Technology in Higher Ed: We Ain’t Seen Nothin’ Yet

Jim ShimabukuroBy Jim Shimabukuro

Technology is increasingly dividing the academy, but this is a natural pattern in change. Most HE institutions fail to grasp that disruption is an outside force that creates a whole new population of students. This oversight or denial leaves colleges and universities fighting to defend its traditional practices — but they’re battling a strawman.

The real “enemy,” if you will, is a whole new way (MOOCs) to reach the world’s nontraditional student population. MOOCs aren’t aimed at traditional college students, but many traditional students are exploring the benefits of MOOCs and some institutions are exploring MOOC-like courses for their students.

The leadership in MOOC development and deployment is increasingly shifting to other parts of the world where HE has been a pipe dream for the masses. In the US, it is also shifting, on little cat feet, to small groups or departments in lesser-known colleges and universities with staff who understand and are exploring the potential of MOOCs. These garage and bootstrap operations are where change is being forged, and it will be interesting to see, in the coming months (not years), where this will take us.

We’re only seeing the tip of the iceberg in terms of technology-driven changes to come in HE. On our campuses, we need to take our eyes off the little islands that we call home and look beyond our shores to the vast ocean of possibilities. If we think we’ve witnessed change, we have another think coming. We ain’t seen nothin’ yet!

MOOCs Outside of Mainstream U.S. Higher Ed (updated 10/20/13):

China MOOC: xuetangX, accessed 10/20/13.

Tim Johnson, “Online education inspires eager students in Latin America,” CSM, 10/4/13.

MOOCs take off in Rwanda: Accreditation, sustainability and quality issues,” Institute of Learning Innovation, 10/1/13.

Carolyn Fox, “Higher, open education for India,” Open Source, 8/29/13. \

Hiep Pham, “Research chemist launches Vietnam’s first MOOCs site,” University World News, 9/21/13., 2013: “Higher Education MOOCs“; “K – 12 MOOCs“; “MOOCsNews© on Credits, Certificates, Degrees, Career Services, Job Placement and other related subjects.”

8 Responses

  1. Future MOOCs may or may not be termed MOOCs. Things are reaching the point where small operations may change the world. Just look at the impact that Salman Khan had on education.

    The Kepler project in Rwanda is an example of being a bit more creative by taking MOOCs and combining them with in-person teachers to deliver high-quality education. After all, they’re free!

    How this resource comes to be used will effect how it evolves.

    Another factor will be adaptive learning options and more interactivity.

    I’m currently taking my first MOOC, given by my alma mater, just to learn something new (machine learning — haha) and learn about MOOCs first-hand. So far, it’s nothing very exciting, but I haven’t bothered with any of the discussion group stuff because I just don’t have time for it. I may not have time to complete the course, but at least I’ll have learned SOMETHING and experienced it.

  2. Agreed. This is basically my assessment as well.

  3. […] Technology is increasingly dividing the academy, but this is a natural pattern in change. Most HE institutions fail to grasp that disruption is an outside force that creates a whole new population of students. This oversight or denial leaves colleges and universities fighting to defend its traditional practices — but they’re battling a strawman.  […]

  4. Follow up on my MOOC — I handed in first homework assignment. I tried to do the last problem (requiring writing software) the hard way (by quantitative analysis) and decided that it would just take too long and settled for alternative approach (Monte Carlo method), which only took a few minutes to program and run.

    My first homework grade = 10/10. I took a look at the discussion group after I finished by homework to see what sort of questions and answers were being posted. I guess I’m rather biased from having been a Caltech student and having done essentially all homework solo. I think figuring out how to do it is as important (maybe more so) that doing it.

    In any event, I was disappointed by the questions because the people asking them clearly hadn’t spent much time or mental effort (or both) on the problem before running for help.

    Nevertheless, I am not being judgmental here, but noting a fact. Many people come to MOOCs for many reasons. Some of those reasons may well lead to such questions.

    The professor is also monitoring the discussions (maybe by proxy — don’t know) and will help out if need be. Still, a question came up in my mind in one of the two lectures so far that I would have liked to have asked of the professor. So, I’m left with an unanswered question. That’s not very satisfactory to me but hardly a course killer.

    My purpose here is to understand machine learning well enough to decide if it can play a role in my company’s work (don’t know yet) and, if so, exactly how to apply it.

    I also like the relaxation that comes from doing something engaging and completely different for a change.

