Exploring the factorial validity of the beliefs about nature of science questionnaire
Abstract
The purpose of this study was to validate a new questionnaire for assessing students’ beliefs about the nature of science (BANOS). Existing instruments have limitations in terms of psychometric validity. A new questionnaire termed “BANOS” was developed to address such limitations. The BANOS is based on dimensions of the nature of science as a theoretical framework. The BANOS was administered to 860 Grade 12 students in Namibia, using the paper-and-pencil method. Data analysis employed reliability analysis, exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and parallel analysis. The reliability of the BANOS was α = 0.87. EFA revealed a final interpretable five-factor structure, and the factor solution accounted for 67.73% of the total variance. However, parallel analysis revealed that only four factors had eigenvalues that were statistically significant and the resultant scree plot also supported the retention of four factors. CFA results showed that the measurement model had a poor statistical fit for the data. These findings indicate that the eight-dimensional framework could not be confirmed at EFA level. However, the BANOS had adequate construct validity and reliability. Results are discussed in terms of intricate similarities among the dimensions of nature of science.References
Ab Hamid, M, R., Sami, W., & Mohmad Sidek, M, H. (2017). Discriminant Validity Assessment : Use of Fornell & Larcker criterion versus HTMT Criterion. Journal of Physics: Conference Series, 890(12163). https://doi.org/https://doi.org/10.1088/1742-6596/890/1/012163
Abd-El-khalick, F., & Lederman, N. G. (2000). Improving science teachers’ conceptions of nature of science: A critical review of the literature. International Journal of Science Education, 22(7), 665–701. https://doi.org/10.1080/09500690050044044
Abd-El-Khalick, F., Myers, J. Y., Summers, R., Brunner, J., Waight, N., Wahbeh, N., … Belarmino, J. (2017). A longitudinal analysis of the extent and manner of representations of nature of science in U.S. high school biology and physics textbooks. Journal of Research in Science Teaching, 54(1), 82–120. https://doi.org/10.1002/tea.21339
Bell, R. L., Blair, L. M., Crawford, B. A., & Lederman, N. G. (2003). Just do it? Impact of a science apprenticeship program on high school students’ understandings of the nature of science and scientific inquiry. Journal of Research in Science Teaching, 40(5), 487–509. https://doi.org/10.1002/tea.10086
Bell, R. L., Matkins, J. J., & Gansneder, B. M. (2011). Impacts of contextual and explicit instruction on preservice elementary teachers’ understandings of the nature of science. Journal of Research in Science Teaching, 48(4), 414–436. https://doi.org/10.1 002/tea.20402
Cabrera-Nguyen, P. (2010). Author Guidelines for Reporting Scale Development and Validation Results in the Journal of the Society for Social Work and Research. Journal of the Society for Social Work and Research, 1(2), 99–103. https://doi.org/10.5 243/jsswr.2010.8
Chen, J. A. (2012). Implicit theories, epistemic beliefs, and science motivation: A person-centered approach. Learning and Individual Differences, 22(6), 724–735. https://doi.org /10.1016/j.lindif.2012.07.013
Chen, J. A., Metcalf, S. J., & Tutwiler, M. S. (2014). Motivation and beliefs about the nature of scientific knowledge within an immersive virtual ecosystems environment. Contemporary Educational Psychology, 39(2), 112–123. https://doi.org/10.1016 /j.cedpsych.2014.02.004
Chen, S. (2006). Development of an instrument to assess views on nature of science and attitudes toward teaching science. Science Education, 90(5), 803–819. https://doi.org/10.1002/sce.20147
Cohen, L., Manion, L., & Morrison, K. (2007). Research methods in education (Sixth). New York: Routledge.
Conley, A. M. M., Pintrich, P. R., Vekiri, I., & Harrison, D. (2004). Changes in epistemological beliefs in elementary science students. Contemporary Educational Psychology, 29(2), 186–204. https://doi.org/10.1016/j.cedpsych.2004.01.004
Cristobal, E., Flavián, C., & GuinalÃu, M. (2007). Perceived eâ€service quality (PeSQ). Managing Service Quality: An International Journal, 17(3), 317–340. https://doi.org/ 10.1108/09604520710744326
DeBacker, T. K., Crowson, H. M., Beesley, A. D., Thoma, S. J., & Hestevold, N. L. (2008). The challenge of measuring epistemic beliefs: An analysis of three self-report instruments. Journal of Experimental Education, 76(3), 281–312. https://doi.org/10.3200/JEXE. 76.3.281-314
DeVellis, R. F. (2003). Scale development: Theory and applications (2nd ed.). Thousand Oaks, CA: Sage.
