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Small Group Learning

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International Handbook of Psychology Learning and Teaching

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Abstract

Small group learning has been shown to be an effective study method across a variety of disciplines, including psychology. The goal of this chapter is to provide an overview over research on small group learning to explain its potential with respect to teaching and learning psychology. The chapter starts with a description of motivational, neo-Piagetian, neo-Vygotskian, and cognitive theoretical approaches that explain why small group learning can be an effective learning method. Based on evidence that indicates that learners do not always benefit from small group learning, the following section introduces four kinds of scaffolding approaches that have been shown to be powerful means of improving learning processes and outcomes of small group learning. These are (a) the jigsaw method, (b) the peer feedback approach, (c) collaboration scripts, and (d) group awareness tools. Next, the chapter gives an overview over important research issues and related approaches. After that, core findings and current trends in research on small group learning are reported. The chapter ends with a description of the consequences that can be drawn for the teaching and learning of psychology.

Chapter to be published in Zumbach, J., Bernstein, D. A., Narciss, S., & Marsico, G. (in prep.). International Handbook of Psychology Learning and Teaching. New York: Springer.

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References

  • Alqassab, M., Strijbos, J.-W., & Ufer, S. (2018). Training peer-feedback skills on geometric construction tasks: Role of domain knowledge and peer-feedback levels. European Journal of Psychology of Education, 33, 11–30. https://doi.org/10.1007/s10212-017-0342-0.

    Article  Google Scholar 

  • Alrassi, J., & Mortensen, M. (2020). Jigsaw group-based learning in difficult airway management: An alternative way to teach surgical didactics. Journal of Surgical Education, 77(4), 723–725. https://doi.org/10.1016/j.jsurg.2020.02.003.

    Article  Google Scholar 

  • Andriessen, J., Baker, M. J., & Suthers, D. D. (2003). Argumentation, computer support, and the educational context of confronting cognitions. In J. Andriessen, M. J. Baker, & D. Suthers (Eds.), Arguing to learn: Confronting cognitions in computer-supported collaborative learning environments (pp. 1–25). Dordrecht, Netherlands: Kluwer.

    Chapter  Google Scholar 

  • Aronson, E., Blaney, N., Stephan, C., Sikes, J., & Snapp, M. (1978). The jigsaw classroom. Beverly Hills, CA: Sage.

    Google Scholar 

  • Baken, E. K., Adams, D. C., & Rentz, M. S. (2020). Jigsaw method improves learning and retention for observation-based undergraduate biology laboratory activities. Journal of Biological Education. https://doi.org/10.1080/00219266.2020.1796757.

  • Barclay, K. H., & Breheny, C. (1994). Letting the children take over more of their own learning: Collaborative research in the Kindergarten classroom. Young Children, 49(6), 33–39.

    Google Scholar 

  • Barron, B. (2003). When smart groups fail. Journal of the Learning Sciences, 12(3), 307–359. https://doi.org/10.1207/S15327809JLS1203_1.

    Article  Google Scholar 

  • Bellhäuser, H., Konert, J., Müller, A., & Röpke, R. (2018). Who is the perfect match? Effects of algorithmic learning group formation using personality traits. i-com, 17(1), 65–77. https://doi.org/10.1515/icom-2018-0004.

    Article  Google Scholar 

  • Chen, J., Wang, M., Kirschner, P. A., & Tsai, C.-C. (2018). The role of collaboration, computer use, learning environments, and supporting strategies in CSCL: A meta-analysis. Review of Educational Research, 88(6), 799–843. https://doi.org/10.3102/0034654318791584.

    Article  Google Scholar 

  • Chi, M. T. H., & Wylie, R. (2014). The ICAP framework: Linking cognitive engagement to active learning outcomes. Educational Psychologist, 49(4), 219–243. https://doi.org/10.1080/00461520.2014.965823.

    Article  Google Scholar 

  • Cress, U., Rosé, C., Wise, A., & Oshima, J. (Eds.). (2021). International handbook of computer-supported collaborative learning. New York, NY: Springer.

    Google Scholar 

  • Cummings, D. J., & Sheeran, N. (2019). Do academic motivation and personality influence which students benefit the most from peer-assisted study sessions? Psychology Learning and Teaching, 18(3), 244–258. https://doi.org/10.1177/1475725719840502.

