IJSSER

Title: Using Self-Assessment and Remediation to Raise Student Achievement in Mathematics
Authors: Prathima Prakash and John Leddo
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Prathima Prakash and John Leddo MyEdMaster, LLC, Virginia, USA
MLA 8 Prakash, Prathima, and John Leddo. "Using Self-Assessment and Remediation to Raise Student Achievement in Mathematics." Int. j. of Social Science and Economic Research, vol. 10, no. 1, Jan. 2025, pp. 447-456, doi.org/10.46609/IJSSER.2025.v10i01.027. Accessed Jan. 2025. APA 6 Prakash, P., & Leddo, J. (2025, January). Using Self-Assessment and Remediation to Raise Student Achievement in Mathematics. Int. j. of Social Science and Economic Research, 10(1), 447-456. Retrieved from https://doi.org/10.46609/IJSSER.2025.v10i01.027 Chicago Prakash, Prathima, and John Leddo. "Using Self-Assessment and Remediation to Raise Student Achievement in Mathematics." Int. j. of Social Science and Economic Research 10, no. 1 (January 2025), 447-456. Accessed January, 2025. https://doi.org/10.46609/IJSSER.2025.v10i01.027.
References [1] . Ahmad, S., & Leddo, J. (2023). Cognitive Structure Analysis and its effectiveness in scientific method problem-solving. Journal of Educational Psychology, 119(2), 145-159. [2] . Chaoui, F. (2011). The efficacy of multiple-choice tests in large classrooms. Educational Research Review, 6(3), 103-115. [3] . Cynkin, A., & Leddo, J. (2023). The effectiveness of Cognitive Structure Analysis in high school calculus. Journal of Educational Research, 58(1), 78-91. [4] . Dandemraju, M., Dandemraju, R., & Leddo, J. (2024). Chemistry assessment and remediation with Cognitive Structure Analysis. Journal of Science Education, 10(2), 220-233. [5] . de Ayala, R. J. (2009). The reliability and validity of standardized tests in education. Educational Measurement, 18(4), 35-50. [6] . Elbrink, H., & Waits, B. (1970). The reliability of multiple-choice testing methods in educational assessments. Testing and Evaluation, 14(1), 54-67. [7] . Frary, R. (1985). Constructive response tests and their impact on academic learning. Educational Measurement, 22(3), 119-132. [8] . Herman, J. L., Klein, D. C., Heath, T. M., & Wakai, S. T. (1994). A first look: Are claims for alternative assessment holding up? (CSE Tech. Rep. No. 391). Los Angeles: University of California, Center for Research on Evaluation, Standards, and Student Testing. [9] . Jackson, S. (1948). The Lottery. New York: Farrar, Straus and Giroux. [10] . Leddo, J., Ahmad, S., & Zhou, Y. (2022). Correlation of Cognitive Structure Analysis with problem-solving performance in Algebra 1. Journal of Educational Psychology, 120(4), 289-302. [11] . Leddo J., Boddu B., Krishnamurthy S., Yuan K., & Chippala S. (2017). The effectiveness of [12] . selfdirected learning and teacher-led learning on gifted and talented vs. non-gifted and talented students. International Journal of Advanced Educational Research, 2(6):18-21. [13] . Leddo, J., Clark, D., & Clark, E. (2021). Self-assessment and its role in self-directed learning. Journal of Cognitive Development, 45(2), 78-90. [14] . Leddo, J., Cohen, M.S., O'Connor, M.F., Bresnick, T.A., and Marvin, F.F. (1990). Integrated knowledge elicitation and representation framework (Technical Report 90?3). Reston, VA: Decision Science Consortium, Inc. [15] . Leddo, J. & Kalwala, S. (2023). The Effectiveness of Self-directed Learning and Teacher-led Learning of Advanced Subject Matter on Gifted and Talented Students. International Journal of Social Science and Economic Research, 8(9), 2819-2825. [16] . Leddo, J., Li, S. & Zhang, Y. (2022). Cognitive Structure Analysis: A technique for assessing what students know, not just how they perform. International Journal of Social Science and Economic Research, 7(11), 3716-3726. [17] . Nehra, P., & Leddo, J. (2024). The effects of Cognitive Structure Analysis in self-assessing and remediating knowledge gaps in introductory Spanish. Journal of Educational Psychology, 45(3), 78-89. [18] . Newell, A., & Simon, H. (1972). Human Problem Solving. Prentice-Hall. [19] . O’Neil, H. F., & Brown, D. S. (1997). The impact of self-assessment on student performance. Journal of Educational Psychology, 12(1), 89-102. [20] . Quillian, M. R. (1966). Semantic memory. In M. Minsky (Ed.), Semantic Information Processing (pp. 227-270). MIT Press. [21] . Prakash, P. & Leddo, J. (2025, in press). Using Self-Assessment and Remediation to Raise Student Achievement in Reading Comprehension. International Journal of Social Science and Economic Research, 10(1), in press. [22] . Ravi, D., & Leddo, J. (2024). Improving Student Performance by Having Students: Assess and Remediate Their Own Knowledge Deficiencies. International Journal of Social Science and Economic Research, 9(10), 4717-4724. [23] . Schank, R. C., & Abelson, R. P. (1977). Scripts, plans, goals, and understanding. Lawrence Erlbaum. [24] . Zhou, Y., & Leddo, J. (2023). The role of Cognitive Structure Analysis in understanding precalculus. Journal of Educational Research, 64(2), 139-154.
ABSTRACT: Cognitive Structure Analysis (CSA) is an educational framework designed to help students identify and address knowledge deficits through self-assessment, enabling them to remediate gaps in understanding. Previous studies have demonstrated the reliability of teaching students to use CSA to assess their own knowledge in various academic disciplines, including calculus (Cynkin and Leddo, 2023) and chemistry (Dandemraju, Dandemraju, and Leddo, 2024). These studies, however, primarily focused on the identification of knowledge gaps rather than their remediation. As accurate assessment does not inherently address deficiencies, later studies began to investigate CSA’s role in addressing the gap. Ravi and Leddo (2024) conducted a study in which students learned an advanced chemistry topic by watching a video. Half of the students rewatched to reinforce their understanding, while the other half were trained to use CSA to selfassess their knowledge and then rewatched the video specifically to remediate assessed knowledge gaps. The CSA-trained group outperformed the control group by 15 points (1.5 letter grades) on a post-test. Similarly, Nehra and Leddo (2024) replicated this approach in Spanish instruction, finding that CSA-trained students scored an average of 25 percentage points (2.5 letter grades) higher than those who simply reread the material without self assessing. Prakash and Leddo (2025, in press) built on the findings of Ravi and Leddo (2024) and Nehra and Leddo (2024) by investigating CSA’s applicability to reading comprehension; post-test results displayed that the CSA-trained group scored an average of 93%, outperforming the control group’s 69%. This study builds on prior research by investigating the applicability of CSA in learning Bayes’ Theorem, a foundational concept in probability theory and statistics. Twenty high school students were divided into two groups. Both groups studied Bayes’ Theorem from a provided instructional document, but only the experimental group used CSA to self-assess their knowledge and remediate gaps. Post-test results revealed that the experimental group significantly outperformed the control group, scoring an average of 85.5% compared to the control group’s 58.5%. These findings underscore CSA’s potential to improve understanding of abstract mathematical concepts while fostering self-directed learning.

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