Students’ Self-Diagnosis Using Worked-Out Examples

Abstract

Students in physics classrooms are often asked to review their solution to a problem by comparing it to a textbook or worked-out example. Learning in this setting depends to a great extent on students' inclination forself-repair; i.e., their willingness and ability to recognize and resolve conflicts between their mental model and the scientifically acceptable model. This study examined the extent to which self-repair can be identified and assessed in students’written responses on a self-diagnosis task in which they are given time and credit for identifying and explaining the nature of their mistakes assisted by a worked-out example. Analysis of 180 10th and 11th grade physics students in private and public schools in the Arab sector in Israel showed that although most students were able to identify differences between their solution and the worked-out example that significantly affected the way they approached the problem many did not acknowledge the underlying conflicts between their interpretation and a scientifically acceptable interpretation of the concepts and principles involved. Rather, students related to the worked-out example as an ultimate template and simply considered their deviations from it as mistakes. These findings were consistent in all the classes and across all the teachers, irrespective of grade level or school affiliation. However, younger students in some classrooms also perceived the task as a communication channel to provide feedback to their teachers on their learning and the instructional materials used in the task. Taken together, the findings suggest that instructional intervention is needed to develop students’ ability to self-diagnose their work so that they can learn from this type of task.


Share and Cite:

Safadi, R. and Yerushalmi, E. (2013) Students’ Self-Diagnosis Using Worked-Out Examples. Creative Education, 4, 205-216. doi: 10.4236/ce.2013.43031.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] Aleven, V. A. W. M. M., & Koedinger, K. R. (2002). An effective metacognitive strategy: Learning by doing and explain with a computer-based Cognitive Tutor. Cognitive Science, 26, 147-179. doi:10.1207/s15516709cog2602_1
[2] Atkinson, R. K, Derry, S. J., Renkl, A., & Wortham, D. W. (2000). Learning from examples: Instructional principles from the worked examples research. Review of Educational Research, 70, 181-214.
[3] Atkinson, R. K., Renkl, A., & Merrill, M. M. (2003). Transitioning from studying examples to solving problems: Effects of self-explanation prompts and fading worked-out examples. Journal of Educational Psychology, 95, 774-783. doi:10.1037/0022-0663.95.4.774
[4] Bereiter, C., & Scardamalia, M. (1989). Intentional learning as a goal of instruction. In L. B. Resnick (Ed.), Knowing, learning, and instructtion: Essays in honor of Robert Glaser (p. 361). Hillsdale, NJ: Lawrence Erlbaum Associates.
[5] Catrambone, R. (1998). The subgoal learning model: Creating better examples so that students can solve novel problems. Journal of Experimental Psychology: General, 127, 355-376. doi:10.1037/0096-3445.127.4.355
[6] Chandler, P., & Sweller, J. (1991). Cognitive load theory and the format of instruction. Cognition and Instruction, 8, 293-332. doi:10.1207/s1532690xci0804_2
[7] Chandler, P., & Sweller, J. (1992). The split-attention effect as a factor in the design of instruction. British Journal of Educational Psychology, 62, 233-246. doi:10.1111/j.2044-8279.1992.tb01017.x
[8] Chi, M. T. H. (2000). Self-explaining expository texts: The dual processes of generating inferences and repairing mental models. In R. Glaser (Ed.), Advances in Instructional Psychology (pp. 161-238). Mahwah, NJ: Lawrence Erlbaum Associates.
[9] Chi, M. T. H., Bassok, M., Lewis, M. H., Reimann, P., & Glaser, R. (1989). Self-explanations: How students study and use examples in learning to solve problems. Cognitive Science, 13, 145-182. doi:10.1207/s15516709cog1302_1
[10] Chi, M. T. H., de Leeuw, N., Chiu, M. H., & LaVancher, C. (1994). Eliciting self-explanations improves understanding. Cognitive Science, 18, 439-477.
