4-7pm Larsen G-08 | T509massive.org | bit.ly/t509canvas2014

Project Support Meetings 6:00-7:30 on 9/17, 9/24, 10/22, 10/29, 11/12


Week 1: What is Massive?

Week 2: The Long History of Distance and Online Education

Part I: Under the Hood

Week 3: Connectivism and Syndication

Week 4: The LMS and Algorithms

Week 5: Assessment and Credentials: Self, Peer, Expert, AI

Week 6: Blended Learning

Part II: Implications

Week 7: Production: How the MOOCs are Made

Week 8: Economics and Policy

Week 9: Research and the Science of Learning

Week 10: Worst Case Scenarios

Week 11: Equity and Openness


Week 12: Project Presentations and Closure

Course Overview

Video lectures, peer networks, and intelligent tutors now enable teachers to lecture to mass audiences, software platforms to train millions, and vast online communities to support one another’s growth. Optimists see new innovations as harbingers of transformation in educational systems, and critics see these cheap technologies as poor substitutes for human experts. This course will explore the opportunities, limits, and tradeoffs of new technologies that support teaching and learning at scale. Through examining MOOCs, intelligent tutors, blended learning environments, and interest based learning communities, students will examine the implications of these new modes of learning for classrooms, software, equity, opportunity, research, and policy. Through readings, discussions, encounters with experts in the field, and immersion in the technologies of large scale learning, students will work collectively to understand where technologies of large scale learning might enhance or transform learning and where they fall short or might even harm learners or systems. Ideally, the course community will include students with a deep understanding of education (but perhaps little background in technology) and students with extensive experience with computing technologies (but perhaps little background in education). Framing questions for the course include: Where can large-scale learning technologies most enhance student learning, and where do they offer no value? Who benefits and who is harmed from the increasing use of large scale learning environments? What pedagogical theories are implicitly or explicitly baked into the architecture of different massive learning platforms? How does the utility of large scale learning platforms vary across different domains of learning and sectors of education? What do computers do best? What do peer networks do best? What do expert teachers do best? What are the policy implications for new technology and new models of learning in K-12, higher education, and other sectors?

Welcome to T509-Massive: The Future of Learning at Scale

What will we study?

This course is a collaborative investigation of large-scale learning environments where there are many learners and few expert instructors, environments such as connectivist MOOCs, xMOOCs, intelligent tutors, blended learning environments, and interest-based learning communities. The goal of the course is to create a networked and residential learning community that supports one another in more deeply understanding the underlying features of these environments and their implications for educational systems.

Who should take this course?

Since large-scale learning environments are poised to reshape nearly every sector of education—from professional development for early childhood educators to ongoing training for lifelong learners—the course is designed to serve the widest possible community of learners. Students with deep backgrounds in technology or deep backgrounds in education, students with interests in early childhood, K-12, higher ed, and lifelong adult learning, students with great excitement for online learning and students with deep skepticism are all invited into the course.  Of course, such a diverse student community will have diverse needs and interests. The challenge will be to create a learning community where we support each other’s specific inquiry into a broad topic.

What is the model of learning in this course?

The central metaphor of T509-Massive is the potluck. As an instructional team, our job is to lay out a spread of opportunities, but students in the course will also need to bring dishes to the table. Each of us then as learners will need to create a plate for ourselves—a meal that meets our individual needs. There will be too much on the buffet line for anyone to eat everything, so part of the learning experience will involve figuring out how to select the most satisfying possible meal for ourselves and how to help our fellow learners do the same. The main prerequisite for the course, therefore, is a willingness to contribute to an emergent learning community and an understanding that a central part of the experience is navigating a variety of learning options rather that following a clearly demarked path.

When will we meet?

We will have two kinds of meeting times and spaces. HGSE calls these times “lecture” and “lab,” but they are probably better understood as “whole group” and “small group.”

Every week we will meet as a whole group from 4pm-6pm on Wednesdays, currently scheduled for Larsen G-08.

