Skip to main content
SpringerLink
Log in

Students’ Progression in Monitoring Anomalous Results Obtained in Inquiry-Based Laboratory Tasks

  • Published:
Research in Science Education Aims and scope Submit manuscript

Abstract

This paper examines students’ engagement in monitoring anomalous results across a 2-year longitudinal study with 9th and 10th graders (14–15 and 15–16 years of age). The context is a set of five inquiry-based laboratory tasks, requiring students to plan and carry out investigations. The study seeks to examine students’ interpretation of data, in particular anomalous results generated by them during the process of solving the tasks, and their ability to monitor them. Data collected include video and audio recordings as well as students’ written products. For the analysis, two rubrics were developed drawing on Chinn and Brewer (Cognition and Instruction, 19, 323–393, 2001) and Hmelo-Silver et al. (Science Education, 86, 219–243, 2002). The findings point to a pattern of progress in students’ responses across the 2 years: (a) responses revealing a low capacity of monitoring due to not recognizing the data as anomalous or recognizing it as anomalous but being unable to explain their causes are more frequent in the first tasks and (b) responses revealing an improved capacity of monitoring are more frequent in the last tasks. The factors influencing students’ regulation of their performances, as the requirement of planning, and specific scaffolding based on activity theory are discussed.

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

Access this article

Log in via an institution

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

References

  • Achieve. (2013). Next Generation Science Standards (NGSS). Washington, DC: The National Academies Press.

    Google Scholar 

  • Boekaerts, M., & Cascallar, E. (2006). How far have we moved toward the integration of theory and practice in self-regulation? Educational Psychologist Review, 18, 199–210.

    Article  Google Scholar 

  • Chan, C., Burtis, J., & Bereiter, C. (1997). Knowledge building as a mediator of conflict in conceptual change. Cognition and Instruction, 15(1), 1–40.

    Article  Google Scholar 

  • Chika, N., Obodo, A. C., & Okafor, G. (2015). Effect of self regulated learning approach on junior secondary school students’ achievement in basic science. Journal of Education and Practice, 6(5), 45–52.

    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 

  • Chinn, C. A., & Brewer, W. F. (1998). An empirical test of a taxonomy of responses to anomalous data in science. Journal of Research in Science Teaching, 35, 623–654.

    Article  Google Scholar 

  • Chinn, C. A., & Brewer, W. F. (2001). Models of data: a theory of how people evaluate data. Cognition and Instruction, 19, 323–393.

    Article  Google Scholar 

  • Chinn, C. A., & Malhotra, B. (2002). Children’s responses to anomalous scientific data: how is conceptual change impeded? Journal of Educational Psychology, 94(2), 327–343.

    Article  Google Scholar 

  • Coleman, A. B., Lam, D. P., & Soowal, L. N. (2015). Correlation, necessity, and sufficiency: common errors in the scientific reasoning of undergraduate students for interpreting experiments. Biochemistry and Molecular Biology Education, 43(5), 305–315.

    Article  Google Scholar 

  • Creswell, J. W. (2005). Educational research. Planning, conducting, and evaluating quantitative and qualitative research (2nd ed.). New Jersey: Pearson.

    Google Scholar 

  • Crujeiras-Pérez, B., & Jiménez-Aleixandre, M.P. (2017). High school students' engagement in planning investigations: findings from a longitudinal study in Spain. Chemistry Education Research and Practice, 18(1), 99-112.

  • Davis, J. P. (2017). Emotions, social beings and ethnomethods: understanding analogical reasoning in everyday science classrooms. In A. Bellocchi, K. Otrel-Cass, & C. Quigley (Eds.), Exploring emotions, aesthetics and wellbeing in science education research (pp. 121–140). Dordrecht: Springer. doi: 10.1007/978-3-319-43353-0_7

  • Delen, I., & Krajcik, J. (2015). What do students’ explanations look like when they use secondary data? International Journal of Science Education, 37(12), 1953–1973.

    Article  Google Scholar 

  • Denzin, N. K., & Lincoln, Y. S. (2000). The discipline and practice of qualitative research. In N. K. Denzin & Y. S. Lincoln (Eds.), Handbook of qualitative research (2nd ed., pp. 1–28). California: Sage Publications.

    Google Scholar 

  • Dewey, J. (1997). Democracy and education: an introduction to the philosophy of education. New York: The Free Press.

    Google Scholar 

  • Duschl, R. A. (1990). Restructuring science education: the importance of theories and their development. New York: Teachers College Press.

    Google Scholar 

  • Duschl, R. A. (2008). Science education in three-part harmony: balancing conceptual, epistemic, and social learning goals. Review of Research in Education, 32, 268–291.

    Article  Google Scholar 

  • Duschl, R. A., & Bybee, R. W. (2014). Planning and carrying out investigations: an entry to learning and to teacher professional development around NGSS science and engineering practice. International Journal of STEM Education, 1(12), 1–9.