    Article  Google Scholar 

  • Daxenberger, J., Csanadi, A., Ghanem, C., Kollar, I., & Gurevych, I. (2018). Domain-specific aspects of scientific reasoning and argumentation. In F. Fischer, C. Chinn, K. Engelmann, & J. Osborne (Eds.), Scientific reasoning and argumentation: The roles of domain-specific and domain-general knowledge (pp. 34–55). New York, NY: Routledge.

    Google Scholar 

  • De Backer, L., Van Keer, H., & Valcke, M. (2020). Variations in socially shared metacognitive regulation and their relation with university students’ performance. Metacognition and Learning, 15(2), 233–259. https://doi.org/10.1007/s11409-020-09229-5.

    Article  Google Scholar 

  • de Hei, M., Tabacaru, C., Sjoer, E., Rippe, R., & Walenkamp, J. (2020). Developing intercultural competence through collaborative learning in international higher education. Journal of Studies in International Education, 24(2), 190–211. https://doi.org/10.1177/1028315319826226.

    Article  Google Scholar 

  • De Lisi, R., & Golbeck, S. L. (1999). Implications of piagetian theory for peer learning. In A. M. O’Donnell & A. King (Eds.), Cognitive perspectives on peer learning (pp. 3–37). Mahwah, NJ: Erlbaum.

    Google Scholar 

  • De Wever, B., van Keer, H., Schellens, T., & Valcke, M. (2011). Assessing collaboration in a wiki: The reliability of university students’ peer assessment. The Internet and Higher Education, 14(4), 201–206. https://doi.org/10.1016/j.iheduc.2011.07.003.

    Article  Google Scholar 

  • Deiglmayr, A. (2018). Instructional scaffolds for learning from formative peer assessment: Effects of core task, peer feedback, and dialogue. European Journal of Psychology of Education, 33, 185–198. https://doi.org/10.1007/s10212-017-0355-8.

    Article  Google Scholar 

  • Dillenbourg, P. (1999). What do you mean by collaborative learning? In P. Dillenbourg (Ed.), Collaborative learning: Cognitive and computational approaches (pp. 1–19). Amsterdam, Netherlands: Elsevier.

    Google Scholar 

  • Fischer, F., Kollar, I., Stegmann, K., & Wecker, C. (2013). Towards a script theory of guidance in computer-supported collaborative learning. Educational Psychologist, 48(1), 56–66. https://doi.org/10.1080/00461520.2012.748005.

    Article  Google Scholar 

  • Gielen, M., Tops, L., Dochy, F., Onghena, P., & Smeets, S. (2010). A comparative study of peer and teacher feedback and of various feedback forms in a secondary school writing curriculum. British Educational Research Journal, 36(1), 143–162.

    Article  Google Scholar 

  • Hattie, J. A. C. (2009). Visible learning: A synthesis of over 800 meta-analyses related to achievement. London: Routledge.

    Google Scholar 

  • Hogan, D. M., & Tudge, J. R. H. (1999). Implications of Vygotsky’s theory for peer learning. In A. M. O’Donnell & A. King (Eds.), Cognitive perspectives on peer learning (pp. 39–65). Mahwah, NJ: Erlbaum.

    Google Scholar 

  • Janssen, J., & Bodemer, D. (2013). Coordinated computer-supported collaborative learning: Awareness and awareness tools. Educational Psychologist, 48(1), 40–55. https://doi.org/10.1080/00461520.2012.749153.

    Article  Google Scholar 

  • Järvelä, S., & Hadwin, A. F. (2013). New frontiers: Regulating learning in CSCL. Educational Psychologist, 48(1), 25–39. https://doi.org/10.1080/00461520.2012.748006.

    Article  Google Scholar 

  • Johnson, D. W., & Johnson, R. T. (2018). Cooperative learning: The foundation for active learning. Available on https://www.intechopen.com/books/active-learning-beyond-the-future/cooperative-learning-the-foundation-for-active-learning. Last accessed 02 Feb 2021.

  • Jurkowski, S., & Hänze, M. (2012). Kooperatives Lernen aus dem Blickwinkel sozialer Kompetenzen. Eine Untersuchung des Zusammenhangs sozialer Kompetenzen mit dem Lernerfolg, dem Unterrichtserleben und dem Gruppenarbeitsergebnis in verschiedenen kooperativen Lernumgebungen [Collaborative learning viewed from the perspective of social competences. An investigation of the relation of social competences with learning outcomes, perception of instruction, and products of collaborative learning in different learning environments]. Unterrichtswissenschaft, 40(3), 259–276.

