RESEARCH PAPER
Construction and Evaluation of an Instrument to Measure High School Students Biological Content Knowledge
 
More details
Hide details
1
Nazarbayev University, Nur-Sultan, KAZAKHSTAN
 
2
Miami University College of Education, Cincinnati, Ohio, USA
 
3
Ohio State University, College of Education and Human Ecology, Department of Teaching and Learning Columbus, Ohio, USA
 
4
University of Minnesota - Twin Cities, College of Biological Sciences, Department of Biology Teaching and Learning, Minneapolis, Minnesota, USA
 
5
Ohio State University, College of Arts and Sciences, Department of Evolution, Ecology, and Organismal Biology, Columbus, OH, USA
 
 
Publication date: 2021-11-26
 
 
EURASIA J. Math., Sci Tech. Ed 2021;17(12):em2048
 
KEYWORDS
ABSTRACT
Instruments for assessing secondary students’ conceptual understanding of core concepts in biology are needed by educational practitioners and researchers alike. Most instruments available for secondary biology (years 9 to 12) focus only on highly specific biological concepts instead of multiple core concepts. This study describes the development of a 25-item instrument designed to fill this gap, the High School Biology Concept Inventory (HS-BCI). The HS-BCI not only assesses student knowledge of key biological concepts but also alternative conceptions. Using Rasch theory, the initial instrument was constructed from a pool of 61 instrument items using test results from 1015 students. The final 25-item instrument was validated with 1955 students. The results provide reliability and validity evidence for the HS-BCI. The findings suggest that it can be utilized to assess both conceptual knowledge and alternative conceptions.
REFERENCES (68)
1.
AAAS Project 2061 (n.d.). Pilot and field test data collected between 2006 and 2010 (Unpublished raw data).
 
2.
Abate, T., Michael, K., & Angell, C. (2020). Assessment of scientific reasoning: Development and validation of scientific reasoning assessment tool. Eurasia Journal of Mathematics, Science and Technology Education, 16(12), em1927. https://doi.org/10.29333/ejmst....
 
3.
Adeoye, A. G., & Abimbola, O. I. (2016). Effects of senior school students’ use of demo kit on their achievement in biology in Omu-Aran, Nigeria. Electronic Journal of Science Education, 20(8), 88-102. https://ejrsme.icrsme.com/arti....
 
4.
Anderson D. L., Fisher, K. M., & Norman, G. J. (2002). Development and evaluation of the conceptual inventory of natural selection. Journal of Research in Science Teaching, 39(10), 952-978. https://doi.org/10.1002/tea.10....
 
5.
Anderson, C. W., Sheldon, T. H., & Dubay, J. (1990). The effects of instruction on college nonmajors’ conceptions of respiration and photosynthesis. Journal of Research in Science Teaching, 27(8), 761-776. https://doi.org/10.1002/tea.36....
 
6.
Andrich, D., & Marais, I. (2019). A course in Rasch measurement theory. Measuring in the educational, social and health sciences. Springer. https://doi.org/10.1007/978-98....
 
7.
Baghaei, P. (2008). The Rasch model as a construct validation tool. Rasch Measurement Transactions, 22(1), 1145-1146.
 
8.
Barman, C. R., Griffiths, A. K., & Okebukola, P. A. (1995). High school students’ concepts regarding food chains and food webs: A multinational study. International Journal of Science Education, 17(6), 775-782. https://doi-org/10.1080/095006....
 
9.
Berthelsen, B. (1999). Students naïve conceptions in life science. Michigan Science Teachers Association Journal, 44(1), 13-19.
 
10.
Berti, A. E., Barbetta, V., & Toneatti, L. (2017). Third-graders’ conceptions about the origin of species before and after instruction: An exploratory study. International Journal of Science and Mathematics Education, 15(2), 215-232. https://doi.org/10.1007/s10763....
 
11.
Boone, W. J., & Noltemeyer, A. (2017). Rasch analysis: A primer for school psychology researchers and practitioners. Cogent Education, 4(1), 1416898.
 
12.
Boone, W. J., & Staver, J. R. (2020). Advances in Rasch analyses in the human sciences. Springer International Publishing.
 
13.
Boone, W. J., Staver, J. R., & Yale, M. S. (2014). Rasch analysis in the human sciences. Springer Nature.
 
14.
Brewer, C. A., & Smith, D. (2011). Vision and change in undergraduate biology education: A call to action. American Association for the Advancement of Science, Washington, DC.
 