    Google Scholar 

  • Etkina, E., Karelina, A., Ruibal-Villasenor, M., Rosengrant, D., Jordan, R., & Hmelo-Silver, C. (2010). Design and reflection help students develop scientific abilities: learning in introductory physics laboratories. Journal of the Learning Sciences, 19(1), 54–98.

    Article  Google Scholar 

  • Gee, J. P. (2005). An introduction to discourse analysis: theory and method. London: Routledge.

    Google Scholar 

  • Gee, J. P., & Handford, M. (2012). The Routledge handbook of discourse analysis. Oxon: Routledge.

    Google Scholar 

  • Guba, E., & Lincoln, Y. (1989). Fourth generation evaluation. Beverly Hills: Sage.

    Google Scholar 

  • Hmelo-Silver, C., Nagarajan, A., & Day, R. S. (2002). “It’s harder than we thought it would be”: a comparative case study of expert-novice experimentation strategies. Science Education, 86, 219–243.

    Article  Google Scholar 

  • Hug, B., & McNeill, K. (2008). Use of primary and secondary data in science: does data type influence classroom conversations? International Journal of Science Education, 30(13), 1725–1751.

    Article  Google Scholar 

  • Ibáñez, V. E., & Gómez Alemany, I. (2005). Interaction and regulation of the learning processes in the Science classroom: analysis of an experience. Enseñanza de las Ciencias, 23(1), 97–110.

  • 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(3), 463–481.

    Article  Google Scholar 

  • Jeong, H., Songer, N. B., & Lee, S.-Y. (2007). Evidentiary competence: sixth graders’ understanding for gathering and interpreting evidence in scientific investigations. Research in Science Education, 37, 75–97.

    Article  Google Scholar 

  • Kanari, Z., & Millar, R. (2004). Reasoning from data: how students collect and interpret data in science investigations. Journal of Research in Science Teaching, 41(7), 748–769.

    Article  Google Scholar 

  • Kelly, G. J. (2008). Inquiry, activity and epistemic practice. In R. A. Duschl & R. E. Grandy (Eds.), Teaching scientific inquiry (pp. 99–117). Rotterdam: Sense Publishers.

    Google Scholar 

  • Lin, J.-Y. (2007). Responses to anomalous data obtained from repeatable experiments in the laboratory. Journal of Research in Science Teaching, 44(3), 506–528.

    Article  Google Scholar 

  • Lubben, F., & Millar, R. (1996). Children’s ideas about the reliability of experimental data. International Journal of Science Education, 18(8), 955–968.

    Article  Google Scholar 

  • Manlove, S., Lazonder, A. W., & de Jong, T. (2007). Software scaffolds to promote regulation during scientific inquiry learning. Metacognition Learning, 2, 141–155.

    Article  Google Scholar 

  • Mason, L. (2001). Responses to anomalous data on controversial topics and theory change. Learning and Instruction, 11(6), 453–483.

    Article  Google Scholar 

  • Mayring, P. (2007). On generalization in qualitatively oriented research. Forum: Qualitative Social Research, 8(3), Art. 26 http://nbn-resolving.de/urn:nbn:de:0114-fqs0703262.

    Google Scholar 

  • Millar, R., & Lubben, F. (1996). Knowledge and action: students’ understanding of the procedures of scientific enquiry. In G. Welford, J. Osborne, & P. Scott (Eds.), Research in science education in Europe. Current issues and themes (pp. 191–199). London: Falmer Press.

    Google Scholar 

  • National Research Council. (2012). A framework for K-12 science education: practices, crosscutting concepts, and core ideas. Committee on a Conceptual Framework for New K-12 Science Education Standards. Washington, DC: The National Academies Press.

    Google Scholar 

  • Nielsen, W. S., Nashon, S., & Anderson, D. (2009). Metacognitive engagement during field-trip experiences: a case study of students in an amusement park physics program. Journal of Research in Science Teaching, 46(3), 265–288.

    Article  Google Scholar 

  • Organisation for Economic Cooperation and Development (OECD). (2006). Assessing scientific, reading and mathematical literacy: a framework for PISA 2006. Paris: Author.

    Google Scholar 

  • Organisation for Economic Cooperation and Development (OECD). (2013). PISA 2015 draft science framework. Paris: OECD.

    Google Scholar 

  • Palincsar, A. S., & Magnusson, S. J. (2001). The interplay of primary and secondary investigations to model and support the development of scientific knowledge and reasoning. In S. M. Carver & D. Klahr (Eds.), Cognition and instruction: twenty-five years of progress (pp. 151–193). Mahwah: Lawrence Erlbaum Associates.

    Google Scholar 

  • Pickering, M., & Monts, D. L. (1982). How students reconcile discordant data: a study of lab report discussions. Journal of Chemical Education, 59, 794–796.

