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Student strategies for categorizing IT-related terms

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Abstract

The ability to categorize concepts is an essential capability for human thinking and action. On the one hand, the investigation of such abilities is the purview of psychology; on the other hand, subject-specific educational research is also of interest, as a number of research works in the field of science education show. For computer science education, no corresponding studies are currently available. However, investigating how learners build categories from a choice of given terms may be useful for several reasons; for example, learners’ perspectives on relations between terms, as well as potential misconceptions, can be detected and made available to educators aiming to improve lesson planning. Therefore, we conducted an empirical study with 490 German students from primary to higher education, in which we presented them with 23 information technology-related terms (such as computer, Facebook, hard drive, virus) on a questionnaire, with the task of assigning these to self-defined categories (and then giving their categories individual names). In the results, we identified a number of potential categorization strategies the participants might have used to categorize the given terms; these include generalization, purpose, place of use, state, part-whole relationships, and association. Recognizing and defining such categorization strategies can help teachers construct learner-adequate concept maps of the domain, which helps foster the elaboration of learners’ knowledge structures in this field. We found that the younger participants used less abstract names for their categories, and observed that some participants had difficulty categorizing some terms (such as robot and 3D).

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References

  • Anderson, J.R. (1991). The adaptive nature of human categorization. Psychological Review, 98(3), 409–429. https://doi.org/10.1037/0033-295X.98.3.409.

    Article  Google Scholar 

  • Anderson, J.R. (2015). Cognitive psychology and its implications, 8th edn. New York: Macmillan Learning.

    Google Scholar 

  • Anderson, J.R., & Betz, J. (2001). A hybrid model of categorization. Psychonomic Bulletin & Review, 8(4), 629–647. https://doi.org/10.3758/BF03196200.

    Article  Google Scholar 

  • Ashcraft, M.H. (1978). Property norms for typical and atypical items from 17 categories: a description and discussion. Memory & Cognition, 6(3), 227–232. https://doi.org/10.3758/BF03197450.

    Article  Google Scholar 

  • Baacke, D. (2005). Die 13- bis 18-Jahrigen:̈ Einführung in die Probleme des Jugendalters, 9th edn. Weinheim: Beltz.

    Google Scholar 

  • Bengston, J.K., & Cohen, S.J. (1979). Concept acquisition and the perception of meaning. Contemporary Educational Psychology, 4(4), 348–365. https://doi.org/10.1016/0361-476X(79)90055-9.

    Article  Google Scholar 

  • Borowski, C, Diethelm, I, Wilken, H. (2016). What children ask about computers, the internet, robots, mobiles, games etc. In Proceedings of the 11th workshop in primary and secondary computing education, WiPSCE ’16 (pp. 72–75). New York: ACM, DOI https://doi.org/10.1145/2978249.2978259, (to appear in print).

  • Brinda, T., Napierala, S., Behler, G.A. (2018). What do secondary school students associate with the digital world?. In Proceedings of the 13th Workshop in Primary and Secondary Computing Education, WiPSCE ’18. http://doi.acm.org/10.1145/3265757.3265763 (pp. 6:1–6:10). New York: ACM, DOI https://doi.org/10.1145/3265757.3265763, (to appear in print).

  • Cao, R., Nosofsky, R.M., Shiffrin, R.M. (2017). The development of automaticity in short-term memory search: Item-response learning and category learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 43 (5), 669–679. https://doi.org/10.1037/xlm0000355.

    Article  Google Scholar 

  • Diethelm, I, Hubwieser, P, Klaus, R. (2012). Students, teachers and phenomena: educational reconstruction for computer science education. In Proceedings of the 12th Koli calling international conference on computing education research, Koli Calling ’12 (pp. 164–173). New York: ACM, DOI https://doi.org/10.1145/2401796.2401823, (to appear in print).

  • Diethelm, I., Brinda, T., Schneider, N. (2017). How pupils classify digital artifacts. In Proceedings of the 12th Workshop on Primary and Secondary Computing Education, WiPSCE ’17 (pp. 99–100). New York: ACM, DOI https://doi.org/10.1145/3137065.3137079, (to appear in print).

  • Donkin, C., Newell, B.R., Kalish, M., Dunn, J.C., Nosofsky, R.M. (2015). Identifying strategy use in category learning tasks: a case for more diagnostic data and models. Journal of Experimental Psychology: Learning, Memory, and Cognition, 41 (4), 933–948. https://doi.org/10.1037/xlm0000083.

    Article  Google Scholar 

  • Edwards, D.J., Pothos, E.M., Perlman, A. (2012). Relational versus absolute representation in categorization. The American Journal of Psychology, 125 (4), 481–497. https://doi.org/10.5406/amerjpsyc.125.4.0481.

    Article  Google Scholar 

  • Gagné, R M. (1985). The Conditions of Learning, 4th edn. New York: Holt, Rinehart & Winston.

