Nothing Special   »   [go: up one dir, main page]
Skip to main content
Springer Nature Link
Log in

Students’ engagement with real-time graphs in CSCL settings: scrutinizing the role of teacher support

  • Published:
International Journal of Computer-Supported Collaborative Learning Aims and scope Submit manuscript

Abstract

This paper reports on a study of teacher support in experimental computer-supported collaborative learning (CSCL) settings where students engage with graphs in real-time labs within the context of school science. Real-time labs are digital devices and software connected to student-controlled sensors or probes that can measure and visualize data graphically. The empirical setting was a science project about ocean acidification (OA) where lower secondary school students conducted measurements of the pH value of water with increased concentrations of CO2. The analytical focus is on student–teacher interaction during group-work activities where the students carried out, reviewed and reported on the real-time lab experiment. The analyses show that students needed additional support from the teacher in interpreting the real-time graphs and in making connections between the graphic representation, the practical undertakings of the experiment and the underlying scientific phenomena. Most importantly, the study demonstrates the complexity of teacher support in CSCL settings and how this type of support intersects with the support provided by digital resources, peer collaboration and applied instructional design.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

Notes

  1. https://padlet.com/

  2. https://www.pasco.com/

  3. https://www.pasco.com/sparkvue/

References

  • Adams, D. D., & Shrum, J. W. (1990). The effects of microcomputer-based laboratory exercises on the acquisition of line graph construction and interpretation skills by high school biology students. Journal of Research in Science Teaching, 27(8), 777–787.

    Article  Google Scholar 

  • Ainsworth, S. (2006). DeFT: A conceptual framework for considering learning with multiple representations. Learning and Instruction, 16(3), 183–198.

    Article  Google Scholar 

  • Ares, N., Stroup, W. M., & Schademan, A. R. (2009). The power of mediating artifacts in group-level development of mathematical discourses. Cognition and Instruction, 27(1), 1–24.

    Article  Google Scholar 

  • Arnseth, H. C., & Krange, I. (2016). What happens when you push the button? Analyzing the functional dynamics of concept development in computer supported science inquiry. International Journal of Computer-Supported Collaborative Learning, 11(4), 479–502.

    Article  Google Scholar 

  • Bezemer, J., & Kress, G. (2008). Writing in multimodal texts - A social semiotic account of designs for learning. Written Communication, 25(2), 166–195.

    Article  Google Scholar 

  • Derry, S. J., Pea, R. D., Barron, B., Engle, R. A., Erickson, F., Goldman, R., et al. (2010). Conducting video research in the learning sciences: Guidance on selection, analysis, technology, and ethics. Journal of the Learning Sciences, 19(1), 3–53.

    Article  Google Scholar 

  • Dillenbourg, P. (2013). Design for classroom orchestration. Computers & Education, 69, 485–492.

    Article  Google Scholar 

  • Erkens, M., Bodemer, D., & Hoppe, H. U. (2016). Improving collaborative learning in the classroom: Text mining based grouping and representing. International Journal of Computer-Supported Collaborative Learning, 11(4), 387–415.

    Article  Google Scholar 

  • Friedler, Y., & McFarlane, A. E. (1997). Data logging with portable computers, a study of the impact on graphing skills in secondary pupils. Journal of Computers in Mathematics and Science Teaching, 16(4), 527–550.

    Google Scholar 

  • Furberg, A. (2016). Teacher support in computer-supported lab work: Bridging the gap between lab experiments and students’ conceptual understanding. International Journal of Computer-Supported Collaborative Learning, 11(1), 89–113.

    Article  Google Scholar 

  • Furberg, A., Kluge, A., & Ludvigsen, S. (2013). Student sensemaking with science diagrams in a computer-based setting. International Journal of Computer-Supported Collaborative Learning, 8(1), 41–64.

    Article  Google Scholar 

  • Gillen, J., Littleton, K., Twiner, A., Staarman, J. K., & Mercer, N. (2008). Using the interactive whiteboard to resource continuity and support multimodal teaching in a primary science classroom. Journal of Computer Assisted Learning, 24(4), 348–358.

