nach oben

International Journal of Computer-Supported Collaborative Learning

Erschienen in:

02.05.2019

Guiding collaborative revision of science explanations

verfasst von: Libby Gerard, Ady Kidron, Marcia C. Linn

Erschienen in: International Journal of Computer-Supported Collaborative Learning | Ausgabe 3/2019

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

This paper illustrates how the combination of teacher and computer guidance can strengthen collaborative revision and identifies opportunities for teacher guidance in a computer-supported collaborative learning environment. We took advantage of natural language processing tools embedded in an online, collaborative environment to automatically score student responses using human-designed knowledge integration rubrics. We used the automated explanation scores to assign adaptive guidance to the students and to provide real-time information to the teacher on students’ learning. We study how one teacher customizes the automated guidance tools and incorporates it with her in-class monitoring system to guide 98 student pairs in meaningful revision of two science explanations embedded in an online plate tectonics unit. Our study draws on video and audio recordings of teacher-student interactions during instruction as well as on student responses to pretest, embedded and posttest assessments. The findings reveal five distinct strategies the teacher used to guide student pairs in collaborative revision. The teacher’s strategies draw on the automated guidance to personalize guidance of student ideas. The teacher’s guidance system supported all pairs to engage in two rounds of revision for the two explanations in the unit. Students made more substantial revisions on posttest than on pretest yet the percentage of students who engaged in revision overall remained small. Results can inform the design of teacher professional development for guiding student pairs in collaborative revision in a computer-supported environment.

Vorheriger Artikel What information should CSCL teacher dashboards provide to help teachers interpret CSCL situations?

Nächster Artikel Supporting classroom orchestration with real-time feedback: A role for teacher dashboards and real-time agents

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Berland, L. K., & Reiser, B. J. (2011). Classroom communities' adaptations of the practice of scientific argumentation. Science Education, 95(2), 191–216.CrossRef

Berland, L. K., Schwarz, C. V., Krist, C., Kenyon, L., Lo, A. S., & Reiser, B. J. (2016). Epistemologies in practice: Making scientific practices meaningful for students. Journal of Research in Science Teaching, 53(7), 1082–1112. https://doi.org/10.1002/tea.21257.CrossRef

Black, P., & Wiliam, D. (1995). Meanings and consequences: A basis for distinguishing formative and summative functions of assessment? British Educational Research Journal, 22(5), 537–548.

Brownell, S. E., Price, J. V., & Steinman, L. (2013). Science communication to the general public: Why we need to teach undergraduate and graduate students this skill as part of their Formal Scientific Training. Journal of Undergraduate Neuroscience Education, 12(1), E6–E10.

Chen, J., Wang, M., Kirschner, P. A., & Chin-Chung, T. (2018). The role of collaboration, computer use, learning environments, and supporting strategies in CSCL: A meta-analysis. Review of Educational Research, 88, 1082–1112. https://doi.org/10.3102/0034654318791584.CrossRef

Clark, H. H., & Chase, W. G. (1972). On the process of comparing sentences against pictures. Cognitive Psychology, 3(3), 472–517. https://doi.org/10.1016/0010-0285(72)90019-9.CrossRef

Clark, D. B., & Sampson, V. (2008). Assessing dialogic argumentation in online environments to relate structure, grounds, and conceptual quality. Journal of Research in Science Teaching, 45(3), 293–321.CrossRef

Cohen, E. G. (1994a). Restructuring the classroom: Conditions for productive small groups. Review of Educational Research, 64(1), 1–35.CrossRef

Cohen, E. G. (1994b). Designing Groupwork strategies for Heterogenous classrooms. New York: Teachers College Press.

Cohen, M., & Riel, M. (1989). The effect of distant audiences on Students' writing. American Educational Research Journal, 26(2), 143–159.CrossRef

Crawford, L., Lloyd, S., & Knoth, K. (2008). Analysis of student revisions on a state writing test. Assessment for Effective Intervention, 33(2), 108–119. https://doi.org/10.1177/1534508407311403.CrossRef

diSessa, A. A. (2006). A history of conceptual change research: Threads and fault lines. In K. Sawyer (Ed.), The Cambridge handbook of the learning sciences (pp. 265–282). New York: Cambridge University Press.

Donnelly, D. F., Linn, M. C., & Ludvigsen, S. (2014). Impacts and characteristics of computer-based science inquiry learning environments for precollege students. Review of Educational Research, 20(10), 1–37. https://doi.org/10.3102/0034654314546954.CrossRef

Feynman, R. P., Leighton, R., & Hutchings, E. (1985). "Surely you're joking, Mr. Feynman!" : Adventures of a curious character. New York: W.W. Norton.

