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A framework for exploring small group learning in high school science classrooms: The triple problem solving space

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Abstract

Classroom activities using an inquiry approach often feature students working in small groups to reduce teacher-centeredness and maximize student autonomy. Within science classrooms, group work may mirror modern scientific research: successful interaction among team members (social/relational) that engages probing questioning and creativity (cognitive/content) with emotional attachment to their work (affective). Previous research on small group work in school science focused either on single dimensions of group work—mostly on needed cognitive resources, e.g., knowledge and skills for understanding and addressing the problem—or on the interplay between cognitive and social resources (e.g., science knowledge and capacity to foster group interactions), while the role of affects is relatively unexplored. We propose that group work demands the collective construction of a “triple problem solving space” in which all three dimensions—cognitive/content (the problem to be solved), social/relational (the challenges based on social interactions within the group), and affective (the emotional life of the group)—are developed on a moment-by-moment basis. Assessing whether and to what extent students collectively construct a positive triple problem solving space, we videotaped small groups’ interactions (3–4 students per group) during inquiry-based activities in three ninth grade science classes. Results showed that when a group collectively positions itself positively in terms of social and affective dynamics, it tends to engage effectively in the cognitive aspects of the assigned tasks. The qualitative analysis further highlights the socially-shared regulation processes that involve an ongoing negotiation between intra- and inter-individual resources and which are the result of each group member deploying individual resources along each dimension, monitoring and evaluating their peers’ processes, and adjusting their processes accordingly through integration of information from self and others.

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Notes

  1. Though the size of the groups varied slightly, there was no discernible relationship between group size and the amount of time groups needed to complete the tasks or the number of interactions within the group. For this reason, we do not believe that the size of the group (three or four members) influenced our findings.

  2. We offer gender composition as a context in our analysis. Although gender and group gender composition effects on small group work are worth ongoing study, they are not the focus in this analysis.

References

  • Abbott, A. (1995). Sequence analysis: New methods for old ideas. Annual Review of Sociology,21, 93–113.

    Article  Google Scholar 

  • Andriessen, J., Pardijs, M., & Baker, M. (2013). Getting on and getting along tension in the development of collaborations. In M. Baker, J. Andriessen, & S. Järvelä (Eds.), Affective learning together—social and emotional dimensions of collaborative learning (pp. 205–230). New York: Routledge.

    Google Scholar 

  • Aubé, C., Rousseau, V., Brunelle, E., & Marques, D. (2018). The relevance of being “on the same page” to succeed as a project team: A moderated mediation model. Motivation and Emotion,42, 804–815.

    Article  Google Scholar 

  • Bakhtiar, A., Webster, E. A., & Hadwin, A. F. (2018). Regulation and socio-emotional interactions in a positive and negative group climate. Metacognitive Learning,13, 57–90.

    Article  Google Scholar 

  • Barron, B. (2003). When smart groups fail. Journal of the Learning Sciences,12, 307–359.

    Article  Google Scholar 

  • Bennett, J., Hogarth, S., Lubben, F., Campbell, B., & Robinson, A. (2010). Talking Science: The research evidence on the use of small group discussions in science teaching. International Journal of Science Education,32(1), 69–95.

    Article  Google Scholar 

  • Blumenfeld, P., Soloway, E., Marx, R. W., Krajcik, J. S., Guzdial, M., & Palincsar, A. (1991). Motivating project-based learning: Sustaining the doing, supporting the learning. Educational Psychologist,26, 369–398.

    Article  Google Scholar 

  • Boekaerts, M., Pintrich, P. R., & Zeidner, M. (2000). Handbook of self-regulation. San Diego: Academic Press.

    Google Scholar 

  • Braun, V., & Clark, V. (2012). Thematic analysis. In H. Cooper, P. M. Camic, D. L. Long, A. T. Panter, D. Rindskopf, & K. J. Sher (Eds.), APA handbook of research methods in psychology, Research designs: Quantitative, qualitative, neuropsycholgical, and biological (Vol. 2). Hoboken, NJ: Wiley.

