Skip to main content
Log in

Measuring Science Instructional Practice: A Survey Tool for the Age of NGSS

  • Published:
Journal of Science Teacher Education

Abstract

Ambitious efforts are taking place to implement a new vision for science education in the United States, in both Next Generation Science Standards (NGSS)-adopted states and those states creating their own, often related, standards. In-service and pre-service teacher educators are involved in supporting teacher shifts in practice toward the new standards. With these efforts, it will be important to document shifts in science instruction toward the goals of NGSS and broader science education reform. Survey instruments are often used to capture instructional practices; however, existing surveys primarily measure inquiry based on previous definitions and standards and with a few exceptions, disregard key instructional practices considered outside the scope of inquiry. A comprehensive survey and a clearly defined set of items do not exist. Moreover, items specific to the NGSS Science and Engineering practices have not yet been tested. To address this need, we developed and validated a Science Instructional Practices survey instrument that is appropriate for NGSS and other related science standards. Survey construction was based on a literature review establishing key areas of science instruction, followed by a systematic process for identifying and creating items. Instrument validity and reliability were then tested through a procedure that included cognitive interviews, expert review, exploratory and confirmatory factor analysis (using independent samples), and analysis of criterion validity. Based on these analyses, final subscales include: Instigating an Investigation, Data Collection and Analysis, Critique, Explanation and Argumentation, Modeling, Traditional Instruction, Prior Knowledge, Science Communication, and Discourse.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2

Similar content being viewed by others

Notes

  1. Although it is difficult to precisely measure the cognitive level in any given task in a survey instrument (Tekkumru Kisa et al., 2015), the delineations described in this instrument represent a reasonable step toward attending to levels of cognitive involvement in the practices examined.

References

  • Abd-El-Khalick, F., Boujaoude, S., Duschl, R. A., Lederman, N. G., Mamlok-Naaman, R., Hofstein, A., & Tuan, H.-L. (2004). Inquiry in science education: International perspectives. Science Education, 88, 397–419.

    Article  Google Scholar 

  • Allen, M. J., & Yen, W. M. (1979). Introduction to measurement theory. Monterey, CA: Brooks-Cole.

    Google Scholar 

  • Anderson, R. D. (2002). Reforming science teaching: What research says about inquiry. Journal of Science Teacher Education, 13, 1–12.

    Article  Google Scholar 

  • Au, W. (2007). High-stakes testing and curricular control: A qualitative metasynthesis. Educational Researcher, 36(5), 258–267.

    Article  Google Scholar 

  • Bandalos, D. L., & Finney, S. J. (2010). Factor analysis: Exploratory and confirmatory. In G. R. Hancock & R. O. Mueller (Eds.), The reviewer’s guide to quantitative methods in the social sciences (pp. 93–114). New York: Routledge.

    Google Scholar 

  • Banilower, E. R., Heck, D. J., & Weiss, I. R. (2007). Can professional development make the vision of the standards a reality? The impact of the national science foundation’s local systemic change through teacher enhancement initiative. Journal of Research in Science Teaching, 44, 375–395.

    Article  Google Scholar 

  • Banilower, E. R., Smith, S. P., Weiss, I. R., Malzahn, K. A., Campbell, K. M., & Weis, A. M. (2013). Report of the 2012 national survey of science and mathematics education. Chapell Hill, NC: Horizon Research.

    Google Scholar 

  • Bartholomew, H., Osborne, J., & Ratcliffe, M. (2004). Teaching students “ideas-about-science”: Five dimensions of effective practice. Science Education, 88, 655–682.

    Article  Google Scholar 

  • Burstein, L., McDonnell, L. M., Van Winkle, J., Ormseth, T., Mirocha, J., & Guitón, G. (1995). Validating national curriculum indicators. Santa Monica, CA: RAND Corporation.

    Google Scholar 

  • Calabrese Barton, A. (2002). Learning about transformative research through others’ stories: What does it mean to involve “others” in science education reform? Journal of Research in Science Teaching, 39, 110–113.

    Article  Google Scholar 

  • Calabrese Barton, A., Tan, E., & Rivet, A. (2008). Creating hybrid spaces for engaging school science among urban middle school girls. American Educational Research Journal, 45(1), 68–103.

    Article  Google Scholar 

  • Campbell, T., Abd-Hamid, N. H., & Chapman, H. (2010). Development of instruments to assess teacher and student perceptions of inquiry experiences in science classrooms. Journal of Science Teacher Education, 21, 13–30.

    Article  Google Scholar 

  • Canale, M., & Swain, M. (1980). Theoretical bases of communicative approaches to second language teaching and testing. Applied Linguistics, 1, 1–47.

    Article  Google Scholar 

  • Capps, D. K., & Crawford, B. A. (2013). Inquiry-based instruction and teaching about nature of science: Are they happening? Journal of Science Teacher Education, 24, 497–526.

