Optimization of engineering student learning and assessment by cognitive methods

This study addresses the learning objectives and the student outcomes of industrial engineering students by examining them at three different levels: course level, program level, and graduate level. Three learning domains are developed and analyzed for this purpose to assess the performance of students during and after graduation. These domains are labeled as the house of cognitive learning, which shows the level of learning, its outcome elements, and the depth of understanding. In the higher education system, the correct assessment of student learning is always considered as a challenging task. The aim of this study was to develop an integrated integer-programming algorithm to accurately determine the learning level of students. The method incorporates quality control charts and statistical assessment tools to present the findings. In this study, level of learning is calculated as a learning index that presents the contribution of a course to the respective student outcomes. Moreover, it depicts the overall achievements of students during their learning. Therefore, another aim of this study was to explore how to better utilize the collected data for the assessment of learning level. The outcomes of algorithm and statistical approaches are quite encouraging for the evaluation of students' learning, thus improving the quality of engineering program.

Optimization of engineering student learning and assessment by cognitive methods Academic Article