    Article  Google Scholar 

  • Reiser, B. J., Berland, L. K., & Kenyon, L. (2012). Engaging students in scientific practices of explanation and argumentation. Science and Children, 49(8), 8–13.

    Google Scholar 

  • Roth, W. M. (2013). What more in/for science education: an ethnomethodological perspective. Rotterdam: Sense Publishers.

    Book  Google Scholar 

  • Ryoo, K., & Linn, M. C. (2016). Designing automated guidance for concept diagrams in inquiry instruction. Journal of Research in Science Teaching, 53(7), 1003–1035.

    Article  Google Scholar 

  • Schraw, G., Crippen, K. J., & Hartley, K. (2006). Promoting self-regulation in science education: metacognition as part of a broader perspective on learning. Research in Science Education, 36, 111–139.

    Article  Google Scholar 

  • Schultheis, E. H., & Kjelvik, M. K. (2015). Data nuggets: bringing real data into the classroom to unearth students’ quantitative & inquiry skills. The American Biology Teacher, 77(1), 19–29.

    Article  Google Scholar 

  • Schunk, D. (1996). Goal and self-evaluative influences during children’s cognitive skill learning. American Educational Research Journal, 33(2), 359–382.

    Article  Google Scholar 

  • Schwab, J. J. (1962). The teaching of science as inquiry. In J. J. Schwab & P. F. Brandwein (Eds.), The teaching of science (pp. 1–103). Massachusetts: Harvard University Press.

    Google Scholar 

  • Shepardson, D. P., & Moje, E. B. (1999). The role of anomalous data in restructuring fourth graders’ frameworks for understanding electric circuits. International Journal of Science Education, 21(1), 77–94.

    Article  Google Scholar 

  • Silverman, D. (2000). Doing qualitative research: a practical handbook. London: Sage.

    Google Scholar 

  • Snape, D., & Spencer, L. (2003). The foundations of qualitative research. In J. Ritchie & J. Lewis (Eds.), Qualitative research practice. A guide for social science students and researchers (pp. 1–23). London: Sage publications.

    Google Scholar 

  • Toplis, R. (2007). Evaluating science investigations at ages 14–16: dealing with anomalous results. International Journal of Science Education, 29(2), 127–150.

    Article  Google Scholar 

  • Ucan, S., & Webb, M. (2015). Social regulation of learning during collaborative inquiry learning in science: how does it emerge and what are its functions? International Journal of Science Education, 37(15), 2503–2532.

    Article  Google Scholar 

  • Weinstein, C. E., Husman, J., & Dierking, D. R. (2000). Self-regulation interventions with a focus on learning strategies. In M. Boekaerts, P. R. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation (pp. 727–747). San Diego: Elsevier Academic Press.

    Chapter  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 

  • Zimmerman, B. (2000). Attaining self-regulated learning: a social–cognitive perspective. In M. Boekaerts, P. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation (pp. 13–39). San Diego: Academic Press.

    Chapter  Google Scholar 

  • Zimmerman, B. J. (2001). Theories of self-regulated learners and academic achievement. An overview and analysis. In B. J. Zimmerman & D. H. Schunk (Eds.), Self-regulated learning and academic achievement: theoretical perspectives (pp. 1–38). Mahwah: Erlbaum.

    Google Scholar 

  • Zimmerman, B. J., & Schunk, D. (2011). Self-regulated learning and performance: an introduction and an overview. In B. J. Zimmerman & D. Schunk (Eds.), Handbook of self-regulation of learning and performance (pp. 1–12). New York: Routledge.

    Google Scholar 

  • Zohar, A. (2006). The nature and development of teachers’ meta-strategic knowledge in the context of teaching higher order thinking. The Journal of the Learning Sciences, 15(3), 331–377.

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by the Spanish Ministerio de Economía y Competitividad (MINECO). Contract grant number: EDU2015-66643-C2-2-P. The authors thank the students and the teacher who participated in the study.

Author information

Authors and Affiliations

  1. Departamento de didácticas aplicadas, Facultade de Formación do Profesorado, Universidade de Santiago de Compostela, Lugo, Spain

    Beatriz Crujeiras-Pérez

  2. Departamento de didácticas aplicadas, Facultade de Ciencias da Educación, Universidade de Santiago de Compostela, Santiago de Compostela, Spain

    Maria Pilar Jiménez-Aleixandre

Authors
  1. Beatriz Crujeiras-Pérez
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Maria Pilar Jiménez-Aleixandre
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Beatriz Crujeiras-Pérez.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Crujeiras-Pérez, B., Jiménez-Aleixandre, M.P. Students’ Progression in Monitoring Anomalous Results Obtained in Inquiry-Based Laboratory Tasks. Res Sci Educ 49, 243–264 (2019). https://doi.org/10.1007/s11165-017-9641-3

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11165-017-9641-3

Keywords

Search

Navigation