    Article  Google Scholar 

  • Glazer, N. (2011). Challenges with graph interpretation: A review of the literature. Studies in Science Education, 47(2), 183–210.

    Article  Google Scholar 

  • Greiffenhagen, C. (2012). Making rounds: The routine work of teacher during collaborative learning with computers. International Journal of Computer-Supported Collaborative Learning, 7(1), 11–42.

    Article  Google Scholar 

  • Ivarsson, J., Linderoth, J., & Säljö, R. (2009). Representations in practices: A socio-cultural approach to multimodality in reasoning. In J. Carey (Ed.), The Routledge handbook of multimodal analysis (pp. 201–212). London: Routledge.

    Google Scholar 

  • Järvelä, S., Kirschner, P. A., Hadwin, A., Järvenoja, H., Malmberg, J., Miller, M., & Laru, J. (2016). Socially shared regulation of learning in CSCL: Understanding and prompting individual- and group-level shared regulatory activities. International Journal of Computer-Supported Collaborative Learning, 11(3), 263–280.

    Article  Google Scholar 

  • Jefferson, G. (1984). Transcription notation. In J. Atkinson & J. Heritage (Eds.), Structures of social interaction (pp. ix–xvi). New York: Cambridge University Press.

    Google Scholar 

  • Jordan, B., & Henderson, A. (1995). Interaction analysis: Foundations and practice. The Journal of the Learning Sciences, 4(1), 39–103.

    Article  Google Scholar 

  • Jornet, A., & Roth, W. M. (2015). The joint work of connecting multiple (re)presentations in science classrooms. Science Education, 99(2), 378–403.

    Article  Google Scholar 

  • Kelly, G. J., & Crawford, T. (1997). An ethnographic investigation of the discourse processes of school science. Science Education, 81(5), 533–559.

    Article  Google Scholar 

  • Knain, E. (2015). Scientific literacy for participation - A systemic functional approach to analysis of school science discourses. Rotterdam: Sense Publishers.

    Google Scholar 

  • Leinhardt, G., Zaslavsky, O., & Stein, M. K. (1990). Functions, graphs, and graphing: Tasks, learning, and teaching. Review of Educational Research, 60(1), 1–64.

    Article  Google Scholar 

  • Lemke, J. L. (1998). Multiplying meaning: Visual and verbal semiotics in scientific text. In J. R. Martin & R. Veel (Eds.), Reading science (pp. 87–113). London: Routledge.

    Google Scholar 

  • Lindwall, O., & Ivarsson, J. (2011). Difference that make a difference: Contrasting the local enactment of two technologies in a kinematics lab. In S. Ludvigsen, A. Lund, I. Rasmussen, & R. Säljö (Eds.), Learning across sites: New tools, infrastructures and practices (pp. 364–380). London: Routledge.

    Google Scholar 

  • Lindwall, O., & Lymer, G. (2008). The dark matter of lab work: Illuminating the negotiation of disciplined perception in mechanics. Journal of the Learning Sciences, 17, 180–224.

    Article  Google Scholar 

  • Linell, P. (1998). Approaching dialogue: Talk, interaction and contexts in dialogical perspective. Amsterdam: John Benjamins.

    Book  Google Scholar 

  • Linell, P. (2009). Rethinking language, mind and world dialogically: Interactional and contextual theories of human sense-making. Charlotte: Information Age Publishing.

    Google Scholar 

  • Linn, M. C., & Eylon, B.-S. (2011). Science Learning and instruction: Taking advantage of technology to promote knowledge integration. New York: Routledge.

    Book  Google Scholar 

  • Linn, M. C., Layman, J. W., & Nachmias, R. (1987). Cognitive consequences of microcomputer-based laboratories: Graphing skills development. Contemporary Educational Psychology, 12(3), 244–253.

    Article  Google Scholar 

  • Ludvigsen, S. (2016). CSCL towards the future: The second decade of ijCSCL. International Journal of Computer-Supported Collaborative Learning, 11(1), 1–7.

