Call for Abstracts

Description

In order to facilitate conversation and establish a foundation for the discussion in game-based learning analytics, we invite attendees to submit an abstract related to challenges encountered while implementing or analyzing learning data captures by game-like / playful platform (eg. learning game). 

These abstracts will be published to CEUR-WS with a potential option to expand the abstract to a short a paper (4 pages max). More information will be shared on this along with the notification of acceptance. If you have any questions or concerns, you may reach out to the organizing team at gbla@nyu.edu.

The content of your abstract must include the following:

• A description of a past, recent, or in-progress project involving learning analytics in learning game

• A description of one or more challenges unique to the combination of learning analytics and learning games, including but not limited to: 

  • designing and analyzing game-based learning models

  • systems and infrastructure for capturing learning data

  • ethics of using learning data 

Your abstract submission must follow these requirements:

• The abstract must not exceed 250 words.

• Your submission must use the CEUR-WS template. (Overleaf, Word)

• Your submission must be submitted in PDF format.

• Your submission must be submitted by the submission deadline of December 4th, 2024.