Visualising the temporal aspects of collaborative inquiry-based learning processes in technology-enhanced physics learning

References

• Alfieri, L., Brooks, P. J., Aldrich, N. J., & Tenenbaum, H. R. (2011). Does discovery-based instruction enhance learning? Journal of Educational Psychology, 103(1), 1–18. doi: 10.1037/a0021017
   Web of Science ®Google Scholar
• Arthurs, L. A., & Kreager, B. Z. (2017). An integrative review of in-class activities that enable active learning in college science classroom settings. International Journal of Science Education, 39(15), 2073–2091. doi: 10.1080/09500693.2017.1363925
   Web of Science ®Google Scholar
• Balgopal, M. M., Casper, A. M. A., Atadero, R. A., & Rambo-Hernandez, K. (2017). Responses to different types of inquiry prompts: College students’ discourse, performance, and perceptions of group work in an engineering class. International Journal of Science Education, 39(12), 1625–1647. doi: 10.1080/09500693.2017.1346847
   Web of Science ®Google Scholar
• Bell, T., Urhahne, D., Schanze, S., & Ploetzner, R. (2010). Collaborative inquiry learning: Models, tools, and challenges. International Journal of Science Education, 32(3), 349–377. doi: 10.1080/09500690802582241
   Web of Science ®Google Scholar
• Blikstein, P., & Worsley, M. (2016). Multimodal learning analytics and education data mining: Using computational technologies to measure complex learning tasks. Journal of Learning Analytics, 3(2), 220–238. doi: 10.18608/jla.2016.32.11
   Google Scholar
• Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. doi: 10.1191/1478088706qp063oa
   Google Scholar
• Bush, D., Sieber, R., Seiler, G., & Chandler, M. (2017). University-level teaching of anthropogenic global climate change (AGCC) via student inquiry. Studies in Science Education, 53(2), 113–136. doi: 10.1080/03057267.2017.1319632
   Web of Science ®Google Scholar
• Çelik, H., & Pektaş, H. (2017). Graphic comprehension and interpretation skills of preservice teachers with different learning approaches in a technology-aided learning environment. International Journal of Science and Mathematics Education, 15(1), 1–17. doi: 10.1007/s10763-015-9667-9
   Web of Science ®Google Scholar
• Chang, C.-J., Chang, M.-H., Liu, C.-C., Chiu, B.-C., Fan Chiang, S.-H., Wen, C.-T., … Chai, C.-S. (2017). An analysis of collaborative problem-solving activities mediated by individual-based and collaborative computer simulations. Journal of Computer Assisted Learning, 33(6), 649–662. doi: 10.1111/jcal.12208
   Web of Science ®Google Scholar
• de Jong, T., & Ferguson-Hessler, M. (1996). Types and qualities of knowledge. Educational Psychologist, 31(2), 105–113. doi: 10.1207/s15326985ep3102_2
   Web of Science ®Google Scholar
• De Wever, B., Hämäläinen, R., Voet, M., & Gielen, M. (2015). A wiki task for first-year university students: The effect of scripting students’ collaboration. The Internet and Higher Education, 25, 37–44. doi: 10.1016/j.iheduc.2014.12.002
   Web of Science ®Google Scholar
• Ding, L., Wei, X., & Mollohan, K. (2016). Does higher education improve student scientific reasoning skills? International Journal of Science and Mathematics Education, 14(4), 619–634. doi: 10.1007/s10763-014-9597-y
   Web of Science ®Google Scholar
• Freeman, S., Eddy, S. L., McDonoug, M., Smith, M. K., Okoroafor, N., Jordt, H., & Wenderoth, M. P. (2014). Active learning increases student performance in science, engineering, and mathematics. Proceedings of the National Academy of Sciences, 111(23), 8410–8415. doi: 10.1073/pnas.1319030111
   PubMed Web of Science ®Google Scholar
• Hämäläinen, R., & Arvaja, M. (2009). Scripted collaboration and group-based variations in a higher education CSCL context. Scandinavian Journal of Educational Research, 53(1), 1–16. doi: 10.1080/00313830802628281
   Web of Science ®Google Scholar
• Hämäläinen, R., & Vähäsantanen, K. (2011). Theoretical and pedagogical perspectives on orchestrating creativity and collaborative learning. Educational Research Review, 6(3), 169–184. doi: 10.1016/j.edurev.2011.08.001
   Web of Science ®Google Scholar
• Hmelo-Silver, C., Jeong, C., Faulkner, R., & Hartley, K. (2017). Computer-supported collaborative learning in STEM domains: Towards a meta-synthesis. Proceedings of the 50th Hawaii International Conference on System Sciences.