Dogan, N., & Abd-El-Khalick, F. (2008). Turkish grade 10 students’ and science teachers’ conceptions of nature of science: A national study. Journal of Research in Science Teaching, 45(10), 1083–1112. https://doi.org/10.1002/tea.20243
Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39. https://doi.org/10.2307/3151312
Garson, G. D. (2015). Structural equation modelling. Asheboro, NC: Statistical Associates Publishers.
Gaskin, J. (2016). Validity master: Stats Tools Package. Retrieved from http://statwiki. kolobkreations.com
Gess-Newsome, J. (2002). The use and impact of explicit instruction about the nature of science and science inquiry in an elementary science methods course. Science and Education, 11(1), 55–67. https://doi.org/10.1023/A:1013054823482
Glynn, S. M., Brickman, P., Armstrong, N., & Taasoobshirazi, G. (2011). Science motivation questionnaire II: Validation with science majors and nonscience majors. Journal of Research in Science Teaching, 48(10), 1159–1176. https://doi.org/10.1002/tea.20442
Hair Jr, J., Black, W., Babin, B., & Anderson, R. (2010). Multivariate data analysis (7th ed.). Upper Saddle River, NJ, USA: Prentice-Hall, Inc.
Hair Jr, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2016). A primer on partial least squares structural equation modeling (PLS-SEM). Sage Publications.
Henson, R. K., & Roberts, J. K. (2006). Use of exploratory factor analysis in published research: Common errors and some comment on improved practice. Educational and Psychological Measurement, 66(3), 393–416. https://doi.org/10.1177/0013164405282485
Hillman, S. J., Zeeman, S. I., Tilburg, C. E., & List, H. E. (2016). My Attitudes Toward Science (MATS): the development of a multidimensional instrument measuring students’ science attitudes. Learning Environments Research, 19(2), 203–219. https://doi.org/10.1007/s1 0984-016-9205-x
Hooper, D., Coughlan, J., & Mullen, M. R. (2008). Structural Equation Modelling : Guidelines for Determining Model Fit. The Electronic Journal of Business Research Methods, 6(1), 53–60.
Huang, C.-C., Wang, Y.-M., Wu, T.-W., & Wang, P.-A. (2013). An Empirical Analysis of the Antecedents and Performance Consequences of Using the Moodle Platform. International Journal of Information and Education Technology, 3(2), 217–221. https://doi.org/10.77 63/IJIET.2013.V3.267
Kampa, N., Neumann, I., Heitmann, P., & Kremer, K. (2016). Epistemological beliefs in science-a person-centered approach to investigate high school students’ profiles. Contemporary Educational Psychology, 46, 81–93. https://doi.org/10.1016/j.ced psych.2016.04.007
Kaya, G. I. (2017). The Relations between Scientific Epistemological Beliefs and Goal Orientations of Pre-Service Teachers. Journal of Education and Training Studies, 5(10), 33. https://doi.org/10.11114/jets.v5i10.2547
Khishfe, R., & Abd-El-Khalick, F. (2002). Influence of explicit and reflective versus implicit inquiry-oriented instruction on sixth graders’ views of nature of science. Journal of Research in Science Teaching, 39(7), 551–578. https://doi.org/10.1002/tea.10036
Leal-Soto, F., & Ferrer-Urbina, R. (2017). Three-factor structure for Epistemic Belief Inventory: A cross-validation study. PLoS ONE, 12(3), 1–16. https://doi.org/10.1371/ journal.pone.0173295
Lederman, J. S., Lederman, N. G., Bartos, S. A., Bartels, S. L., Meyer, A. A., & Schwartz, R. S. (2014). Meaningful assessment of learners’ understandings about scientific inquiry - The views about scientific inquiry (VASI) questionnaire. Journal of Research in Science Teaching, 51(1), 65–83. https://doi.org/10.1002/tea.21125
Lederman, N. G., Abd-El-Khalick, F., Bell, R. L., & Schwartz, R. S. (2002). Views of Nature of Science Questionnaire: Toward Valid and Meaningful Assessment of Learners’ Conceptions of Nature of Science. Journal of Research in Science Teaching, 39(6), 497–521. https://doi.org/10.1002/tea.10034
Lederman, N. G., Lederman, J. S., & Antink, A. (2013). www.ijemst.com Nature of Science and Scientific Inquiry as Contexts for the Learning of Science and Achievement of Scientific Literacy Nature of Science and Scientific Inquiry as Contexts for the Learning of Science and Achievement of Scientific Literacy. International Journal of Education in Mathematics Science and Technology, 1(3), 138–147. https://doi.org/10.18404/ijem st.19784
Lederman, N. G., Wade, P. D., & Bell, R. L. (1998). Assessing the Nature of Science: What is the Nature of Our Assessments? Science and Education. https://doi.org/10.1023 /A:1008601707321
Liang, J. C., & Tsai, C. C. (2010). Relational analysis of college science-major students’ epistemological. International Journal of Science Education, 32(17), 2273–2289. https://doi.org/10.1080/09500690903397796
Lindfors, M., Winberg, M., & Bodin, M. (2017). The Role of Students’ Scientific Epistemic Beliefs in Computer-Simulated Problem Solving. Scandinavian Journal of Educational Research, 0(0), 1–21. https://doi.org/10.1080/00313831.2017.1324907
Malhotra, N. K., & Dash, S. (2011). Marketing Research: An applied orientation. London: Pearson Publishing.
