LA-Asia20: International Conference on Learning Analytics in Asia 2020 Kyoto Research Park Kyoto, Japan, August 7-9, 2020 |
Conference website | https://sites.google.com/view/la-asia20/home |
Submission link | https://easychair.org/conferences/?conf=lakasia20 |
As the field of learning analytics continues to mature, it is increasingly important to analyze evidence of effective LA implementations and facilitate dissemination throughout the community in Asia. This conference aims to bring together the LA community in Asia to discuss the unique challenges faced in the region and foster developments in the field.
LA-Asia20 invites various research associates to discuss the current status, technical challenges, of the future services and applications, as part of a rich conference program including Keynote talks, Paper Presentations as well as Tutorials and Workshop Sessions.
Submission Guidelines
Main conference track
Submissions Categories
- Full paper: 6 pages
- Short paper: 4 pages
- Poster paper: 2 pages
Submissions of high-quality papers in all areas of Learning Analytics.
Authors are kindly invited to submit their papers following the
LA-Asia20 Proceedings Template: http://bit.ly/laasia20Template
Papers can be submitted through the LA-Asia20 Easychair website:
https://easychair.org/conferences/?conf=lakasia20
Important Dates (tentative)
- Submission due date: 23rd March 2020
- Review notification: end of April 2020
- Camera-ready: end of May 2020
Review Process
All submissions to the research track will undergo a double blind peer review by at least 3 reviews. Workshop and tutorial proposals will go through a single blind peer review process.
List of Topics
We had welcome submissions on some of the following topics (though not restrictive):
- Making sense of learning analytics
- Software systems and tools
- Implementation and organizational development
- Pedagogical models and learning analytics
- Gathering and analyzing multimodal learning 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
- Exploring critical factors that affect students’ learning performance
- Estimating the influence of prevention or intervention
- Psychology-supported learning analytics
Pre-conference event track
Workshop (4 pages) provide an efficient forum for community building, sharing of perspectives, and idea generation for specific and emerging research topics or viewpoints. Proposals should be explicit regarding the kind of activity participants should expect, for example from interactive/generative participatory sessions to mini-conference or symposium sessions.
Tutorials (4 pages) aim to educate stakeholders on a specific learning analytics topic or stakeholder perspective. Proposals should be clear what the need is for particular knowledge, target audience and their prior knowledge, and the intended learning outcomes.
Journal track submissions
Some of the high quality papers will be invited to submit the special issue in Education Technology & Society Journal
Call for papers for a special issue on “Precision Education - A New Challenge for AI in Education”
Objective
Precision education is a new challenge of applying artificial intelligence, machine learning, and learning analytics for improving teaching quality and learning performance. The goal of precision education is to identify at-risk students as early as possible and provide timely intervention based on teaching and learning experiences. The precision education was inspired by the precision medicine initiative proposed by the former USA President Obama in his 2015 State of the Union address. The emergence of precision medicine is to revolutionize the one-size-fits-all treatment of disease by taking into account individual differences in people’s genes, environments, and lifestyles, as well as by improving the diagnosis, prediction, treatment, and prevention of disease.
Similar to medicine, the current education system is designed not fully consider students’ IQ, learning styles, learning environments, and learning strategies. Inspired by precision medicine, precision education is an innovative approach to emphasize the improvement of diagnosis, prediction, treatment, and prevention of at-risk students, such as diagnosis of students’ engagement, learning patterns and behavior; prediction of students’ learning performance; treatment & prevention with teachers’ timely intervention and well-designed pedagogy, learning strategy, and learning activities. In this special issue, at-risk students are confined to students who were diagnosed could get low academic performance, drop/withdraw a course, or students who were low engagement in terms of learning behavior, emotion, and cognition.
The purpose of this special issue is to invite researchers who are engaged in precision education, artificial intelligence, machine learning, and learning analytics to share and exchange research experiences in various applications, methods, pedagogical models and environments. Topics of interests for this special issue include, but are not limited to the following:
- The impact of precision education to emerging pedagogical environments such as MOOCs, eBook, coding, AR/VR, robotics, games, et al.
- Ethical and other concerns relating to precision education
- Diagnosis of students’ engagement, learning patterns and behavior
- Prediction of students’ learning performance and the improvement of predictive models
- Treatment & prevention with teachers’ timely intervention
- The design of pedagogical models and tools for precision education
- The design of learning strategy and learning activity for precision education
- The design of evaluation and assessment methods for precision education
- Exploring the critical factors affecting students’ learning performance based on precision education
- Exploring the influence of teachers’ intervention on students’ learning performance based on precision education
- Data analytics for precision education, such as text analytics, audio analytics, image analytics, video analytics
- Data visualization for precision education, such as dashboard, simulation
Important dates for journal track
Submission due: September 1, 2020
Review notification: October 15, 2020
Revision due: November 15, 2020
Acceptance notification: December 15, 2020
Publication issue: Volume 24, Issue 1, 2021
Committees
Conference co-chairs
- Hiroaki Ogata, Kyoto University, Japan
- Stephen J.H. Yang, National Central University, Taiwan
Program Co-chairs
- Brendan Flanagan, Kyoto University, Japan
- Owen H.T. Lu, National Central University, Taiwan
- Elizabeth Koh, NIE, Singapore
- Leon C.U. LEI, The University of Hong Kong, Hong Kong
Steering Committee
- Gökhan Akçapınar, Hacettepe University, Turkey
- Hyo-Jeong So, Ewha Womans University, South Korea
- Ma. Mercedes T. Rodrigo, Ateneo de Manila University, Philippines
- Seng Chee Tan, National Institute of Education, Nanyang Technological University, Singapore
- Sridhar Iyer, Indian Institute of Technology Bombay, India
- Thepchai Supnithi, NECTEC, Thailand
- Xiaoqing Gu, East China Normal University, China
Web chair
- Rwitajit Majumdar, Kyoto University, Japan