The ability to predict student performance in a course or program creates opportunities to improve educational outcomes. With effective performance prediction approaches, instructors can allocate resources and instruction more accurately. Research in this area seeks to identify features that can be used to make predictions, to identify algorithms that can improve predictions, and to quantify aspects of student performance. Moreover, research in predicting student performance seeks to determine interrelated features and to identify the underlying reasons why certain features work better than others. This working group report presents a systematic literature review of work in the area of predicting student performance. Our analysis shows a cl...
Student dropout still becomes a critical problem in education. Educational Data Mining (EDM) can br...
AbstractPredicting student academic performance is one of the important applications of educational ...
A comprehensive systematic study was carried out in order to identify various deep learning methods ...
The ability to predict student performance in a course or program creates opportunities to improve e...
The ability to predict student performance in a course or program creates opportunities to improve e...
[EN] Academic performance analysis has gained popularity in the past decade. Using various predictio...
Predicting student academic performance is a critical area of education research. Machine learning (...
ABSTRACT Predicting student success has long been an interest of institutions of higher education a...
Despite of providing high quality of education, demand on predicting student academic performance be...
The objective of the study is to use a method to predict student performance during the semesters a...
ABSTRACT Considering the problems and challenges faced by educational institutions in analyzing stu...
AbstractPredicting students performance becomes more challenging due to the large volume of data in ...
Abstract: This study introduces a machine learning-based model for predicting student performance us...
oai:flr.journals.publicknowledgeproject.org:article/13Many studies have explored the contribution of...
The high failure rates of many programming courses means there is a need to identify struggling stud...
Student dropout still becomes a critical problem in education. Educational Data Mining (EDM) can br...
AbstractPredicting student academic performance is one of the important applications of educational ...
A comprehensive systematic study was carried out in order to identify various deep learning methods ...
The ability to predict student performance in a course or program creates opportunities to improve e...
The ability to predict student performance in a course or program creates opportunities to improve e...
[EN] Academic performance analysis has gained popularity in the past decade. Using various predictio...
Predicting student academic performance is a critical area of education research. Machine learning (...
ABSTRACT Predicting student success has long been an interest of institutions of higher education a...
Despite of providing high quality of education, demand on predicting student academic performance be...
The objective of the study is to use a method to predict student performance during the semesters a...
ABSTRACT Considering the problems and challenges faced by educational institutions in analyzing stu...
AbstractPredicting students performance becomes more challenging due to the large volume of data in ...
Abstract: This study introduces a machine learning-based model for predicting student performance us...
oai:flr.journals.publicknowledgeproject.org:article/13Many studies have explored the contribution of...
The high failure rates of many programming courses means there is a need to identify struggling stud...
Student dropout still becomes a critical problem in education. Educational Data Mining (EDM) can br...
AbstractPredicting student academic performance is one of the important applications of educational ...
A comprehensive systematic study was carried out in order to identify various deep learning methods ...