    Google Scholar 

  • Brown, A., & Palincsar, A. (1989). Guided, cooperative learning and individual knowledge acquisition. In L. B. Resnick (Ed.), Knowing, learning, and instruction (pp. 393–451). Mahwah, NJ: Erlbaum.

    Google Scholar 

  • Cartney, P., & Rouse, A. (2006). The emotional impact of learning in small groups: Highlighting the impact on student progression and retention. Teaching in Higher Education,11(1), 79–91.

    Article  Google Scholar 

  • Cheng, R. W.-Y., Lam, S.-F., & Chan, J. C.-Y. (2008). When high achievers and low achievers work in the same group: the roles of group heterogeneity and processes in project-based learning. British Journal of Educational Psychology,78(2), 205–221.

    Article  Google Scholar 

  • Chinn, C. A., & Brewer, W. F. (1993). The role of anomalous data in knowledge acquisition: A theoretical framework and implications for science instruction. Review of Educational Research,63(1), 1–49.

    Article  Google Scholar 

  • Cohen, E. G. (1994a). Designing group work: Strategies for the heterogeneous classroom (2nd ed.). New York: Teachers College Press.

    Google Scholar 

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

    Article  Google Scholar 

  • Cohen, E. G., & Lotan, R. A. (1995). Producing equal-status interaction in the heterogeneous classroom. American Educational Research Journal,32, 99–120.

    Article  Google Scholar 

  • Cohen, E. G., Lotan, R. A., Scarloss, B. A., & Arellano, A. R. (1999). Complex instruction: Equity in cooperative learning classrooms. Theory into Practice,38(2), 80–86.

    Article  Google Scholar 

  • Cornelius, L., & Herrenkohl, L. (2004). Power in the classroom: How the classroom environment shapes students’ relationships with each other and with concepts. Cognition and Instruction,22(4), 467–498.

    Article  Google Scholar 

  • de Jong, J. P., Curşeu, P. L., & Leenders, R T h A J. (2014). When do bad apples not spoil the barrel? Negative relationships in teams, team performance, and buffering mechanisms. Journal of Applied Psychology,99(3), 514–522.

    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). Oxford: Elsevier.

    Google Scholar 

  • Dillenbourg, P., Baker, M. J., Blaye, A., & O’Malley, C. (1995). The evolution of research on collaborative learning. In E. Spada & P. Reiman (Eds.), Learning in humans and machine: Towards an interdisciplinary learning science (pp. 189–211). Oxford: Elsevier.

    Google Scholar 

  • Dimant, R. J., & Bearison, D. J. (1991). Development of formal reasoning during successive peer interactions. Developmental Psychology,27(2), 277–284.

    Article  Google Scholar 

  • Dohn, N. B. (2013). Situational interest in engineering design activities. International Journal of Science Education,35(12), 2057–2078.

    Article  Google Scholar 

  • Duffy, M. C., Azevedo, R., Sun, N.-Z., Griscom, S. E., Stead, V., Crelinsten, L., et al. (2015). Team regulation in a simulated medical emergency: An in-depth analysis of cognitive, metacognitive, and affective processes. Instructional Science,43(3), 401–426.

    Article  Google Scholar 

  • Durik, A. M., Hulleman, C. S., & Harackiewicz, J. M. (2015). One size fits some: Instructional enhancements to promote interest. In A. K. Renninger & S. Hidi (Eds.), Interest in mathematics and science learning (pp. 49–62). Washington, DC: AERA.

    Chapter  Google Scholar 

  • Duschl, R. A., & Osborne, J. (2002). Supporting and promoting argumentation discourse in science education. Studies in Science Education,38, 39–72.

