Yuniarti, Wenty Dwi and Winarko, Edi and Musdholifah, Aina (2020) Data mining for student assessment in e-leaming: A survey. In: 5th International Conference on Informatics and Computing, ICIC 2020.
Data_Mining_for_Student_Assessment_in_e-Leaming_A_Survey.pdf
Restricted to Registered users only
Download (425kB) | Request a copy
Abstract
The diffusion of technology in learning is increasingly massive, marked by the rapid transfer of learning into online environments such as e-Learning. Assessment is an important element of education. Assessment in e-Learning requires methods to be efficient and effective. Data mining is a method of analysis to reveal and recognize hidden patterns in educational databases. Deepening data mining for assessment in e-Learning is both an interesting and a challenge for teachers and institutions to find the right method and make a significant contribution in this area. Therefore, we conducted a literature review and presented state-of-the-art data mining for student assessment in e-Learning from relevant literature publishing from 2016 to 2020. We specifically focus on student assessment research in e-Learning, namely the scope of utilizing data mining, a comparison of several methods, and an analysis of several aspects related to assessment. This study also sheds light on future research directions. We identify the process mining approach as a data mining sub-discipline for the current trend assessment.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Additional Information: | Cited by: 5 |
| Uncontrolled Keywords: | Data mining; E-Learning; Student assessment |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering > Electronics > Computer engineering. Computer hardware |
| Divisions: | Faculty of Engineering > Electrical and Information Technology Department |
| Depositing User: | Sri JUNANDI |
| Date Deposited: | 08 Oct 2025 03:12 |
| Last Modified: | 08 Oct 2025 03:12 |
| URI: | https://ir.lib.ugm.ac.id/id/eprint/22082 |