    Article  Google Scholar 

  • Center on Education Policy. (2007). Choices, changes, and challenges: Curriculum and instruction in the NCLB era. Washington, DC: Center on Education Policy.

    Google Scholar 

  • Crocker, L., & Algina, J. (1986). Introduction to classical and modern test theory. Orlando, FL: Holt, Rinehart and Winston.

    Google Scholar 

  • Cuban, L. (2013). Inside the black box of classroom practice: Change without reform in American education. Cambridge, MA: Harvard Education Press.

    Google Scholar 

  • Desimone, L. M., & Le Floch, K. C. (2004). Are we asking the right questions? Using cognitive interviews to improve surveys in education research. Educational Evaluation and Policy Analysis, 26, 1–22.

    Article  Google Scholar 

  • Desimone, L. M., Porter, A. C., Garet, M. S., Yoon, K. S., & Birman, B. F. (2002). Effects of professional development on teachers’ instruction: Results from a three-year longitudinal study. Educational Evaluation and Policy Analysis, 24, 81–112.

    Article  Google Scholar 

  • Dorph, R., Sheilds, P., Tiffany-Morales, J., Hartry, A., & McCaffrey, T. (2011). High hopes-few opportunities: The status of elementary science education in California. Sacramento, CA: The Center for the Future of Teaching and Learning at WestEd.

    Google Scholar 

  • Driver, R., Asoko, H., Leach, J., Scott, P., & Mortimer, E. (1994). Constructing scientific knowledge in the classroom. Educational Researcher, 23(7), 5–12.

    Article  Google Scholar 

  • Driver, R., Newton, P., & Osborne, J. (2000). Establishing the norms of scientific argumentation in classrooms. Science Education, 84, 287–312.

    Article  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 

  • Forbes, C. T., Biggers, M., & Zangori, L. (2013). Investigating essential characteristics of scientific practices in elementary science learning environments: The practices of science observation protocol (P-SOP). School Science and Mathematics, 113, 180.

    Article  Google Scholar 

  • Garet, M. S., Birman, B. F., Porter, A. C., Desimone, L., & Herman, R. (1999). Designing effective professional development: Lessons from the Eisenhower Program [and] technical appendices. Jessup, MD: Editorial Publications Center, US Department of Education.

    Google Scholar 

  • Germuth, A., Banilower, E., & Shimkus, E. (2003). Test-retest reliability of the Local Systemic Change teacher questionnaire. Chapel Hill, NC: Horizon Research.

    Google Scholar 

  • Gogol, K., Brunner, M., Goetz, T., Martin, R., Ugen, S., Keller, U., … Preckel, F. (2014). ”My Questionnaire is Too Long!” The assessments of motivational-affective constructs with three-item and single-item measures. Contemporary Educational Psychology, 34, 188–205.

    Article  Google Scholar 

  • Hayes, K. N., & Trexler, C. J. (2016). Testing predictors of instructional practice in elementary science education: The significant role of accountability. Science Education. (in press).

  • Hill, L., & Betz, D. (2005). Revisiting the retrospective pretest. American Journal of Evaluation, 26(4), 501–517.

    Article  Google Scholar 

  • Hogan, K., Nastasi, B. K., & Pressley, M. (1999). Discourse patterns and collaborative scientific reasoning in peer and teacher-guided discussions. Cognition and Instruction, 17, 379.

    Article  Google Scholar 

  • Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6, 1–55.

    Article  Google Scholar 

  • Huffman, D., Thomas, K., & Lawrenz, F. (2003). Relationship between professional development, teachers’ instructional practices, and the achievement of students in science and mathematics. School Science and Mathematics, 103, 378–387.

    Article  Google Scholar 

  • Jiménez-Aleixandre, M. P., & Erduran, S. (2007). Argumentation in science education: An overview. In S. Erduran & M. P. Jiménez-Aleixandre (Eds.), Argumentation in science education: Perspectives from classroom-based research (pp. 3–27). Berlin: Springer.

    Chapter  Google Scholar 

  • Klein, S., Hamilton, L., McCaffrey, D., Stecher, B., Robyn, A., & Burroughs, D. (2000). Teaching practices and student achievement: Report of first-year findings from the “Mosaic” study of Systemic Initiatives in Mathematics and Science. Santa Monica, CA: Rand Corporation.

    Google Scholar 

  • Krathwohl, D. R. (2002). A revision of Bloom’s taxonomy: An overview. Theory into practice, 41(4), 212–218.

    Article  Google Scholar 

  • Kuhn, D. (2015). Thinking together and alone. Educational Researcher, 44, 46–53.

