Skip to main content

Intellectual Work Required of Students in Science Classrooms: Students’ Opportunities to Learn Science

Abstract

Students’ opportunities to learn science are shaped by the intellectual work in which they engage in science classrooms. By considering the opportunity to learn as a more nuanced and complex concept than simply as exposure to the subject matter, we argue that the kind of tasks that teachers assign to students presents an important element to understand how students are positioned to learn in science classrooms. Teachers, undoubtedly, play a critical role in the selection of these instructional tasks. This study aims to investigate the cognitive demand of science tasks and teachers’ reasoning for what makes these tasks cognitively demanding. Guided by a framework, which was designed to classify science tasks according to cognitive demand and the integration of science content and practices, we analyzed 224 science tasks shared by 125 teachers through a statewide survey. The analyses revealed many of the science tasks, which were identified by teachers as demanding high-level intellectual work from students and were classified into low-level categories of this framework. The qualitative analyses of teachers’ responses to survey questions revealed the factors that influenced science teachers’ decisions about the cognitive demand of instructional tasks.

This is a preview of subscription content, access via your institution.

Fig. 1

References

  • Banilower, E. R., Smith, P. S., Malzahn, K. A., Plumley, C. L., Gordon, E. M., & Hayes, M. L. (2018). Report of the 2018 NSSME+. Chapel Hill: Horizon Research, Inc..

    Google Scholar 

  • Blumenfeld, P. C. (1992). The task and the teacher: Enhancing student thoughtfulness in science. Advances in Research on Teaching, 3, 81–114.

    Google Scholar 

  • Boston, M. D. (2014). Assessing instructional quality in mathematics classrooms through collections of students’ work. In Y. Li, E. A. Silver, & S. Li (Eds.), Transforming mathematics instruction (pp. 501–523). Switzerland: Springer International Publishing.

    Google Scholar 

  • Carroll, J. B. (1963). A model of school learning. Teachers College Record, 64(8), 723–733.

  • Cartier, J. L., Smith, M. S., Stein, M. K., & Ross, D. K. (2013). 5 practices for orchestrating productive task-based discussions in science. Reston: National Council of Teachers of Mathematics.

    Google Scholar 

  • Chinn, C. A., & Malhotra, B. A. (2002). Epistemologically authentic inquiry in schools: a theoretical framework for evaluating inquiry tasks. Science Education, 86(2), 175–218.

    Article  Google Scholar 

  • Doyle, W. (1983). Academic work. Review of Educational Research, 53(2), 159.

    Article  Google Scholar 

  • Doyle, W. (1988). Work in mathematics classes: The context of students' thinking during instruction. Educational Psychologist, 23(2), 167–180.

  • European Commission. (2015). Science education for responsible citizens. Luxembourg: European Union. https://doi.org/10.2777/12626.

    Book  Google Scholar 

  • Floden, R. (2002). The measurement of opportunity to learn. In A. Porter & A. Gamoran (Eds.), Methodological advances in cross-national surveys of educational achievement (pp. 231–266). Washington, DC: National Academy Press.

    Google Scholar 

  • Förtsch, C., Werner, S., von Kotzebue, L., & Neuhaus, B. J. (2018). Effects of high-complexity and high-cognitive-level instructional tasks in biology lessons on students’ factual and conceptual knowledge. Research in Science & Technological Education, 36(3), 353–374.

    Article  Google Scholar 

  • Gamoran, A., Porter, A. C., Smithson, J., & White, P. A. (1997). Upgrading high school mathematics instruction: Improving learning opportunities for low-achieving, low-income youth. Educational Evaluation and Policy Analysis, 19(4), 325–338.

    Article  Google Scholar 

  • Germann, P. J., Haskins, S., & Auls, S. (1996). Analysis of nine high school biology laboratory manuals: Promoting scientific inquiry. Journal of Research in Science Teaching, 33(5), 475–499.

    Article  Google Scholar 

  • Gorski, P. C. (2015). Reaching and teaching students in poverty: strategies for erasing the opportunity gap. New York: Teachers College Press.

    Google Scholar 

  • Greeno, J. G., & Gresalfi, M. S. (2008). Opportunities to learn in practice and identity. In P. A. Moss, D. Pullin, J. P. Gee, G. Haertel, & L. J. Young (Eds.), Assessment, equity, and opportunity to learn (pp. 170–199). NewYork: Cambridge University Press.

    Chapter  Google Scholar 

  • Haberman, M. (1991). The pedagogy of poverty versus good teaching. Phi Delta Kappan, 73(4), 290–294. https://doi.org/10.1177/003172171009200223.

    Article  Google Scholar 

  • Hiebert, J., & Wearne, D. (1993). Instructional tasks, classroom discourse, and students’ learning in second-grade arithmetic. American Educational Research Journal, 30(2), 393–425.

    Article  Google Scholar 

  • Hiebert, J., & Grouws, D. A. (2007). The effects of classroom mathematics teaching on students’ learning. Second Handbook of Research on Mathematics Teaching and Learning, 1, 371–404.

    Google Scholar 

  • Hofstein, A., & Lunetta, V. N. (2004). The laboratory in science education: foundations for the twenty-first century. Science Education, 88(1), 28–54.

    Article  Google Scholar 

  • Jackson, K., Garrison, A., Wilson, J., Gibbons, L., & Shahan, E. (2013). Exploring relationships between setting up complex tasks and opportunities to learn in concluding whole-class discussions in middle grades mathematics instruction. Journal for Research in Mathematics Education, 44(4), 646–682.