   Google Scholar
• Holmes, N. G., Olsen, J., Thomas, J. L., & Wieman, C. E. (2017). Value added or misattributed? A multi-institution study on the educational benefit of labs for reinforcing physics content. Physical Review Physics Education Research, 13(1), 010129-1–010129-12.
   Google Scholar
• Jensen, J. L., & Lawson, A. (2011). Effects of collaborative group composition and inquiry instruction on reasoning gains and achievement in undergraduate biology. CBE – Life Science Education, 10(1), 64–73. doi: 10.1187/cbe.10-07-0089
   PubMed Web of Science ®Google Scholar
• Jeong, H., & Hmelo-Silver, C. E. (2010). Productive use of learning resources in an online problem-based learning environment. Computers in Human Behavior, 26(1), 84–99. doi: 10.1016/j.chb.2009.08.001
   Web of Science ®Google Scholar
• Kapur, M. (2011). Temporality matters: Advancing a method for analyzing problem-solving processes in a computer-supported collaborative environment. International Journal of Computer-Supported Collaborative Learning, 6(1), 39–56. doi: 10.1007/s11412-011-9109-9
   Web of Science ®Google Scholar
• Kapur, M., Voiklis, J., & Kinzer, C. K. (2008). Sensitivities to early exchange in synchronous computer-supported collaborative learning (CSCL) groups. Computers & Education, 51(1), 54–66. doi: 10.1016/j.compedu.2007.04.007
   Web of Science ®Google Scholar
• Klette, K. (2009). Challenges in strategies for complexity reduction in video studies. Experiences from the PISA+ study: A video study of teaching and learning in Norway. In T. Janik & T. Seidel (Eds.), The power of video studies in investigating teaching and learning in the classroom (pp. 61–82). New York, NY: Waxmann Publishing.
   Google Scholar
• Knight, R. D. (2014). Physics for scientists and engineers: A strategic approach with modern physics (3rd ed.). Harlow: Pearson Education.
   Google Scholar
• Kobbe, L., Weinberger, A., Dillenbourg, P., Harrer, A., Hämäläinen, R., Häkkinen, P., & Fischer, F. (2007). Specifying computer-supported collaboration scripts. International Journal of Computer-Supported Collaborative Learning, 2(2), 211–224. doi: 10.1007/s11412-007-9014-4
   Web of Science ®Google Scholar
• Koretsky, M. D., Brooks, B. J., & Higgins, A. Z. (2016). Written justifications to multiple-choice concept questions during active learning in class. International Journal of Science Education, 38(11), 1747–1765. doi: 10.1080/09500693.2016.1214303
   Web of Science ®Google Scholar
• Koskinen, P., Lämsä, J., Maunuksela, J., Hämäläinen, R., & Viiri, J. (2018). Primetime learning: Collaborative and technology-enhanced studying with genuine teacher presence. International Journal of STEM Education, 5(20), 1–13.
   Google Scholar
• Krathwohl, D. R. (2002). A revision of Bloom’s taxonomy: An overview. Theory into Practice, 41(4), 212–218. doi: 10.1207/s15430421tip4104_2
   Web of Science ®Google Scholar
• Krippendorff, K. (2004). Content analysis: An introduction to its methodology (2nd ed.). Thousand Oaks, CA: Sage.