Some weeks, we will then continue to meet from 6-7pm. Other weeks, we will have “labs” or “sections,” where we can work on issues in smaller groups. These will be 90 minute sessions, with times and places to be scheduled.  So every week, we will get together for about 3-3.5 hours per week.

Having some extra time scheduled for class meetings will allow students to self-organize sessions—birds-of-a-feather meetings, project meetings, guest lecturers, etc.—and allow us to meet in a variety of configurations.

How will students be evaluated?

Students will receive self, peer, and instructor feedback on their activities throughout the course. Grades will be computed holistically, but roughly 40% of grades will be based on the course project, 40% on participation in the online network, and 20% on pre-class assignments such as peer evaluations.

Academic integrity is a cornerstone of the intellectual enterprise, and plagiarism is a serious violation of that integrity. Don’t. You might find two tutorials helpful in this regard: Principles of Paraphrasing (http://isites.harvard.edu/icb/icb.do?keyword=paraphrasing) and APA Exposed (http://isites.harvard.edu/icb/icb.do?keyword=apa_exposed). If you are struggling to complete an assignment, please reach out to the instructional team about an extension.

Who is teaching the course?

The lead learner for the course is Justin Reich, the Richard L. Menschel HarvardX Research fellow. Justin does research for HarvardX, is an affiliate of the Berkman Center for Internet and Society, teaches at HGSE and in the MIT Scheller Teacher Education program, founded a professional development consultancy called EdTechTeacher, serves on the Massachusetts Digital Learning Advisory Council, and writes the EdTech Researcher blog for Education Week. You can find out more about Justin from his about page, portfolio, Twitter feed, or blog.

More details about our teaching/learning fellows will follow.

What are the goals of this course?

Here is how the goals of this course were submitted to the Committee on Curriculum and Instruction

In the spirit of the original MOOCs, students will be presented with a selection of learning experiences and they will create many others for themselves. They will identify their own path through a variety of possible learning opportunities, set their own goals, and find a community willing to support them on their own explorations. I anticipate that many students would find some of the following learning goals resonant:

1.     Students will experience participation in a variety of forms of large-scale learning environments

2.     Students will be able to locate contemporary developments in large-scale learning within a long history of distance and computer-mediated learning

3.     Students will be able to participate in a networked learning environment constructed on the open web, with an emphasis on domains and accounts that they own and control

4.     Students will develop an interrogative stance towards technology-mediated learning platforms and a disposition to ask how platform features shape the experiences of teachers and learners

5.     Students will explore the implications of advances in large-scale learning as they will shape issues of equity and opportunity, the economics of higher education, education policy, classroom practice, and other dimensions of education.

6.     Students will pursue an extended study of a particular dimension of the field—through design, critique, policy analysis, or research


There are three types of assignments in this course: pre-class assignments, network participation, and course projects.

Pre-Class Assignments

For each week of the course, the instructional team has curated a series of readings, media, and activities. Some of these assignments are “Required,” and we ask that you complete them before class meeting so we have a series of shared texts. Some of these assignments encourage you to fall down the “Rabbit Hole,” additional opportunities for deep investigations of particular topics.

Several times throughout the semester, you will be asked to peer evaluate another student’s assignment submission.

Network Participation

As part of this class, you will be asked to contribute to an online learning network that exists on the open Web. Your task in participating in this network is threefold: 1) to enhance your own learning, 2) to enhance the learning experience of colleagues, and 3) to enhance the learning experiences of other communities that you care about.  Your participation in these networks will be in public online spaces, such as Twitter, Wordpress, and Flickr. We will aggregate and syndicate your activities at one of the course websites: t509massive.org.

You will determine how best to participate in this network, balancing your interests and needs and the needs of the community. If I define an overly specific and prescriptive list of ways to participate in the network, then you will all do the same thing, your efforts will be duplicative, and the results will both boring and not particularly suited to your needs. So, individually and as a community, we need to find meaningful ways to participate in the network. Some students might commit to curating and sharing additional readings. Some students might liveblog each session and post their notes. Some might group together and start a webinar series with guest experts. Some might write reflective posts about readings. Some might form study groups or birds-of-a-feather groups, and share their discussion or reading notes. Some folks might do nothing but comment on other peoples work, drawing links and connections. Some might host a regular twitter chat. Someone might do a weekly write-up of the top 5 community produced pieces of the week. Some might create summaries of weekly learning that are focused on serving communities outside our own, like a school or industry that you plan to return to after graduation.