    Google Scholar 

  • Kelsen, B. A., & Liang, H.-Y. (2019). Role of the big 5 personality traits and motivation in predicting performance in collaborative presentations. Psychological Reports, 122(5), 1907–1924. https://doi.org/10.1177/0033294118795139.

    Article  Google Scholar 

  • King, A. (2007). Scripting collaborative learning processes: A cognitive perspective. In F. Fischer, I. Kollar, H. Mandl, & J. M. Haake (Eds.), Scripting computer-supported collaborative learning: Cognitive, computational and educational perspectives (pp. 14–37). New York, NY: Springer.

    Google Scholar 

  • Kollar, I., Wecker, C., & Fischer, F. (2018). Scaffolding and scripting (computer-supported) collaborative learning. In F. Fischer, C. E. Hmelo-Silver, S. R. Goldman, & P. Reimann (Eds.), International handbook of the learning sciences (pp. 340–350). New York, NY: Routledge/Taylor & Francis.

    Chapter  Google Scholar 

  • Kyndt, E., Raes, E., Lismont, B., Timmers, F., Cascallar, E., & Dochy, F. (2013). A meta-analysis of the effects of face-to-face cooperative learning. Do recent studies falsify or verify earlier findings? Educational Research Review, 10, 133–149. https://doi.org/10.1016/j.edurev.2013.02.002.

    Article  Google Scholar 

  • Malmberg, J., Järvelä, S., Järvenoja, H., & Panadero, E. (2015). Promoting socially shared regulation of learning in CSCL: Progress of socially shared regulation among high- and low-performing groups. Computers in Human Behavior, 52, 562–572. https://doi.org/10.1016/j.chb.2015.03.082.

    Article  Google Scholar 

  • Mayring, P. (2014). Qualitative content analysis: Theoretical foundation, basic procedures and software solution. Klagenfurt, Austria: Beltz.

    Google Scholar 

  • McNaughton, J., Crick, T., Joyce-Gibbons, A., Beauchamp, G., Young, N., & Tan, E. (2017). Facilitating collaborative learning between two primary schools using large multi-touch devices. Journal of Computers in Education, 4, 307–320. https://doi.org/10.1007/s40692-017-0081-x.

    Article  Google Scholar 

  • Melzner, N., Greisel, M., Dresel, M., & Kollar, I. (2020). Regulating self-organized collaborative learning: The importance of homogeneous problem perception, immediacy, and intensity of strategy use. International Journal of Computer-Supported Collaborative Learning, 15(2), 149–177. https://doi.org/10.1007/s11412-020-09323-5.

    Article  Google Scholar 

  • Menekse, M., Stump, G. S., Krause, S., & Chi, M. T. H. (2013). Differentiated overt learning activities for effective instruction in engineering classrooms. Journal of Engineering Education, 102(3), 346–274. https://doi.org/10.1002/jee.20021.

    Article  Google Scholar 

  • Näykki, P., Isohätälä, J., Järvelä, S., Poysa-Tarhonen, J., & Häkkinen, P. (2017). Facilitating socio-cognitive and socio-emotional monitoring in collaborative learning with a regulation macro script – An exploratory study. International Journal of Computer-Supported Collaborative Learning, 12(3), 251–279. https://doi.org/10.1007/s11412-017-9259-5.

    Article  Google Scholar 

  • Palincsar, A. S., & Brown, A. L. (1984). Reciprocal teaching of comprehension-fostering and comprehension-monitoring activities. Cognition and Instruction, 1(2), 117–175. https://doi.org/10.1207/s1532690xci0102_1.

    Article  Google Scholar 

  • Renkl, A. (2011). Aktives Lernen: Von sinnvollen und weniger sinnvollen theoretischen Perspektiven zu einem schillernden Konstrukt [Active learning: About sensible and less sensible theoretical perspectives on a multifaceted construct]. Unterrichtswissenschaft, 39(3), 197–212.

