LAKMLA 2018 - Second Annual Workshop of the Methodology in Learning Analytics Bloc

As the learning analytics community matures, it is particularly important to establish standards for good practice. Clear methodological guidelines increase the quality of work and facilitate communication not only within the community but also with practitioners in other research communities, where norms may be clearer. This community-building workshop intends to convene methodology-focused researchers to discuss new and established approaches, comment on the state of current practice, author pedagogical manuscripts and posters, and co-develop guidelines to help move the field forward with quality and rigor.
In addition to a call for papers, we have added two new formats this year to help intermediate and novice researchers participate meaningfully in shaping the discussion: a poster session and solicitation for infographics on methodological guidelines; and a whole-workshop discussion session - bring a published paper to discuss, critique, or just ask questions about.
Submissions
The workshop is soliciting two publishable contribution types:
[NEW!] Methodology Guidelines Posters
Methodology Guideline Posters (MGPs) are infographic representations of decision flows in learning analytics methodology, working backwards from the ultimate goals. An MGP will emphasize how operational decisions are guided not only by the goals but also by the types and properties of available data and by problems of statistical inference. MGPs should not detail how to carry out analyses, but may point the reader to appropriate references. The emphasis of MGPs will be interrogating the methodological choices. As such they should describe alternate case scenarios, explain pitfalls, and suggest options for sensitivity and goodness-of-fit tests.
Posters can be submitted as a poster abstract (max 300 words) with a link to a high-resolution (print-ready) infographic poster, or a 2-page paper reporting on the poster content.
Workshop Papers
The workshop seeks to build a community of researchers with an interest in methodology and its rigorous application and development to the field of learning analytics. Recognizing the cross-disciplinarity of learning analytics, the workshop welcomes contributions from education and data science researchers. Specifically, we welcome papers on the following:
• Position papers that take a critical look at methodological practice in the learning analytics community.
• Exploration of new metrics and methods that are relevant, or indigenous, to learning analytics.
• Constructive analysis of metrics for both model evaluation, and comparison of model results where multiple models are reported on.
• Critique of sensitivities arising from data collection and variable operationalization choices in learning analytics.
• Considerations on inferring latent constructs of learning from measurable factors.
Please submit poster abstract and papers to EasyChair at the following link: https://easychair.org/conferences/?conf=lakmla2018. Submissions should follow the LAK'18 Companion Proceedings Template.
Important Dates
Submission Deadline for Workshop Posters and Papers: 18 December 2017
Notification of Acceptance: 15 January 2018
Camera-ready Posters and Papers for Companion Proceedings: 30 January 2018
Organising Committee
Yoav Bergner, Assistant Professor of Learning Sciences and Educational Technology at NYU Steinhardt.
Charles Lang, Visiting Assistant Professor in Learning Analytics at Teachers College, Columbia University.
Geraldine Gray, Senior Lecturer in Data Science, Institute of Technology Blanchardstown, Ireland.
For further information, please visit the workshop website at https://sites.google.com/a/nyu.edu/lakmla/, or email any of the organising committee.
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