Abstract
In this chapter we introduce a computer-based and highly automated measurement technique which enables us to analyze even large sets of data within a few seconds. Closely linked to the demand of new approaches for designing and developing up-to-date learning environments is the necessity of enhancing the design and delivery of assessment systems and automated computer-based diagnostics. In many settings, manual and therefore labor-intensive methods have limits. Hence, following a general assessment framework design, we introduce several automated and integrated tools which have helped us in many studies so far. The technologies which we discuss in this chapter aim at the assessment, re-representation, analysis, and comparison of knowledge. The tools were developed independently and then integrated step by step. The possible applications go beyond the structural and semantic analysis and comparison of knowledge. The tools also allow the development of self-assessment technologies which can be used directly by the learners.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Almond, R. G., Steinberg, L. S., & Mislevy, R. J. (2002). Enhancing the design and delivery of assessment systems: A four process architecture. Journal of Technology, Learning, and Assessment, 1(5), 3–63.
Bonato, M. (1990). Wissenstrukturierung mittels Struktur-Lege-Techniken. Eine grapentheoretische Analyse von Wissensnetzen. Frankfurt am Main: Lang.
Brill, E. (1995). Unsupervised learning of dismabiguation rules for part of speech tagging. Paper presented at the Second Workshop on Very Large Corpora, WVLC-95, Boston.
Cañas, A. J., Hill, R., Carff, R., Suri, N., Lott, J., Eskridge, T., et al. (2004). CmapTools: A knowledge modeling and sharing environment. In A. J. Cañas, J. D. Novak, & F. M. González (Eds.), Concept maps: Theory, methodology, technology, proceedings of the first international conference on concept mapping (pp. 125–133). Pamplona: Universidad Pública de Navarra.
Chartrand, G. (1977). Introductory graph theory. New York: Dover.
Chung, K. L. (1968). A course in probability theory. New York: Harcourt, Brace & World.
Ellson, J., Gansner, E. R., Koutsofios, E., North, S. C., & Woodhull, G. (2003). GraphViz and Dynagraph. Static and dynamic graph drawing tools. Florham Park, NJ: AT&T Labs.
Hannafin, M. J. (1992). Emerging technologies, ISD, and learning environments: Critical perspectives. Educational Technology, Research & Development, 40(1), 49–63.
Harary, F. (1974). Graphentheorie. München: Oldenbourg.
Ifenthaler, D. (2006). Diagnose lernabhängiger Veränderung mentaler Modelle. Entwicklung der SMD-Technologie als methodologisches Verfahren zur relationalen, strukturellen und semantischen Analyse individueller Modellkonstruktionen. Freiburg: FreiDok.
Ifenthaler, D. (2008a). Practical solutions for the diagnosis of progressing mental models. In D. Ifenthaler, P. Pirnay-Dummer, & J. M. Spector (Eds.), Understanding models for learning and instruction. Essays in honor of Norbert M. Seel (pp. 43–61). New York: Springer.
Ifenthaler, D. (2008b). Relational, structural, and semantic analysis of graphical representations and concept maps. Educational Technology Research and Development. doi: 10.1007/s11423-008-9087-4
Ifenthaler, D. (in press-a). Learning and instruction in the digital age. In J. M. Spector, D. Ifenthaler, P. IsaÃas, Kinshuk, & D. G. Sampson (Eds.), Learning and instruction in the digital age: Making a difference through cognitive approaches, technology-facilitated collaboration and assessment, and personalized communications. New York: Springer.
Ifenthaler, D. (in press-b). Model-based feedback for improving expertise and expert performance. Technology, Instruction, Cognition and Learning.
Ifenthaler, D., Masduki, I., & Seel, N. M. (2009). The mystery of cognitive structure and how we can detect it. Tracking the development of cognitive structures over time. Instructional Science. doi: 10.1007/s11251-009-9097-6
Janetzko, D. (1996). Knowledge tracking. A method to analyze cognitive structures. Freiburg: Albert-Ludwigs-Universität.
