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A4L Network Announces Whitepaper Series

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The Analytics for Learning (A4L) Network is pleased to announce the release of the Whitepaper Series, Measurement in Digital Environments. The purpose of this series was to provide emerging researchers with an opportunity to develop and share their work related to measuring learning behaviors within digital learning environments using data intensive research techniques. To participate in the series, researchers submitted a proposal outlining their  idea, and invited researchers received support on using evidence-centered design as a framework for developing measures of learning strategies and behaviors. These whitepapers serve as excellent examples of how to measure hard-to-measure constructs using data from digital learning environments.

  • Jun Xie and Xiangen Hu examines the error-management strategies (e.g., help seeking) that students used within Assessment and LEarning in Knowledge Spaces (ALEKS) environment.
  • Laura Allen describes an approach to measuring affect as students develop texts within automated writing environments.
  • Maria Ofelia Z. San Pedro outlines ways of measuring carelessness across different digital learning environments.
  • Vitomir Kovanović and colleagues describe how to measure cognitive presence (i.e., engagement and knowledge construction) using multiple techniques.
  • Mutlu Cukurova, Manolis Mavrikis, and Rose Luckin provide a multi-modal approach to measuring collaborative problem solving.
  • Ningyu Zhang and Gautam Biswas measure science and computational thinking within the Computational Thinking for Simulation and Modeling (CTSiM) learning environment.
  • Drew Hicks, Michael Eagle, and Elizabeth Rowe use interaction networks to measure wheel-spinning behaviors across different digital environments.
  • Caitlin Mills describes ways of measuring mind wandering using system log data.
  • Srećko Joksimović and colleagues outline approaches for bringing together different data types to understand learning in nonformal environments.
  • SungJin Nam, Kevyn Collins-Thompson, and Gwen Frishkoff provide a detailed account of measuring off-tasks behaviors within intelligent tutoring systems.
  • Hannah Gogel and Shir Nehama describe strategies for measuring pain points in digital learning environments, such as wheel-spinning events and transfer failures.
  • Roya Hosseini examines how to measure problem-solving within programming environments.
  • Ji-Eun Lee and Mimi Recker describe approaches for measuring self-regulated learning behaviors using data from learning management systems.
  • Kristopher Kyle outlines ways of measuring writing quality using multiple data-driven indices.
10 Feb, 17

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