Exploring core ideas of procedural understanding in scientific inquiry using educational data mining

References

• Abd-El-Khalick, F., S. BouJaoude, R. Duschl, N. G. Lederman, R. Mamlok-Naaman, A. Hofstein, M. Niaz, D. Treagust, and H.-L. Tuan. 2004. “Inquiry in Science Education: International Perspectives.” Science Education 88 (3): 397–419. doi:10.1002/sce.10118.
   Web of Science ®Google Scholar
• Allie, S., and A. Buffler. 1998. “A Course in Tools and Procedures for Physics I.” American Journal of Physics 66 (7): 613–624. doi:10.1119/1.18915.
   Web of Science ®Google Scholar
• Allie, S., A. Buffler, B. Campbell, and F. Lubben. 1998. “First-year Physics Students’ Perceptions of the Quality of Experimental Measurements.” International Journal of Science Education 20 (4): 447–459. doi:10.1080/0950069980200405.
   Web of Science ®Google Scholar
• Anderson, J. R. 1983. The Architecture of Cognition. Cambridge, MA: Harvard Univ. Press.
   Google Scholar
• Anderson, R. D. 2002. “Reforming Science Teaching: What Research Says About Inquiry.” Journal of Science Teacher Education 13 (1): 1–12. doi:10.1023/A:1015171124982.
   Google Scholar
• Arnold, J. 2015. Die Wirksamkeit von Lernunterstützungen beim Forschenden Lernen: Eine Interventionsstudie zur Förderung des Wissenschaftlichen Denkens in der gymnasialen Oberstufe. Berlin: Logos.
   Google Scholar
• Arnold, J., K. Kremer, and A. Mühling. 2017. “Denn sie wissen nicht, was sie tun« Educational Data Mining zu Schülervorstellungen im Bereich Methodenwissen.” Mathematisch und naturwissenschaftlicher Unterricht (MNU) 70 (5): 334–340.
   Google Scholar
• Arnold, J., K. Kremer, and J. Mayer. 2016. “Concept Cartoons als diskursiv-reflexive Szenarien zur Aktivierung des Methodenwissens beim Forschenden Lernen.” Biologie Lehren und Lernen– Zeitschrift für Didaktik der Biologie 20 (1): 33–43. doi:10.4119/UNIBI/zdb-v1-i20-324.
   Google Scholar
• Arnold, J., K. Kremer, and J. Mayer. 2017. “Scaffolding beim Forschenden Lernen - Eine empirische Untersuchung zur Wirkung von Lernunterstützungen.” Zeitschrift für Didaktik der Naturwissenschaften 23 (1): 21–37. doi:10.1007/s40573-016-0053-0.
   Google Scholar
• Arnold, J. C., K. Kremer, and J. Mayer. 2014. “Understanding Students‘ Experiments—What Kind of Support Do They Need in Inquiry Tasks?” International Journal of Science Education 36 (16): 2719–2749. doi:10.1080/09500693.2014.930209.
   Web of Science ®Google Scholar
• Arnold, J. C., W. J. Boone, K. Kremer, and J. Mayer. 2018. “Assessment of Competencies in Scientific Inquiry through the Application of Rasch Measurement Techniques.” Education Sciences 8 (4): 184. doi:10.3390/educsci8040184.
   Web of Science ®Google Scholar
• Baker, R. S. J. D. 2010. “Data Mining.” In International Encyclopedia of Education, edited by B. McGaw, P. Peterson, and E. Baker, 112–118. Oxford: Elsevier.
   Google Scholar
• Baker, R. S. J. D., and K. Yacef. 2009. “The State of Educational Data Mining in 2009: A Review and Future Visions.” Journal of Educational Data Mining 1 (1): 3–16.
   Google Scholar
• Balakrishnan, R., and K. Ranganathan. 2012. A Textbook of Graph Theory. Heidelberg: Springer.
   Google Scholar
• Baroody, A. J. 2003. “The Development of Adaptive Expertise and Flexibility: The Integration of Conceptual and Procedural Knowledge.” In The Development of Arithmetic Concepts and Skills: Constructing Adaptive Expertise, edited by A. J. Baroody and A. Dowker, 1–33. Mahwah, NJ: Erlbaum.
