ALIN Open Dataset for Math Adaptive Learning

# Student Test Results Prediction based on Learning Behavior: Learning Beyond Tests The Goal is to predict Test Results, in the form of averaged correctness, averaged timespent in the test, based only on the learning history (learning  behavior records) # The DataSet The raw data is provided by ALIN.ai where a large number of students participated in math learning and tests, online. The feature constructed from the raw data is achieved by applying statistic functionals to the backend data sheets where learning behavior is recorded, such as 'points earned' in a 'learning session'. The final cohort we build from this learning senario consists of the predicting target: averaged correctness, and the averaged timespent, and the input features (43 dimensions). The input features consist of two parts, one contains information(5 dimensions) on the test itself, e.g. the difficulty; the other contains the rest 38 dimensions of features.     # Files Description ## student_data_processed.csvcontains data cohort used for modeling ## github link: https://github.com/AdaptiveLearning2022/DataSetALIN2022