   Google Scholar
• Lazonder, A., & Harmsen, R. (2016). Meta-analysis of inquiry-based learning: Effects of guidance. Review of Educational Research, 86(3), 681–718. doi: 10.3102/0034654315627366
   Web of Science ®Google Scholar
• Leinonen, R., Asikainen, M. A., & Hirvonen, P. E. (2017). Peer discussions in lecture-based tutorials in introductory physics. Physical Review Physics Education Research, 13(1), 010114-1–010114-13. doi: 10.1103/PhysRevPhysEducRes.13.010114
   Web of Science ®Google Scholar
• Matthews, K. E., Firn, J., Schmidt, S., & Whelan, K. (2017). A comparative study on student perceptions of their learning outcomes in undergraduate science degree programmes with differing curriculum models. International Journal of Science Education, 39(6), 742–760. doi: 10.1080/09500693.2017.1304672
   Web of Science ®Google Scholar
• Mercer, N. (2008). The seeds of time: Why classroom dialogue needs a temporal analysis. Journal of the Learning Sciences, 17(1), 33–59. doi: 10.1080/10508400701793182
   Web of Science ®Google Scholar
• Nehring, A., Nowak, K. H., zu Belzen, A. U., & Tiemann, R. (2015). Predicting students’ skills in the context of scientific inquiry with cognitive, motivational, and sociodemographic variables. International Journal of Science Education, 37(9), 1343–1363. doi: 10.1080/09500693.2015.1035358
   Web of Science ®Google Scholar
• Pedaste, M., Mäeots, M., Siiman, L. A., de Jong, T., van Riesen, S. A. N., Kamp, E. T., … Tsourlidaki, E. (2015). Phases of inquiry-based learning: Definitions and the inquiry cycle. Educational Research Review, 14, 47–61. doi: 10.1016/j.edurev.2015.02.003
   Web of Science ®Google Scholar
• Perkins, K., Adams, W., Dubson, M., Finkelstein, N., Reid, S., Wieman, C., & LeMaster, R. (2006). Phet: Interactive simulations for teaching and learning physics. The Physics Teacher, 44(1), 18–23. doi: 10.1119/1.2150754
   Google Scholar
• Rau, M. A., Bowman, H. E., & Moore, J. W. (2017). An adaptive collaboration script for learning with multiple visual representations in chemistry. Computers & Education, 109, 38–55. doi: 10.1016/j.compedu.2017.02.006
   Web of Science ®Google Scholar
• Sins, P. H. M., Savelsbergh, E. R., van Joolingen, W. R., & van Hout-Wolters, B. H. A. M. (2011). Effects of face-to-face versus chat communication on performance in a collaborative inquiry modeling task. Computers & Education, 56(2), 379–387. doi: 10.1016/j.compedu.2010.08.022
   Web of Science ®Google Scholar
• Stahl, G. (2017). Group practices: A new way of viewing CSCL. International Journal of Computer-Supported Collaborative Learning, 12(1), 113–126. doi: 10.1007/s11412-017-9251-0
   Web of Science ®Google Scholar
• Summers, M., & Volet, S. (2010). Group work does not necessarily equal collaborative learning: Evidence from observations and self-reports. European Journal of Psychology of Education, 25(4), 473–492. doi: 10.1007/s10212-010-0026-5
   Web of Science ®Google Scholar
• Taub, R., Armoni, M., Bagno, E., & Ben-Ari, M. (2015). The effect of computer science on physics learning in a computational science environment. Computers & Education, 87, 10–23. doi: 10.1016/j.compedu.2015.03.013
   Web of Science ®Google Scholar
• Thompson, K., Ashe, D., Carvalho, L., Goodyear, P., Kelly, N., & Parisio, M. (2013). Processing and visualizing data in complex learning environments. American Behavioral Scientist, 57(10), 1401–1420. doi: 10.1177/0002764213479368
   Web of Science ®Google Scholar
• Wagh, A., Cook-Whitt, K., & Wilensky, U. (2017). Bridging inquiry-based science and constructionism: Exploring the alignment between students tinkering with code of computational models and goals of inquiry. Journal of Research in Science Teaching, 54(5), 615–641. doi: 10.1002/tea.21379
   Web of Science ®Google Scholar
• Wang, H., Duh, H., Li, N., Lin, T., & Tsai, C. (2014). An investigation of university students’ collaborative inquiry learning behaviors in an augmented reality simulation and a traditional simulation. Journal of Science Education and Technology, 23(5), 682–691. doi: 10.1007/s10956-014-9494-8
   Web of Science ®Google Scholar
• Williams, G., & Clement, J. (2015). Identifying multiple levels of discussion-based teaching strategies for constructing scientific models. International Journal of Science Education, 37(1), 82–107. doi: 10.1080/09500693.2014.966257
   Web of Science ®Google Scholar