    Article  Google Scholar 

  • Edmondson, A. (1999). Psychological safety and learning behavior in work teams. Administrative Science Quarterly,44, 350–383.

    Article  Google Scholar 

  • Engle, R. A., & Conant, F. R. (2002). Guiding principles for fostering productive disciplinary engagement: Explaining an emergent argument in a community of learners’ classroom. Cognition and Instruction,20, 399–483.

    Article  Google Scholar 

  • Festinger, L. (1950). Informal social communication. Psychological Review,57(5), 271–282.

    Article  Google Scholar 

  • Gillies, R. M. (2003). The behaviors, interactions, and perceptions of junior high school students during small-group learning. Journal of Educational Psychology,95(1), 137–147.

    Article  Google Scholar 

  • Gore, J. (1995). On the continuity of power relations in pedagogy. International Studies in Sociology of Education,5(2), 165–188.

    Article  Google Scholar 

  • Hadwin, A. F., Oshige, M., Gress, C. L., & Winne, P. H. (2010). Innovative ways for using Study to orchestrate and research social aspects of self-regulated learning. Computers in Human behavior,26(5), 794–805.

    Article  Google Scholar 

  • Hand, V. M. (2010). The co-construction of opposition in a low-track mathematics classroom. American Educational Research Journal,47(1), 97–132.

    Article  Google Scholar 

  • Hidi, S., & Renninger, A. (2006). The four-phase model of interest development. Educational Psychologist,41, 111–127.

    Article  Google Scholar 

  • Hogan, K. (1999). Sociocognitive roles in science group discourse. International Journal of Science Education,21, 855–882.

    Article  Google Scholar 

  • Howe, C. (2010). Peer dialogue and cognitive development. In K. Littleton & C. Howe (Eds.), Educational dialogues: Understanding and promoting productive interaction (pp. 32–47). Oxford: Routledge.

    Google Scholar 

  • Järvelä, S., & Järvenoja, H. (2011). Socially constructed self-regulated learning and motivation regulation in collaborative learning groups. Teachers College Record,113(2), 350–374.

    Google Scholar 

  • Järvelä, S., Kirschner, P. A., Panadero, E., Malmberg, J., Phielix, C., Jaspers, J., et al. (2015). Enhancing socially shared regulation in collaborative learning groups: Designing for CSCL regulation tools. Educational Technology Research and Development,63(1), 125–142.

    Article  Google Scholar 

  • Järvenoja, H., & Järvelä, S. (2009). Emotion control in collaborative learning situations: Do students regulate emotions evoked by social challenges? British Journal of Educational Psychology,79, 463–481.

    Article  Google Scholar 

  • Järvenoja, H., Järvelä, S., & Malmberg, J. (2017). Supporting groups’ emotion and motivation regulation during collaborative learning. Learning and Instruction. https://doi.org/10.1016/j.learninstruc.2017.11.004.

    Article  Google Scholar 

  • Jiménez-Aleixandre, M. P., Rodriguez, A. B., & Duschl, R. A. (2000). ‘Doing the lesson’ or ‘doing science’: Argument in high school genetics. Science and Education,84, 757–792.

    Article  Google Scholar 

  • Johnson, D. W., & Johnson, R. T. (1999). Making cooperative learning work. Theory into Practice,38(2), 67–73.

    Article  Google Scholar 

  • Johnson, D. W., & Johnson, R. T. (2009). An educational psychology success story: Social interdependence theory and cooperative learning. Educational Researcher,38(5), 365–379.

    Article  Google Scholar 

  • Jones, A., & Issroff, K. (2005). Learning technology: Affective and social issues in computer-supported collaborative learning. Computers & Education,44, 395–408.

    Article  Google Scholar 

  • Kapur, M. (2008). Productive failure. Cognition and Instruction,26, 379–424.

    Article  Google Scholar 

  • Kapur, M. (2012). Designing for productive failure. Journal of the Learning Sciences,21, 45–83.

