A review on learning analytics in mobile learning and assessment

Abstract

Employers are facing difficulties in selecting the most suitable candidates for employment and the transition from education to work is challenging for young graduates. Therefore, it is important to have indicators that could show the suitability of a potential candidate for his/her chosen job. A person who possesses knowledge but lacks confidence may struggle to perform assigned tasks, while an overly confident person with limited knowledge is likely to make errors in their job. Although there is existing research on learning analytics related to assessments, the research on learning analytics specifically focused on the confidence-knowledge relationship based on assessment data is still lacking. This article aims to examine the application of analytics in providing insights based on assessment data that can be utilized by potential employers. To achieve this, a systematic review was carried out, analyzing a total of 141 articles. The findings contribute to a better understanding of the use of assessment analytics in identifying the knowledge-confidence quadrants of students.