To help guide your efforts, several weeks into the course you will devise a rubric for yourself that you will use to self-evaluate your participation in our network. You will revise this rubric a few weeks later after you have more experience participating. At the end of the semester, you will grade yourself on this rubric, and write a reflective essay (~1,000 words) synthesizing your contributions and reflecting on what you learned from participating.

Several sessions of class will be devoted to helping students develop the technological skills to participate effectively in an online network, so social media novices should find themselves very well supported.  Students will leave T509-Massive with the ability to participate in networked online communities and to effectively disseminate and share their ideas and questions.

Important: Public participation in this network is a required feature of the course. You may choose to participate pseudonymously, but it is impossible to have an immersive learning experience about networked online learning without public participation.  

Key Due Dates: September 17: Preliminary participation plan/rubric; October 8: Participation rubric revision; December 10: Final network participation reflective essay

Course Project

All students will complete a semester long course project, that should require about 3-4 hours of work per week during the semester. The project experience is designed to let students explore some facet of large-scale online learning in detail. Students will propose a rubric for their project evaluation at the end of September, will revise that project rubric and provide an update at the end of October, will have a project presentation at the end of November, and submit the final project and a reflective essay in December.

Projects will come in two flavors: partnerships and individual projects. Ideally, projects will be not only intellectually engaging, but will have the possibility to have a real impact somewhere in the world.

Partnerships and structured projects

The instructional team has developed relationships with partners at HarvardX, MIT, YouCubed, EdTechTeacher, and the Clayton Christensen Institute to provide some exciting learning experiences for students. Partners within these institutions have been asked to develop outlines for projects that are intellectually engaging and scoped appropriately for a semester’s worth of work. Because of the moment we find ourselves in and the shape of the edtech scene in Boston, these opportunities lean more towards MOOCs than other large-scale learning environments. (One of the goals of this course is to help students build connections with these institutions in Boston that might lead to winter/spring internships or future career opportunities).

Partner Project Opportunities can be found here.

Independent Projects

Students may also propose an independently designed course project.  These might be of the following kinds:

Course or Platform Critique: Students would select a small number of online courses (such as a trio of courses on poetry or computer science) or learning platforms (such as a trio of interest-based learning communities for artists) and then craft an essay or video essay offering a substantive comparison and critique of the platform and pedagogy, highlighting strengths and offering suggestions for improvement.

Course Design: Students design a module or short course, ideally for delivery in the near-term to a real group of learners. Students would provide an outline for an entire course and prototype 1-2 units.

Policy Brief: Students write a policy brief for a school community or state regulatory agency to respond to policy issues emerging with delivering and accrediting online learning experiences. Ideally, the brief would have implications for a real audience and context.

Other: Students may propose an alternative project; ideally in partnership with an organization or towards meeting a real need.

The Independent Project Proposal form can be found here.


Students may conduct group projects. They should develop a shared rubric, but individually assess the project on that rubric. The external evaluation component will be the same for all group members.

Final Deliverables

Deliverables will vary from project to project, but might include research briefs, design documents, prototypes, or wireframes.

All students should have some visual evidence of their project to share at the project presentations on November 19. Students will submit their final project documentation, along with a reflective essay (~1,000 words) on the process and learnings from their project on Dec. 3

Key Due Dates: September 12: Project Application/Initial Project Proposal; September 24: Project Proposal/Preliminary Rubric; October 1: Project Proposal Peer Review; Oct. 22: Project Update/Rubric; Oct. 29: Peer Review; Nov 19: Project Presentations; Dec. 3: Final project submissions and reflective essay.

T509 Course Sessions

Session 1 Date: 3 September

Session Topics: What is Massive?

Framing Questions: What is the object of study in this course? How will we study it? How do we form an online community to pursue our inquiry?





