A Comparison of the Relative Effectiveness of Student Self-Assessment/Remediation vs. Using a Self-Assessment Chatbot on Raising
Student Performance

Sanjay Rapolu; John Leddo

doi:10.46609/IJSSER.2026.v11i07.049

Title: A Comparison of the Relative Effectiveness of Student Self-Assessment/Remediation vs. Using a Self-Assessment Chatbot on Raising Student Performance
Authors: Sanjay Rapolu and John Leddo
Journal: International Journal of Social Science and Economic Research (IJSSER) ISSN: 2455-8834 Volume: 11 Issue: 7 Publication Date: July 2026 DOI: 10.46609/IJSSER.2026.v11i07.049
\|\| \|\|
Sanjay Rapolu1 and John Leddo1,2,3 1. MyEdMaster, LLC 2. METY Technology, Inc. 3. METY Foundation
MLA 8 Rapolu, Sanjay, and John Leddo. "A Comparison of the Relative Effectiveness of Student Self-Assessment/Remediation vs. Using a Self-Assessment Chatbot on Raising Student Performance." Int. j. of Social Science and Economic Research, vol. 11, no. 7, July 2026, pp. 3613-3629, doi.org/10.46609/IJSSER.2026.v11i07.049. Accessed July 2026. APA 6 Rapolu, S., & Leddo, J. (2026, July). A Comparison of the Relative Effectiveness of Student Self-Assessment/Remediation vs. Using a Self-Assessment Chatbot on Raising Student Performance. Int. j. of Social Science and Economic Research, 11(7), 3613-3629. Retrieved from https://doi.org/10.46609/IJSSER.2026.v11i07.049 Chicago Rapolu, Sanjay, and John Leddo. "A Comparison of the Relative Effectiveness of Student Self-Assessment/Remediation vs. Using a Self-Assessment Chatbot on Raising Student Performance." Int. j. of Social Science and Economic Research 11, no. 7 (July 2026), 3613-3629. Accessed July, 2026. https://doi.org/10.46609/IJSSER.2026.v11i07.049.
References [1] . Ahmad, M. and Leddo, J. (2023). The Effectiveness of Cognitive Structure Analysis in Assessing Students’ Knowledge of the Scientific Method. International Journal of Social Science and Economic Research, 8(8), 2397-2410 [2] . Anderson, J.R. (1982). Acquisition of cognitive skill. Psychological Review, 89, 369-405. [3] . Bekkari, V., and Leddo, J., (2023). Cognitive Structure Analysis: Assessing Elementary School Students in Math to Determine the Types of Knowledge They Have. International Journal of Social Science and Economic Research, 8(10) [4] . Bloom, B. S. (1984). The 2 sigma problem: The search for methods of group instruction as effective as one-to-one tutoring. Educational researcher, 13(6), 4-16. [5] . Brna, P., Ohlsson, S.and Pain, H. (1993) (Eds.). Proceeding of Artificial Intelligent in Education ‘93. Charlottesville, VA: Association for the Advancement of Computing in Education. [6] . Challagulla, M & Leddo, J. (2025). Assessing and Remediating Knowledge Improves Problem- solving Performance in Middle School Math Compared to Remediating Problem-solving Steps. International Journal of Social Science and Economic Research, 10(8), 3618-3629. [7] . Cynkin, C. and Leddo, J. (2023). Teaching Students to Self-Assess Using Cognitive Structure Analysis: Helping Students Determine What They Do and Do Not Know. International Journal of Social Science and Economic Research, 8(9), 3009-3020. [8] . Dandemraju, A., Dandemraju, R. and Leddo, J. (2024). Teaching students to self-assess their own chemistry knowledge. International Journal of Social Science and Economic Research, 9(2), 541-549. [9] . De Kleer, J. and Brown, J.S. (1981). Mental models of physical mechanisms and their acquisition. In J.R. Anderson (Ed.), Cognitive Skills and their acquisition. Hillsdale, NJ: Erlbaum [10] . Greer, J. (1995) (Ed.) Proceeding of Artificial Intelligent in Education ‘95. Charlottesville, VA: Association for the Advancement of Computing in Education. [11] . Hasanein, M., & Sobaih, A. (2023). Conversational AI chatbots for health-related support: User engagement, accuracy, and satisfaction. European Journal of Investigation in Health, Psychology and Education. [12] . Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F. and Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and individual differences, 103, 102274. [13] . Koedinger, K. R., & Corbett, A. (2006). Cognitive Tutors: Technology Bringing Learning Sciences to the Classroom. In R. K. Sawyer (Ed.), The Cambridge handbook of: The learning sciences (pp. 61–77). Cambridge University Press. [14] . Konadu, E., & Kusi, A. (2025). Effects of conversational mental-health chatbots on stress, confidence, and engagement among high-school and college students. American Journal of Education and Learning. [15] . Leddo, J., Chen, T., Menachery, A., Agarwal, J. and Agarwal, T. (2021). Towards Improving Personal Assistants and Educational Software: How Questions Are Answered Affects Learning. International Journal of Social Science and Economic Research, 6(2), 696-705. [16] . Leddo, J. Clark, A. and Clark, E. (2021). Self-Assessment of Understanding: We Don’t Always Know What We Know. International Journal of Social Science and Economic Research, 6(6), 1717-1725. [17] . Leddo, J. Clark, E. and Clark, A. (2025). Using self-assessment and remediation to raise middle school student achievement in math. International Journal of Social Science and Economic Research, 10(3), 1083-1092. [18] . 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.. [19] . Leddo, J., Li, S. and 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. [20] . Leddo, J. and Sak, S. (1994). Knowledge Assessment: Diagnosing what students really know. Presented at Society for Technology and Teacher Education. [21] . Leddo, J., Zhang, Z. and Pokorny, R. (1998).Automated Performance Assessment Tools. Proceedings of the Interservice/Industry Training Systems and Education Conference. Arlington, VA: National Training Systems Association. [22] . Liang, I. and Leddo, J. (2020). An intelligent tutoring system-style assessment software that diagnoses the underlying causes of students’ mathematical mistakes. International Journal of Advanced Educational Research, 5(5), 26-30. [23] . Létourneau, A., Deslandes Martineau, M., Charland, P., Karran, J. A., Boasen, J., and Léger, P. M. (2025). A systematic review of AI-driven intelligent tutoring systems (ITS) in K-12 education. Science of Learning, 10(1), 29. [24] . Maviti, A. and Leddo, J. (2025). A Self-assessment Chatbot Greatly Outperforms Chat GPT in Teaching High School Students Calculus. International Journal of Social Science and Economic Research, 10(10), 5519-5531. [25] . Maviti, A., Leddo, J. and Prakash, P. (2025). A Self-assessment Chatbot Greatly Outperforms Gemini in Teaching High School Students Calculus. International Journal of Social Science and Economic Research, 10(11), 6073-6085. [26] . Nehra, P. and Leddo, J. (2024). The effects of Cognitive Structure Analysis in self-assessing and remediating knowledge gaps in introductory Spanish. International Journal of Social Science and Economic Research, 9(12), 5956-5964. [27] . Newell, A. and Simon, H.A. (1972). Human problem solving. Englewood Cliffs, NJ: Prentice [28] . Prakash, P. and Leddo, J. (2025a). Using Self-Assessment and Remediation to Raise Student Achievement in Reading Comprehension. International Journal of Social Science and Economic Research, 10(1), 277-286. [29] . Prakash, P. and Leddo, J. (2025b). Using Self-Assessment and Remediation to Raise Student Achievement in Mathematics. International Journal of Social Science and Economic Research, 10(1), 447-456. [30] . Prakash, P. and Leddo, J. (2025c). Using Self-Assessment and Remediation to Raise Student Achievement in History. International Journal of Social Science and Economic Research, 10(3), 650-659. [31] . Prakash, P. and Leddo, J. (2025d). Using Self-Assessment and Remediation to Raise Middle School Student Achievement in Reading Comprehension. International Journal of Social Science and Economic Research, 10(3), 1130-1140. [32] . Prakash, P. and Leddo, J. (2025e). Using Self-Assessment and Remediation to Raise Middle School Student Achievement in Science. International Journal of Social Science and Economic Research, 10(4), 