   Google Scholar
• Bortz, J., and N. Döring. 2006. Forschungsmethoden Und Evaluation Für Human- Und Sozialwissenschaftler [Research Methods and Evaluation for Human and Social Scientists]. Heidelberg: Springer.
   Google Scholar
• Brin, S., and L. Page. 1998. “The Anatomy of a Large-scale Hypertextual Web Search Engine.” Computer Networks and ISDN Systems 30 (1–7): 107–117. doi:10.1016/S0169-7552(98)00110-X.
   Web of Science ®Google Scholar
• Buffler, A., S. Allie, F. Lubben, and B. Campbell. 2001. “The Development of First Year Physics Students’ Ideas about Measurement in Terms of Point and Set Paradigms.” International Journal of Science Education 23 (11): 1137–1156. doi:10.1080/09500690110039567.
   Web of Science ®Google Scholar
• Byrnes, J. P., and B. A. Wasik. 1991. “Role of Conceptual Knowledge in Mathematical Procedural Learning.” Developmental Psychology 27 (5): 777–786. doi:10.1037/0012-1649.27.5.777.
   Web of Science ®Google Scholar
• Chen, Z., and D. Klahr. 1999. “All Other Things Being Equal: Acquisition and Transfer of the Control of Variables Strategy.” Child Development 70 (5): 1098–1120. doi:10.1111/1467-8624.00081.
   PubMed Web of Science ®Google Scholar
• Cox, T. F., and M. A. A. Cox. 2001. Multidimensional Scaling. Boca Raton, FL: Chapman and Hall/CRC.
   Google Scholar
• Glaesser, J., R. Gott, R. Roberts, and B. Cooper. 2009a. “The Roles of Substantive and Procedural Understanding in Open-Ended Science Investigations: Using Fuzzy Set Qualitative Comparative Analysis to Compare Two Different Tasks.” Research in Science Education 39 (4): 595–624. doi:10.1007/s11165-008-9108-7.
   Web of Science ®Google Scholar
• Glaesser, J., R. Gott, R. Roberts, and B. Cooper. 2009b. “Underlying Success in Open-Ended Investigations in Science: Using Qualitative Comparative Analysis to Identify Necessary and Sufficient Conditions.” Research in Science and Technological Education 27 (1): 5–30. doi:10.1080/02635140802658784.
   Google Scholar
• Goldin-Meadow, S., M. W. Alibali, and R. B. Church. 1993. “Transitions in Concept Acquisition: Using the Hand to Read the Mind.” Psychological Review 100 (2): 279–297. doi:10.1037/0033-295X.100.2.279.
   PubMed Web of Science ®Google Scholar
• Gott, R., and R. Roberts. 2003. “Assessment of Performance in Practical Science and Pupils` Attributes.” British Educational Research Association Annual Conference, Heriot-Watt University, Edinburgh.
   Google Scholar
• Gott, R., and R. Roberts. 2008. “Concepts of Evidence and Their Role in Open-ended Practical Investigations and Scientific Literacy; Background to Published Papers.” https://www.dur.ac.uk/resources/education/research/res_rep_short_master_final.pdf
   Google Scholar
• Gott, R., and S. Duggan. 1995. Investigative Work in the Science Curriculum. Buckingham: Open University Press.
   Google Scholar
• Gott, R., and S. Duggan. 1996. “Practical Work: Its Role in the Understanding of Evidence in Science.” International Journal of Science Education 18 (7): 791–806. doi:10.1080/0950069960180705.
   Web of Science ®Google Scholar
• Gott, R., S. Duggan, and R. Roberts. n.d. “Concepts of Evidence.” http://www.dur.ac.uk/rosalyn.roberts/Evidence/CofEv_Gott_et_al.pdf
   Google Scholar
• Hammann, M. 2006. “Fehlerfrei Experimentieren [Error-free experimentation].” Der Mathematische und Naturwissenschaftliche Unterricht 5 (59): 292–299.