Latour, B. (1992) Where are the missing masses? The sociology of a few mundane artifacts. In Wiebe, E & Law, J. (eds) Shaping Technology.Building Society: Studies in Sociotechnical Change (Cambridge, MA: MIT Press), pp 225-258  Link 

Chen, M. (2011) How a new actor was temporarily enrolled into the network of game playing. Computer Supported Collaborative Learning 2011: Conference Proceedings Volume II. Link  pg 661- 665

Reich, J. (2012) Using data to kill demons: learning from World of Warcraft. EdTechResearcher. Link (note: if you access Education Week through Hollis, you have full free access).

This Syllabus

Cormier, D. What is a MOOC? Link 


Rabbit Hole

Session Meetings:  Whole: 4-7pm Class Video (Reg. Required) 

Shopping Slides | Week 1 Slides | Chen Slides || Twitter Slides 

Twitter Challenges | Twitter Resources

Tools from Latour | Norms for Class

Labs: Optional, 7:30-9pm

Session Activities:

First Block: (4:10-5:00/Lecture Hall): Collective Thinking: What counts as a Massive learning environment?

        How will we study: Syllabus Review and Mini-lecture on Latour and Chen; Q&A on syllabus review

Second Block: (5:00-5:50/Lecture Hall): Building Blocks: Networks and Projects

Exploration of syndication engines—

        Review expectations for network participation: rubric, activities, reflective essay (Socrative, surface ideas for network contributions)        

Third Block: (6-7pm/Lecture Hall) Building Online Networks with Twitter

Optional Lab: (7:00pm-8:30/Lecture Hall) Extra Social Networking Help

Session 2 Date: 10-September

Session Topics:  The Long History of Distance and Online Education

Framing Questions: How have humans over the centuries attempted to teach other humans at a distance?





 Mullaney, T. (2014) MOOCs in Historical Context.

Harvard Social Studies Thesis. pp 12-34 Link 

Hollands, F. (2014) MOOCs: Expectations and Reality. Link (Sections on origins of MOOCs, pp 31-41)

Noble. D. (1998) Digital diploma mills: The automation of higher education. First Monday. 3(1). Link 

Syndey Pressey Demonstrates the Teaching Machine (1964) Link

Begin co-constructing our online network

Bring your name card!

Due Friday: Submit Partner Project Application (opens 9/12 7pm) or Initial Project Proposal

Rabbit Hole

Watters, A. (2014) Personalization and teaching machines. Hack Education. Link 

Myth and Millennialism in disruptive innovation.


History of EdTech via Patents http://www.hackeducation.com/2014/06/22/ed-tech-patents/

The History of the Future of EdTech


Atkinson, R.C. &  Wilson H.A. (1968) Computer-assisted instruction. Science. Link  (See also more papers here: http://www.rca.ucsd.edu/selected-cai.asp )

Green, K. C. (1999). When Wishes Come True: Colleges and the Convergence of Access, Lifelong Learning, and Technology. Change, 31(2), 10–15. Link 

Ghesquire, J.R. (1975) Introduction to TUTOR. Link.

Search online for History of MOOCs. Read everything.

Khan, S. and Noer, M. (2012) The History of Education. Forbes Link 

Suggested writing prompts: write a statement describing your personal compass for this course. What are you trying to accomplish? How will you do it? How will you know that you have succeeded?

Session Meetings:  4-7pm lecture hall

Audrey’s Talk, Slides, and Storify | Class Video (Reg. Required)

Labs: Optional Blog/Social Media Jams: TBD

Session Activities:

First Block: (4:10-5:00/Lecture Hall): The history of online and distance education (Guest visit from Audrey Watters).

Second Block: (5:00-5:50/Lecture Hall): Project Possibilities and Expectations

Third Block: (6-7:00 pm/Lecture Hall): Building a Wordpress blog and connecting to the syndication engine.

Extra Help: (7:00-8:30pmTBD): Help with social media, blogging, and syndication.

