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Software Engineering and Modeling in TEL

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The New Development of Technology Enhanced Learning

Part of the book series: Lecture Notes in Educational Technology ((LNET))

Abstract

Very different types of systems for teaching and training based on a computer have been developed and put together under term TEL (technology-enhanced learning). Starting with Hyperbooks and Intelligent Tutoring Systems (influenced by cognitive psychology), going to other adaptive systems, embracing single-user and multiuser systems, and, in the last years, becoming mobile, a plethora of systems emerged. Surprisingly, not many of these system types have made their way to off-the-shelf products, but remained at the level of research. Moreover, the following questions can be posed: what insights have been drawn from the development of this multitude of systems. How shall technology be designed to enhance learning? One insight is that system design on the model basis has been widely ignored by the community. This results in a lack of discussable basic concepts, in systems, which are empirical, not comparable, and in system ideas, which cannot be reused. The approach sketched in this chapter shows how different levels of system design can be (and have successfully been) supported by models. These models work independent of the programming language, they can be reused for the development of (at least) some different system types, and they can be used as boundary objects for interdisciplinary communication.

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References

  • Albert, D., Hockemeyer, C., Kickmeier-Rust, M., Peirceb, N., & Conlan, O. (2007). Microadaptivity within complex learning situations – A personalized approach based on competence structures and problem spaces. In International conference on computers in education (ICCE 2007), Hiroshima, Japan.

    Google Scholar 

  • Alpert, S. R., Singley, M. K., & Fairweather, P. G. (1999). Deploying intelligent tutors on the Web: An architecture and an example. International Journal of Artificial Intelligence, 10(2), 183–197.

    Google Scholar 

  • Anderson, J. R., Boyle, C. F., Corbett, A. T., & Lewis, M. W. (1990). Cognitive modeling and intelligent tutoring. Artificial Intelligence, 42, 17–49.

    Article  Google Scholar 

  • Baker, M. (2000). The roles of models in artificial intelligence and education research: A prospective view. International Journal of Artificial Intelligence in Education, 11, 122–143.

    Google Scholar 

  • Bergin, R. A., & Fors, U. G. H. (2003). Interactive simulated patient – An advanced tool for student-activated learning in medicine and healthcare. Computers and Education, 40(4), 361–376.

    Article  Google Scholar 

  • Clancey, W. J. (1984). Methodology for building an intelligent tutoring system. In W. Kintsch, J. R. Miller, & P. G. Polson (Eds.), Methods and tactics in cognitive sciences (pp. 51–84). Hillsdale/London: Lawrence Erlbaum Associates.

    Google Scholar 

  • Clancey, W. J. (1987). Knowledge-based tutoring – The GUIDON program. Cambridge, MA: The MIT Press.

    Google Scholar 

  • Corbett, A. T., Koedinger, K. R., & Anderson, J. R. (1997). Intelligent tutoring systems. In M. Helander, T. K. Landauer, & P. Prabuh (Eds.), Handbook of human-computer interaction (2 completely revised editionth ed., pp. 849–874). Amsterdam: Elsevier Science B.V.

    Google Scholar 

  • de Jong, T., & van Joolingen, W. (1998). Discovery learning with computer simulations of conceptual domains. Review of Educational Research, 68, 179–201.

    Article  Google Scholar 

  • Doignon, J.-P., & Falmagne, J.-C. (1999). Knowledge spaces. Berlin/New York: Springer.

    Book  Google Scholar 

  • Gamma, E., Helm, R., Johnson, R., & Vlissides, J. (1995). Design patterns: Elements of reusable object-oriented software. Reading: Addison-Wesley.

    Google Scholar 

  • Harrer, A. (2003). Software engineering methods for re–use of components and design in educational systems. International Journal of Computers & Applications, Special Issue on Intelligence and Technology in Educational Applications, 25, 1, Anaheim, CA.

    Google Scholar 

  • Harrer, A., & Martens, A. (2006). Towards a pattern language for intelligent teaching and training systems. In T.-W. Chan, M. Ikeda, & K. D. Ashley (Eds.), Proceedings of the 8th international conference on intelligent tutoring systems (Lecture notes in computer science LNCS 4053, pp. 298–307). Berlin: Springer.

    Chapter  Google Scholar 

  • Heller, J., Steiner, C., Hockemeyer, C., & Albert, D. (2006). Competence-based knowledge structures for personalised learning. International Journal on E-Learning, 5(1), 75–88.

    Google Scholar 

  • Himmelspach, J., & Uhrmacher, A. M. (2007). Plug’n simulate. In Proceedings of the 40th annual simulation symposium (pp. 137–143). Los Alamitos: IEEE Computer Society.

    Chapter  Google Scholar 

  • Illmann, T., Weber, M., Martens, A., & Seitz, A. (2000). A pattern-oriented design of a web-based and case-oriented multimedia training system in medicine. In Proceedings of the 4th world conference on integrated design and process technology, Dallas, USA.

    Google Scholar 

  • Jameson, A. (1996). Numerical uncertainty management in user and student modeling: An overview of systems and issues. User Modeling and User-Adapted Interaction, 5, 193–251 (Special Issue on Numerical Uncertainty Management in User and Student Modeling).

