日本データベース学会の皆様 （重複してお受け取りの際はご容赦ください） 京都大学のフラナガンと申します。 学習分析（ラーニングアナリティクス）に関する国際ワークショップLA@ICCE2018 を2018年11月26日～27日（のいずれか1日）にManilaで開催予定です。 今年、教材の閲覧ログに基づいて、学生の成績予測に関するタスクを開催致します。 詳細はこちらをご覧下さい。 https://easychair.org/cfp/LA-ICCE18 投稿締切は2018年8月17日（金）となっております。 皆様のご投稿、ご参加をお待ちしております。 -------------------------------------------------------------------- LA@ICCE2018 5th ICCE workshop on Learning Analytics (LA) & Joint Activity on predicting student performance All accepted papers for mini-conference-style workshop will appear in one volume of workshop proceedings with ISBN and will be indexed by Elsevier Bibliographic Database. -------------------------------------------------------------------- :::Important Dates::: Paper submission: August 17, 2018 Notification of acceptance: September 7, 2018 Camera-Ready and registration deadline: September 14, 2018 :::Workshop Overview::: The increasing amount of data generated in digital learning contexts provides opportunities to benefit from learning analytics as well as challenges related to interoperability, privacy, and pedagogical and organizational models. As a consequence, new methodologies and technological tools are necessary to analyze and make sense of these data and provide personalized scaffolding and services to stakeholders including students, faculty/teachers and administrators, as well as parents. Pedagogical and organizational models must also be incorporated in order to take advantage of the personalized scaffolding and services to ensure productive learning and teaching. In addition, access to data from different sources raises a number of concerns related to data sharing and interoperability, and protection of privacy for individuals and business interests for institutions. :::Joint Activity on predicting student performance::: This year participants will also have a chance to partake in a joint activity on the prediction of student performance by analyzing reading patterns from logs of an e-book system. A dataset of anonymized reading log data is provided in advance to create models that can predict the final grade scores for each student. Participants will be encouraged to share their results and insights by submitting a paper for presentation at the workshop. For more details please refer to the joint activity website: https://lab.let.media.kyoto-u.ac.jp/icce2018la/. We call for papers in addition to the joint activity that cover technical, theoretical, pedagogical, as well as organizational issues in learning analytics. We also welcome submissions on some of the topics concerning LA from the following (though not restrictive) list: - Making sense of learning analytics - Software systems and tools - Implementation and organizational development - Pedagogical models and learning analytics - Gathering diverse learning data, e.g., related to linked data - Algorithms for analytics based on gathered data - Predictive models, visualization and statistical analysis - Privacy concerns and policy aspects related to LA - Data sharing for learning analytics - Evaluation and Assessment - Standardization and Interoperability - Challenges and approaches for scaling up LA in education practices --- Co-Organizers: Brendan Flanagan Weiqin Chen