    Article  Google Scholar 

  • Karau, S. J., & Williams, K. D. (1995). Social loafing: Research findings, implications, and future directions. Current Directions in Psychological Science,4(5), 134–140.

    Article  Google Scholar 

  • Kelly, J. R., & Barsade, S. G. (2001). Mood and emotions in small groups and work teams. Organizational Behavior and Human Decision Processes,86(1), 99–130.

    Article  Google Scholar 

  • Kempler, T. M., & Linnenbrink, E. A. (2006). Helping behaviors in collaborative groups in math: A descriptive analysis. In S. Karabenick & R. Newman (Eds.), Help seeking in academic settings: goals, groups, and context (pp. 89–115). Mahwah, NJ: Erlbaum.

    Google Scholar 

  • Kempler Rogat, T., & Linnenbrink-Garcia, L. (2011). Socially shared regulation in collaborative groups: An analysis of the interplay between quality of social regulation and group processes. Cognition and Instruction,29(4), 375–415.

    Article  Google Scholar 

  • Kempler Rogat, T., & Adams-Wiggins, K. R. (2014). Other-regulation in collaborative groups: Implications for regulation quality. Instructional Science,42(6), 879–904.

    Article  Google Scholar 

  • Keys, C. W. (1997). An investigation of the relationship between scientific reasoning, conceptual knowledge and model formulation in a naturalistic setting. International Journal of Science Education,19, 957–970.

    Article  Google Scholar 

  • Kirschner, P. A., Beers, P. J., Boshuizen, H. P. A., & Gijselaers, W. H. (2008). Coercing shared knowledge in collaborative learning environments. Computers in Human Behavior,24(2), 403–420.

    Article  Google Scholar 

  • Krajcik, J. S., Blumenfeld, P., Marx, R. W., Bass, K., Fredricks, J., & Soloway, E. (1998). First attempts at inquiry strategies in middle school, project-based science classrooms. Journal of the Learning Sciences,7, 313–350.

    Article  Google Scholar 

  • Kreijns, K., Kirschner, P. A., & Jochems, W. (2003). Identifying the pitfalls for social interaction in computer-supported collaborative learning environments: a review of research. Computers in Human Behavior,19, 335–353.

    Article  Google Scholar 

  • Kurth, L. A., Anderson, C. W., & Palincsar, A. S. (2002). The case of Carla: Dilemmas of helping all students to understand science. Science Education,86, 287–313.

    Article  Google Scholar 

  • Lajoie, S. P., Lee, L., Poitras, E., Bassiri, M., Kazemitabar, M., Cruz-Panesso, I., et al. (2015). The role of regulation in medical student learning in small groups: Regulating oneself and others' learning and emotions. Computers in Human Behavior,52, 601–616.

    Article  Google Scholar 

  • Lee, O. (2002). Science inquiry for elementary students from diverse backgrounds. In W. G. Secada (Ed.), Review of research in education (Vol. 26, pp. 23–69). Washington, DC: American Educational Research Association.

    Google Scholar 

  • Linnenbrink-Garcia, L., Rogat, T. K., & Koskey, K. L. (2011). Affect and engagement during small group instruction. Contemporary Educational Psychology,36, 13–24.

    Article  Google Scholar 

  • Linnenbrink-Garcia, L., Pugh, K. J., Koskey, K. L., & Stewart, V. C. (2012). Developing conceptual understanding of natural selection: The role of interest, efficacy, and basic prior knowledge. The Journal of Experimental Education,80(1), 45–68.

    Article  Google Scholar 

  • Lou, Y., Abrami, P. C., & Spence, J. C. (2000). Effects of within-class grouping on student achievement: An exploratory model. The Journal of Educational Research,94, 101–112.

    Article  Google Scholar 

  • McFarland, D. A. (2001). Student resistance: How the formal and informal organization of classrooms facilitate everyday forms of student defiance. American Journal of Sociology,107(3), 612–678.