1471-1482. [33] . Quillian, M.R. (1966). Semantic memory. Cambridge, MA: Bolt, Beranek and Newman. [34] . Rapolu, S. and Leddo, J. (2026). Impact of a Self-Assessment Chatbot on High School Students’ Learning of Cell CommunicationAchievement in History. International Journal of Social Science and Economic Research, 11(1),320-333. [35] . Sathiyamoorthy, S.S. and Leddo, J. (2025). Using Self-Assessment and Remediation to Raise College Student Achievement in Psychology. International Journal of Social Science and Economic Research, 10(5), 1859-1869. [36] . Schank, R.C. (1982). Dynamic Memory: A theory of learning in computers and people. New York: Cambridge University Press. [37] . Schank, R.C. and Abelson, R.P. (1977). Scripts, Plans, Goals, and Understanding. Hillsdale, NJ: Erlbaum. [38] . Van Lehn, K. (2011). The relative effectiveness of human tutoring, intelligent tutoring systems and other tutoring systems. Educational psychologist, 46(4), 197-221. [39] . Villegas-Ch, W., Buenano-Fernandez, D., Navarro, A. M., and Mera-Navarrete, A. (2025). Adaptive intelligent tutoring systems for STEM education: analysis of the learning impact and effectiveness of personalized feedback. Smart Learning Environments, 12(1), 1-31. [40] . Wang, Y. and Leddo, J. (2025). Improving the Effectiveness of Chatbots by Incorporating Self-Assessed User Knowledge into the Question-Answering Process. International Journal of Social Science and Economic Research, 10(8), 3574-3586. [41] . Zawacki-Richter, O., Marín, V. I., Bond, M., and Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education–where are the educators?. International journal of educational technology in higher education, 16(1), 1-27. [42] . Zhou, L.N. and Leddo, J. (2023). Cognitive Structure Analysis: Assessing Students’ Knowledge of Precalculus. International Journal of Social Science and Economic Research, 8(9), 2826-2836.
ABSTRACT: In previous research, we have shown that teaching students to self-assess and remediate their own knowledge (gaps) or giving them self-assessment chatbots that take student self-assessments as inputs and use those inputs in answering students’ questions both lead to large gains in student performance. The present study compares the relative effectiveness of each approach to see whether adding a chatbot to aid in remediation provides any benefit to having students selfremediate without the aid of technology. Forty fourth- and fifth-grade students studied a geometry unit on angle relationships and completed identical instruction followed by a Cognitive Structure Analysis (CSA)-based self-assessment that identified strengths and deficiencies in four knowledge categories: facts, strategies, procedures, and rationales. Participants were randomly assigned to one of two remediation conditions. The control group used its self-assessment to guide independent review of the instructional materials, whereas the experimental group submitted the same self-assessment to an LLM-powered chatbot that generated personalized explanations and guidance targeted to each learner's reported knowledge gaps. Learning was measured using parallel pretests and posttests. Both groups demonstrated statistically significant gains from pretest to posttest (both p < .0001). However, students using the self-assessment informed chatbot improved by 32.6 percentage points compared with 21.2 percentage points for students performing self-assessment without chatbot support, a statistically significant difference of 11.4 percentage points (t(38) = 4.02, p = .0003). These findings suggest that combining learner-generated knowledge models with LLM-based conversational tutoring produces substantially greater learning gains than self-directed remediation alone. The results support the integration of structured learner models into generative AI tutoring systems and indicate that self-assessment may provide a practical, scalable mechanism for personalizing AI-assisted instruction in educational settings.

IJSSER is Member of