   Google Scholar
• Harwood, W. S., R. Reiff, and T. Phillipson. 2002. “Scientists´ Conceptions of Scientific Inquiry: Voices from the Front.” Paper presented at the Proceedings of the Annual International Conference of the Association for the Education of Teachers in Science, Charlotte, NC.
   Google Scholar
• Hasselhorn, M., and A. Gold. 2006. Pädagogische Psychologie: Erfolgreiches Lernen und Lehren [Educational psychology: Successful learning and teaching]. Stuttgart: Kohlhammer.
   Google Scholar
• Hiebert, J., and P. Lefevre. 1986. “Conceptual and Procedural Knowledge in Mathematics: An Introductory Analysis.” In Conceptual and Procedural Knowledge: The Case of Mathematics, edited by J. Hiebert, 1–27. Hillsdale, NJ: Lawrence Erlbaum Associates.
   Google Scholar
• Keogh, B., and S. Naylor. 1998. “Teaching and Learning in Science Using Concept Cartoons.” Primary Science Review.
   Google Scholar
• Kremer, K., and J. Mayer. 2013. “Entwicklung und Stabilität von Vorstellungen über die Natur der Naturwissenschaften.” Zeitschrift für Didaktik der Naturwissenschaften (ZfDN) 19, 77–101.
   Google Scholar
• Kuhn, D., J. Black, A. Keselman, and D. Kaplan. 2000. “The Development of Cognitive Skills to Support Inquiry Learning.” Cognition and Instruction 18 (4): 495–523. doi:10.1207/S1532690XCI1804_3.
   Web of Science ®Google Scholar
• Lederman, J. S., N. G. Lederman, S. A. Bartos, S. L. Bartels, A. A. Meyer, and R. S. Schwartz. 2014. “Meaningful Assessment of Learners‘ Understandings about Scientific inquiry-The Views about Scientific Inquiry (VASI) Questionnaire.” Journal of Research in Science Teaching 51 (1): 65–83. doi:10.1002/tea.21125.
   Web of Science ®Google Scholar
• Lederman, N. G., F. Abd-El-Khalick, R. L. Bell, and R. S. Schwartz. 2002. “Views of Nature of Science Questionnaire: Toward Valid and Meaningful Assessment of Learners‘ Conceptions of Nature of Science.” Journal of Research in Science Teaching 39 (6): 497–521. doi:10.1002/tea.10034.
   Web of Science ®Google Scholar
• Lubben, F., B. Campbell, A. Buffler, and S. Allie. 2001. “Point and Set Reasoning in Practical Science Measurement by Entering University Freshmen.” Science Education 85 (4): 311–327. doi:10.1002/sce.1012.
   Web of Science ®Google Scholar
• Lubben, F., and R. Millar. 1996. “Children’s Ideas about the Reliability of Experimental Data.” International Journal of Science Education 18 (8): 955–968. doi:10.1080/0950069960180807.
   Web of Science ®Google Scholar
• Mayer, J. 2007. “Erkenntnisgewinnung als wissenschaftliches Problemlösen [Knowledge acquisition as scientific problem solving].” In Theorien in Der Biologiedidaktischen Forschung [Theories in Biology Education Research], edited by D. Krüger and H. Vogt, 177–186. Berlin: Springer.
   Google Scholar
• Mayer, J., and H.-P. Ziemek. 2006. “Offenes Experimentieren - Forschendes Lernen Im Biologieunterricht [Open Experimentation– Inquiry Learning in Biology Education].” Unterricht Biologie 317: 4–12.
   Google Scholar
• Millar, R., F. Lubben, R. Gott, and S. Duggan. 1994. “Investigating in the School Science Laboratory: Conceptual and Procedural Knowledge and Their Influence on Performance.” Research Papers in Education 9 (2): 207–248. doi:10.1080/0267152940090205.
   Google Scholar
• Naylor, S., and B. Keogh. 1999. “Constructivism in Classroom: Theory into Practice.” Journal of Science Teacher Education 10 (2): 93–106. doi:10.1023/A:1009419914289.
   Google Scholar
• NRC/National Research Council. 2012. A Framework for K-12 Science Education: Practices, Crosscutting Concepts, and Core Ideas. Washington, DC: National Academies Press.