Session 3 Date: 17 September

Session Topics: Connectivism and Syndication

Framing Questions: What is the epistemology of connectivism? How do we instantiate its learning theories in online courses?





 Illych, I. (1971) Deschooling society. (New York: Harper & Row). Chapter 6: Learning Webs. Link

Siemens, G. (2004) Connectivism: A learning theory for the digital age. elearnspace. Link 

Downes, S (2011) Connectivism and connective knowledge. Huffington Post.  Link 

Explore the ds106.us About page: http://ds106.us/about/ 

Complete the blog challenges, including submitting your URL for syndication.

Due Friday: Submit Preliminary Participation Plan/Rubric

Rabbit Hole

Ito, M. et. al. (2012). Connected Learning: An Agenda for Research and Design. Link. (K-12 or informal ed folks really ought to read this)

Downes, S (2014) Connectivism as a learning theory. Half an hour. Link 

RSS Explained: Link 

Do two Daily Creates from tdc.DS106.us. (Try tdc.ds106.us/random).

Explore other Connectivist MOOCs, like DS106, http://ds106.us ThoughtVectors, http://thoughtvectors.net/,  Making Learning Connected, http://clmooc.educatorinnovator.org/2014/ , and Connected Courses http://connectedcourses.net 

Suggested posts: Write about your reactions to connectivism

Session Meetings:  4-6pm lecture hall

Connectivist Exploration Document Slides | Video Link (reg. required)

Labs: 6-7:30 Support Labs

Session Activities:

First Block: (4:10-5:00/Lecture Hall) Navigating Constructivist Inspired Learning Spaces

Second Block: (5:00-5:50/Lecture Hall): Under the Hood of Syndication: RSS and API

Understanding Connectivism and Connectivist Learning Environments.

Third Block: (6-7:30 pm/TBD): Support Labs: Design Thinking for consultants, introduction to online course design, introduction to qualitative research, social media extra help

Session 4 Date: 24 September

Session Topics: The LMS and Algorithms

Framing Questions: How do enclosed online spaces shape student learning experiences? What are the benefits and costs of standardization through Learning Management Systems? How do algorithms make it possible create adaptive learning environments?





 Hollands, F. (2014) MOOCs: Expectations and Reality. http://cbcse.org/wordpress/wp-content/uploads/2014/05/MOOCs_Expectations_and_Reality.pdf Goals 1&2, pp53-74; Goals4&5, pp 90-112

Groom, J. & Lamb, B. (2014) Reclaiming innovation. Educause Review Online. Link 

John Hansen Video Sequence on Item-Response Theory and applications to Computer-Assisted Instruction  bit.ly/t509canvas2014

Livingstone, S. (2013) Danielson Lecture: Digital connections and disconnections. http://vimeo.com/80082000. (Start at 14:30, end at 27:00, but the whole is great.)

Spend at least 20 minutes OVER TWO DAYS doing “All of Math” on Khan Academy (also sometimes called The World of Math).

Due Friday: Project Proposal / Preliminary Rubric  Due in Canvas

Rabbit Hole

Knewton Blog. (2012) The mismeasure of students: Using IRT instead of traditional grading to assess student proficiency


Straumshein, C. (2014) Where does the LMS go from here? Inside Higher Ed.  Link

Groom, J. A Domain of One’s Own. Plenary Address, 2014 Digital Media and Learning Conference. http://youtu.be/6m90BzVVPG4?t=34m37s (Start at 34:37, though the other two talks are great, too).

Klopfer, E. Next Generation MOOCs: Perspectives from the Learning Sciences. Link 

Reich, J. Personalized Learning, Backpacks Full of Cash, Rockstar Teachers, and MOOC Madness. Link 

Session Meetings:  4-6pm

Questions for Class 4 Slides | Video Link (Reg. Required)

Labs:  Support Labs, 6-7:30

Session Activities:

First Block: (4:10-5:00/Lecture Hall): In-class problem solving-IRT problems and computer assisted adaptive testing and learning; mini-lecture: The advantages of familiarity

Second Block: (5:00-5:50/Lecture Hall): The Learning Management System as the building block for MOOCs, intelligent tutors and blended learning

Third Block: (6-7:30 pm/TBD):Support Labs: (TBD /Breakout) Project support labs

Session 5 Date: 1 October: Session Topics: Assessment: Expert, AI, Peer, and Self, and Credentials

Framing Questions: How do we assess student competence with limited expert labor?