15.
Cary, T. L., Wienhold, C. J., & Branchaw, J. (2019). A Biology Core Concept Instrument (BCCI) to teach and assess student conceptual understanding. CBE—Life Sciences Education, 18(3), ar46. https://doi.org/10.1187/cbe.18....
 
16.
Cavalho, J. C. Q. D., Beltramini, L. M., & Bossolan, N. R. S. (2018). Using a board game to teach protein synthesis to high school students. Journal of Biological Education, 53(2), 205-216. https://doi.org/10.1080/002192....
 
17.
Chan, S. W., Ismail, Z., & Sumintono, B. (2014). A Rasch model analysis on secondary students’ statistical reasoning ability in descriptive statistics. Procedia-Social and Behavioral Sciences, 129, 133-139. https://doi.org/10.1016/j.sbsp....
 
18.
Couch, B. A., Wright, C. D., Freeman, S., Knight, J. K., Semsar, K., Smith, M. K., Summers, M. M., Zheng, Yi, Crowe, A. J., & Brownell, S. E. (2019). GenBio-MAPS: A programmatic assessment to measure student understanding of vision and change core concepts across general biology programs. CBE—Life Sciences Education, 18(1), ar1. https://doi.org/10.1187/cbe.18....
 
19.
Deane, T., Nomme, K., Jeffery, E., Pollock, C., & Birol, G. (2016). Development of the statistical reasoning in biology concept inventory (SRBCI). CBE—Life Sciences Education, 15(1), ar5. https://doi.org/10.1187/cbe.15....
 
20.
Ding, L. (2014). Seeking missing pieces in science concept assessments: Reevaluating the brief electricity and magnetism assessment through Rasch analysis. Physical Review Special Topics-Physics Education Research, 10(1). https://doi.org/10.1103/PhysRe....
 
21.
Finger, R. P., Fenwick, E., Pesudovs, K., Marella, M., Lamoureux, E. L., & Holz, F. G. (2012). Rasch analysis reveals problems with multiplicative scoring in the macular disease quality of life questionnaire. Ophthalmology, 119(11), 2351-2357. https://doi.org/10.1016/j.opht....
 
22.
Fisher, K. M., Williams, K. S., & Lineback, J. E. (2011). Osmosis and diffusion conceptual assessment. CBE—Life Sciences Education, 10(4), 418-429. https://doi.org/10.1187/cbe.11....
 
23.
Gray, J., Kim, J., Ciesla, J. R., & Yao, P. (2014). Rasch Analysis of the Lubben Social Network Scale–6 (LSNS-6). Journal of Applied Gerontology, 35(5), 508-528.
 
24.
Green, A. L., Lambert, M. C., & Hurley, K. D. (2019). Measuring activation in parents of youth with emotional and behavioral disorders. The Journal of Behavioral Health Services & Research, 46(2), 306-318. https://doi.org/10.1007/s11414....
 
25.
Hartley, L. M., Wilke, B. J., Schramm, J. W., D’Avanzo, C., & Anderson, C. W. (2011). College students’ understanding of the carbon cycle: Contrasting principle-based and informal reasoning. BioScience, 61(1), 65-75. https://doi.org/10.1525/bio.20....
 
26.
Haslam, F., & Treagust, D. F. (1987). Diagnosing secondary students’ misconceptions of photosynthesis and respiration in plants using a two-tier multiple choice instrument. Journal of Biological Education, 21(3), 203-211. https://doi.org/10.1080/002192....
 
27.
Hestenes, D., Wells, M., & Swackhamer, G. (1992). Force concept inventory. Physics Teacher, 30, 141-158. https://doi.org/10.1119/1.2343....
 
28.
Hogan, K. (2000). Assessing students’ systems reasoning in ecology, Journal of Biological Education, 35(1), 22-28. https://doi.org/10.1080/002192....
 
29.
Kalas, P., O’Neill, A., Pollock, C., & Birol, G. (2013). Development of a meiosis concept inventory. CBE—Life Sciences Education, 12(4), 655-664. https://doi.org/10.1187/cbe.12....
 
30.
Kalinowski, S. T., Leonard, M. J., & Taper, M. L. (2016). Development and validation of the Conceptual Assessment of Natural Selection (CANS). CBE-Life Sciences Education, 15(4), ar64. https://doi.org/10.1187/cbe.15....
 
31.
Klymkowsky, M. W., & Garvin-Doxas, K. (2020). Concept inventories: Design, application, uses, limitations, and next steps. In Active Learning in College Science (pp. 775-790). Springer. https://doi.org/10.1007/978-3-....
 
