Machine Learning Prediction and Recommendation Framework to Support Introductory Programming Course
Decision trees; Failure analysis; Forecasting; Machine learning; Predictive analytics; F measure; Failure rate; High-accuracy; Introductory programming; Introductory programming course; Precautionary measures; Prediction model; Students
Saved in:
Main Authors: | Khan I., Ahmad A.R., Jabeur N., Mahdi M.N. |
---|---|
Other Authors: | 58061521900 |
Format: | Article |
Published: |
International Association of Online Engineering
2023
|
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Tracking student performance in introductory programming by means of machine learning
by: Khan I., et al.
Published: (2023) -
A Conceptual Framework to Aid Attribute Selection in Machine Learning Student Performance Prediction Models
by: Khan I., et al.
Published: (2023) -
A Systematic Approach to Transform Machine Learning Students� Performance Prediction Model into Preventive Procedures
by: Khan I., et al.
Published: (2023) -
Selecting Machine Learning Models for Student Performance Prediction Aligned with Pedagogical Objectives
by: Khan I., et al.
Published: (2024) -
Learning problem solving skills: Comparison of E-learning and M-learning in an introductory programming course
by: Malik S.I., et al.
Published: (2023)