    • Harry, it’s great that you’re actively engaged in a MOOC as a student. I’m not sure how the course is orgnzed in terms of student roles, but you might want to take on an active role in discussions to experiment with the community or peer facilitation aspect of MOOCs, which some theorists believe is the true strength of huge open courses. Please continue to keep us posted on your experiences.

      I’m on my second MOOC, being run by the University of Hawaii’s Leeward Community College, and like you I’m enjoying the role of student. The title of the course is How to Teach Online, and we’re nearly done, with one week to go. I like the way Greg Walker and his staff are placing the participants right in the mix where theory and practice are still being hammered out.

      Perhaps the most critical lesson is that the role of learner changes and simply showing up and compketing the required work is not an option. To learn, one has to become actively involved in the dialogue among participants. -JimS

  5. MOOCs are great in that cheaply make knowledge widely available to those who may not have the inclination or desire to study otherwise. Discussion groups attempt to fill the gap for personalized learning, in a very inefficient way. In my opinion, they are useful if accompanied by localized or small group recitations, but the knowing what the students are learning is difficult.

    What is a better, but far more expensive to develop at this time is personalized learning such as those developed by the Open Learning Initiative at Carnegie Mellon University. Studies show the incredible efficiency gains in learning and retention using courses such as the statistics course developed and taught by Oded Meyer. By reviewing student logs, teachers are able to understand and focus on what the student(s) do not comprehend.

    **Plug** We have developed one-year interdisciplinary masters, jointly taught by the Human Computer Interaction Institute and the Psychology Department. This program trains students to design, develop and evaluate evidenced-based programs for learning. We teach students to used evidence-based research to challenge the future of learning by re-examining the goals of education and assessment. See

    • I’ll primarily comment on the first, non-plug paragraph.

      Those without the “inclination or desire to study” will be the worst MOOC students. Taking a MOOC requires some real self-discipline.

      Discussion groups succeed or fail in this venue based on many factors, including instructor participation and quality of students.

      Small groups led by an expert, whether F2F or remote synchronous, can raise a MOOC to the standard of a “real” course.

      As a general rule, improving the personalization of a course can lead to greater learning gains. We don’t require studies to prove that.

      Whether it’s expert-led small groups or review of student work to tailor material to the student, a truly good learning experience costs more than just a server and bandwidth.

      The MOOC I’m taking now may be “Introduction to,” but it’s not an entry-level course. You have to be ready to learn, both in attitude and in prior knowledge. The discussion group material shows that some are not. They’re having difficulty with concepts that are prerequisites for this course.

      I’ve been through four lectures and two homework assignments so far (out of twenty total lectures). I’m learning a great deal. The lectures are paced so that I can think that I understand everything. Then, I go to the homework and find out that my understanding is shallow. This course moves along at a rapid but not supersonic speed, but if you miss one week, you’ll have trouble making it up. Right now, my goal is making it to the mid-term — through week 5 and lecture 10. Then, I’ll decide whether to complete the course, which I am only auditing.

      I already have enough degrees and have taken enough courses for credit for any single person. I’m interested in having a real working knowledge of machine learning. The next two weeks are theory. Hope I survive them.

  6. The discussion group is becoming more interesting. I’m guessing that some students are dropping out and leaving behind the ones who “get” it better. Questions have ranged from clueless to banal to intelligent. The second week had fewer of the clueless questions.

    This MOOC is very technical; machine learning. It may sound prosaic, but it requires knowledge of matrix algebra and calculus for the theory and computer programming skills for the homework.

    The homework questions are quite penetrating. They have been cleverly constructed to require understanding of the material rather than just parroting back the lectures and notes. I was used to this sort of thing as an undergraduate but haven’t seen it for many decades. Well, it’s a Caltech course. What else should you expect?

    I’ve been scanning the discussions but not yet participating. The questions in the homework are generally terse and assume quite a bit of knowledge as well as paying attention to the lectures. There is no textbook. It’s not really surprising that quite a bit of discussion is generated.

    This is a ten-week course and is moving along rather rapidly. Given the pace, I am confident that those who complete it will have a good grounding in the principles and application of machine learning. The professor knows how to pace his lectures and explain more difficult concepts thoroughly. The Q&A after each lecture shows that he knows this subject very deeply.

    Given my reasons for taking this course and the nature of the material, this format works for me — so far. It mirrors my undergraduate experience.

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