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.CrossRef

Gerard, L. F., & Linn, M. C. (2016). Using automated scores of student essays to support teacher guidance in classroom inquiry. Journal of Science Teacher Education, 27(1), 111–129. https://doi.org/10.1007/s10972-016-9455-6.CrossRef

Gerard, L. F., Ryoo, K., McElhaney, K., Liu, L., Rafferty, A. N., & Linn, M. C. (2015). Automated guidance for student inquiry. Journal of Educational Psychology, 108(1), 60–81.CrossRef

Gerard, L. F., Linn, M. C., & Madhok, J. (2016). Examining the impacts of annotation and automated guidance on essay revision and science learning. In C.-K. Looi, J. Polman, U. Cress, & P. Reimann (Eds.), International conference of the learning sciences (Vol. 1, pp. 394–401). Singapore: International Society of the Learning Sciences.

Hamalainen, R., & Vahasantanen, K. (2011). Theoretical and pedagogical perspectives on orchestrating creativity and collaborative learning. Educational Research Review, 6(3), 169–184.CrossRef

Harrison, E. J., Gerard, L. F., & Linn, M. C. (2018). Encouraging revision of scientific ideas with critique in an online genetics unit. Paper presented at the rethinking learning in the digital age: Making the learning sciences count, 13th international conference of the learning of the learning sciences (ICLS), London.

Ingulfsen, L., Furberg, A., & Stromme, T. (2018). Students’ engagement in real-time graphs in CSCL settings: Scrutinizing the role of teacher support. International Journal of Computer-Supported Collaborative Learning, 13(4), 365–390.CrossRef

Isaacson, W. (2017). Leonardo da Vinci. New York: Simon & Schuster.

Jimenenez-Aleixandre, M. P., Rodriguez, A. B., & Duschl, R. A. (2000). “Doing the lesson” or “doing science”: Argument in high school genetics. Science Education, 84(3), 757–792.CrossRef

Kali, Y., Linn, M. C., & Roseman, J. E. (Eds.). (2008). Designing coherent science education: Implications for curriculum, instruction, and policy. New York: Teachers College Press.

Lakkala, M., Lallimo, J., & Hakkarainen, K. (2005). Teachers’ pedagogical designs for technology-supported collective inquiry: A national case study. Computers & Education, 45, 337–356. https://doi.org/10.1016/j.compedu.2005.04.010.CrossRef

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

Liu, O. L., Lee, H. S., Hofstetter, C., & Linn, M. C. (2008). Assessing knowledge integration in science: Construct, measures and evidence. Educational Assessment, 13(1), 33–55.CrossRef

Liu, O. L., Lee, H.-S., & Linn, M. C. (2011). Measuring knowledge integration: A four year study. Journal of Research in Science Teaching, 48(9), 1079–1107.CrossRef

Liu, O. L., Ryoo, K., Linn, M. C., Sato, E., & Svihla, V. (2015). Measuring knowledge integration learning of energy topics: A two-year longitudinal study. International Journal of Science Education, 37(7), 1044–1066. https://doi.org/10.1080/09500693.2015.1016470.CrossRef

Liu, O. L., Rios, J. A., Heilman, M., Gerard, L. F., & Linn, M. C. (2016). Validation of automated scoring of science assessments. Journal of Research in Science Teaching, 53(2), 215–233. https://doi.org/10.1002/tea.21299.CrossRef

Matuk, C. F., & Linn, M. C. (2015). Examining the real and perceived impacts of a public idea repository on literacy and science inquiry. In O. Lindwall, P. Hakkinen, T. Koschmann, P. Tchounikine, & S. Ludvigsen (Eds.), Exploring the Material Conditions of Learning: The Computer Supported Collaborative Learning (CSCL) Conference (Vol. 1, pp. 150–157). Gothenburg: International Society of the Learning Sciences.

Matuk, C., & Linn, M. C. (2018). Why and how do middle school students exchange ideas during science inquiry. International Journal of Computer-Supported Collaborative Learning, 13, 1–37. https://doi.org/10.1007/s11412-018-9282-1.CrossRef

Mercier, H., & Sperber, D. (2011). Why do humans reason? Arguments for an argumentative theory. Behavioral and Brain Sciences, 34, 57–111. https://doi.org/10.1017/S0140525X10000968.CrossRef

Perin, D., Lauterbach, M., Raufman, J., & Santikian Kalamkarian, H. (2016). Text-based writing of low-skilled adults: Relation to comprehension, self-efficacy and teacher judgments. Reading and Writing: An Interdisciplinary Journal, 30(4), 887–915. https://doi.org/10.1007/s11145-016-9706-0.CrossRef

Raes, A., Schellens, T., & De Wever, B. (2013). Web-based collaborative inquiry to bridge gaps in secondary science education. Journal of the Learning Sciences, 22, 316–347. https://doi.org/10.1080/10508406.2013.836656.CrossRef

Reiser, B. J. (2012). A framework for K-12 science education: Practices, crosscutting concepts, and core ideas: National Research Council, board on science education, division of behavioral and social sciences and education. Washington, DC: National Academies Press.