[11] Chi, M. T. H., & VanLehn, K. A. (1991). The content of physics self-explanations. The Journal of the Learning Sciences, 1, 69-105. doi:10.1207/s15327809jls0101_4
[12] Clark, R. C., Nguyen, F., & Sweller, J. (2006). Efficiency in learning: Evidence-based guidelines to manage cognitive load. San Francisco: Pfeiffer.
[13] Cohen, E., Mason, A., Singh, C., & Yerushalmi, E. (2008). Identifying differences in diagnostic skills of physics students: Students’ self-diagnostic performance given alternative scaffolding. 2008 Proceedings of the Physics Education Research Conference (pp. 99-102). Edmonton: AIP.
[14] Crippen, K. J., & Earl, B. L. (2005). The impact of web-based worked examples and self-explanation on performance, problem solving, and self-efficacy. Computers & Education, 49, 809-821. doi:10.1016/j.compedu.2005.11.018
[15] Dkeidek, I., Hofstien, A., & Mamlouk, R. (2011). Effect of culture on high-school students’ question-asking ability resulting from an inquiry-oriented chemistry laboratory. International Journal of Science and Mathematics Education, 9, 1305-1331. doi:10.1007/s10763-010-9261-0
[16] Eilam, B. (2002). Passing through a western-democratic teacher education: The case of Israeli-Arab teachers. Teacher College Record, 104, 1656-1701. doi:10.1111/1467-9620.00216
[17] Elby, A. (2001). Helping physics students learn how to learn. American Journal of Physics, Physics Education Research Supplement, 69, S54-S64.
[18] Etkina, E., Van Heuvelen, A., White-Brahmia, S., Brookes, D. T., Gentile, M., Murthy, S., Rosengrant, D., & Warren, A. (2006). Developing and assessing student scientific abilities. Physical Review. Special Topics, Physics Education Research, 2, 020103. doi:10.1103/PhysRevSTPER.2.020103
[19] Eylon, B., & Helfman, J. (1982). Deductive and analogical problemsolving processes in physics. New York: American Educational Research Association (AERA).
[20] Gick, M. L., & Holyack, K. J. (1983). Schemainduction and analogical transfer. Cognitive Psychology, 15, 1-38. doi:10.1016/0010-0285(83)90002-6
[21] Gro?e, C. S., & Renkl, A. (2007). Finding and fixing errors in worked examples: Can this foster learning outcomes? Learning and Instruction, 17, 612-634. doi:10.1016/j.learninstruc.2007.09.008
[22] Halloun, I. A., & Hestenes, D. (1985). Common sense concepts about motion. American Journal of Physics, 53, 1056-1065. doi:10.1119/1.14031
[23] Hausmann, R. G. M., & Chi, M. T. H. (2002). Can a computer interface support self-explaining? Cognitive Technology, 7, 4-14.
[24] Hausmann, R. G. M., & VanLehn, K. (2007). Explaining self-explaining: A contrast between content and generation. In R. Luckin, K. R. Koedinger, & J. Greer (Eds.), Artificial intelligence in education: Building technology rich learning contexts that work (Vol. 158, pp. 417-424). Amsterdam: IOS Press.
[25] Heller, P., & Hollbaugh, M. (1992). Teaching problem solving through cooperative grouping. Part 2: Designing problems and structuring groups. American Journal of Physics, 60, 637-645. doi:10.1119/1.17118
[26] Henderson, C., & Harper, K. A. (2009). Quiz corrections: Improving learning by encouraging students to reflect on their mistakes. The Physics Teacher, 47, 581-586. doi:10.1119/1.3264589
[27] Hieggelke, C. J., Maloney, D. P., O’Kuma, T. L., & Kanim, S. (2006). E&M TIPERs: Electricity & magnetism tasks. Boston, MA: Addison Wesley.
[28] Kalyuga, S., Ayres, P., Chandler, P., & Sweller, J. (2003). The expertise reversal effect. Educational Psychologist, 38, 23-31. doi:10.1207/S15326985EP3801_4
[29] Labudde, P., Reif, F., & Quinn, L. (1988). Facilitation of scientific concept learning by interpretation procedures and diagnosis. International Journal of Science Education, 10, 81-98. doi:10.1080/0950069880100108
[30] Maloney, D. (2011). An overview of physics education research on problem solving. Getting Started in PER (Vol. 2). URL (last checked 1 May 2012). http://www.compadre.org/Repository/document/ServeFile.cfm?ID=11457&DocID=2427
[31] Mason, A., Cohen, E., Singh, C., & Yerushalmi, E. (2009). Self-diagnosis, scaffolding and transfer: A tale of two problems. In M. Sabella, C. Henderson, & C. Singh (Eds.), 2009 Physics Education Research Conference (pp. 27-30). Ann Arbor, MI: AIP.