    Article  Google Scholar 

  • Kuenzel, J., & Haemmer, V. (2003). Simulation in university education: The artificial agent PSI as a teaching tool. Simulation – Special Issue on Modeling and Simulation in Teaching and Training, 82(11), 761–767.

    Article  Google Scholar 

  • Lelouche, R. (1999). Intelligent tutoring systems from birth to now. KI-Kuenstliche Intelligenz, 4, 5–11.

    Google Scholar 

  • Maciuszek, D., & Martens, A. (2010). Patterns for the design of educational games. In F. Edvarsen & H. Kulle (Eds.), Educational games: Design, learning and applications. Hauppauge: Nova Science Publishing, Chapter 8, Technologies, IEEE.

    Google Scholar 

  • Maciuszek D., & Martens, A. (2011). Computer role-playing games as an educational game genre: Activities and reflection. In Proceedings of the ECGBL 2011 European conference on game-based learning, Cork, Ireland.

    Google Scholar 

  • Maciuszek, D., & Martens, A. (2012). Integrating cognitive tasks in game activities. In Proceedings of the international conference on advanced learning technologies (ICALT), Rome, Italy.

    Google Scholar 

  • Maciuszek, D., & Martens, A. (2013). Composing game-based learning scenarios by connecting instructional design patterns. In P. Felicia (Ed.), Handbook of research on improving learning and motivation through educational games: Multidisciplinary approaches. Hershey: IGI Global.

    Google Scholar 

  • Martens, A. (2003). Support cognitive processes in intelligent tutoring systems. In Proceedings of the international conference on cognitive modelling ICCM 2003. Poster presentation, Bamberg, Germany.

    Google Scholar 

  • Martens, A. (2005). Modeling of adaptive tutoring processes. In Z. Ma (Ed.), Web-based intelligent e-learning systems: Technologies and applications (pp. 193–215). Hershey/London: Information Science Publishing, Idea Group Inc.

    Chapter  Google Scholar 

  • Martens, A. (2006). Time in the adaptive tutoring process model. In M. Ikeda, K. D. Ashlay, & T.-W. Chan (Eds.), Proceedings of the 8th international conference on intelligent tutoring systems 2006 (pp. 134–143). Berlin/Heidelberg: Springer.

    Google Scholar 

  • Martens, A., & Uhrmacher, A. M. (2004). A formal tutoring process model for intelligent tutoring systems. In R. L. Mantaras & L. Saitta (Eds.), Proceedings of the 16th European artificial intelligence conference ECAI (pp. 124–128). Amsterdam: IOS Press.

    Google Scholar 

  • Martens, A., Bernauer, J., Illmann, T., & Seitz, A. (2001). Docs’n drugs – The virtual poly-clinic, an intelligent tutoring system for web-based and case-oriented training in medicine. In Proceedings of the American Medical Informatics Association conference 2001, AMIA 01 (pp. 433–437), USA.

    Google Scholar 

  • Martens, A., Hambach, S., & Lucke, U. (2009). Multi-perspective cooperation based on boundary objects. In Proceedings of the ICALT 2009, the 9th IEEE international conference on advanced learning technologies (pp. 476–488). Las Vegas: IEEE.

    Chapter  Google Scholar 

  • Mayo, M., Mitrovic, A., & McKenzie, J. (2000). CAPIT: An intelligent tutoring system for capitalization and punctuation. In Proceedings of the international workshop for advanced learning technologies IWALT (pp. 151–157), Palmerston North, New Zealand.

    Google Scholar 

  • Michaud, L., McCoy, K., & Pennington, C. (2000). An intelligent tutoring system for deaf learners of written English. In Proceedings of the 4th international ACM conference on assistive technologies 2000. New York: ACM Press.

    Google Scholar 

  • Oertel, M., Martens, A., & Himmelspach, J. (2008). Teaching and training system plus modeling and simulation – A component based approach. In Proceedings of the EUROSIM, Cambridge, UK.

    Google Scholar 

  • Ruddeck, G., & Martens, A. (2010). Communication patterns in component-based intelligent tutoring systems. In Proceedings of the international conference on advanced learning technology, ICALT, Sousse, Tunisia.

    Google Scholar 

  • Schuemmer, T., & Lukosch, S. (2007). Patterns for computer-mediated interaction. Chichester/Hoboken: Wiley.

    Google Scholar 

  • Szyperski, C. (2002). Component software (Addison Wesley, component software series). New York: ACM Press.

    Google Scholar 

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Authors and Affiliations

  1. Department of Computer Science and Electrical Engineering, Institute of Informatik, University of Rostock, Albert-Einstein-Str. 22, 18059, Rostock, Germany

    Alke Martens

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  1. Alke Martens
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Correspondence to Alke Martens .

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Editors and Affiliations

  1. Faculty of Education, Beijing Normal University, Beijing, China

    Ronghuai Huang

  2. Faculty of Science and Technology, Athabasca University, Athabasca, Alberta, Canada

    Kinshuk

  3. Department of Information Management, National Sun Yat-sen University, Kaohsiung, Taiwan

    Nian-Shing Chen

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Martens, A. (2014). Software Engineering and Modeling in TEL. In: Huang, R., Kinshuk, ., Chen, NS. (eds) The New Development of Technology Enhanced Learning. Lecture Notes in Educational Technology. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38291-8_2

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