Open Source Python Psychometrics Projects

PsychoPy is a free, open-source software package for creating and conducting behavioral science experiments. It is widely used in psychology, neuroscience, psychophysics, and related research disciplines. The software provides precise control over visual and auditory stimuli, experimental timing, and participant responses. Researchers can create experiments through a graphical Builder interface or develop customized procedures using Python scripts. PsychoPy supports behavioral measurements, stimulus presentation, and integration with specialized research hardware. Experiments can run locally, while compatible studies can be deployed online using JavaScript and Pavlovia. Its flexible architecture and extensive experimental design capabilities make it suitable for students, educators, and researchers conducting reproducible scientific investigations.

The Model Zoo of Cognitive Diagnosis Models, including classic Item Response Ranking (IRT), Multidimensional Item Response Ranking (MIRT), Deterministic Input, Noisy "And" model(DINA), and advanced Fuzzy Cognitive Diagnosis Framework (FuzzyCDF), Neural Cognitive Diagnosis Model (NCDM), Item Response Ranking framework (IRR), Incremental Cognitive Diagnosis (ICD) and Knowledge-association baesd extension of NeuralCD (KaNCD). Cognitive diagnosis model (CDM) for intelligent educational systems is a type of model that infers students' knowledge states from their learning behaviors (especially exercise response logs). Typically, the input of a CDM could be the students' response logs of items (i.e., exercises/questions), the Q-matrix that denotes the correlation between items and knowledge concepts (skills). The output is the diagnosed student knowledge states, such as students' abilities and students' proficiencies on each knowledge concepts.

Datasets in Education and convenient interface for downloading and preprocessing dataset in education. The CLI tools to quickly convert the "raw" data of the dataset into "mature" data for knowledge tracing task. The "mature" data is in json sequence format and can be modeled by XKT and TKT(TBA) The analysis dataset tool only supports the json sequence format. To check the following statical indexes of the dataset. In order to better verify the effectiveness of the model, the dataset is usually divided into train/valid/test or using kfold method. Each item in the sequence represents one interaction. The first element of the item is the exercise id (in some works, the exercise id is not one-to-one mapped to one knowledge unit(ku)/concept, but in junyi, one exercise contains one ku) and the second one indicates whether the learner correctly answers the exercise, 0 for wrongly while 1 for correctly.

psignifit is a toolbox to fit psychometric functions and test hypotheses on psychometric data. This is version 3 which will now predominantly support python.