Archives
Current issue
About
About us
Aims and Scope
Abstracting and Indexing
Editorial Office
Open Access Policy
Publication Ethics
Journal History
Publisher
Follow us: Twitter
Contact
For Authors
Editorial Policy
Peer Review Policy
Manuscript Preparation Guidelines
Copyright & Licencing
Publication Fees
Fee Waiver Policy for Doctoral Students
EJMSTE Language Editing Service
More
Statistics
Special Issues
Special Issue Announcements
Published Special Issues
RESEARCH PAPER
The Physics Problem-Solving Taxonomy (PPST): Development and Application for Evaluating Student Learning
1
Ben Gurion University of the Negev, Beer Sheva, ISRAEL
Online publication date: 2019-05-09
Publication date: 2019-05-09
EURASIA J. Math., Sci Tech. Ed 2019;15(11):em1764
KEYWORDS
ABSTRACT
This study addresses the development and evaluation of the Physics Problem-Solving Taxonomy (PPST), comprising five levels: retrieval, diagnosis, strategy, conceptual, and creative thinking. The taxonomy draws on Bloom’s revised taxonomy in the cognitive domain, the Types of Knowledge Taxonomy, and the Problem-Solving Taxonomy in engineering. The study includes applying PPST to analyze the content of the Israeli national physics exam (the Bagrut), student Bagrut scores (n = 18,000), and student answers to a school-level physics exam (n = 164). The findings indicate that in both the Bagrut and the school exam, the higher an item ranks on PPST, the lower the students’ grades on this item. In addition, the distribution of student scores on the two exams is similar, indicating high reliability and validity of the PPST scale. This tool could help physics teachers to rank difficulty levels of the high school physics exam questions, and create high school physics questions, to foster students’ proficiency in physics problem solving.
REFERENCES (36)
1.
American Association for the Advancement of Science. (1993). Benchmarks for scientific literacy. New York, NY: Oxford University Press.
2.
Anderson, L. W., & Krathwohl, D. R. (Eds.). (2001). A taxonomy for learning, teaching and assessing: A revision of Bloom’s taxonomy of educational objectives. New York, NY: Longman.
3.
Barak, M. (2013). Teaching engineering and technology: Cognitive, knowledge and problem-solving taxonomies. Journal of Engineering, Design and Technology, 11, 316–333. https://doi.org/10.1108/JEDT-0....
4.
Bennett, J. (2001). Practical work at the upper high school level: The evaluation of a new model of assessment. International Journal of Science Education, 23, 97–110. https://doi.org/10.1080/095006....
5.
Biggs, J. B., & Collis, K. F. (1982). Evaluating the quality of learning: The SOLO taxonomy. New York: Academic Press.
6.
Bissell, A. N., & Lemons, P. P. (2006). A new method for assessing critical thinking in the classroom. Bioscience, 56, 66–72. https://doi.org/10.1641/0006-3....
7.
Bloom, B. S., & Krathwohl, D. R. (1956). Taxonomy of educational objectives: The classification of educational goals. New York: McKay.
8.
Blumberg, P. (2009). Maximizing learning through course alignment and experience with different types of knowledge. Innovative Higher Education, 34, 93–103. https://doi.org/10.1007/s10755....
9.
Davis, J. D. (2005). Connecting procedural and conceptual knowledge of functions. Mathematics Teacher, 99, 36–39.
10.
Fabby, C., & Koenig, K. (2015). Examining the relationship of scientific reasoning with physics problem solving. Journal of STEM Education: Innovations & Research, 16, 20–26.
11.
Groth, R. E., & Bergner, J. A. (2006). Preservice elementary teachers’ conceptual and procedural knowledge of mean, median and mode. Mathematical Thinking and Learning, 8, 37–63. https://doi.org/10.1207/s15327....
12.
Guilford, J. P. (1967). The nature of human intelligence. New York, NY: McGraw-Hill.
13.
Hiebert, J., & Lefevre, P. (1986). Conceptual and procedural knowledge in mathematics: An introductory analysis. In J. Hiebert (Ed.), Conceptual and procedural knowledge: The case of mathematics (pp. 1–28). Hillsdale, NJ: Erlbaum.
14.
Kastberg, S. E. (2003). Using Bloom’s taxonomy as a framework for classroom assessment. Mathematics Teacher, 96, 402–405.
15.
Kilpatrick, J., Swafford, J., & Findell, B. (Eds.) (2001). Adding it up: Helping children learn mathematics. Washington, DC: National Academies Press.
16.
