Workshop Details

This event is a half-day face-to-face workshop that uses a mini-conference series style. There will be a handful of paper presentations, a keynote speaker, and a panel discussion with leading experts to discuss key challenges and opportunities for situating affect in learning analytics.

Interdisciplinary research teams are invited to submit 1) work-in-progress or 2) completed papers related to affect in learning and education and its role in learning analytics and related themes with emerging technologies.

We will also have open participation such that anyone interested may register to attend.

We will also discuss the emergence of a special interest group that contributes to building bridges between interdisciplinary community members to increase knowledge and understanding of the current state-of-the-art and future directions and applications. The formation of this group will be discussed in the meeting and possibly a working group may be formed to work on this issue.

Submission Guidelines

Authors should submit their papers (min. 500 words) to Elizabeth Cloude at ecloude@upenn.edu. The format is should adhere to a 1-column style using a Word document (found here). Please ensure the paper is less than 10 pages.

Please note all papers selected for presentation during the workshop will NOT be included in the LAK companion proceedings this year. Independent proceedings shall be submitted to CEUR-WS.org for online publication, but this is voluntary for authors.

All questions can be directed to Elizabeth Cloude at ecloude@upenn.edu.

Possible Themes

Addressing the current challenges of situating affect in the field of learning analytics with emerging technologies including

How can researchers address the issues of practice application and impact?
How can accounting for affect in learning analytics inform socio-emotional and emotion regulation skills?
How can situating affect in learning anlaytics contribute to increasing the accessibility, inclusivity, and quality of education for diverse learners with particular focus on under-represented groups (gender, race, disability, socio-economic statuc, etc.)?
How can affective science approaches contribute to the development of equitable proactices for teaching and learning?
How can accounting for affective experiences contribute to building trustworthy learning analytics that more accurately represent a learner's experience?

Discussions on leveraging novel methods, theories, and/or applications for operationally linking affect to theory:

Recent advances in affective sciences and affective computing methods and approaches, including new paradigms, tools, measures, and techniques applied to learning or learners
- Both large- and small-scale approaches are encouraged
Personalized and adaptive learning with emerging technologies
Innovative data collection, analysis, or presentation methods
Temporal aspects of affect and their dynamics in relation to learning and performance