Reich, J. (2012) Grading automated essay scoring programs.  Education Week: EdTech Researcher. Link (optional are parts 2 and 3)

Shermis, M. & Hammer, B. (2012) Contrasting state-of-the-art automated scoring of essays: Analysis. Link 

Rees, J. (2013). Peer grading can’t work. Inside Higher Ed. Link 

Morrison, D. (2013). Why and when peer grading is effective for learning. Online Learning Insights. Link 

Wiggins, B. (2014) Can peer grading actually work? More or Less Bunk. Link 

Explore at least one xMOOC on Coursera, edX, or Udacity

Peer Review of Project Proposals Due Wednesday Oct. 1

Rabbit Hole

Piech, C., Huang, J., Chen, Z., Do, C., Ng, A., & Koller, D. (2013). Tuned models of peer assessment in MOOCs. arXiv preprint arXiv:1307.2579.

Suen, H. (2014) Peer assessment for massive open online courses. International Review of Research in Open and Distance Learning 15(3) Link

Linn, M.C., Gerard, L., Ryoo, K., McElhaney, K., Liu, O.L., Rafferty, A. (2014) Computer-guided inquiry to improve science learning. Science. (344:6180) Link

Session Meetings:  4-7pm Lecture Hall

Lecture Video (reg required) Studio Challenges Slides

Optional Labs: Hands-on with Studio

Session Activities:

First Block: (4:10-5:00/Lecture Hall): Self-Assessment, Peer-Assessment, and Machine Learning

Second Block: (5:00-5:50/Lecture Hall): More on designing and learning with xMOOCs

Optional Lab: (6:00-7:00 /Lecture Hall): Hands on with Studio

Session 6 Date: 8 October

Session Topics: Blended Learning

Framing Questions: How do we integrate just-in-time content delivery, intelligent tutors, and human teachers?





 Christensen, C., Horn, M.B., Staker, H. (2013) Is K-12 blended learning disruptive? Clayton Christensen Institute Link 

Giffiths, R., Chingos, M., Mulhern, C., Spies, R.  (2014) Interactive online learning on campus. Ithaka S+R. Link  (Appendices are optional)

Read some posts from our guest, Julia Freeland Link

Greenberg, B. and Horn, M.B. Blended learning. Khan Academy. Link (You are required to watch at least 40 minutes of video. You can choose which ones.)

Participation Rubric Revision Due Wed October 8

Rabbit Hole

John Pane et al. (2014) Does An Algebra Course with Tutoring Software Improve Student Learning. Rand Research Brief. Link. 

Dan Meyer (2014) Don’t Personalize Learning. Link

Justin Reich (2013) Blended Learning vs. Connected Learning; New Terms Old Debate Link.

The Headlines vs. the Study in Blended Algebra Program Link

Justin Reich (2014) The Role of Humans in Blended Learning Link.

Blended Learning But the Data Are Useless. Link

Nudging Priming and Motivation in Blended Learning. Link. .

Results from the 2017 Khan Academy Study. Link.


Session Meetings:  Julia’s Slides  #t509whys Theory-to-Practice AdultLearners DevelopingWorld


Session Activities:

First Block: (4:10-5:00/Lecture Hall) Guest Presentation: Julia Freeland from CCIDI

Second Block: (5:00-5:50/Lecture Hall) More Blending

Third Block: (6-7:00 pm/Lecture Hall): EdCafe- Student Lead Discussions on Topics to wrap up “Under the Hood”

Optional Lab: () - None

Session 7 Date: 15 October

Session Topics: Production: How MOOCs and LMS are Made

Framing Questions: What are the priorities, talents, experiences, and processes of the people who make MOOCs? How do those conditions shape student learning experiences?





