Developing an Interactive Online Diagnostic Framework to Grade 7 Students’ Misconceptions in Integer Operations

Abstract

The objectives of this research were 1) to develop and validate a diagnostic test for identifying misconceptions in the mixed operations of integers (addition, subtraction, multiplication, and division) for Grade 7 students. 2) to develop an interactive online testing information system capable of identifying individual misconceptions and providing automated feedback and 3) to evaluate student satisfaction toward the developed testing system. The sample consisted of two distinct groups from a school in Nong Bua Lamphu Province, selected through cluster random sampling: Group 1 comprised 36 Grade 8 students, and Group 2 comprised 36 Grade 7 students. Research instruments included subjective tests, diagnostic tests, the online testing system, and a satisfaction questionnaire. Data were analyzed using the Index of Item-Objective Congruence (IOC), difficulty index (p), discrimination index (r), reliability coefficients, mean (), and standard deviation (S.D.). The results revealed that. 1) The developed diagnostic test, consisting of 22 items, successfully identified 11 types of misconceptions. It demonstrateda content validity (IOC) of 1.00, difficulty indices ranging from 0.29 to 0.71, discrimination indices between 0.57 and 1.00, and a reliability coefficient of 0.98. 2) The information system was developed based on the "D-AIM Model," a conceptual framework for learning diagnostic systems that integrates learner error data with Artificial Intelligence (AI) to provide immediate diagnostic feedback. 3) Student satisfaction toward the system was at the highest level  = 4.70, S.D. = 0.48).

The objectives of this research were 1) to develop and validate a diagnostic test for identifying misconceptions in the mixed operations of integers (addition, subtraction, multiplication, and division) for Grade 7 students. 2) to develop an interactive online testing information system capable of identifying individual misconceptions and providing automated feedback and 3) to evaluate student satisfaction toward the developed testing system. The sample consisted of two distinct groups from a school in Nong Bua Lamphu Province, selected through cluster random sampling: Group 1 comprised 36 Grade 8 students, and Group 2 comprised 36 Grade 7 students. Research instruments included subjective tests, diagnostic tests, the online testing system, and a satisfaction questionnaire. Data were analyzed using the Index of Item-Objective Congruence (IOC), difficulty index (p), discrimination index (r), reliability coefficients, mean (), and standard deviation (S.D.). The results revealed that. 1) The developed diagnostic test, consisting of 22 items, successfully identified 11 types of misconceptions. It demonstrateda content validity (IOC) of 1.00, difficulty indices ranging from 0.29 to 0.71, discrimination indices between 0.57 and 1.00, and a reliability coefficient of 0.98. 2) The information system was developed based on the "D-AIM Model," a conceptual framework for learning diagnostic systems that integrates learner error data with Artificial Intelligence (AI) to provide immediate diagnostic feedback. 3) Student satisfaction toward the system was at the highest level  = 4.70, S.D. = 0.48).