    Google Scholar 

  • Rosé, C., & Ferschke, O. (2016). Technology support for discussion based learning: From computer supported collaborative learning to the future or massive open online courses. International Journal of Artificial Intelligence in Education, 26, 660–678. https://doi.org/10.1007/s40593-016-0107-y.

  • Rumain, B., & Geliebter, A. (2020). A process-oriented guided-inquiry learning (POGIL)-based curriculum for the experimental psychology laboratory. Psychology Learning and Teaching, 19(2), 194–206. https://doi.org/10.1177/1475725720905973.

    Article  Google Scholar 

  • Rummel, N., & Spada, H. (2005). Learning to collaborate: An instructional approach to promoting collaborative problem-solving in computer-mediated settings. The Journal of the Learning Sciences, 14(2), 201–241. https://doi.org/10.1207/s15327809jls1402_2.

    Article  Google Scholar 

  • Schnaubert, L., & Bodemer, D. (2019). Providing different types of group awareness information to guide collaborative learning. International Journal of Computer-Supported Collaborative Learning, 14, 7–51. https://doi.org/10.1007/s11412-018-9293-y.

    Article  Google Scholar 

  • Selleck, C. S., Fifolt, M., Burkart, H., Frank, J. S., Curry, W. A., & Hites, L. S. (2017). Providing primary care using an interprofessional collaborative practice model: What clinicians have learned. Journal of Professional Nursing, 33(6), 410–416. https://doi.org/10.1016/j.profnurs.2016.11.004.

    Article  Google Scholar 

  • Shaffer, D. W., Collier, W., & Ruis, A. R. (2016). A tutorial on epistemic network analysis: Analyzing the structure of connections in cognitive, social, and interaction data. Journal of Learning Analytics, 3(3), 9–45. https://doi.org/10.18608/jla.2016.33.3.

    Article  Google Scholar 

  • Slavin, R. E., & Tanner, A. M. (1979). Effects of cooperative reward structures and individual accountability on productivity and learning. The Journal of Educational Research, 72(5), 294–298. https://doi.org/10.1080/00220671.1979.10885175.

    Article  Google Scholar 

  • Sobocinski, M., Järvelä, S., Malmberg, J., Dindar, M., Isosalo, A., & Noponen, K. (2020). How does monitoring set the stage for adaptive regulation or maladaptive behavior in collaborative learning? A multimodal analysis. Metacognition and Learning, 15(2), 99–127. https://doi.org/10.1007/s11409-020-09224-w.

    Article  Google Scholar 

  • Springer, L., Stanne, M. E., & Donovan, S. S. (1999). Effects of small group learning on undergraduates in science, mathematics, engineering, and technology: A meta-analysis. Review of Educational Research, 69(1), 21–51. https://doi.org/10.3102/00346543069001021.

    Article  Google Scholar 

  • Teasley, S. D. (1995). Talking about reasoning: How important is the peer in peer collaboration? In L. B. Resnick, R. Säljö, C. Pontecorvo, & B. Burge (Eds.), Discourse, tools, and reasoning: Essays on situated cognition (pp. 361–384). Berlin, Germany: Springer. https://doi.org/10.1007/978-3-662-03362-3_16.

    Chapter  Google Scholar 

  • Topping, K. (1998). Peer assessment between students in college and universities. Review of Educational Research, 68(3), 249–267. https://doi.org/10.3102/00346543068003249.

    Article  Google Scholar 

  • Vogel, F., Kollar, I., Ufer, S., Reichersdorfer, E., Reiss, K., & Fischer, F. (2016). Developing argumentation skills in mathematics through computer-supported collaborative learning: The role of transactivity. Instructional Science, 44(5), 477–500. https://doi.org/10.1007/s11251-016-9380-2.

    Article  Google Scholar 

  • Vogel, F., Wecker, C., Kollar, I., & Fischer, F. (2017). Socio-cognitive scaffolding with collaboration scripts: A meta-analysis. Educational Psychology Review, 29(3), 477–511. https://doi.org/10.1007/s10648-016-9361-7.

    Article  Google Scholar 

  • Wang, X., Kollar, I., & Stegmann, K. (2017). Adaptable scripting to foster regulation processes and skills in computer-supported collaborative learning. International Journal for Computer-Supported Collaborative Learning, 12(2), 153–172. https://doi.org/10.1007/s11412-017-9254-x.