    Google Scholar 

  • Gallese, V., & Lakoff, G. (2005). The brain’s concepts: the role of the sensory-motor system in conceptual knowledge. Cognitive Neuropsychology, 22(3-4), 455–479. https://doi.org/10.1080/02643290442000310.

    Article  Google Scholar 

  • Hampton, J.A. (2009). Stability in concepts and evaluating the truth of generic statements - Oxford scholarship. In Pelletier, F J (Ed.) Kinds, things, and stuff: mass terms and generics. New York: Oxford University Press.

    Chapter  Google Scholar 

  • Kattmann, U., & Schmitt, A. (1996). Elementares Ordnen: Wie Schuler̈ Tiere klassifizieren. Zeitschrift für Didaktik der Naturwissenschaften, 2, 21–38.

    Google Scholar 

  • Kattmann, U., Duit, R., Gropengiesser, H., Komorek, M. (1996). Educational reconstruction – bringing together issues of scientific clarification and students‘ conceptions. In Annual meeting of the national association of research in science teaching (pp. 1–19). St. Louis: NARST.

  • Krüger, D, & Burmester, A. (2005). Wie Schuler̈ Pflanzen ordnen. Zeitschrift für Didaktik der Naturwissenschaften, 11, 85–102.

    Google Scholar 

  • Lieto, A., Radicioni, D., Rho, V. (2017). Dual PECCS: a cognitive system for conceptual representation and categorization. Journal of Experimental & Theoretical Artificial Intelligence, 29, 1–24. https://doi.org/10.1080/0952813X.2016.1198934.

    Article  Google Scholar 

  • Mahon, B.Z., & Caramazza, A. (2009). Concepts and categories: a cognitive neuropsychological perspective. Annual Review of Psychology, 60(1), 27–51. https://doi.org/10.1146/annurev.psych.60.110707.163532.

    Article  Google Scholar 

  • Matlin, M.W. (2014). Cognitive psychology, 8th edn. Singapore: Wiley.

    Google Scholar 

  • Mayring, P. (2014). Qualitative content analysis - theoretical foundation, basic procedures and software solution. Klagenfurt: Social Science Open Access Repository.

    Google Scholar 

  • Medienpädagogischer Forschungsverbund Südwest. (2013). KIM-Studie 2012. Tech. rep. MPFS. Stuttgart, Germany.

  • Murphy, G.L. (2004). The big book of concepts. Cambridge: MIT Press.

    Google Scholar 

  • Nguyen, S.P., & Murphy, G.L. (2003). An apple is more than just a fruit: cross-classification in children’s concepts. Child Development, 74(6), 1783–1806. https://doi.org/10.1046/j.1467-8624.2003.00638.x.

    Article  Google Scholar 

  • Piaget, J., & Inhelder, B. (1958). The growth of logical thinking from childhood to adolescence: an essay on the construction of formal operational structures, digital printed in 2007 edn. Abingdon: Routledge.

    Google Scholar 

  • Rosch, E., & Mervis, C.B. (1975). Family resemblances: studies in the internal structure of categories. Cognitive Psychology, 7(4), 573–605. https://doi.org/10.1016/0010-0285(75)90024-9.

    Article  Google Scholar 

  • Rubin, D.B. (2004). Multiple imputation for nonresponse in surveys, wiley classics library edn. Hoboken: Wiley.

    Google Scholar 

  • Smith, E.E., & Medin, D.L. (1981). Categories and concepts, 9th edn. Cambridge: Harvard University Press.

    Book  Google Scholar 

  • Studer, T. (2008). Verschiedene Strategien der Objektkategorisierung: Evidenz durch funktionelle Gehirnasymmetrien. PhD thesis University Konstanz, Konstanz, Germany.

  • Tobinski, D.A. (2017). Kognitive Psychologie: Problemlösen, Komplexität und Gedächtnis. Berlin: Springer https://doi.org/10.1007/978-3-662-53948-4.

    Book  Google Scholar 

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Authors and Affiliations

  1. Computing Education Research Group, University of Duisburg-Essen, Essen, Germany

    Torsten Brinda

  2. Interdisciplinary Centre for Educational Research, University of Duisburg-Essen, Essen, Germany

    Stephan Napierala

  3. Cognitive and Educational Psychology, University of Duisburg-Essen, Essen, Germany

    David Tobinski

  4. Computing Education Research Group, University of Oldenburg, Oldenburg, Germany

    Ira Diethelm

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  1. Torsten Brinda
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  2. Stephan Napierala
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  3. David Tobinski
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  4. Ira Diethelm
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Correspondence to Torsten Brinda.

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Brinda, T., Napierala, S., Tobinski, D. et al. Student strategies for categorizing IT-related terms. Educ Inf Technol 24, 2095–2125 (2019). https://doi.org/10.1007/s10639-019-09861-y

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