Add to ORKGStudents of computer science studies enter university education with very different competencies, experience and knowledge. 145 datasets collected of freshmen computer science students by learning management systems in relation to exam outcomes and learning dispositions data (e. g. student dispositions, previous experiences and attitudes measured through self-reported surveys) has been exploited to identify indicators as predictors of academic success and hence make effective interventions to deal with an extremely heterogeneous group of students
The goal of this project was to assess student learning in the Computer Science section of the Front...
Academic performance of students is a primary factor in student attrition. Being able to relia...
In recent years, not only has there been a dramatic drop in the number of students enrolling in comp...
Four studies were conducted using different data analytic techniques to give insight into how underg...
This study examined the problem of predicting achievement for introductory computer science courses ...
Professors often develop anecdotal guidelines about how each student’s past performance in their aca...
A computing student will over the first three years of their studies complete approximately 20 exams...
This paper presents a new approach to automatically detect- ing lower-performing or “at-risk” studen...
A model for predicting student performance on introductory programming modules is presented. The mod...
Abstract Predicting Student Success in an Introductory Programming Course at an Urban Midwestern Com...
With its strong commitment in supporting students to complete a high quality education within four y...
Educational data mining has been extensively used to predict students’ performance in university cou...
AbstractEducational data mining is a growing field that uses the data obtained from educational info...
Computer science students starting their studies at our uni-versity often fail their first mandatory...
This thesis describes a longitudinal study on factors which predict academic success in introductory...
The goal of this project was to assess student learning in the Computer Science section of the Front...
Academic performance of students is a primary factor in student attrition. Being able to relia...
In recent years, not only has there been a dramatic drop in the number of students enrolling in comp...
Four studies were conducted using different data analytic techniques to give insight into how underg...
This study examined the problem of predicting achievement for introductory computer science courses ...
Professors often develop anecdotal guidelines about how each student’s past performance in their aca...
A computing student will over the first three years of their studies complete approximately 20 exams...
This paper presents a new approach to automatically detect- ing lower-performing or “at-risk” studen...
A model for predicting student performance on introductory programming modules is presented. The mod...
Abstract Predicting Student Success in an Introductory Programming Course at an Urban Midwestern Com...
With its strong commitment in supporting students to complete a high quality education within four y...
Educational data mining has been extensively used to predict students’ performance in university cou...
AbstractEducational data mining is a growing field that uses the data obtained from educational info...
Computer science students starting their studies at our uni-versity often fail their first mandatory...
This thesis describes a longitudinal study on factors which predict academic success in introductory...
The goal of this project was to assess student learning in the Computer Science section of the Front...
Academic performance of students is a primary factor in student attrition. Being able to relia...
In recent years, not only has there been a dramatic drop in the number of students enrolling in comp...