MAS S70

Design for Learning in the Flow of Everyday Life:  Children, Families, Communities, and Beyond

Grading: Pass/Fail

Credit Hours: 6 or 12 (readings and lecture participation = 6; also complete project or paper = 12)

Meetings

Wednesdays, 11:00 AM - 1:00 PM  

  • Feb: 7, 14, 21, 28

  • March: 7, 14, 21 (no class on March 28, Spring Break)

  • April: 4, 11, 18, 25

  • May: 2, 16  (no class on May 9, Media Lab Members week)

MIT Media Lab (75 Amherst Street, Cambridge, MA)

Room: E15-466

 

Overview

In this seminar, we will explore various approaches to learning as playful, social processes in community/cultural settings -- primarily outside of school -- based on guest speakers’ readings, presentations, and discussions. We will consider how these natural processes of learning may be enhanced by AI, machine learning, and other advanced digital technologies. For example, Playful Words is an LSM literacy learning project that uses various digital Power Tools to support children as creative authors in community learning networks of families, coaches, and peers. Students will have the option of applying weekly topics to a learning exemplar or project of their own.  

 

Description

We live in a time of “re-imagining education”, systemic “school reform” and the advent of “learning science” as societies around the world transition away from industrial models of learning. Technology is often cited as a solution, yet the reality of educational technology’s impact typically falls short. Too often, the fundamentally human basis of education is pushed aside. Needed are innovative new ways to cultivate children’s learning as it naturally occurs during play, within nurturing relationships, in a supportive community. Many approaches to learning technology design attempt to replace human teachers or create stand-alone educational apps. By contrast, we will focus on a human-centered perspective on learning and intelligence, and explore the design of smart tools to extend them as they occur in real life communities and social networks.

 

Schedule & Format

The seminar will meet weekly for 2 hours. Each meeting will begin with prepared remarks by a guest speaker followed by moderated discussion with the class. Readings will be assigned for each meeting, and students will be required to submit questions based on the readings in advance of each class. These questions will form the basis for discussions. All remarks by guest speakers and ensuing discussions will be audio and video recorded. Designated note-takers will seek to capture the highlights of each speaker's’ remarks and follow-on discussion each week. The resulting recordings and notes will be combined to create a publicly accessible web archive of the seminar.

 

In addition to guest speakers, there will also be two optional lab sessions for students who plan to complete the final project. The first will be a project critique session where students and their teammates can pitch their ideas and receive feedback from others in the class. The second will provide an opportunity for students to demo all or parts of their final projects for feedback and refinement prior to their final presentations and submission. Depending on speakers’ availability and interest, we may offer additional lab sessions that serve as a practicum for developing and exercising techniques described during class (e.g., supporting early literacy development, self-directed learning, working in other cultural/racial communities to support learning).

 

Topics

  • Constructionist learning through passion, play, peers, and projects

  • Parasocial interactions for learning: from Video to Personal Robotics

  • Social Machines: Playful Words and other socio-technical systems for learning

  • Cultural processes of learning

  • Family and Community in Learning

  • Equity in Educational Opportunity

  • Socio-historical perspectives: Vygotsky’s Tools of the Mind

  • Language and Literacy development in children

  • Playful Learning

  • Science of learning: Five pillars for design

  • Self-directed learning

  • Neuroscience of Learning