32.
Klymkowsky, M. W., Underwood, S. M., & Garvin-Doxas, R. K. (2010). Biological Concepts Instrument (BCI): A diagnostic tool for revealing student thinking. arXiv preprint arXiv:1012.4501.
 
33.
KMK [Sekretariat der Ständigen Konferenz der Kultusminister der Länder in der BRD] (Ed.). (2005). Bildungsstandards im fach biologie für den Mittleren Schulabschluss [Biology education standards for the Mittlere Schulabschluss]. Wolters Kluwer.
 
34.
Lamb, R. L., Annetta, L., Meldrum, J., & Vallett, D. (2012). Measuring science interest: Rasch validation of the science interest survey. International Journal of Science and Mathematics Education, 10(3), 643-668. https://doi.org/10.1007/s10763....
 
35.
Lazarowitz, R., & Lieb, C. (2006). Formative assessment pre-test to identify college students’ prior knowledge, misconceptions and learning difficulties in biology. International Journal of Science and Mathematics Education, 4(4), 741-762. https://doi.org/10.1007/s10763....
 
36.
Lin, S. W. (2004). Development and application of a two-tier diagnostic test for high school students’ understanding of flowering plant growth and development. International Journal of Science and Mathematics Education, 2(2), 175-199. https://doi.org/10.1007/s10763....
 
37.
Linacre J.M. (2001). Category, step and threshold: Definitions & disordering. Rasch Measurement Transactions, 15(1), 794.
 
38.
Linacre, J. M. (1998). Structure in Rasch residuals: Why principal components analysis. Rasch Measurement Transactions, 12(2), 636.
 
39.
Linacre, J. M. (2002). What do infit and outfit, mean-square and standardized mean?. Rasch Measurement Transactions, 16(2), 878.
 
40.
Linacre, J. M. (2018). Winsteps ministep: Rasch-model computer programs. https://www.winsteps.com/winma....
 
41.
Liu, X. (2010). Using and developing measurement instruments in science education: A Rasch modeling approach. Information Age Pub.
 
42.
Malec, J. F., Torsher, L. C., Dunn W. F., Wiegmann, D. A., Arnold, J. J., Brown, D. A., & Phatak V. (2007). The Mayo high performance teamwork scale: Reliability and validity for evaluating key crew resource management skills. Journal of the Society for Simulation in Healthcare, 2(1), 4-10. https://doi.org/10.1097/SIH.0b....
 
43.
Malone, K. L., Schuchardt A. M., & Sabree, Z. (2019). Models and modeling in evolution. In U. Harms, & M. J. Reiss (Eds), Evolution education re-considered: understanding what works (pp. 207-226). Springer International Publishing.
 
44.
Marmaroti, P., & Galanopoulou, D. (2006). Pupils’ understanding of photosynthesis: A questionnaire for the simultaneous assessment of all aspects. International Journal of Science Education, 28(4), 383-403. https://doi.org/10.1080/095006....
 
45.
Minner, D., Ericson, E., Wu, S., & Martinez, A (2012, November). Compendium of research instruments for STEM education part 2: Measuring students’ content knowledge, reasoning skills, and psychological attributes. http://www.cadrek12.org/resour....
 
46.
Mintzes, J. J., Wandersee, J. H., & Novak, J. D. (2001). Assessing understanding in biology. Journal of Biological Education, 35(3), 118-124. https://doi.org/10.1080/002192....
 
47.
Moeini, S., Rasmussen, J. V., Klausen, T. W., & Brorson, S. (2016). Rasch analysis of the Western Ontario Osteoarthritis of the Shoulder Index–the Danish version. Patient Related Outcome Measures, 7, 173. https://doi.org/10.2147/PROM.S....
 
48.
Nadelson, L. S., & Southerland, S. A. (2009). Development and preliminary evaluation of the measure of understanding of macroevolution: Introducing the MUM. The Journal of Experimental Education, 78(2), 151-190. https://doi.org/10.1080/002209....
 
49.
NGSS Lead States. 2013. Next Generation Science Standards: For States, By States. The National Academies Press.
 
50.
Opitz, S. T., Blankenstein, A., & Harms, U. (2017). Student conceptions about energy in biological contexts. Journal of Biological Education, 51(4), 427-440. https://doi.org/10.1080/002192....
 