    Article  Google Scholar 

  • McFarland, D. A. (2004). Resistance as a social drama: A study of change-oriented encounters. American Journal of Sociology,109(6), 1249–1318.

    Article  Google Scholar 

  • McEneaney, E. H., & Nieswandt, M. (2017). The critical role of group affect in engineering design tasks in high school Biology. In Proceedings of the 2017 American Society for Engineering Education Conference and Exposition. https://www.asee.org/public/conferences/78/papers/19670/view

  • Megías, A., Cándido, A., Maldonado, A., & Catena, A. (2018). Neural correlates of risk perception as a function of risk level: An approach to the study of risk through a daily life task. Neuropsychologia,119, 464–473.

    Article  Google Scholar 

  • Mercer, N. (1996). The quality of talk in children’s collaborative activity in the classroom. Learning and Instruction,6(4), 359–377.

    Article  Google Scholar 

  • Micari, M., Pazos, P., Streitweiser, B., & Light, G. (2010). Small-group learning in undergraduate STEM disciplines: Effect of group type on student achievement. Educational Research and Evaluation,16(3), 269–286.

    Article  Google Scholar 

  • Moshman, D., & Geil, M. (1998). Collaborative reasoning: Evidence for collective rationality. Thinking and Reasoning,4(3), 231–248.

    Article  Google Scholar 

  • National Research Council. (1996). National science education standards. Washington, DC: The National Academy Press.

    Google Scholar 

  • NGSS Lead States. (2013). Next generation science standards: For states, by states. Washington, DC: The National Academic Press.

    Google Scholar 

  • Nieswandt, M., Affolter, R., & McEneaney, E. H. (2014). Interest, instructional strategies, and the creation of groups space. International Journal of Education and Psychological Research, 3(3), 1–5.

    Google Scholar 

  • Organisation for Economic Co-operation and Development (OECD) (2019). 2018 Teaching and Learning International Survey—TALIS. www.oecd.org/education/talis/.

  • Osman, G., Duffy, T. M., Chang, J., & Lee, J. (2011). Learning through collaboration: Student perspectives. Asia Pacific Education Review,12, 547–558.

    Article  Google Scholar 

  • Panadero, E., & Järvelä, S. (2015). Socially shared regulation of learning: A review. European Psychologist,20(3), 190–203.

    Article  Google Scholar 

  • Parsons, E. R. C., Tran, L. U., & Gomillion, C. T. (2008). An investigation of student roles within small, racially mixed science groups: A racial perspective. International Journal of Science Education,30(11), 1469–1489.

    Article  Google Scholar 

  • Patchen, T., & Smithenry, D. W. (2015). More than just chemistry: The impact of a collaborative participant structure on student perceptions of science. Research in Science Education,45, 75–100.

    Article  Google Scholar 

  • Pekrun, R. (2006). The control-value theory of achievement emotions: Assumptions, corollaries, and implications for educational research and practice. Educational Psychology Review,18(4), 315–341.

    Article  Google Scholar 

  • Pekrun, R., Elliot, A. J., & Maier, M. A. (2006). Achievement goals and discrete achievement emotions: A theoretical model and prospective test. Journal of Educational Psychology,98(3), 583–597.

    Article  Google Scholar 

  • Pekrun, R., Goetz, T., Titz, W., & Perry, R. P. (2002). Academic emotions in students’ self-regulated learning and achievement: A program of quantitative and qualitative research. Educational Psychologist,37, 91–106.

    Article  Google Scholar 

  • Pintrich, P. R. (1999). The role of motivation in promoting and sustaining self-regulated learning. International Journal of Educational Research,31(6), 459–470.

    Article  Google Scholar 

  • Richmond, G., & Striley, J. (1996). Making meaning in classrooms: Social processes in small- group discourse and scientific knowledge building. Journal of Research in Science Teaching,33, 839–858.

