Ambitious Mashups: Research Methods

Authors: Judi Fusco & Patricia Schank; Contributor: Jeremy Roschelle

“I see exciting possibilities in Cyberlearning for thinking about tool design and analytics design together, such that learning environments produce useful data and are designed to take advantage of the data to support teachers and students as well as their own continual self-improvement.”
– Alyssa Wise (excerpt from 6/1/20 reflections on her work and field)

Definition

Cyberlearning projects explore the frontiers of learning with technology, and to do so, the methods they use need to be innovative and informative. While methods are part of every project, they sometimes become the prime focus of the project—for example, when the methods are uniquely innovative or being refined as part of the work. Even established methods can take center stage when they deeply shape the work being done. Because of the interdisciplinarity of Cyberlearning projects, we also see methods from different fields combined in new ways to provide insights to questions. In reviewing the portfolio, the most common or growing methodological approaches found were:

  • Design-Based Research (DBR). Researchers create learning experiences and study them to investigate potential advances and to better understand what the target users and communities need. In Cyberlearning, DBR is a methodology that rigorously explores which design features have the most potential to improve learning (Brown, 1992; Hoadley, 2002).
  • Learning Analytics. Learning analytics can provide insights to the learning process and are often linked to formative assessment, sometimes in Intelligent Tutoring Systems (ITS), to provide students with direct feedback and/or give teachers more information to help their students. In addition, learning analytics have been used to support group problem solving by helping learners acquire content knowledge or to support collaborative processes.
  • Multimodal Analytics. Building on learning analytics, multimodal analytics is a method that involves the integration and analysis of multiple data sources (e.g., visual, audio, gestural, movement, eye gaze, heart rate, and/or other types) to help researchers measure learning in new ways and gain insight into learners’ abilities, emotions, needs, and preferences and how these impact learning interventions.

Please see the full report for additional information on how this theme changed over time in cyberlearning research and for some questions that arose as we investigated the theme.

Project Examples and Resources

Design-based Research (DBR)

  • 22 projects
  • 4 sessions at cyberlearning convenings

Stimulating Quotes and Snippets

  • “I use design-based research approaches to co-create learning experiences that promote disciplinary engagement mediated by practitioners’ tools and cyberlearning innovations” – Ale Magana
  • “The curriculum, which being co-designed by teachers, scientists, and curriculum developers, is being implemented in the New York City public schools, the largest school district in the U.S. To me, the most important component is the lasting impact, the sustainability of that impact, and integration within the community.” – Lauren Birney

Example Project Abstracts:

Related Primers/Spotlights/Reports:

Showcase Videos and/or Gallery Posters:

Cross Connections:
AI (Robotics), Emerging / Smart & Connected

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