, G. (eds.) Intelligent Tutoring Systems: At the Crossroads of Artificial Intelligence and Education, pp. 107–123. Ablex Publishing, Norwood (1990)
Shute, V.J.: SMART: Student modeling approach for responce tutoring. User Model. User Adapt. Interact. 5(1), 1–44 (1995)
Smith, A.S.G., Blandford, A.: MLTutor: an application of machine learning algorithms for an adaptive Web-based information system. Int. J. Artif. Intell. Educ. 13(2–4), 235–261 (2003)
Sosnovsky, S., Brusilovsky, P.: Layered evaluation of topic-based adaptation to student knowledge. In: Proceedings of Fourth Workshop on the Evaluation of Adaptive Systems at 10th International User Modeling Conference, UM 2005, pp. 47–56. 26 July 2005
Sosnovsky, S., Brusilovsky, P., Hsiao, I.-H.: Adaptation ”in the Wild”: Ontology-based personalization of open-corpus learning material. In: Proceedings of 7th European Conference on Technology Enhanced Learning (EC-TEL 2012), pp. 425–431. Saarbrücken, Germany (2012)
Sosnovsky, S., Brusilovsky, P., Lee, D.H., Zadorozhny, V., Zhou, X.: Re-assessing the value of adaptive navigation support in e-learning. In: Nejdl, W., Kay, J., Pu, P., Herder, E. (eds.) Proceedings of 5th International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems (AH’2008), pp. 193–203. Springer, Hannover, Germany, 29 July–1 August, 2008
Sosnovsky, S., Brusilovsky, P., Yudelson, M.: Supporting adaptive hypermedia authors with automated content indexing. In: Proceedings of Second International Workshop on Authoring of Adaptive and Adaptable Educational Hypermedia at the Third International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems (AH’2004), Eindhoven, the Netherlands (2004)
Specht, M., Kravcik, M., Pesin, L., Klemke, R.: Learner’s Lounge: Information Brokering for the Adaptive Learning Environment. In: Driscoll, M., Reeves, T.C. (eds.) Proceedings of World Conference on E-Learning, E-Learn 2002, pp. 2510–2512. AACE, Montreal, Canada, 15–19 October 2002
Specht, M., Oppermann, R.: ACE—adaptive courseware environment. New Rev. Hypermed. Multimed. 4, 141–161 (1998)
Specht, M., Weber, G., Heitmeyer, S., Schöch, V.: AST: Adaptive WWW-Courseware for statistics. In: Brusilovsky, P., Fink, J., Kay, J. (eds.) Proceedings of Workshop ”Adaptive Systems and User Modeling on the World Wide Web” at 6th International Conference on User Modeling, UM97, Chia Laguna, Sardinia, Italy, June 2, 1997, pp. 91–95, also available at http://www.contrib.andrew.cmu.edu/~plb/UM97_workshop/Specht.html (1997)
Srivastava, J., Cooley, R., Deshpande, M., Tan, P.: Web usage mining: discovery and applications of usage patterns from Web data. SIGKDD Explor. Newsl. 1(2), 12–23 (2000)
Stern, M.K., Woolf, B.P.: Curriculum sequencing in a Web-based tutor. In: Goettl, B.P., Halff, H.M., Redfield, C.L., Shute, V.J. (eds.) Proceedings of 4th International Conference, ITS-98, pp. 574–583. Springer, Berlin, 16–19 August 1998
Triantafillou, E., Pomportis, A., Demetriadis, S., Georgiadou, E.: The value of adaptivity based on cognitive style: an empirical study. Br. J. Educ. Technol. 35(1), 95–106 (2004)
VanLehn, K.: Student models. In: Polson, M.C., Richardson, J.J. (eds.) Foundations of Intelligent Tutoring Systems, pp. 55–78. Lawrence Erlbaum Associates, Hillsdale (1988)
Vassileva, J.: DCG + GTE: dynamic courseware generation with teaching expertise. Instr. Sci. 26(3/4), 317–332 (1998)
Virvou, M., Moundridou, M.: Student and instructor models: Two kinds of user models and their interaction in an ITS authoring tools. In: Bauer, M., Gmytrasiewicz, P.J., Vassileva, J. (eds.) Proceedings of 8th International Conference on User Modeling, UM 2001, pp. 158–167. Springer, Berlin, 13–17 July 2001
Wang, J.Z., Taylor, W.: Concept forest: a new ontology-assisted text document similarity measurement method. In: Lin, T.Y. et al. (eds.) Proceedings of the 2007 international conference on Web Intelligence, WI ’07, pp. 395–401. IEEE, Silicon Valey, CA, USA, 2–5 November 2007
Weber, G., Kuhl, H.-C., Weibelzahl, S.: Developing adaptive internet based courses with the authoring system NetCoach. In: Reich, S., Tzagarakis, M.M., De Bra, P.M.E. (eds.) Hypermedia: Openness, Structural Awareness, and aptivity, pp. 226–238. Springer, Berlin (2002)
Yudelson, M.: Providing service-based personalization in an adaptive hypermedia University of Pittsburgh (2010)
Yudelson, M., Fancsali, S., Ritter, S., Berman, S., Nixon, T., Joshi, A.: Better data beats big data. In: Stamper, J., Pardos, Z., Mavrikis, M., McLaren, B.M. (eds.) Proceedings of the 7th International Conference on Educational Data Mining (EDM 2014), pp. 205–208. London, UK, 4–7 July 2014
Yudelson, M., Koedinger, K., Gordon, G.: Individualized Bayesian knowledge tracing models. In: Lane, H.C., Yacef, K., Mostow, J., Pavlik, P. (eds.) Proceedings of Artificial Intelligence in Education 2013, pp. 171–180. Springer, Berlin/Heidelberg, Germany (2013)
Acknowledgments
This research is supported by the National Science Foundation under Grants No. 0447083 and 0633494 to the second author.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Sosnovsky, S., Brusilovsky, P. Evaluation of topic-based adaptation and student modeling in QuizGuide. User Model User-Adap Inter 25, 371–424 (2015). https://doi.org/10.1007/s11257-015-9164-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11257-015-9164-4