[32] Mason, A., Cohen, E., Yerushalmi, E., & Singh, C. (2008). Identifying differences in diagnostic skills between physics students: Developing a rubric. In L. Hsu, C. Henderson, & M. Sabella (Eds.), 2008 Proceedings of the Physics Education Research Conference (pp. 147- 150). Edmonton: AIP.
[33] Mazur, E. (1997). Peer instruction: A user’s manual. Upper Saddle River, NJ: Prentice Hall.
[34] McDermott, L. C., Shaffer, P. S., & The Physics Education Group at the University of Washington (1998). Tutorials in introductory physics (Preliminary Ed.). Upper Saddle River, NJ: Prentice Hall.
[35] Redish, E., Saul, J., & Steinberg, R. (1998). Student expectations in introductory physics. American Journal of Physics, 66, 212-224. doi:10.1119/1.18847
[36] Reif, F., & Scott, L. (1999). Teaching scientific thinking skills: Students and computers coaching each other. American Journal of Physics, 67, 819-831. doi:10.1119/1.19130
[37] Renkl, A. (1997). Learning from worked-out examples: A study on individual differences. Cognitive Science, 21, 1-29. doi:10.1207/s15516709cog2101_1
[38] Renkl, A., Stark, R., Gruber, H., & Mandl, H. (1998). Learning from worked-out examples: The effects of example variability and elicited self-explanations. Contemporary Educational Psychology, 23, 90-108. doi:10.1006/ceps.1997.0959
[39] Reisslein, J., Atkinson, R. K., Seeling, P., & Reisslein, M. (2006). Encountering the expertise reversal effect with a computer-based environment on electrical circuit analysis. Learning and Instruction, 16, 92-103. doi:10.1016/j.learninstruc.2006.02.008
[40] Schwartz, D. L., & Martin, T. (2004). Inventing to prepare for learning: The hidden efficiency of original student production in statistics instruction. Cognition & Instruction, 22, 129-184. doi:10.1207/s1532690xci2202_1
[41] Sokoloff, D. R., & Thornton, R. K. (2001). Interactive lecture demonstrations. New York, NY: Wiley.
[42] Sweller, J., van Merri?nboer, J. J. G., & Paas, F. G. (1998). Cognitive architecture and instructional design. Educational Psychology Review, 10, 251-296. doi:10.1023/A:1022193728205
[43] Tamir, P., & Caridin, H. (1993). Characteristics of the learning environment in biology and chemistry classes as perceived by Jewish and Arab high school students in Israel. Research in Science and Technological Education, 11, 5-14. doi:10.1080/0263514930110102
[44] Van Gog, T., Paas, F., & van Merri?nboer, J. J. G. (2008). Effects of studying sequences of process-oriented and product-oriented worked examples on troubleshooting transfer efficiency. Learning and Instruction, 18, 211-222. doi:10.1016/j.learninstruc.2007.03.003
[45] Viennot, L. (1979). Spontaneous reasoning in elementary dynamics. European Journal of Science Education, 1, 205-221. doi:10.1080/0140528790010209
[46] Ward, M., & Sweller, J. (1990). Structuring effective worked examples. Cognition and Instruction, 7, 1-39. doi:10.1207/s1532690xci0701_1
[47] Wertsch, J. V. (1984). The zone of proximal development & some conceptual issues. In B. Rogoff & J. V. Wertsch (Eds.), Children’s learning in the “zone of proximal development”—New directions for child development (pp. 7-18). San Francisco: Jossey-Bass.
[48] Yerushalmi, E., Henderson, C., Heller, K., Heller, P., & Kuo, V. (2007). Physics faculty beliefs and values about the teaching and learning of problem solving part 1: Mapping the common core. Physical Review Special Topics—Physics Education Research, 3, 020109. doi:10.1103/PhysRevSTPER.3.020109
[49] Yerushalmi, E., Mason, A., Cohen, E., & Singh, C. (2009). Self-diagnosis, scaffolding and transfer in a more conventional introductory physics problem. In M. Sabella, C. Henderson, & C. Singh (Eds.), 2009 Physics Education Research Conference (pp. 23-27). Ann Arbor, MI: AIP.
[50] Yerushalmi, E., Puterkovski, M., & Bagno, E., (2012). Knowledge integration while interacting with an online troubleshooting activity, Journal of Science Education and Technology. doi:10.1007/s10956-012-9406-8
[51] Yerushalmi, E., Singh, C., & Eylon, B. (2007). Physics learning in the context of scaffolded diagnostic tasks (1): The experimental setup. In L. McCullough, L. Hsu, & C. Henderson (Eds.), Proceedings of the Physics Education Research Conference (pp. 27-30). Greensboro, NC: AIP.

Copyright © 2024 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.