Roshcelle, J., Dimitriadis, Y., & Hoppe, U. (2013). Classroom orchestration: Synthesis. Computers and Education, 69, 523–526.CrossRef

Ruiz-Primo, M. A., & Furtak, E. M. (2007). Exploring teachers’ informal formative assessment practices and students’ understanding in the context of scientific inquiry. Journal of Research in Science Teaching, 44(1), 57–84.CrossRef

Ruiz-Primo, M. A., & Li, M. (2013). Analyzing Teachers' feedback practices in response to Students' work in science classrooms. Applied Measurement in Education, 26(3), 163–175. https://doi.org/10.1080/08957347.2013.793188.CrossRef

Ryoo, K., Bedell, K., & Swearingen, A. (2018). Promoting linguistically diverse students’ short-term and long-term understanding of chemical phenomena using visualizations. Journal of Science Education and Technology, 27(6), 508–522.CrossRef

Sharples, M. (2013). Shared orchestration within and beyond the classroom. Computers and Education, 69, 504–506.CrossRef

Sinha, S., Rogat, T. K., Adams-Wiggins, K. R., & Hmelo-Silver, C. E. (2015). Collaborative group engagement in a computer-supported inquiry learning environment. International Journal of Computer Supported Collaborative Learning, 10(3), 273–307.CrossRef

Sisk-Hilton, S. (2009). Teaching and Learning in Public: Professional Development Through Shared Inquiry. Columbia: Teachers College Press.

Songer, N. B. (1996). Exploring learning opportunities in coordinated network-enhanced classrooms - a case of kids as global scientists. Journal of the Learning Sciences, 5(4), 297–327.CrossRef

Sun, D., Looi, C.-K., & Xie, W. (2017). Learning with collaborative inquiry: A science learning environment for secondary students. Technology, Pedagogy and Education, 26(3).

Tansomboon, C., Gerard, L. F., Vitale, J. M., & Linn, M. C. (2017). Designing automated guidance to promote productive revision of science explanations. International Journal of Artificial Intelligence in Education, 27(4), 729–757.CrossRef

Thagard, P. (1992). Conceptual Revolutions. Princeton: Princeton University Press.CrossRef

Tissenbaum, M., Lui, M., & Slotta, J. D. (2012). Smart Classrooms for Knowledge Communities: Learning Across Contexts in Secondary Science Paper presented at the American Educational Research Association annual meeting, Vancouver, BC.

van Zee, E. H., & Minstrell, J. (1997). Reflective discourse: Developing shared understandings in a physics classroom. International Journal of Science Education, 19(2), 209–228.CrossRef

Vitale, J. M., Lai, K., & Linn, M. C. (2015). Taking advantage of automated assessment of student-constructed graphs in science. Journal of Research in Science Teaching, 52(10), 1426–1450. https://doi.org/10.1002/tea.21241.CrossRef

Williams, M., Linn, M. C., Ammon, P., & Gearhart, M. (2004). Learning to teach inquiry science in a technology-based environment: A case study. Journal of Science Education and Technology, 13(2), 189–206.CrossRef

Zertuche, A. N., Gerard, L. F., & Linn, M. C. (2012). How do openers contribute to student learning? International Electronic Journal of Elementary Education, 5(1), 79–92.

Zheng, B., Lawrence, J., Warschauer, M., & Lin, C.-H. (2015). Middle school Students' writing and feedback in a cloud-based classroom environment. Technology, Knowledge and Learning, 20(2), 201–229.CrossRef

Titel: Guiding collaborative revision of science explanations
verfasst von: Libby Gerard
Ady Kidron
Marcia C. Linn
Publikationsdatum: 02.05.2019
Verlag: Springer US
Erschienen in: International Journal of Computer-Supported Collaborative Learning / Ausgabe 3/2019
Print ISSN: 1556-1607
Elektronische ISSN: 1556-1615
DOI: https://doi.org/10.1007/s11412-019-09298-y

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"

Weitere Artikel der Ausgabe 3/2019

Correction to: A handheld classroom dashboard: teachers’ perspectives on the use of real-time collaborative learning analytics

Supporting classroom orchestration with real-time feedback: A role for teacher dashboards and real-time agents

A handheld classroom dashboard: Teachers’ perspectives on the use of real-time collaborative learning analytics

Real-time orchestrational technologies in computer-supported collaborative learning: an introduction to the special issue

What information should CSCL teacher dashboards provide to help teachers interpret CSCL situations?

It is not either or: An initial investigation into combining collaborative and individual learning using an ITS