Predicting academic success in higher education: literature review and best practices
Imam Abdulrahman Bin Faisal University
Abstract
Abstract Student success plays a vital role in educational institutions, as it is often used as a metric for the institution’s performance. Early detection of students at risk, along with preventive measures, can drastically improve their success. Lately, machine learning techniques have been extensively used for prediction purpose. While there is a plethora of success stories in the literature, these techniques are mainly accessible to “computer science”, or more precisely, “artificial intelligence” literate educators. Indeed, the effective and efficient application of data mining methods entail many decisions, ranging from how to define student’s success , through which student attributes to focus on , up to…
Citation impact
- FWCI
- 73.18
- Percentile
- 100%
- References
- 111
Authors
2Topics & keywords
- Computer science
- Field (mathematics)
- Higher education
- Process (computing)
- Set (abstract data type)
- Metric (unit)
- Educational data mining
- Data science
- Quality Education