    Article  Google Scholar 

  • Ludvigsen, S., & Arnseth, H. C. (2017). Computer-supported collaborative learning. In E. Duval, M. Sharples, & R. Sutherland (Eds.), Technology enhanced learning (pp. 47–58). Chicago: Springer International Publishing.

    Chapter  Google Scholar 

  • Mäkitalo-Siegl, K., Kohnle, C., & Fischer, F. (2011). Computer-supported collaborative inquiry learning and classroom scripts: Effects on help seeking processes and learning outcomes. Learning and Instruction, 21(2), 257–266.

    Article  Google Scholar 

  • Mercer, N. (2004). Sociocultural discourse analysis: Analyzing classroom talk as a social mode of thinking. Journal of Applied Linguistics, 1(2), 137–168.

    Article  Google Scholar 

  • Mercer, N., & Littleton, K. (2007). Dialogue and the development of children's thinking: A sociocultural approach. London: Routledge.

    Book  Google Scholar 

  • Mitnik, R., Recabarren, M., Nussbaum, M., & Soto, A. (2009). Collaborative robotic instruction: A graph teaching experience. Computers & Education, 53(2), 330–342.

    Article  Google Scholar 

  • Mokros, J. R., & Tinker, R. F. (1987). The impact of microcomputer-based labs on children’s ability to interpret graphs. Journal of Research in Science Teaching, 24(4), 369–383.

    Article  Google Scholar 

  • Mortimer, E. F., & Scott, P. H. (2003). Meaning making in secondary science classrooms. Philadelphia: Open University Press.

    Google Scholar 

  • Nakhleh, M. B. (1994). A review of microcomputer-based labs: How have they affected science learning? Journal of Computers in Mathematics and Science Teaching, 13(4), 368–381.

    Google Scholar 

  • Nemirovsky, R., Tierney, T., & Wright, T. (1998). Body motion and graphing. Cognition and Instruction, 16(2), 119–172.

    Article  Google Scholar 

  • Nicolaou, C. T., Nicolaidou, I., Zacharia, Z., & Constantinou, C. P. (2007). Enhancing fourth graders’ ability to interpret graphical representations through the use of microcomputer-based labs implemented within an inquiry-based activity sequence. Journal of Computers in Mathematics and Science Teaching, 26(1), 75–99.

    Google Scholar 

  • Pea, R. D. (2004). The social and technological dimensions of scaffolding and related theoretical concepts for learning, education, and human activity. Journal of the Learning Sciences, 13(3), 423–451.

    Article  Google Scholar 

  • Roth, W.-M. (1996). Where is the context in contextual word problems? Mathematical practices and production grade 8 students’ answers to story problems. Cognition and Instruction, 14(4), 487–527.

    Article  Google Scholar 

  • Roth, W.-M., & McGinn, M. K. (1997). Graphing: Cognitive ability or practice? Science Education, 81(1), 91–106.

    Article  Google Scholar 

  • Roth, W.-M., & McGinn, M. K. (1998). Inscriptions: Toward a theory of representing as social practice. Review of Educational Research, 68(1), 35–59.

    Article  Google Scholar 

  • Roth, W. M., & Tobin, K. (1997). Cascades of inscriptions and the re-presentation of nature: How numbers, tables, graphs, and money come to re-present a rolling ball. International Journal of Science Education, 19(9), 1075–1091.

    Article  Google Scholar 

  • Säljö, R. (2010). Digital tools and challenges to institutional traditions of learning: Technologies, social memory and the performative nature of learning. Journal of Computer Assisted Learning, 26, 53–64.

    Article  Google Scholar 

  • Säljö, R., & Bergqvist, K. (1997). Seeing the light: Discourse and practice in the optics lab. In L. B. Resnick, R. Säljö, C. Pontecorvo, & B. Burge (Eds.), Discourse, tools and reasoning: Essays on situated cognition (pp. 385–405). Berlin: Springer Berlin Heidelberg.

    Chapter  Google Scholar 

  • Schwarz, B. B., Prusak, N., Swidan, O., Livny, A., Gal, K., & Segal, A. (2018). Orchestrating the emergence of conceptual learning: A case study in a geometry class. International Journal of Computer-Supported Collaborative Learning. https://doi.org/10.1007/s11412-018-9276-z.