 Kolowich, S. (2013) The professors who make the MOOCs. Chronicle of Higher Education. Link 

Bombardieri, M. (2014) Harvard goes all in for online courses. Boston Globe. Link 

Hollands, F. (2014) MOOCs: Expectations and Reality. Link Sections on Resource Requirements: 134-148 and Appendix IV

Post an informal progress update on your project

Complete the mid-course survey

Rabbit Hole

Making MOOCs. Cornell University. Link (Panel Discussion with 6 MOOC faculty)

Session Meetings:  4-7pm- Some time for HarvardX tour and Hauser studio

Labs: none

Session Activities: Possible rotations so that we can do tours?

First Block: (4:10-5:00/Lecture Hall): HarvardX Panel: (Annie Valva, Associate Director for Instructional Development; Jeff Emmanuel, Senior Project Lead; Meghan Morrissey MEd’13, Project Lead)—how are MOOCs made?

Second Block: (5:00-5:50/Lecture Hall): edX Panel: (Miki Goyal, Director of Engineering; Victor Schnader, Product Owner)—How is an LMS made?

Third Block: (6-7:00 pm/Lecture Hall): HarvardX/Houser Studio Tour (TBD)

Optional Lab: () - None

Session 8 Date: 22 October

Session Topics: Economics and Policy

Framing Questions:





Institute –wide Task Force on the Future of MIT Education: Final Report Link  (pp. 1-30)

Hill, P. School finance in the digital-learning era. In eds, Finn, C. & Fairchild, D. Education Reform for the Digital Era. Fordham Institute. Link 

Hoxby, C.(2014) The Economics of Online Postsecondary Education: MOOCs, Nonselective Education, and Highly Selective Education. National Bureau of Economic Research. Link 

Shirky, C. Napster, Udacity, and the Academy. Link 

Ussem, J. (2014) Business School, Disrupted. New York Times. Link 

Anant Agarwal, Why Massive Open Online Courses Still Matter. http://www.ted.com/talks/anant_agarwal_why_massively_open_online_courses_still_matter?language=en 

Project Update/Expectation Rubric Submitted

Rabbit Hole

Reich, J. The yoking of virtual schools and market-based reforms. Education Week: EdTech Researcher Link 

Christensen, C. & Weiss, M. MOOCs disruption is only the beginning. Boston Globe. Link 

Session Meetings:  4-6pm Video Recording (Reg Required)

Labs:  6-7:30 Project Updates with Teaching Fellows Part II

Session Activities:

First Block: (4:15-5:00/Lecture Hall): Invited guests on Future of Higher Education,, Peter Bol, Vice Provost for Advances in Learning, Harvard University Sanjay Sarma, MIT ODL

Second Block: (5:30-5:50/Lecture Hall): The economics of individualism…

Third Block: (6-7:30 pm/Lecture Hall): Project Updates with Teaching Fellows, Part I

Session 9 Date: 29 October

Session Topics: MOOCs, Research, and the Science of Learning

Framing Questions: What can we learn from MOOCs about engagement? What can we learn from MOOCs about learning?





Baker, R.S.J.d & Siemens, G. (2014) Educational data mining and learning analytics. Cambridge Handbook of the Learning Sciences. Link 

Reich, J. (2014) Big data MOOC research breakthrough: Learning activities lead to achievement. Education Week: EdTech Researcher. Link (Non Reg-Wall Link)

Ho, Andrew, Reich, Justin, et al. (2014) HarvardX and MITX: The First Year of Open Online Courses. Link

Reich, J. (2014) MOOCs and the science of learning. Berkman Center Luncheon Series. http://www.youtube.com/watch?v=cXrrysTwvMA  (At least watch the talk, you don’t have to watch Q&A, but it’s pretty good, especially Charlie Nesson at the end)

Rabbit Hole

Findings from Gates MOOC Research Initiative: http://www.moocresearch.com/reports

Papers from the 2014 Learning@Scale conference:

http://learningatscale.acm.org/las2014/papers.html (for Harvard Access, search for ACM Digital Library in Hollis, then search for Learning@Scale)

