Aggregating concept map data to investigate the knowledge of beginning CS students

References

• Albert, D., & Steiner, C. (2005). Empirical validation of concept maps: Preliminary methodological considerations. In P. Goodyear, D. G. Sampson, D. J.-T. Yang, Kinshuk, T. Okamoto, R. Hartley, \ & N.-S. Chen (Eds.), Proceedings of the Fifth International Conference on Advanced Learning Technologies, Kaohsiung, Taiwan, 2005, July 5--8 (pp. 952–953). Los Alamitos, CA: IEEE Computer Society Press. doi: 10.1109/ICALT.2005.135
   Google Scholar
• Ausubel, D. P. (2000). The acquisition and retention of knowledge: A cognitive view. Dordrect: Kluwer Academic Publishers.
   Google Scholar
• Baker, R. S. J. D. (2010). Data mining. In P. Peterson (Ed.), International encyclopedia of education (pp. 112–118). Oxford: Elsevier.
   Google Scholar
• Biswas, G., & Sulcer, B. (2010). Visual exploratory data analysis methods to characterize student progress in intelligent learning environments. 2010 International Conference on Technology for Education (T4E) (pp. 114–121), Mumbai.
   Google Scholar
• Breier, N., & Hubwieser, P. (2002). An information-oriented approach to informatical education. Informatics in Education, 1, 31–42.
   Google Scholar
• Cañas, A. J., Carff, R., Hill, G., Carvalho, M., Arguedas, M., Eskridge, T., ... Carvajal, R. (2005). Concept maps: Integrating knowledge and information visualization. In S.-O. Tergan & T. Keller (Eds.), Knowledge and information visualization, Lecture notes in computer science (Vol. 3426, pp. 205–219). Berlin: Springer. doi: 10.1007/11510154\_11
   Google Scholar
• Cañas, A. J., Hill, G., Carff, R., Suri, N., Lott, J., \ & Gómez, G. (2004). CmapTools: A knowledge modeling and sharing environment. In A. J. Cañas, J. D. Novak, & F. M. González García (Eds.), Concept maps: Theory, methodology, technology, Proceedings of the First International Conference on Concept Mapping (Vol. 1, pp. 125–134), Pamplona.
   Google Scholar
• Cañas, A. J., & Novak, J. D. (2012). Freedom vs. restriction of content and structure during concept mapping – possibilities and limitations for construction and assessment. In A. J. Cañas, J. D. Novak, & J. Vanhear. (Eds.), Concept maps: Theory, methodology, technology, Proceedings of the Fifth International Conference on Concept Mapping (Vol. 2, pp. 247–257), Valletta.
   Google Scholar
• Cooke, N. J. (1994). Varieties of knowledge elicitation techniques. International Journal of Human-Computer Studies, 41, 801–849.
   Web of Science ®Google Scholar
• Dearholt, D. W., & Schvaneveldt, R. W. (1990). Properties of pathfinder netowrks. In R. W. Schvaneveldt. (Ed.), Pathfinder associative networks (pp. 1–30). Norwood, NJ: Ablex Publishing Corporation.
   Google Scholar
• Derbentseva, N., Safayeni, F., & Cañas, A. J. (2007). Concept maps: Experiments on dynamic thinking. Journal of Research in Science Teaching, 44, 448–465. doi: 10.1002/tea.20153
   Web of Science ®Google Scholar
• Freeman, L. C. (1978). Centrality in social networks conceptual clarification. Social Networks, 1, 215–239.
   Web of Science ®Google Scholar
• Gebhardt, M., Mühling, A., Gartmeier, M., & Tretter, T. (2015). Wissen über Inklusion als gedankliches Netz: Vergleich zwischen Studierenden des beruflichen und des sonderpädagogischen Lehramts mithilfe von Concept-Maps. Zeitschrift für Heilpädagogik, 66, 609–622.
   Google Scholar
• Glaser, R., & Bassok, M. (1989). Learning theory and the study of instruction. Annual Review of Psychology, 40, 631–666.