    Article  Google Scholar 

  • Weinberger, A., & Fischer, F. (2006). A framework to analyze argumentative knowledge construction in computer-supported collaborative learning. Computers & Education, 46(1), 71–95. https://doi.org/10.1016/j.compedu.2005.04.003.

    Article  Google Scholar 

  • Weinberger, A., Stegmann, K., & Fischer, F. (2010). Learning to argue online: Scripted groups surpass individuals (unscripted groups do not). Computers in Human Behavior, 26(4), 506–515. https://doi.org/10.1016/j.chb.2009.08.007.

    Article  Google Scholar 

  • Wekerle, C., Daumiller, M., & Kollar, I. (2022). Using digital technology to promote higher education learning: The importance of different learning activities and their relations to learning outcomes. Journal of Research on Technology in Education, 54(1), 1–17. https://doi.org/10.1080/15391523.2020.1799455.

  • Wichmann, A., Funk, A., & Rummel, N. (2018). Leveraging the potential of peer feedback in an academic writing activity through sense-making support. European Journal of Psychology of Education, 33, 165–184. https://doi.org/10.1007/s10212-017-0348-7.

    Article  Google Scholar 

  • Yalch, M. M., Vitale, E. M., & Ford, J. K. (2019). Benefits of peer review on students’ writing. Psychology Learning and Teaching, 18(3), 317–325. https://doi.org/10.1177/1475725719835070.

    Article  Google Scholar 

  • Yoon, S., Anderson, E., Park, M., Elinich, K., & Lin, J. (2018). How augmented reality, textual, and collaborative scaffolds work synergistically to improve learning in a science museum. Research in Science and Technological Education, 36(1), 1–21. https://doi.org/10.1080/02635143.2017.1386645.

    Article  Google Scholar 

  • Zheng, L., Zhang, X., & Gyasi, J. F. (2019). A literature review of features and trends of technology-supported collaborative learning in informal settings from 2007 to 2018. Journal of Computers in Education, 6, 529–561. https://doi.org/10.1007/s40692-019-00148-2.

    Article  Google Scholar 

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Authors and Affiliations

  1. Lehrstuhl für Psychologie m.b.B.d. Pädagogischen Psychologie, University of Augsburg, Augsburg, Germany

    Ingo Kollar & Martin Greisel

Authors
  1. Ingo Kollar
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  2. Martin Greisel
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Corresponding author

Correspondence to Ingo Kollar .

Editor information

Editors and Affiliations

  1. School of Education, Univ of Salzburg, Salzburg, Austria

    Joerg Zumbach

  2. Department of Psychology, University of South Florida, Bonita Springs, FL, USA

    Douglas Bernstein

  3. Psychology Learning & Instruction, Technische Universität Dresden, Dresden, Sachsen, Germany

    Susanne Narciss

  4. DISUFF, University of Salerno, Salerno, Salerno, Italy

    Giuseppina Marsico

Section Editor information

  1. University of Salzburg, Salzburg, Austria

    Joerg Zumbach

  2. Psychologie des Lehrens und Lernens, Technische Universität Dresden, Dresden, Deutschland

    Susanne Narciss

  3. Department of Psychology, University of South Florida, Tampa, FL, USA

    Douglas A. Bernstein

  4. Department of Human, Philosophic, and Education Sciences, University of Salerno, Salerno, Italy

    Giuseppina Marsico

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Kollar, I., Greisel, M. (2022). Small Group Learning. In: Zumbach, J., Bernstein, D., Narciss, S., Marsico, G. (eds) International Handbook of Psychology Learning and Teaching. Springer International Handbooks of Education. Springer, Cham. https://doi.org/10.1007/978-3-030-26248-8_60-3

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  • DOI: https://doi.org/10.1007/978-3-030-26248-8_60-3

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  • Print ISBN: 978-3-030-26248-8

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Chapter history

  1. Latest

    Small Group Learning
    Published:
    10 October 2022

    DOI: https://doi.org/10.1007/978-3-030-26248-8_60-3

  2. Small Group Learning
    Published:
    10 December 2021

    DOI: https://doi.org/10.1007/978-3-030-26248-8_60-2

  3. Original

    Small Group Learning
    Published:
    28 August 2021

    DOI: https://doi.org/10.1007/978-3-030-26248-8_60-1

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