   Google Scholar
• Osborne, J., S. Collins, M. Ratcliffe, R. Millar, and R. Duschl. 2003. “What “Ideas-about-science” Should Be Taught in School Science? A Delphi Study of the Expert Community.” Journal of Research in Science Teaching 40 (7): 692–720. doi:10.1002/tea.10105.
   Web of Science ®Google Scholar
• R Core Team. 2013. “R: A Language and Environment for Statistical Computing.” Retrieved from http://www.R-project.org
   Google Scholar
• Rittle-Johnson, B., and M. Schneider. 2015. “Developing Conceptual and Procedural Knowledge of Mathematics.” In Oxford Handbook of Numerical Cognition, edited by R. Cohen Kadosh and A. Dowker, 1112–1118. Oxford: University Press.
   Google Scholar
• Roberts, R. 2001. “Procedural Understanding in Biology: The ‘Thinking behind the Doing’.” Journal of Biological Education 35 (3): 113–117. doi:10.1080/00219266.2001.9655758.
   Web of Science ®Google Scholar
• Roberts, R., and P. Johnson. 2015. “Understanding the Quality of Data: A Concept Map for ‘The Thinking behind the Doing’ in Scientific Practice.” The Curriculum Journal 26 (3): 345–369. doi:10.1080/09585176.2015.1044459.
   Web of Science ®Google Scholar
• Roberts, R., and R. Gott. 2003. “Assessment of Biology Investigations.” Journal of Biological Education 37 (3): 114–121. doi:10.1080/00219266.2003.9655865.
   Web of Science ®Google Scholar
• Roberts, R., and R. Gott. 2004. “A Written Test for Procedural Understanding: A Way Forward for Assessment in the UK Science Curriculum?” Research in Science and Technological Education 22 (1): 5–21. doi:10.1080/0263514042000187511.
   Google Scholar
• Schalk, L., P. A. Edelsbrunner, A. Deiglmayr, R. Schumacher, and E. Stern. 2019. “Improved Application of the Control-of-variables Strategy as a Collateral Benefit of Inquiry-based Physics Education in Elementary School.” Learning and Instruction 59: 34–45. doi:10.1016/j.learninstruc.2018.09.006.
   Web of Science ®Google Scholar
• Schneider, M. 2006. Konzeptuelles Und Prozedurales Wissen Als Latente Variablen: Ihre Interaktion Beim Lernen Mit Dezimalbrüchen [Conceptual and Procedural Knowledge as Latent Variables: Their Interaction in Learning with Decimal Fractions]. Berlin: Technische Universität Berlin.
   Google Scholar
• Schwichow, M., S. Croker, C. Zimmerman, T. Höffler, and H. Härtig. 2016. “Teaching the Control-of-variables Strategy: A Meta-analysis.” Developmental Review 39: 37–63. doi:10.1016/j.dr.2015.12.001.
   Web of Science ®Google Scholar
• Star, J. R. 2005. “Reconceptualizing Procedural Knowledge.” Journal for Research in Mathematics Education 36 (5): 404–411.
   Web of Science ®Google Scholar
• Star, J. R., and K. J. Newton. 2009. “The Nature and Development of Experts’ Strategy Flexibility for Solving Equations.” ZDM - the International Journal on Mathematics Education 41 (5): 557–567. doi:10.1007/s11858-009-0185-5.
   Google Scholar
• Star, J.R. 2000. “On the relationship between knowing and doing in procedural learning.” In Fourth international conference of the learning sciences, edited by B. Fishman and S. O’Connor-Divelbiss, 80–86. Mahwah, NJ: Erlbaum.
   Google Scholar
• Tamir, P., R. L. Doran, and Y. Oon Chye. 1992. “Practical Skills Testing in Science.” Studies in Educational Evaluation 18 (3): 263–275. doi:10.1016/0191-491X(92)90001-T.
   Google Scholar
• Winkel, S., F. Petermann, and U. Petermann. 2006. Lernpsychologie [Psychology of Learning]. Paderborn: Verlag Ferdinand Schöningh.
   Google Scholar
• Woolfolk, A. 2008. Pädagogische Psychologie [Educational Psychology]. München: Pearson.
   Google Scholar