   Web of Science ®Google Scholar
• Goldstone, R. L., & Kersten, A. (2003). Concepts and categorization. In I. B. Weiner (Ed.), Handbook of psychology (Vol. 4, pp. 599–621). Hoboken: John Wiley.
   Google Scholar
• Gouli, E. (2007). Concept mapping in didactics of informatics. assessment as a tool for learning in web-based and adaptive educational environments ( Phd thesis), National and Kapodistrian University of Athens, Athen.
   Google Scholar
• Grundspenkis, J., & Strautmane, M. (2010). Usage of graph patterns for knowledge assessment based on concept maps. Scientific Journal of Riga Technical University. Computer Sciences, 38, 60–71. doi: 10.2478/v10143-009-0005-y
   Google Scholar
• Gurlitt, J., & Renkl, A. (2010). Prior knowledge activation: How different concept mapping tasks lead to substantial differences in cognitive processes, learning outcomes, and perceived self-efficacy. Instructional Science, 38, 417–433. doi: 10.1007/s11251-008-9090-5
   Web of Science ®Google Scholar
• Hoffman, R. R., Shadbolt, N. R., Burton, A. M., & Klein, G. (1995). Eliciting knowledge from experts: A methodological analysis. Organizational Behavior and Human Decision Processes, 62, 129–158. doi: 10.1006/obhd.1995.1039
   Web of Science ®Google Scholar
• Hubwieser, P., & Mühling, A. (2011). What students (should) know about object oriented programming. In K. Sanders, M. E. Caspersen, & A. Clear (Eds.), Proceedings of the Seventh International Workshop on Computing Education Research, Rhode Island, USA, 2011, August 8--9 (pp. 77–84). New York, NY: ACM. doi: 10.1145/2016911.2016929
   Google Scholar
• Keppens, J., & Hay, D. B. (2008). Concept map assessment for teaching computer programming. Computer Science Education, 18, 31–42.
   Google Scholar
• Kern, C., & Crippen, K. J. (2008). Mapping for conceptual change. Science Teacher, 75(6), 32–38.
   Google Scholar
• Kinnebrew, J. S., Segedy, J. R., & Biswas, G. (2014). Analyzing the temporal evolution of students’ behaviors in open-ended learning environments. Metacognition and Learning, 9, 187–215. doi: 10.1007/s11409-014-9112-4
   Web of Science ®Google Scholar
• Koponen, I. T., & Pehkonen, M. (2010). Entropy and energy in characterizing the organization of concept maps in learning science. Entropy, 12, 1653–1672. doi: 10.3390/e12071653
   Web of Science ®Google Scholar
• Kwon, S. Y., & Cifuentes, L. (2009). The comparative effect of individually-constructed vs. collaboratively-constructed computer-based concept maps. Computers & Education, 52, 365–375. doi: 10.1016/j.compedu.2008.09.012
   Web of Science ®Google Scholar
• Larraza-Mendiluze, E., & Garay-Vitoria, N. (2013). Use of concept maps to analyze students’ understanding of the I/O subsystem. In M.-J. Laakso, & Simon (Eds.), Proceedings of the 13th Koli Calling International Conference on Computing Education Research, Koli, Finnland, Koli Calling ’13, 2013, November 14--17 (pp. 67–76). New York: ACM. doi: 10.1145/2526968.2526976
   Google Scholar
• Leake, D. B., Maguitman, A., & Reichherzer, T. (2005). Understanding knowledge models: modeling assessment of concept importance in concept maps. In K. Forbus, D. Gentner, & T. Regier. (Eds.), Proceedings of the Twenty-sixth Annual Conference of the Cognitive Science Society, Chicago, USA, 2004, August 4--7 (pp. 785–800). Mahwah, NJ: Lawrence Erlbaum Associates.
   Google Scholar
• Leake, D. B., Reichherzer, T., Cañas, A. J., Carvalho, M., \ & Eskridge, T. (2004). “Googling” from a concept map: Towards automatic concept-map based query formation. In A. J. Cañas, J. D. Novak, & F. M. González García (Eds.), Concept maps: Theory, methodology, technology, Proceedings of the First International Conference on Concept Mapping (Vol. 1, pp. 409–416), Pamplona.