    Article  Google Scholar 

  • Strømme, T. A., & Furberg, A. (2015). Exploring teacher intervention in the intersection of digital resources, peer collaboration, and instructional design. Science Education, 99(5), 837–862.

    Article  Google Scholar 

  • Testa, I., Monroy, G., & Sassi, E. (2002). Students’ reading images in kinematics: The case of real-time graphs. International Journal of Science Education, 24(3), 235–256.

    Article  Google Scholar 

  • Tytler, R., Prain, V., Hubber, P., & Waldrip, B. E. (2013). Constructing representations to learn in science. In Rotterdam. Netherlands: Sense Publishers.

    Google Scholar 

  • Urhahne, D., Schanze, S., Bell, T., Mansfield, A., & Holmes, J. (2010). Role of the teacher in computer-supported collaborative inquiry learning. International Journal of Science Education, 32(2), 221–243.

    Article  Google Scholar 

  • van Joolingen, W. R., de Jong, T., & Dimitrakopoulou, A. (2007). Issues in computer supported inquiry learning in science. Journal of Computer Assisted Learning, 23(2), 111–119.

    Article  Google Scholar 

  • Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Cambridge: Harvard University Press.

    Google Scholar 

  • Vygotsky, L. S. (1986). Thought and language. Cambridge: MIT Press.

    Google Scholar 

  • Warwick, P., Mercer, N., & Kershner, R. (2013). “Wait, let’s just think about this”: Using the interactive whiteboard and talk rules to scaffold learning for co-regulation in collaborative science activities. Learning, Culture and Social Interaction, 2(1), 42–51.

    Article  Google Scholar 

  • Wells, G. (1999). Dialogic inquiry. Towards a sociocultural practice and theory of education. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Wertsch, J. V. (1998). Mind as action. New York: Oxford University Press.

    Google Scholar 

  • White, T. (2018). Connecting levels of activity with classroom network technology. International Journal of Computer-Supported Collaborative Learning, 13(1), 93–122.

    Article  Google Scholar 

  • White, T., & Pea, R. (2011). Distributed by design: On the promises and pitfalls of collaborative learning with multiple representations. Journal of the Learning Sciences, 20(3), 489–547.

    Article  Google Scholar 

  • Wu, H.-K., & Krajcik, J. S. (2006). Inscriptional Practices in Two Inquiry-Based Classrooms: A Case Study of Seventh Graders' Use of Data Tables and Graphs. Journal of Research in Science Teaching, 43(1), 63–95.

    Article  Google Scholar 

Download references

Acknowledgements

We would like to thank our colleagues in the research project Representation and Participation in School Science (REDE) and members of the REDE Advisory Board for discussions and comments on earlier drafts that have benefited this article. We also like to thank our colleagues in the research groups TEPEC, MEDIATE and LinCS for their constructive feedback on earlier drafts. We are also grateful to Professor Andreas Lund, Associate Professor Kenneth Silseth and the anonymous reviewers for their valuable contributions. Special thanks are extended to the teachers and students taking part in the REDE project. This research was funded by the Department of Teacher Education and School Research, University of Oslo, and the Research Council of Norway (the FINNUT program, grant number 249872).

Author information

Authors and Affiliations

  1. Department of Teacher Education and School Research, University of Oslo, P.O. Box 1099 Blindern, N-0317, Oslo, Norway

    Line Ingulfsen, Anniken Furberg & Torunn Aanesland Strømme

Authors
  1. Line Ingulfsen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Anniken Furberg
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Torunn Aanesland Strømme
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Line Ingulfsen.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix

Appendix

Table 2 Transcript conventions
Full size table

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ingulfsen, L., Furberg, A. & Strømme, T.A. Students’ engagement with real-time graphs in CSCL settings: scrutinizing the role of teacher support. Intern. J. Comput.-Support. Collab. Learn 13, 365–390 (2018). https://doi.org/10.1007/s11412-018-9290-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11412-018-9290-1

Keywords

Search

Navigation