Call for papers DS-LAK24

This workshop aims to explore methodological (formal and practical) approaches to actively increase data storytelling (DS) adoption and impact in the learning analytics (DS) community. Thus, this workshop will provide a scenario for participants to reflect and critically discuss the following aspects:

• What methodologies from other domains are suitable for DS in LA?
• How can researchers effectively evaluate the impact of DS in LA?
• How can we automate the process of generating fair and unbiased data stories?

To start, the organisers of the workshop will provide a review of lessons learnt from using DS to support stakeholders’ interpretations of visual interfaces from the current literature in LA and other research fields, such as Information Visualization (InfoVis) and Human-Computer Interaction (HCI). This review will be a starting point to open the discussion with participants regarding challenges (e.g., automating DS according to particular needs) and opportunities (e.g., the use of AI to generate narratives to support interpretations) of DS to effectively support educational stakeholders to make sense of their data traces and make them actionable to improve their practice.

Topics of interest

We invite researchers to submit their work, including case studies, interactive visualisations, and narrative-driven stories.

• Data storytelling for impact: How can data storytelling be used to communicate learning insights and inform students/teachers' actions?
• Developing and evaluating methodologies for data storytelling: What are the most effective ways to communicate learning/teaching stories with data? What methodological approaches can be adopted to generate educational data stories?
• Evaluating and measuring the impact of data storytelling approaches on learning outcomes: How can we measure the effectiveness of data storytelling in teaching and learning? What other evaluation methodologies beyond usability could be adopted to measure the impact of educational data storytelling?
• Designing and implementing automated data storytelling tools and techniques: Which tools and techniques could automate the process of creating educational data stories? How can Generative-AI be incorporated to automate the design and deployment of educational data stories and learning analytics dashboards?
• Addressing bias and fairness in data storytelling approaches: How can we ensure that educational data stories are fair and accurate representations of reality?

This list is not exhaustive, and we encourage you to submit your ideas for other data storytelling topics. 

Submission Guidelines

Submissions will follow a double-blinded peer review process. Each submission will be reviewed by at least two PC members. Please, remove all identifying information.

Submission types:

• Short papers (up to 5 pages + references): can address ongoing work, including a briefly described theoretical underpinning, an initial proposal or rationale for a technical solution, and preliminary results.
• Long papers (up to 10 pages + references): include a clearly explained substantial conceptual, technical or empirical contribution to educational data storytelling and/or its application in learning analytics dashboards. 

Use the following templates to prepare your submission.

• Overleaf Template
• Microsoft Word template

Accepted full and short research papers will be included in the DS-LAK24 workshop proceedings and published on the website and in CEUR-workshop proceedings (depending on the number of papers accepted).

Please note at least one of the authors of each accepted submission must register for the workshop before February 15, 2024.

Important dates 

• Workshop Paper Submission: 16 Dec 2023
• Notification of acceptance:  13 Jan 2024