    Article  Google Scholar 

  • Renninger, K. A., & Hidi, S. (2011). Revisiting the conceptualization, measurement, and generation of interest. Educational Psychologist,46(3), 168–184.

    Article  Google Scholar 

  • Renninger, K. A., & Hidi, S. E. (2016). The power of interest for motivation and engagement. New York: Routledge.

    Google Scholar 

  • Roschelle, J. (1992). Learning by collaborating: Convergent conceptual change. The Journal of the Learning Sciences,2, 235–276.

    Article  Google Scholar 

  • Roschelle, J., & Teasley, S. D. (1995). The construction of shared knowledge in collaborative problem solving. In C. E. O’Malley (Ed.), Computer-supported collaborative learning (pp. 69–197). Berlin: Springer.

    Chapter  Google Scholar 

  • Roth, W.-M. (1995). Inventors, copycats, and everyone else: The emergence of shared resources and practices as defining aspects of classroom communities. Science Education,79(5), 475–502.

    Article  Google Scholar 

  • Salonen, P., Vauras, M., & Efklides, A. (2005). Social interaction—What can it tell us about metacognition and coregulation in learning? European Psychologist,10, 199–208.

    Article  Google Scholar 

  • Sampson, V., & Clark, D. (2009). The effect of collaboration on the outcomes of argumentation. Science Education,93, 448–484.

    Article  Google Scholar 

  • Sargent, L. D., & Sue-Chang, C. (2001). Does diversity affect group efficacy?: The intervening role of cohesion and task interdependence. Small Groups Research,32(4), 426–450.

    Article  Google Scholar 

  • Schwarz, B. B., & Linchevski, L. (2007). The role of task design and argumentation in cognitive development during peer interaction: The case of proportional reasoning. Learning and Instruction,17(5), 510–531.

    Article  Google Scholar 

  • Sears, D. A., & Reagin, J. M. (2013). Individual versus collaborative problem solving: Divergent outcomes depending on task complexity. Instructional Science,41, 1153–1172.

    Article  Google Scholar 

  • Shepardson, D. P. (1996). Social interactions and the mediation of science learning in two small groups of first graders. Journal of Research in Science Teaching,33(2), 159–178.

    Article  Google Scholar 

  • Smith, E. T., Seger, C. R., & Mackie, D. M. (2007). Can emotions be truly group level? Evidence regarding four conceptual criteria. Journal of Personality and Social Psychology,93(3), 431–446.

    Article  Google Scholar 

  • Soller, A. (2001). Supporting social interaction in an intelligent collaborative learning system. International Journal of Artificial Intelligence in Education,12, 40–62.

    Google Scholar 

  • Taub, M., Azevedo, R., Rajendran, R., Cloude, E. B., Biswas, G., & Price, M. J. (2019). How are students’ emotions related to the accuracy of cognitive and metacognitive processes during learning with an intelligent tutoring system? Learning and Instruction. https://doi.org/10.1016/j.learninstruc.2019.04.001.

    Article  Google Scholar 

  • Teasley, S. D., & Roschelle, J. (1993). Constructing a joint problem space: The computer as a tool for sharing knowledge. In S. P. Lajoie & S. J. Derry (Eds.), Computers as cognitive tools (pp. 229–258). Mahwah, NJ: Lawrence Erlbaum Associates Inc.

    Google Scholar 

  • ten Dam, G., & Volman, M. (2007). Educating for adulthood or for citizenship: Social competence as an educational goal. European Journal of Education,42(2), 281–298.

    Article  Google Scholar 

  • Tolmie, A., & Howe, C. (1993). Gender and dialogue in secondary school physics. Gender and Education,5, 191–209.

    Article  Google Scholar 

  • Van Boxtel, C., van der Linden, J., & Kanselaar, G. (2000). Collaborative learning tasks and the elaboration of conceptual knowledge. Learning and Instruction,10, 311–330.

