A Multi-level Remedial Teaching Design Based on Cognitive Diagnostic Assessment: Taking the Electromagnetic Induction as an Example

Abstract

Multi-level teaching has been proven to be more effective than a one-size-fits-all learning approach. This study aimed to develop and implement a multi-level remedial teaching scheme in various high school classes containing students of a wide range of learning levels and to determine its effect of their learning. The deterministic inputs noisy and gate model of cognitive diagnosis theory was used to classify students at multiple levels according to their knowledge and desired learning outcomes. A total of 680 senior high school students from central provinces in China participated in the initial cognitive diagnostic test, and 1,615 high school sophomores from seven high schools in China participated in a formal cognitive diagnosis test. Thirty-six high school students from Southwestern China participated in the think-aloud protocols, and 258 seniors from three high schools in southwest China participated in the remedial teaching experiment. Through an analysis of students’ think-aloud protocols, cognitive errors of students at all levels were determined, and multi-level remedial teaching programs were designed to address these common cognitive errors. The remedial teaching programs were then implemented in three schools and compared with a control group. The results indicated that the students in the experimental group showed a more significant improvement. In this study, the steps of designing multi-level remedial teaching include assessment, classification, and preparing a teaching scheme, which are feasible and can have remarkable teaching effects. This process can be used for reference by teachers of various subjects.

Optimizing Diagnostic Classification Models Application Considering Real-Life Constraints

“…First, the SMEs determined that students need to master all the required attributes to get the item correct, and this quality is captured in the conjunctive model, such as the DINA model. Secondly, the DINA model is widely applied in the literature (Cui et al, 2012; de la Torre, 2009; Huang et al, 2022; Li & Suen, 2013; Templin & Henson, 2006). After calibrating the data using the DINA model, item parameters estimate, attribute probability, and profile proportion were generated, reported, and analyzed based on the selected model.…”

“…In addition to these four factors, another issue people have not addressed in the literature often is the construction of the Q-matrix given the real-life constraints. Many had discussed the construction of Q-matrix when response data or item bank was given (Henson & Douglas, 2005; Huang et al, 2022; Kuo et al, 2016; Nájera et al, 2021). However, no literature has been found on building a Q-matrix without any given items or responses under application constraints.…”

Development of learning path map of work and energy for high schoolers by using cognitive diagnostic assessment

“…In order to effectively develop students and cater to their individual needs, it is important to consider students' knowledge in each specific attribute by applying cognitive diagnostic assessment (CDA). CDA is able to assess students' thinking processes and provide detailed diagnostic information about their learning (Huang et al, 2022). Additionally, it enables the creation of a personalized learning path map, which can guide teachers in designing learning experiences that are suitable for each individual student.…”