Abstract
The sustainable computer-based evaluation system (SCE) is a scenario-based formative evaluation system, in which students are assigned a task during a course. The tasks include the diversity conditions in real-world scenarios. The goals of this system are learning to think as a professional in a certain discipline. While the substantive, psychological, instructional, and task developmental aspects of the assessment have been investigated, few analytic methods have been proposed that allow us to provide feedback to learners in a formative way. The purpose of this paper is to introduce a framework of a learning analytic method including (1) an assessment design through evidence-centered design (ECD), (2) a data mining method using social network analysis, and (3) an analytic method using a Bayesian network. This analytic framework can analyze the learners’ performances based on a computational psychometric framework. The tasks were designed to measure 21st century learning skills. The 250 samples of data collected from the system were analyzed. The results from the social network analysis provide the learning path during a course. In addition, the 21st century learning skills of each learner were inferred from the Bayesian network over multiple time points. Therefore, the learning analytics proposed in this study can offer the student learning progression as well as effective feedback for learning.
Highlights
Formative assessment systems provide information for teachers and students about whether specific learning goals are being met and what is needed to reach these goals [1,2]
The analytic method should offer information about which parts or steps are difficult for a student to learn as well as how well the student is doing about which parts or steps are difficult for a student to learn as well as how well the student is doing during a course
The purpose of this study is to introduce a framework of the learning analytic method using social network analysis and a Bayesian network for the complex data collected from the sustainable evaluation system
Summary
Formative assessment systems provide information for teachers and students about whether specific learning goals are being met and what is needed to reach these goals [1,2]. Teachers did formative assessments on student learning by interacting with one another in person. The additional technology tools for formatively assessing student learning progress were not necessary. Due to the COVID-19 pandemic, school closures and suspension of exams have been widespread in educational institutions. This crisis renders many conventional means of formative assessment useless [3]. An analytic method is necessary to analyze data collected from the formative assessment system for providing information about student learning
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