    Article  Google Scholar 

  • Vauras, M., Iskala, T., Kajamies, A., Kinnunen, R., & Lehtinen, E. (2003). Shared-regulation and motivation of collaborative peers: A case analysis. Psychologia,46(1), 19–37.

    Article  Google Scholar 

  • Veermans, M., & Järvelä, S. (2004). Generalized achievement goals and situational coping in inquiry learning. Instructional Science,32, 269–291.

    Article  Google Scholar 

  • Visschers-Pleijers, A., Dolmans, D., Wolfhagen, I., & van der Vleuten, C. (2005). Development and validation of a questionnaire to identify learning-oriented group interactions in PBL. Medical Teacher,27(4), 375–381.

    Article  Google Scholar 

  • Volet, S., Vauras, M., & Salonen, P. (2009). Self- and social regulation in learning contexts: An integrative perspective. Educational Psychologist,44(4), 215–226.

    Article  Google Scholar 

  • Webb, N. M., Nemer, K. M., & Ing, M. (2006). Small-group reflections: Parallels between teacher discourse and student behavior in peer-directed groups. The Journal of the Learning Sciences,15(1), 63–119.

    Article  Google Scholar 

  • Webb, N. M., & Palincsar, A. S. (1996). Group processes in the classroom. In D. C. Berliner & R. C. Calfee (Eds.), Handbook of educational psychology (pp. 841–873). New York/London: Macmillan Library Reference USA/Prentice Hall International.

    Google Scholar 

  • Webb, N. M., Troper, J. D., & Fall, R. (1995). Constructive activity and learning in collaborative small groups. Journal of Educational Psychology,87(3), 406–423.

    Article  Google Scholar 

  • Williams, G. C., Freedman, Z. R., & Deci, E. L. (1998). Supporting autonomy to motivate patients with diabetes for glucose control. Diabetes Care,21, 1644–1651.

    Article  Google Scholar 

  • Wolters, C. A. (2003). Regulation of motivation: Evaluating an underemphasized aspect of self-regulated learning. Educational Psychologist,38(4), 189–205.

    Article  Google Scholar 

  • Woodruff, E., & Meyer, K. (1997). Explanations from intra- and inter-group discourse: Students building knowledge in the science classroom. Research in Science Education,27, 25–39.

    Article  Google Scholar 

  • Xu, J., Du, J., & Fan, X. (2013). Individual and group-level factors for students’ emotion management in online collaborative groupwork. Internet and Higher Education,19, 1–9.

    Article  Google Scholar 

  • Ying, X., Li, H., Jiang, S., Peng, F., & Lin, Z. (2014). Group laziness: The effect of social loafing on group performance. Social Behavior and Personality,42(3), 465–472.

    Article  Google Scholar 

  • Zschocke, K., Wosnitza, M., & Bürger, K. (2016). Emotions in group work: insights from an appraisal-oriented perspective. European Journal of Psychology of Education,31, 359–384.

    Article  Google Scholar 

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This article is based upon work supported by the National Science Foundation under Grant No. DRL 1252339. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

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  1. Martina Nieswandt and Elizabeth H. McEneaney contributed equally to this work.

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  1. University of Massachusetts Amherst, 181 Presidents Drive, Amherst, MA, 01003-9313, USA

    Martina Nieswandt & Elizabeth H. McEneaney

  2. Boston College, Newton, MA, 02467, US

    Renee Affolter

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Appendix: Group observation coding categories

Appendix: Group observation coding categories

See Tables 6, 7 and 8.

Table 6 Cognitive/content space
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Table 7 Social/relational space
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Table 8 Affective space
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Nieswandt, M., McEneaney, E.H. & Affolter, R. A framework for exploring small group learning in high school science classrooms: The triple problem solving space. Instr Sci 48, 243–290 (2020). https://doi.org/10.1007/s11251-020-09510-9

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