McComas, W. F. (2008). Seeking historical examples to illustrate key aspects of the nature of science. Science and Education, 17(2–3), 249–263. https://doi.org/10.1007/s11191-007-9081-y
McDonald, C. V. (2010). The influence of explicit nature of science and argumentation instruction on preservice primary teachers’ views of nature of science. Journal of Research in Science Teaching, 47(9), 1137–1164. https://doi.org/10.1002/tea.20377
Moss, D. M., Abrams, E. D., & Robb, J. (2001). Examining student conceptions of the nature of science. International Journal of Science Education, 23(8), 771–790. https://doi.org/1 0.1080/09500690010016030
Namibia. Ministry of Education [MoE]. (2010). The national curriculum for basic education.
Niaz, M. (2008). What “ideas-about-science†should be taught in school science? A chemistry teachers’ perspective. Instructional Science, 36(3), 233–249. https://doi.org/10.1007/ s11251-007-9031-8
O’connor, B. P. (2000). SPSS and SAS programs for determining the number of components using parallel analysis and Velicer’s MAP test. Behavior Research Methods, Instruments, & Computers, 32(3), 396–402. https://doi.org/10.3758/BF03200807
Osborne, J., Collins, S., Ratcliffe, M., Millar, R., & Duschl, R. (2003). What “ideas-about-science†should be taught in school science? A delphi study of the expert community. Journal of Research in Science Teaching, 40(7), 692–720. https://doi.org /10.1002/tea.10105
Paechter, M., Rebmann, K., Schloemer, T., Mokwinski, B., Hanekamp, Y., & Arendasy, M. (2013). Development of the Oldenburg Epistemic Beliefs Questionnaire (OLEQ), a German questionnaire based on the Epistemic Belief Inventory (EBI). Current Issues in Education, 16(1), 1–18.
Rebelo-Pinto, T., Pinto, J. C., Rebelo-Pinto, H., & Paiva, T. (2014). Validation of a three-dimensional model about sleep: Habits, personal factors and environmental factors. Sleep Science, 7(4), 197–202. https://doi.org/10.1016/j.slsci.2014.12.002
Schraw, G., Bendixen, L. D., & Dunkle, M. E. (2002). Development and validation of the Epistemic Belief Inventory (EBI). In K. Hofer & P. R. Pintrich (Eds.), Personal epistemology: The psychology of beliefs about knowledge and knowing (pp. 261–275). Mahwah, NJ, US: Lawrence Erlbaum Associates Publishers.
Streiner, D. L., & Streiner, D. L. (2003). Starting at the Beginning : An Introduction to Coefficient Alpha and Internal Consistency Starting at the Beginning : An Introduction to Coefficient Alpha and Internal Consistency. Journal of Personality Assessment, 80(1), 99–103. https://doi.org/10.1207/S15327752JPA8001
Summers, R., & Abd-El-Khalick, F. (2017). Development and validation of an instrument to assess student attitudes toward science across grades 5 through 10. Journal of Research in Science Teaching, 55(2), 172–205. https://doi.org/10.1002/tea.21416
Teo, T. (2013). Examining the Psychometric Properties of the Epistemic Belief Inventory (EBI). Journal of Psychoeducational Assessment, 31(1), 72–79. https://doi.org/ 10.1177/0734282912449436
Tsai, C. C., Jessie Ho, H. N., Liang, J. C., & Lin, H. M. (2011). Scientific epistemic beliefs, conceptions of learning science and self-efficacy of learning science among high school students. Learning and Instruction, 21(6), 757–769. https://doi.org/10.1016/j.learn instruc.2011.05.002
Vhurumuku, E. (2010). The impact of explicit instruction on undergraduate students’ understanding of the nature of science. African Journal of Research in Mathematics, Science and Technology Education, 14(1), 99–111. https://doi.org/10.1080/10288457.2010.10740676
Worthington, R. L., & Whittaker, T. A. (2006). Scale Development Research: A Content Analysis and Recommendations for Best Practices. The Counseling Psychologist, 34(6), 806–838. https://doi.org/10.1177/0011000006288127
