Ambitious Mashups: Learning Theories

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

Definition

Theories of how people learn are an integral part of cyberlearning research. Projects interweave learning theories with emerging technology and research methods to uncover processes of how learning unfolds with theoretical depth and empirical precision in service of new theories of learning. Cyberlearning projects also use principles of how people learn to support learning in STEM (for example astronomy, data science, biology), topics beyond STEM (language learning, reading, writing) and workforce skills. In this review, the following three areas in learning theories were considered:

  • Collaborative Learning. Collaborative learning examines how people learn socially through shared words, actions, and meanings. In cyberlearning, collaborative learning occurs when the tool or environment for learning is social. The concept of collaborative learning is broad and includes collective inquiry, knowledge building, joint problem solving, intersubjectivity, shared/collective/group/distributed cognition, collective consciousness, and transactive discourse. From a constructivist perspective, learning occurs as participants make sense of their experience.
  • Embodied Learning. Embodied learning theories seek to understand how movements, gestures, and actions influence learning. In cyberlearning, embodied design guides the integration of gesture and technology; for example, virtual tutors gesture in interactions with learners and technologies recognize movements that are used in relation to concepts.
  • Identity. Sociocultural theories examine how a person forms their own identity situationally, and how learning is about developing identity (not just knowledge or skill). Identity development includes seeking to understand how you think of yourself, your perception of how others see you, and what perspective is promoted by society.

Among all themes examined in our reflection analysis, “learning theories” was the second most frequent tag for cyberlearning convening sessions. While here we focus on the three sub-areas above, other long-standing scientific theories also have a strong place in cyberlearning work. For example, cognitive theories are not explicitly included here, although cognitive theories often inform projects with respect to representations (e.g., games, simulations, and visualizations), methods, and AI (e.g., learning analytics and intelligent tutoring systems), and collaborative learning. Projects guided by neuroscience theories are discussed in the External Trends brief, but also overlap with projects tagged with embodied learning.

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

Collaborative Learning

36 Projects

Stimulating Quotes and Snippets:

  • Collaborative robots are emerging as a new family of advanced technologies that are designed to work side-by-side with people in industrial settings. Bilge Mutlu, Andrew Ruis, David Shaffer
  • This PI team asks (i) how to use the affordances of modular robotics for distributing work among individuals in a student groups to promote both better engagement and better learning among those learning algebra and (ii) what can be learned more generally from this effort about orchestrating and supporting learning when learners have available to them technology that supports distributed group work.
    Harry Cheng

Example Project Abstracts:

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Potential Platforms

Cross Connections:
AI/Robotics/ITS, Learning Analytics, Representations (VR/AR)

Embodied Learning

  • 15 Projects

Stimulating Quotes and Snippets

  • Embodied interactions (e.g., hand gestures, whole-body movements) have shown promise for increasing learning in specific STEM concepts, but less is known about how these interactions promote the understanding of abstract and crosscutting ideas such as scale, rates of change, patterns, etc. Using advanced gesture recognition technologies and immersive visualizations, we are attempting to create an expressive environment where students can learn STEM through their intuitive body actions. Robb Lindren
  • Our framework for this project is deeply rooted in research building on embodied cognition, multimodal learning theory, and science education with interdisciplinary elements that draw from music and arts-infused education. Erin Ottmar

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Cross Connections:
Learning Analytics, Neuroscience, including affective effects, AI/ITS/virtual tutors, AR/VR

Identity

  • 9 Projects

Stimulating Quotes and Snippets

  • Technology is enabling us to offer new identity opportunities for learners. It enables the learners to actually engage in rich learning contexts and then showcase that to their peers, parents, mentors and teachers, who often may not see them in these other realms. It gives us the opportunity to share more than a verbal experience. Tamara Clegg
  • Educational equity requires expanding the influence of socio-cultural approaches and bringing them into the foreground of cyberlearning. Angela Booker and Shirin Vossoughi

Example Project Abstracts:

Related Primers/Spotlights/Reports:

Showcase Videos and/or Gallery Posters:

Cross Connections:
Emergent (Smart and Connected) and Equity, Data Analytics, Methods (DBR), Representations (AR/VR, games), Informal, Collaborative

Exit Survey Highlights (30 total responses)

  • Projects tagged as one or more of the learning theory areas (collaborative learning; embodied; identity): 10
    • Collaborative learning: 6
    • Embodied: 2
    • Identity: 3
    • Some overlap between collaborative learning and identity.
  • Gender of PIs: 7/10 Female
    • CL is a place where women are well-represented among PIs
  • Project Implementation Setting:
    • Majority (6/10) of these projects were implemented in either an informal learning setting, or an informal and formal learning setting.
  • Special populations targeted:
    • 50% of projects specifically targeted a special population (i.e., Learners in special education or with a disability; Learners in low-performing districts or schools; ELLs, women/girls; Underrepresented minorities)
  • Explicit focus on cyberlearning in preparation for and within the context of the work setting: 5/10
    • 4/5 specifically related to supporting the current and future work of teachers in classrooms and other related settings;
    • 1/5: Design and develop future learning environments to educate/re-educate workers for new worker environments and experiences in collaboration with advanced technology.
  • Project included teacher/practitioner partnerships: 5/10
    • Only 50% of these projects included a practitioner partnership, which is a lower percentage than projects addressing other CL themes.
  • Project included 2 or more grad students on project staff: 9/10; CL projects focused on learning theories provide good opportunities engaging and training grad students, with several projects employing 5+ grad students.
  • PI proposals and awards
    • PI received new Cyberlearning award: 5
    • PI submitted proposal to Future of Work program: 2
    • PI received an NSF award for a program other than Cyberlearning: 6
    • About equal distribution of PIs receiving CL awards, and awards from other NSF programs, such as CS for All, AISL, STEM+C, and ITEST
  • Project Publications:
    • 5/10 projects indicated that they published project findings in scholarly journals, including: Journal of Computer-Supported Collaborative Learning; Cognition & Instruction; Journal of the Learning Sciences; Race, Ethnicity & Education; Anthropology & Education Quarterly