Predicting Students Drop Out: A Case Study
By Gerben Dekker, Mykola Pechenizkiy, Jan Vleeshouwers. Educational Data Mining, 2009
443 citations recorded by the source corpus.
View Paper: https://www.semanticscholar.org/paper/b0185d5ffa59106088125d82a3ca296bc5b09c87
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Cristóbal Romero
- Z. Papamitsiou
- Sebastián Ventura
- Anastasios A. Economides
- Ryan Shaun Joazeiro de Baker
- Himabindu Lakkaraju
- Diyi Yang
- Carolyn Penstein Rosé
Citations in the corpus
- Educational data mining and learning analytics for 21st century higher education: A review and synthesis (2019, unknown): “The evaluation and monitoring practices of students learning is considered as an essential aspect in higher education (Dekker et al., 2009).”
- A Machine Learning Framework to Identify Students at Risk of Adverse Academic Outcomes (2015, background): “Each of these aspects allows us to obtain a better understanding of the model behavior.”
- Educational Data Mining: A Review of the State of the Art (2010, methodology): “for engagement prediction [64]; decision tree, Bayesian classifiers, logistic models, the rule-based learner, and random forest to detect/predict first-year student drop out [66]; paired t-test”
- “ Turn on , Tune in , Drop out ” : Anticipating student dropouts in Massive Open Online Courses (2013, methodology): “[23] conducted a case study in which they used machine learning techniques to predict student success using features extracted from student pre-university academic records.”
- Learning Analytics and Educational Data Mining in Practice: A Systematic Literature Review of Empirical Evidence (2014, methodology): “One of the most important goals of the systematic review was to reveal the added value of the field explored.”
- Stupid Tutoring Systems, Intelligent Humans (2016, background): “A similar goal can be achieved with predictive analytics models – models that make a prediction of some longer-term outcome, such as course failure or dropout (Arnold and Pistilli 2012; Barber and Sharkey 2012; Ming and Ming 2012), or failure to graduate (Dekker et al. 2009; Kovačić 2010).”