Introduction
EduStudio is a Unified Library for Student Assessment Models including Cognitive Diagnosis(CD) and Knowledge Tracing(KT) based on Pytorch.
EduStudio first decomposes the general algorithmic workflow into six steps: configuration reading, data prepration, model implementation, training control, model evaluation, and Log Storage. Subsequently, to enhance the reusability and scalability of each step, we extract the commonalities of each algorithm at each step into individual templates for templatization.
Configuration Reading (Step 1) aims to collect, categorize and deliver configurations from different configuration portals.
Data Preparation (Step 2) aims to convert raw data from the hard disk into model-friendly data objects.
Model Implementation (Step 3) refers to the process of implementing the structure of each model and facilitating the reuse of model components.
Training Control (Step 4) focuses primarily on the training methods of various models.
Model Evaluation (Step 5) primarily focuses on the implementation of various evaluation metrics.
Log Storage (Step 6) aims to implement storage specification when store generated data.
The modularization establishes clear boundaries between various programs in the algorithm pipeline, facilitating the introduction of new content to individual modules and enhancing scalability.
The overall structure is illustrated as follows:
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