   Google Scholar
• McClure, J. R., Sonak, B., & Suen, H. K. (1999). Concept map assessment of classroom learning: Reliability, validity, and logistical practicality. Journal of Research in Science Teaching, 36, 475–492.
   Web of Science ®Google Scholar
• Mühling, A. (2014). Investigating knowledge structures in computer science education ( PhD thesis), Technische Universität München, München.
   Google Scholar
• Novak, J. D. (2002). Meaningful learning: The essential factor for conceptual change in limited or inappropriate propositional hierarchies leading to empowerment of learners. Science Education, 86, 548–571. doi: 10.1002/sce.10032
   Web of Science ®Google Scholar
• Novak, J. D. (2010). Learning, creating, and using knowledge: Concept maps as facilitative tools in schools and corporations (2nd ed.). London: Routledge.
   Google Scholar
• Novak, J. D., & Cañas, A. J. (2008). The theory underlying concept maps and how to construct and use them. ( Technical Report IHMC CmapTools 2006–01 Rev 01–2008). Florida.
   Google Scholar
• Novak, J. D., & Cañas, A. J. (2010). The universality and ubiquitousness of concept maps. In J. Sánchez, A. J. Cañas, & J. D. Novak (Eds.), Concept maps: Making learning meaningful (Vol. 1, pp. 1–13). Chile: Universidad de Chile.
   Google Scholar
• R Core Team. (2013). R: A Language and Environment for Statistical Computing, Vienna and Austria. Retrieved from http://www.R-project.org
   Google Scholar
• Rosas, S. R., & Kane, M. (2012). Quality and rigor of the concept mapping methodology: A pooled study analysis. Evaluation and Program Planning, 35, 236–245. doi: 10.1016/j.evalprogplan.2011.10.003
   PubMed Web of Science ®Google Scholar
• Ruiz-Primo, M. A., & Shavelson, R. J. (1996). Problems and issues in the use of concept maps in science assessment. Journal of Research in Science Teaching, 33, 569–600.
   Web of Science ®Google Scholar
• Sanders, K., Boustedt, J., Eckerdal, A., McCartney, R., Moström, J. E., Thomas, L., & Zander, C. (2008). Student understanding of object-oriented programming as expressed in concept maps. ACM Inroads, 40, 332–336.
   Google Scholar
• Sousa, D. A. (2009). How the brain learns: A multimedia kit for professional development (3rd ed.). Thousand Oaks, CA: Corwin Press.
   Google Scholar
• Squire, L. R. (1987). Memory and brain. New York, NY: Oxford University Press.
   Google Scholar
• Taricani, E. M., & Clariana, R. B. (2006). A technique for automatically scoring open-ended concept maps. Educational Technology Research and Development, 54, 65–82.
   Web of Science ®Google Scholar
• Trumpower, D. L., Sharara, H., & Goldsmith, T. E. (2010). Specificity of structural assessment of knowledge. The Journal of Technology, Learning, and Assessment, 8, 4–32.
   Google Scholar
• Valerio, A., Leake, D. B., & Cañas, A. J. (2008). Automatic classification of concept maps based on a topological taxonomy and its application to studying features of human-built maps. In A. J. Cañas, P. Reiska, M. Åhlberg, & J. D. Novak (Eds.), Concept mapping: Connecting educators (Vol. 1, pp. 122–129). Estonia: Tallinn University.
   Google Scholar
• Villalon, J. J., & Calvo, R. A. (2008). Concept map mining: A definition and a framework for its evaluation. In Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, Sydney, Australia, 2008, December 9--12 (Vol. 3, pp. 357–360). IEEE. doi: 10.1109/WIIAT.2008.387
   Google Scholar
• Yoo, J. S., & Cho, M.-H. (2012). Mining concept maps to understand university students’ learning. K. Yacef, O. Zaïane, H. Hershkovitz, M. Yudelson, & J. Stamper (Eds.), Proceedings of the 5th International Conference on Educational Data Mining, Chania, Greece, 2012, June 19--21 (pp. 184).
   Google Scholar