Yousef, A., et al. (2014) MOOCs: A Review of the State of the Art Link

Reich, J.(2014) The first year of HarvardX.  http://www.youtube.com/watch?v=Y8Bic69fS_Q 

Session Meetings:  4-6pm Andrew’s Slides

Labs: 6-7:30 Project Updates with Teaching Fellows, Part I

Session Activities:

First Block: (4:10-5:00/Lecture Hall): MOOCs and the Science of Learning: Andrew Ho, TBD

Second Block: (5:00-5:50/Lecture Hall): MOOCs and Assessment Design

Third Block: (6-7:30 pm/TBD):  Project Updates with Teaching Fellows, Part II

Session 10 Date: 5 November

Session Topics: Worst Case Scenarios

Framing Questions: What are the risks of an increasing reliance on large scale learning environments in our educational systems?





 Rees, J. (2013) The MOOC racket. Slate: Future Tense. Link 

McNeill, J. (2013) MOOCs and Historical Research Perspectives on History. Link 

Warner, J. (2014) The Costs of Big Data. Inside Higher Ed. Link 

Cottom, Tressie McMillan (2014) Democratizing Ideologies and Inequality Regimes. Berkman Talk. Link (Q&A is optional; If you skim, you can’t skip the work about the Roaming Autodidact around 22:30)

DUE Tuesday at Midnight

Post a dramatic rendering of a dystopian vision for the future of education. It can be a story, video, meme, image, painting, poem, etc. You can submit via: via your blog, Twitter, or YouTube (or just email me).

The best of these will kick off our unhangout on Wednesday.

Rabbit Hole

Session Meetings:  4-7pm Storify Slides Video




First Block: (4:10-7:00/UNHANGOUT): Dramatic Renderings of Worst Case Scenarios and discussion

Special Guest Pessimist: Tressie Cottom

Optional Lab: () - None

Session 11 Date: 12 November

Session Topics: Equity and Openness

Framing Questions: Will large-scale learning environments make education more equitable? What role can openness play in promoting or confounding educational equity?





Attewell, P. (2001) Comment: The first and second digital divides. Sociology of Education, 74(July), 252:259. Link (Access through Hollis)

Jaggers, S.S. (2014) Democratization of Education For Whom? Online Learning and Educational Equity. Diversity and Democracy, 17(1). Link 

 Xu, D. & Jaggers, S.S. (2013) Adaptability to online learning. Community College Research Center Working Paper No. 54. Link 

Christensen, G. et al (2013) The MOOC Phenomenon: Who Takes Massively Open Online Courses and Why? Link 

Reich, J. (2012) When open encounters different classrooms. Hewlett Open Education Resources Grantees Meeting. http://www.youtube.com/watch?v=wNSDk8X-oBQ 

Review prompts for

Project Reflection


Portfolio Reflection

Rabbit Hole

Paul, A.M. (2014) Educational technology isn’t leveling the playing field. Hechinger Report. Link

Pappano, L. (2013, September 15). The boy genius of Ulan Bator. The New York Times  Link 

Session Meetings:  4-6pm

Labs: 6-7:30 TBD

Session Activities:

First Block: (4:10-5:00/Lecture Hall): What is Open?

(Dimensions of openness in MOOCs)

Second Block: (5:00-5:50/Lecture Hall): MOOCs and the claims of democratizing education.

Third Block: (6-7:30 pm/ TBD): Optional Sessions: Doug P on Turning a Blog into a Portfolio Site; TF Project Check-Ins

Session 12 Date: 19 November

Session Topics: Project Presentations

Framing Questions: What have we learned together? What can we do to continue our learning?







Final Project Presentations

Rabbit Hole

Session Meetings:  


Session Activities:

First Block: (4:10-5:00/GCC )- Project Presentations

Second Block: (5:00-5:50/GCC )- Project Presentations

Third Block: (6-7:00 pm/GCC): Final Course Wrap Up and Celebration

Optional Lab: () - None

Final Project and Project Reflection Submission Due 12/3

Final Network Participation Reflection Due 12/10