    Article  Google Scholar 

  • Lee, C. D., Luykx, A., Buxton, C., & Shaver, A. (2007). The challenge of altering elementary school teachers’ beliefs and practices regarding linguistic and cultural diversity in science instruction. Journal of Research in Science Teaching, 44, 1269–1291.

    Article  Google Scholar 

  • Lee, O., Maerten-Rivera, J., Buxton, C., Penfield, R., & Secada, W. G. (2009). Urban elementary teachers’ perspectives on teaching science to English language learners. Journal of Science Teacher Education, 20, 263–286.

    Article  Google Scholar 

  • Lemke, J. L. (2001). Articulating communities: Sociocultural perspectives on science education. Journal of Research in Science Teaching, 38(3), 296–316.

    Article  Google Scholar 

  • Lemke, J. (2004). The literacies of science. In E. W. Saul (Ed.), Crossing borders in literacy and science instruction: Perspectives on theory and practice. Newark, DE: International Reading Association.

    Google Scholar 

  • Llewellyn, D. (2013). Teaching high school science through inquiry and argumentation. Thousand Oaks, CA: Corwin.

    Google Scholar 

  • Marsh, H. W. (1986). Global self-esteem: Its relation to specific facets of self-concept and their importance. Journal of Personality and Social Psychology, 51(6), 1224.

    Article  Google Scholar 

  • Marsh, H. W., Hau, K.-T., & Wen, Z. (2004). In search of golden rules: Comment on hypothesis-testing approaches to setting cutoff values for fit indexes and dangers in overgeneralizing Hu and Bentler’s (1999) findings. Structural Equation Modeling, 11, 320–341.

    Article  Google Scholar 

  • Marshall, J. C., Smart, J., & Horton, R. M. (2009). The design and validation of EQUIP: An instrument to assess inquiry-based instruction. International Journal of Science and Mathematics Education, 8, 299–321.

    Article  Google Scholar 

  • Matsunaga, M. (2010). How to factor-analyze your data right: Do’s, don’ts, and how-to’s. International Journal of Psychological Research, 3(1), 97–110.

    Google Scholar 

  • McGinn, M. K., & Roth, W. M. (1999). Preparing students for competent scientific practice: Implications of recent research in science and technology studies. Educational Researcher, 28, 14–24.

    Article  Google Scholar 

  • McNeill, K. L., & Krajcik, J. (2008). Scientific explanations: Characterizing and evaluating the effects of teachers’ instructional practices on student learning. Journal of Research in Science Teaching, 45, 53–78.

    Article  Google Scholar 

  • Moll, L., Amanti, C., Neff, D., & Gonzalez, N. (1992). Funds of knowledge for teaching, using a qualitative approach to connect homes and classrooms. Theory into Practice, 31(2), 132–141.

    Article  Google Scholar 

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

    Google Scholar 

  • National Research Council (NRC). (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 (NRC). (2013). Next generation science standards: For states, by states. Washington, DC: The National Academies Press.

    Google Scholar 

  • Norris, S., Philips, L., & Osborne, J. (2008). Scientific inquiry: The place of interpretation and argumentation. In J. Luft, R. L. Bell, & J. Gess-Newsome (Eds.), Science as inquiry in the secondary setting (pp. 87–98). Arlington, VA: NSTA Press.

    Google Scholar 

  • President’s Council of Advisors on Science and Technology (PCAST). (2010). Report to the President: Prepare and inspire: K-12 education in science, technology, engineering, and mathematics (STEM) for America’s future. Washington, DC: Executive Office of the President. http://www.whitehouse.gov/sites/default/files/microsites/ostp/pcast-stemed-report.pdf

  • Rea, L. M., & Parker, R. A. (2005). Designing and conducting survey research: A comprehensive guide. San Francisco: Jossey-Bass.

    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(8), 839–858.

    Article  Google Scholar 

  • Rosebery, A. S., Warren, B., & Conant, F. R. (1992). Appropriating scientific discourse: Findings from language minority classrooms. The Journal of the Learning Sciences, 2, 61–94.

    Article  Google Scholar 

  • Schwarz, C. V., Reiser, B. J., Davis, E. A., Kenyon, L., Achér, A., Fortus, D., … Krajcik, J. (2009). Developing a learning progression for scientific modeling: Making scientific modeling accessible and meaningful for learners. Journal of Research in Science Teaching, 46(6), 632–654.

    Article  Google Scholar 

  • Smith, M. S. (2000). Balancing old and new: An experienced middle school teacher’s learning in the context of mathematics instructional reform. The Elementary School Journal, 100(4), 351–375.

  • Smolleck, L. D., Zembal-Saul, C., & Yoder, E. P. (2006). The development and validation of an instrument to measure preservice teachers’ self-efficacy in regard to the teaching of science as inquiry. Journal of Science Teacher Education, 17, 137–163.

