Behavior-Based Grade Prediction for MOOCs Via Time Series Neural Networks
By Tsung-Yen Yang, Christopher G. Brinton, Carlee Joe-Wong, Mung Chiang. 2017
129 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computer Science Applications
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Ala Al-Fuqaha
- Mohsen Guizani
- Sameh Sorour
- Dirk Ifenthaler
- M. Mohammadi
- Jane Yin-Kim Yau
- Ekram Hossain
- Sanjay Chawla
In Computer Science Applications
Citations in the corpus
- Deep Learning for IoT Big Data and Streaming Analytics: A Survey (2017, methodology): “Yang et al. [117] proposed a method for predicting student grades in MOOCs.”
- Utilising learning analytics to support study success in higher education: a systematic review (2020, methodology): “…2014; Manrique et al. 2018; Nespereira et al. 2015; Nguyen et al. 2017; Saqr et al. 2017), with the detailed analysis of clickstream or trace-data also being used to predict student dropout (Whitehill et al. 2017), student retention (Wolff et al. 2013), or student performance (Yang et al. 2017).”