Grade prediction via prior grades and text mining on course descriptions: course outlines and intended learning outcomes
Academic grades in assessments are predicted to determine if a student is at risk of failing a course. Sequential models or graph neural networks that have been employed for grade prediction do not consider relationships between course descriptions. We propose the use of text mining to extract seman...
Main Authors: | Li, Jiawei, Supraja, S., Qiu, Wei, Khong, Andy Wai Hoong |
---|---|
Other Authors: | School of Electrical and Electronic Engineering |
Format: | Conference Paper |
Language: | English |
Published: |
2024
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/175885 |
Similar Items
-
Prediction of Academic Performance at Undergraduate Graduation: Course Grades or Grade Point Average?
by: Ahmet Emin Tatar, et al.
Published: (2020-07-01) -
Predicting the final grade using a machine learning regression model: insights from fifty percent of total course grades in CS1 courses
by: Carlos Giovanny Hidalgo Suarez, et al.
Published: (2023-12-01) -
Systemic advantage has a meaningful relationship with grade outcomes in students’ early STEM courses at six research universities
by: Sarah D. Castle, et al.
Published: (2024-02-01) -
Implementation of Alternative Grading Methods in a Mathematical Statistics Course
by: Brenna Curley, et al.
Published: (2023-08-01) -
DESCRIPTIVE GRADES IN INITIAL MATHEMATICAL TEACHING PARENT'S ATTITUDES
by: Dževad Burgić, et al.
Published: (2014-04-01)