Janetzko, D. (1999). Statistische Anwendungen im Internet. Daten in Netzumgebungen erheben, auswerten und präsentieren. München: Addison-Wesley.
Johnson-Laird, P. N. (1983). Mental models. Towards a cognitive science of language, inference, and consciousness. Cambridge, UK: Cambridge University Press.
Johnson-Laird, P. N., & Byrne, R. (1991). Deduction. Hove: Lawrence Erlbaum.
Johnson, T. E., Ifenthaler, D., Pirnay-Dummer, P., & Spector, J. M. (2009). Using concept maps to assess individuals and team in collaborative learning environments. In P. L. Torres & R. C. V. Marriott (Eds.), Handbook of research on collaborative learning using concept mapping (pp. 358–381). Hershey, PA: Information Science Publishing.
Jonassen, D. H., & Cho, Y. H. (2008). Externalizing mental models with mindtools. In D. Ifenthaler, P. Pirnay-Dummer & J. M. Spector (Eds.), Understanding models for learning and instruction. Essays in honor of Norbert M. Seel (pp. 145–160). New York: Springer.
Kirschner, P. A. (2004). Introduction to part II of the special issue: Design, development and implementation of electronic learning environments for collaborative learning. Educational Technology, Research & Development, 52(4), 37.
Koper, R., & Tattersall, C. (2004). New directions for lifelong learning using network technologies. British Journal of Educational Technology, 35(6), 689–700.
MySQL AB. (2008). MySQL. The world’s most popular open source database. Retrieved 11.02.2008, from http://www.mysql.com/
Pirnay-Dummer, P. (2006). Expertise und Modellbildung: MITOCAR. Freiburg: FreiDok.
Pirnay-Dummer, P. (2008). Rendevous with a quantum of learning. In D. Ifenthaler, P. Pirnay-Dummer, & J. M. Spector (Eds.), Understanding models for learning and instruction. Essays in honor of Norbert M. Seel (pp. 105–144). New York: Springer.
Pirnay-Dummer, P., Ifenthaler, D., & Spector, J. M. (2009). Highly integrated model assessment technology and tools. Educational Technology Research and Development. doi: 10.1007/s11423-009-9119-8
Seel, N. M. (1991). Weltwissen und mentale Modelle. Göttingen: Hogrefe.
Seel, N. M. (1999). Educational diagnosis of mental models: Assessment problems and technology-based solutions. Journal of Structural Learning and Intelligent Systems, 14(2), 153–185.
Seel, N. M. (2003). Model-centered learning and instruction. Technology, Instruction, Cognition and Learning, 1(1), 59–85.
Spector, J. M., & Koszalka, T. A. (2004). The DEEP methodology for assessing learning in complex domains (Final report to the National Science Foundation Evaluative Research and Evaluation Capacity Building). Syracuse, NY: Syracuse University.
The Apache Software Foundation. (2008). Apache HTTP Server Project. Retrieved 11.02.2008, from http://httpd.apache.org/
The Perl Foundation. (2008). Perl 6. Retrieved 11.02.2008, from http://www.perlfoundation.org/
The PHP Group. (2008). PHP 4.4.8. Retrieved 11.02.2008, from http://www.php.net/
Tittmann, P. (2003). Graphentheorie. Eine anwendungsorientierte Einführung. München: Carl Hanser Verlag.
Tversky, A. (1977). Features of similarity. Psychological Review, 84, 327–352.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer Science+Business Media, LLC
About this chapter
Cite this chapter
Pirnay-Dummer, P., Ifenthaler, D. (2010). Automated Knowledge Visualization and Assessment. In: Ifenthaler, D., Pirnay-Dummer, P., Seel, N. (eds) Computer-Based Diagnostics and Systematic Analysis of Knowledge. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-5662-0_6
Download citation
DOI: https://doi.org/10.1007/978-1-4419-5662-0_6
Published:
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4419-5661-3
Online ISBN: 978-1-4419-5662-0
eBook Packages: Humanities, Social Sciences and LawEducation (R0)