    Article  Google Scholar 

  • Jones, M. T., & Eick, C. J. (2007). Implementing inquiry kit curriculum: obstacles, adaptations, and practical knowledge development in two middle school science teachers. Science Education, 91(3), 492–513.

    Article  Google Scholar 

  • Kang, H., Windschitl, M., Stroupe, D., & Thompson, J. (2016). Designing, launching, and implementing high quality learning opportunities for students that advance scientific thinking. Journal of Research in Science Teaching, 53(9), 1316–1340.

  • Krajcik, J., Codere, S., Dahsah, C., Bayer, R., & Mun, K. (2014). Planning instruction to meet the intent of the next generation science standards. Journal of Science Teacher Education, 25(2), 157–175.

    Article  Google Scholar 

  • Marx, R. W., & Walsh, J. (1988). Learning from academic tasks. The Elementary School Journal, 88(3), 207–219.

    Article  Google Scholar 

  • Matsumura, L. C., Garnier, H., Slater, S. C., & Boston, M. D. (2008). Toward measuring instructional interactions “at-scale”. Educational Assessment, 13(4), 267–300.

    Article  Google Scholar 

  • Miles, M. B., Huberman, A. M., Huberman, M. A., & Huberman, M. (1994). Qualitative data analysis: An expanded sourcebook. Thousand Oaks: Sage Publishing.

    Google Scholar 

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

    Google Scholar 

  • National Research Council. (2012). A framework for K-12 science education: practices, crosscutting concepts, and core ideas. Washington, DC: The National Academies Press.

    Google Scholar 

  • National Research Council. (2015). Guide to implementing the next generation science standards. Washington, DC: National Academies Press.

    Google Scholar 

  • Remillard, J. T. (1999). Curriculum materials in mathematics education reform: a framework for examining teachers’ curriculum development. Curriculum Inquiry, 29(3), 315–342.

    Article  Google Scholar 

  • Robertson, A. D., Scherr, R., & Hammer, D. (Eds.). (2016). Responsive teaching in science and mathematics. New York: Routledge.

  • Roth, K., & Garnier, H. (2006). What science teaching looks like: an international perspective. Educational Leadership, 64(4), 16.

    Google Scholar 

  • Russo, J. A. (2015). How challenging tasks optimise cognitive load. In Annual conference of the International Group for the Psychology of mathematics education 2015 (pp. 105–112). Praha: International Group for the Psychology of Mathematics Education.

    Google Scholar 

  • Schmidt, W., McKnight, C., & Raizen, S. (1997). A splintered vision: an investigation of U.S. mathematics and science education. Dordrecht: Kluwer.

    Google Scholar 

  • Schneider, R. M., Krajcik, J., & Blumenfeld, P. (2005). Enacting reform-based science materials: the range of teacher enactments in reform classrooms. Journal of Research in Science Teaching, 42(3), 283–312.

    Article  Google Scholar 

  • Schwarz, C. V., Passmore, C. M., & Reiser, B. J. (2017). Moving beyond “knowing” science to making sense of the world. In Helping students make sense of the world using next generation science and engineering practices (pp. 3–21).

    Google Scholar 

  • Stein, M. K., & Lane, S. (1996). Instructional tasks and the development of student capacity to think and reason: an analysis of the relationship between teaching and learning in a reform mathematics project. Educational Research and Evaluation, 2(1), 50–80.

    Article  Google Scholar 

  • Stein, M. K., Grover, B. W., & Henningsen, M. (1996). Building student capacity for mathematical thinking and reasoning: an analysis of mathematical tasks used in reform classroom. American Educational Research Journal, 33(2), 455–488.

    Article  Google Scholar 

  • Sweller, J. (1994). Cognitive load theory, learning difficulty, and instructional design. Learning and Instruction, 4(4), 295–312.

    Article  Google Scholar 

  • Tekkumru-Kisa, M., Stein, M. K., & Schunn, C. (2015). A framework for analyzing cognitive demand and content-practices integration: Task analysis guide in science. Journal of Research in Science Teaching, 52(5), 659–685.

    Article  Google Scholar 

  • Tekkumru-Kisa, M., Schunn, C., & Coker, R. (2017). Promoting teachers' learning to select cognitively demanding science tasks. In Paper presented at the meeting of European science education research association (ESERA). Dublin: Ireland.

    Google Scholar 

  • Tekkumru-Kisa, M., Schunn, C., Stein, M. K., & Reynolds, B. (2019). Change in thinking demands for students across the phases of a science task: An exploratory study. Research in Science Education, 49(3), 859–883.

    Article  Google Scholar 

  • Weiss, I. R., Pasley, J. D., Smith, P. S., Banilower, E. R., & Heck, D. J. (2003). Looking inside the classroom: a study of K−12 mathematics and science education in the United States. Chapel Hill: Horizon Research.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Miray Tekkumru-Kisa.

Additional information

Publisher’s Note

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

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Tekkumru-Kisa, M., Kisa, Z. & Hiester, H. Intellectual Work Required of Students in Science Classrooms: Students’ Opportunities to Learn Science. Res Sci Educ 51, 1107–1121 (2021). https://doi.org/10.1007/s11165-020-09924-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11165-020-09924-y

Keywords

  • Instructional tasks
  • Opportunity to learn
  • Teacher thinking
  • Cognitive demand