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Validation of the EDUSS Framework for Self-Actualization Based on Transparent User Models: A Qualitative Study., , , , , and . UMAP (Adjunct Publication), page 229-238. ACM, (2023)Interactive Explanation with Varying Level of Details in an Explainable Scientific Literature Recommender System., , , , , , and . CoRR, (2023)Justification vs. Transparency: Why and How Visual Explanations in a Scientific Literature Recommender System., , , , , , and . CoRR, (2023)Designing Theory-Driven Analytics-Enhanced Self-Regulated Learning Applications., , , , and . CoRR, (2023)Towards a Flexible User Interface for 'Quick and Dirty' Learning Analytics Indicator Design., , , and . CoRR, (2023)Is More Always Better? The Effects of Personal Characteristics and Level of Detail on the Perception of Explanations in a Recommender System., , , , , , and . CoRR, (2023)Interactive Visualizations of Transparent User Models for Self-Actualization: A Human-Centered Design Approach., , , , and . Multimodal Technol. Interact., 6 (6): 42 (2022)On-demand Personalized Explanation for Transparent Recommendation., , , , , , , and . UMAP (Adjunct Publication), page 246-252. ACM, (2021)Explaining User Models with Different Levels of Detail for Transparent Recommendation: A User Study., , , , , , and . UMAP (Adjunct Publication), page 175-183. ACM, (2022)Learner Modeling and Recommendation of Learning Resources using Personal Knowledge Graphs., , , , , and . LAK, page 273-283. ACM, (2024)