Automatic student performance prediction makes AI-based teaching much more advanced than traditional teaching. Fundamental hands-on skills and key algorithms will be introduced and summarized for the problem of students’ learning level regression. Special focus will be cast on the deep learning method. This workshop provides a wide range of possible applications for different disciplines, like students’ performance prediction, automatic warning/intervention systems, and individualized education systems. This workshop is developed specifically for the participants without any technology or programming background.
In this workshop, participants will be familiar with the basic programming environment setup and user interface of the free computing platform COLAB.
Basic algorithms in regression will be introduced, including Linear Regression, Random Forest, Support Vector Machine, and Deep Learning.
The workshop will also lead the participants to build an Artificial Neural Network (ANN) model in a toy example.
The concepts of pre-trained models and fine-tuning will be introduced. Participants will learn to fine-tune a pre-trained model with custom datasets.
Participants are expected to understand which factors could affect the model performance.
Dr Dongkun Han
Department of Mechanical and Automation Engineering
The Chinese University of Hong Kong