51.
Price, R. M., Andrews, T. C., McElhinny, T. L., Mead, L. S., Abraham, J. K., Thanukos, A., & Perez, K. E. (2014). The genetic drift inventory: A tool for measuring what advanced undergraduates have mastered about genetic drift. CBE—Life Sciences Education, 13(1), 65-75. https://doi.org/10.1187/cbe.13....
 
52.
Pugh, K. J., Koskey, K. L., & Linnenbrink-Garcia, L. (2014). High school biology students’ transfer of the concept of natural selection: A mixed-methods approach. Journal of Biological Education, 48(1), 23-33. https://doi.org/10.1080/002192....
 
53.
Schmeiser, C., B., & Welch, C. J. (2006). Test development. In R. L. Brennan (Ed.), Educational Measurement. Praeger Publishers.
 
54.
Seoh, K. H. R., Subramaniam, R., & Hoh, Y. K. (2016). How humans evolved according to grade 12 students in Singapore. Journal of Research in Science Teaching, 53(2), 291-323. https://doi.org/10.1002/tea.21....
 
55.
Shi, J., Wood, W. B., Martin, J. M., Guild, N. A., Vicens, Q., & Knight, J. K. (2010). A diagnostic assessment for introductory molecular and cell biology. CBE—Life Sciences Education, 9(4), 453-461. https://doi.org/10.1187/cbe.10....
 
56.
Stammen, A. (2018). The development and validation of the Middle School-Life Science Concept Inventory (MS-LSCI) using Rasch Analysis (Doctoral dissertation, Ohio State University).
 
57.
Stammen, A., Lan, D., Schuchardt, A., Malone, K., Ding, L., Sabree, Z., & Boone, W. (2016). Development of the Secondary-Biology Concept Inventory (S-BCI): A study of content and construct validation. In ICMST Conference Committee (Ed.), Education Research Highlights in Mathematics, Science and Technology 2016, Egiten Publishing.
 
58.
Taber, K. S. (2018). The use of Cronbach’s alpha when developing and reporting research instruments in science education. Research in Science Education, 48(6), 1273-1296. https://doi.org/10.1007/s11165....
 
59.
Todd, A., & Romine, W. L. (2016). Validation of the learning progression-based assessment of modern genetics in a college context. International Journal of Science Education, 38(10), 1673-1698. https://doi.org/10.1080/095006....
 
60.
Todd, A., Romine, W. L., & Cook Whitt, K. (2017). Development and validation of the learning progression–based assessment of modern genetics in a high school context. Science Education, 101(1), 32-65. https://doi.org/10.1002/sce.21....
 
61.
Treagust, D. (1986). Evaluating students’ misconceptions by means of diagnostic multiple choice items. Research in Science Education, 16(1), 199-207. https://doi.org/10.1007/BF0235....
 
62.
Treagust, D. F., & Mann, M. (1998). A pencil and paper instrument to diagnose students’ conceptions of breathing, gas exchange and respiration. Australian Science Teachers Journal, 44(2), 55-59.
 
63.
Tsui, C. Y., & Treagust, D. (2010). Evaluating secondary students’ scientific reasoning in genetics using a two‐tier diagnostic instrument. International Journal of Science Education, 32(8), 1073-1098. https://doi.org/10.1080/095006....
 
64.
Velozo, C. A., Choi, B., Zylstra, S. E., & Santopoalo, R. (2006). Measurement qualities of a self-report and therapist-scored functional capacity instrument based on the Dictionary of Occupational Titles. Journal of Occupational Rehabilitation, 16 (1), 109-122. https://doi.org/10.1007/s10926....
 
65.
Wang, J. R. (2004). Development and validation of a two-tier instrument to examine understanding of internal transport in plants and the human circulatory system. International Journal of Science and Mathematics Education, 2(2), 131-157. https://doi.org/10.1007/s10763....
 
66.
Wright, B. D., & Stone, M. H. (1979). Best test design. Mesa Press.
 
67.
Yang, Y., He, P., & Liu, X. (2018). Validation of an instrument for measuring students’ understanding of interdisciplinary science in grades 4-8 over multiple semesters: A Rasch measurement study. International Journal of Science and Mathematics Education, 16(4), 639-654. https://doi.org/10.1007/s10763....
 
68.
Young, C. A., Quincey, A. M. C., Wong, S. M., & Tennant, A. (2018). Quality of life for post-polio syndrome: A patient derived, Rasch standard scale. Disability and Rehabilitation, 40(5), 597-602. https://doi.org/10.1080/096382....
 
eISSN:1305-8223
ISSN:1305-8215
Journals System - logo
Scroll to top