5 papers
Designing for Interpretation Uncertainty: Architecture and Principles for Topological Learning Analytics Dashboards
Hitoshi Inoue, Koichi Yasutake
Topological Data Analysis (TDA) offers novel methods for understanding temporal dynamics in complex systems, yet its application in information systems design faces a fundamental c…
Participation-Sensitive Convergence and the Fragment First, Converge Later Pattern in Asynchronous Online Learning: A Topological Analysis Across 22 OULAD Courses
Hitoshi Inoue, Koichi Yasutake
Asynchronous online learning offers temporal flexibility at a structural cost: learning communities tend to fragment rather than cohere. , the number of disconnected behaviora…
Beyond the Clique: Comparing Clique and Dowker Complexes for Co-occurrence Data in Learning Analytics
Koichi Yasutake, Wakana Tsuji, Hitoshi Inoue
Learning analytics increasingly represents the relations in co-occurrence data (codes in a window of discourse, participants in a thread, tags on a post) as simplicial complexes an…
Period Segmentation in Transition Network Analysis: A Topological Data Analysis Approach
Hitoshi Inoue, Koichi Yasutake
Temporal dynamics in learning behavior can be revealed through period segmentation in Transition Network Analysis (TNA). Cristea et al. demonstrated that segmenting courses into ha…
What fidelity metrics miss: a structural check on synthetic educational data
Hitoshi Inoue, Koichi Yasutake
Secondary use of educational records is increasingly mediated by platforms that share a differentially private synthetic version of a dataset and validate specific findings against…