Krathwohl, D. R. (2002). A revision of Bloom’s taxonomy: An overview. Theory and Practice, 41, 212–217. https://doi.org/10.1207/s15430....
17.
Leppävirta, J., Kettunen, H., & Sihvola, A. (2011). Complex problem exercises in developing engineering students’ conceptual and procedural knowledge of electromagnetics. IEEE Transactions on Education, 54, 63–66. https://doi.org/10.1109%2FTE.2....
18.
Marzano, R. J., & Kendall, J. S. (2007). The new taxonomy of educational objectives. Thousand Oaks, CA: Corwin Press.
19.
McCormick, R. (1997). Conceptual and procedural knowledge. International Journal of Technology and Design Education, 7, 141–159. https://doi.org/10.1023/A:1008....
20.
McCormick, R. (2004). Issues of learning and knowledge in technology education. International Journal of Technology and Design Education, 14, 21–44. https://doi.org/10.1023/B:ITDE....
21.
National Research Council. (1996). National science education standards. Washington, DC: National Academy Press.
22.
O’Neill, G., & Murphy, F. (2010). Assessment: Guide to Taxonomies of learning. Dublin: UCD teaching and learning resources. Retrieved from http://www.ucd.ie/t4cms/ucdtla....
23.
Persaud, C. (2018). Bloom’s Taxonomy, the ultimate guide. TOPHAT Company. Retrieved from https://tophat.com/blog/blooms....
24.
Pintrich, P. R. (2002). The role of metacognitive knowledge in learning, teaching, and assessing. Theory into Practice, 41, 219–225. https://doi.org/10.1207/s15430....
25.
Plants, H. L., Dean, R. K., Sears, J. T., & Venable, W. S. (1980). A taxonomy of problem-solving activities and its implications for teaching. In J. L. Lubkin (Ed.), The teaching of elementary problem-solviyhhujmjhnklp;lng in engineering and related fields (pp. 21–34). Washington DC: American Society for Engineering Education. Retrieved from http://www.wallace-venable.nam..._.
27.
Rittle-Johnson, B., & Koedinger, K. R. (2005). Designing knowledge scaffolds to support mathematical problem solving. Cognition and Instruction, 23, 313–349. https://doi.org/10.1207/s15326....
28.
Simonton, D. K. (2000). Creativity: personal, cognitive, and social aspects. American Psychologist, 55, 151–158. https://doi.org/10.1037/0003-0....
29.
Sternberg, R. J., & Lubart, T. I. (1996). Investing in creativity. American Psychologist, 51, 677–688. https://doi.org/10.1037/0003-0....
30.
Teodorescu, R. E., Bennhold, C., Feldman, G., & Medsker, L. (2013). New approach to analyzing physics problems: a taxonomy of introductory physics problems. Physical Review Special Topics, Physics Education Research, 9, 1. https://doi.org/10.1103/PhysRe....
31.
Teodorescu, R., Bennhold, C., & Feldman, G. (2008). Enhancing cognitive development through physics problem solving: A taxonomy of introductory physics problems (TIPP). American Institute of Physics (AIP) Conference Proceedings, 1064, 203–206. https://doi.org/10.1063/1.3021....
32.
Voutsina, C. (2012). Procedural and conceptual changes in young children’s problem solving. Educational Studies in Mathematics, 79, 193–214. https://doi.org/10.1007/s10649....
33.
Waks, S., & Barak, M. (1988). Characterization of cognitive difficulty level of test items. Research in Science and Technological Education, 6, 181–192. https://doi.org/10.1080/026351....
34.
Waks, S., & Sabag, N. (2004). Technology project learning versus lab experimentation. Journal of Science Education and Technology, 13, 333–342. https://doi.org/10.1023/B:JOST....
35.
Wankat, P. C., & Oreovicz, F. S. (1993). Teaching engineering. New York, NY: Knovel.
36.
Yokomoto, C. H., & Rizkalla, M. E. (2002, June). Development of a problem test bank for linear circuits and its implications for improving learning and the assessment of student learning. Paper presented at the American Society for Engineering Education Annual Conference and Exposition, Montreal, Canada.
Share
RELATED ARTICLE
| eISSN: | 1305-8223 |
| ISSN: | 1305-8215 |
We process personal data collected when visiting the website. The function of obtaining information about users and their behavior is carried out by voluntarily entered information in forms and saving cookies in end devices. Data, including cookies, are used to provide services, improve the user experience and to analyze the traffic in accordance with the Privacy policy. Data are also collected and processed by Google Analytics tool (more).
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
