Digital Module 42: An Introduction to Analyzing Unstructured Data in Education

Module Abstract Unstructured data, for example, text, audio, handwriting and drawings, video, and interaction logs, are increasingly abundant in education. However, they lack the predefined schema that conventional psychometric tools assume. This module introduces a principled, end‐to‐end workflow for turning such data into defensible measures. In this module, we first define unstructured data (Section 1) and then proceed to four analytic stages: preprocessing across modalities (Section 2), data representation (Section 3), making inferences (Section 4), and evaluating the resulting measures against psychometric standards (Section 5). Finally, Section 6 gives an overview of data privacy, consent, and governance. We demonstrate the methodologies using a dataset collected from a collaborative problem‐solving task. By the end, learners will have a conceptual map of the analysis pipeline from raw signals to valid inference, a solid understanding of modern representation methods, and a framework for evaluating and governing measures built from unstructured data in the field of education.