L@S 2019

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L@S 2019
6th ACM Conference on Learning at Scale
Event in series L@S
Dates 2019/06/24 (iCal) - 2019/06/25
Homepage: https://learningatscale.acm.org/las2019/
Twitter account: @LearningAtScale
Location
Location: Chicago, Illinois, USA
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Committees
General chairs: David Joyner
PC chairs: John C. Mitchell, Kaska Porayska-Pomsta
Table of Contents
Tweets by @LearningAtScale


Event


Example topics: Specific topics of relevance include, but are not limited to:

  • Novel assessments of learning, including those drawing on computational techniques for automated, peer, or human-assisted assessment.
  • New methods for validating inferences about human learning from established measures, assessments, or proxies.
  • Experimental interventions that show evidence of improved learning outcomes, such as
  • Domain independent interventions inspired by social psychology, behavioural economics, and related fields, including those with the potential to benefit learners from diverse socio-economic and cultural backgrounds
  • Domain specific interventions inspired by discipline-based educational research that may advance teaching and learning of specific ideas or theories within a field or redress misconceptions.
  • Heterogeneous treatment effects in large experiments that point the way towards personalized or adaptive interventions
  • Methodological papers that address challenges emerging from the “replication crisis” and “new statistics” in the context of Learning at Scale research:
  • Best practices in open scie nce, including pre-planning and pre-registration
  • Alternatives to conducting and reporting null hypothesis significance testing
  • Best practices in the archiving and reuse of learner data in safe, ethical ways
  • Advances in differential privacy and other methods that reconcile the opportunities of open science with the challenges of privacy protection
  • Tools or techniques for personalization and adaptation, based on log data, user modeling, or choice.
  • Approaches to fostering inclusive education at scale, such as:
  • The blended use of large-scale learning environments in specific residential or small-scale learning communities, or the use of sub-groups or small communities within large-scale learning environments
  • The application of insights from small-scale learning communities to large-scale learning environments
  • Learning environments for neurodevelopmental, cultural, and socio-economic diversity
  • Usability, efficacy and effectiveness studies of design elements for students or instructors, such as:
  • Status indicators of student progress or instructional effectiveness
  • Methods to promote community, support learning, or increase retention at scale
  • Tools and pedagogy such as open learner models, to promote self-efficacy, self-regulation and motivation
  • Log analysis of student behaviour, e.g.:
  • Assessing reasons for student outcome as determined by modifying tool design
  • Modelling learners based on responses to variations in tool design
  • Evaluation strategies such as quiz or discussion forum design
  • Instrumenting systems and data representation to capture relevant indicators of learning
  • New tools and techniques for learning at scale, such as:
  • Games for learning at scale
  • Automated feedback tools, such as for essay writing, programming, and so on
  • Automated grading tools
  • Tools for interactive tutoring
  • Tools for learner modelling
  • Tools for increasing learner autonomy in learning and self-assessment
  • Tools for representing learner models
  • Interfaces for harnessing learning data at scale
  • Innovations in platforms for supporting learning at scale
  • Tools to support for capturing, managing learning data
  • Tools and techniques for managing privacy of learning data

The conference is co-located with and immediately precedes the 2019 International Conference on AI in Education in the same city and venue.

The conference organizers are:

   John C. Mitchell, Stanford University, Program Co-Chair
   Kaska Porayska-Pomsta, University College London, Program Co-Chair
   David Joyner, Georgia Institute of Technology, General Chair