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UKDE 2024 : International Workshop on User-Centered Practices of Knowledge Discovery in Educational Data | |||||||||||||||
Link: http://ukde2024.isti.cnr.it | |||||||||||||||
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Call For Papers | |||||||||||||||
Please accept our apologies in case of multiple receptions.
Please send to interested colleagues and students. UKDE 2024 - Call for Papers 1st International Workshop on User-Centered Practices of Knowledge Discovery in Educational Data to be held as part of ACM UMAP 2024. Event: July 01-04th 2024 (TBD), Cagliari, Sardinia, Italy. Website: http://ukde2024.isti.cnr.it CONTEXT & OBJECTIVES The increasing amount of learning data, originated from a variety of learning contexts (e.g., Massive Open Online Courses - MOOCs, intelligent tutoring systems, and flipped classroom courses) is soliciting interesting educational research questions. Notable research directions include exploring and understanding how students learn and how people teach, as well as developing strategies for supporting learners and teachers effectively. Current research has greatly expanded our understanding on artificial intelligence, but data, methods, and tools applied to (online) education are still limited, and often do not cover different contexts or diverse types of learners, which would require tailored solutions in order to be effective. Given the importance of this domain, top-tier research communities are giving increasing attention to knowledge discovery in educational data, but however, tend to work independently. On the one hand, the more technical-oriented research communities, such as UMAP, are developing effective general-purpose systems that adapt to individual users or groups of users, and that collect, represent, and model user information. On the other hand, the more education-oriented communities, such as Artificial Intelligence in Education (AIED), Educational Data Mining (EDM), and Learning Analytics and Knowledge (LAK) provide rich expertise on cognitive, psychological, and learning science perspectives as the intelligent methods they adopt or propose are specialised on educational data. Complementary to these educational and technical perspectives, the increasing impact of algorithmic decision-making on education has brought about growth opportunities and concerns. Research on responsible user modelling has been growing, but this effort within the considered communities is still under-explored. UKDE 2024 will be the UMAP's workshop event aimed at collecting high-quality, high-impact, original research on important problems related to the design and development of responsible knowledge discovery for teaching and learning.The purpose of UKDE is to bridge theUMAP community with the educational sister communities, challenging all of them into a unique yet sensitive applicative scenario for advancing the field of responsible intelligent models that exploit data from educational environments. To this end, UKDE will promote contributions from researchers, academia, and industries working on topics addressing these challenges from a technical point of view, but also from an ethical, sociological, and cognitive perspective, with interdisciplinarity as the main driver. IMPORTANT DATES Paper Submission Deadline: April 24, 2024 Accept/Reject Notification: 8 May, 2024 Camera-ready Deadline: 16 May, 2024 Event: TBD SUBMISSION & PUBLICATION We warmly invite authors to submit their full and short papers for consideration. Accepted papers will be presented at the conference and published in the adjunct proceedings published by ACM. Submission link: https://easychair.org/my/conference?conf=umap24 TOPICS We welcome contributions that address (but are not limited to) the following topics of interest: Techniques and Models: Modelling representations of learners from data; Building representations of domain knowledge from data; Multimodal/semantic approaches for learners' behaviour modelling or personalization; Personalized support tools and systems for communities of learners; Temporal, behavioural, and physiological analysis of learners' behaviour; Systems that detect and/or adapt the platform to emotional states of learners; Techniques to provide automated proctoring support during online examinations; Developing fair and explainable models for different kinds of stakeholders; Developing privacy-protecting algorithms for learners' data processing; Modelling motivation, metacognition, and affective aspects of learning. AI-assisted and Interactive Technologies: Generative AI; Semantic web technologies; Multi-agent architectures; Wearables; Natural language processing and speech technologies; Virtual and augmented reality. Evaluation Protocol and Metric Formulation: Performing auditing studies with respect to bias and fairness; Defining objective metrics for knowledge discovery in education; Formulating bias-aware protocols to evaluate existing algorithms; Evaluating existing mitigation strategies in unexplored domains; Comparative studies of existing evaluation protocols and strategies; Analyzing efficiency and scalability issues of debiasing methods; Replicating previous studies with different samples, domains and/or contexts. Dataset Collection and Preparation: New tools and systems for capturing educational data; Integrating data from multiple (and diverse) data sources; Creating datasets that allow to explore ethical dimensions; Designing collection protocols tailored to responsible knowledge discovery. Case Study Exploration: Educational games; Learning management systems; Interactive simulations; Intelligent tutoring. PROGRAM CO-CHAIRS Francesca Maridina Malloci, University of Cagliari, Italy Paola Mejia, EPFL, Switzerland Agathe Merceron, Berliner Hochschule für Technik, Germany Anna Monreale, University of Pisa, Italy Daniela Rotelli, University of Pisa, Italy |
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