    Article  Google Scholar 

  • Stapleton, L. M. (2010). Survey sampling, administration, and analysis. In G. R. Hancock & R. O. Mueller (Eds.), The reviewer’s guide to quantitative methods in the social sciences (pp. 399–412). New York: Routledge.

    Google Scholar 

  • Stewart, J., Cartier, J. L., & Passmore, C. M. (2005). Developing understanding through model-based inquiry. In S. Donovan & J. D. Bransford (Eds.), How students learn: Science in the classroom (pp. 515–565). Washington, DC: National Academies Press.

  • Supovitz, J. A., & Turner, H. M. (2000). The effects of professional development on science teaching practices and classroom culture. Journal of Research in Science Teaching, 37(9), 963–980.

    Article  Google Scholar 

  • Tekkumru Kisa, M. T., & Stein, M. K. (2015). Learning to see teaching in new ways: A foundation for maintaining cognitive demand. American Educational Research Journal, 52(1), 105–136.

    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, 659–685.

    Article  Google Scholar 

  • Thorndike, R. M., & Thorndike-Christ, T. (2010). Measurement and evaluation in psychology and education (8th ed.). Boston: Pearson, Merrill.

    Google Scholar 

  • Walczyk, J. J., & Ramsey, L. L. (2003). Use of learner-centered instruction in college science and mathematics classrooms. Journal of Research in Science Teaching, 40, 566–584.

    Article  Google Scholar 

  • Wertsch, J. V. (1985). Vygotsky and the social formation of mind. Cambridge, MA: Harvard University Press.

    Google Scholar 

  • Zimmerman, C. (2007). The development of scientific thinking skills in elementary and middle school. Developmental Review, 27, 172–223.

    Article  Google Scholar 

Download references

Acknowledgments

This work was supported by the National Science Foundation Grant No. 0962804.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Kathryn N. Hayes.

Appendix: Final Survey

Appendix: Final Survey

Instructional approaches

How often do your students do each of the following in your science classes?

Never

Rarely (a few times a year)

Sometimes (once or twice a month)

Often (once or twice a week)

Daily or almost daily

1. Generate questions or predictions to explore

1

2

3

4

5

2. Identify questions from observations of phenomena

1

2

3

4

5

3. Choose variables to investigate (such as in a lab setting)

1

2

3

4

5

4. Design or implement their OWN investigations

1

2

3

4

5

5. Make and record observations

1

2

3

4

5

6. Gather quantitative or qualitative data

1

2

3

4

5

7. Organize data into charts or graphs

1

2

3

4

5

8. Analyze relationships using charts or graphs

1

2

3

4

5

9. Analyze results using basic calculations

1

2

3

4

5

10. Write about what was observed and why it happened

1

2

3

4

5

11. Present procedures, data and conclusions to the class (either informally or in formal presentations)

1

2

3

4

5

12. Read from a science textbook or other hand-outs in class

1

2

3

4

5

13. Critically synthesize information from different sources (i.e., text or media)

1

2

3

4

5

14. Create a physical model of a scientific phenomenon (like creating a representation of the solar system)

1

2

3

4

5

15. Develop a conceptual model based on data or observations (model is not provided by textbook or teacher)

1

2

3

4

5

16. Use models to predict outcomes

1

2

3

4

5

17. Explain the reasoning behind an idea

1

2

3

4

5

18. Respectfully critique each others’ reasoning

1

2

3

4

5

19. Supply evidence to support a claim or explanation

1

2

3

4

5

20. Consider alternative explanations

1

2

3

4

5

21. Make an argument that supports or refutes a claim

1

2

3

4

5

How often do you do each of the following in your science instruction?

Never

Rarely (a few times a year)

Sometimes (once or twice a month)

Often (once or twice a week)

Daily or almost daily

1. Provide direct instruction to explain science concepts

1

2

3

4

5

2. Demonstrate an experiment and have students watch

1

2

3

4

5

3. Use activity sheets to reinforce skills or content

1

2

3

4

5

4. Go over science vocabulary

1

2

3

4

5

5. Apply science concepts to explain natural events or real-world situations

1

2

3

4

5

6. Talk with your students about things they do at home that are similar to what is done in science class (e.g., measuring, boiling water)

1

2

3

4

5

7. Discuss students’ prior knowledge or experience related to the science topic or concept

1

2

3

4

5

8. Use open-ended questions to stimulate whole class discussion (most students participate)

1

2

3

4

5

9. Have students work with each other in small groups

1

2

3

4

5

10. Encourage students to explain concepts to one another

1

2

3

4

5

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hayes, K.N., Lee, C.S., DiStefano, R. et al. Measuring Science Instructional Practice: A Survey Tool for the Age of NGSS. J Sci Teacher Educ 27, 137–164 (2016). https://doi.org/10.1007/s10972-016-9448-5

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10972-016-9448-5

Keywords

Navigation