New Ithaka report: Barriers to the adoption of online learning

Just today,  Ithaka released a new report under the title “Barriers to the adoption of online learning in U.S. higher education".

From the blurb on the Ithaka site:

“This Ithaka S+R report is a landscape review of important developments in online learning today.  It is the first in a series that will provide leaders in higher education with lessons learned from existing online learning efforts to help accelerate productive use of these systems in the future.  The goal of this research was to understand what benefits colleges and universities expect from online learning technologies, what barriers they face in implementing them, and how these technologies might be best shaped to serve different types of institutions.”

I just finished reading the report and must say that I am totally unimpressed. And surprised, the quality of Ithaka reports is usually quite high.

There are three main issues I have with the report.

There is nothing much new to be learned from their analysis of the current state of e-learning in higher education. The obstacles to the implementation of online learning that are discussed in the report have been known for a long time now, and, by consequence, the strategies mentioned for overcoming these barriers should be well known by HE administrators.

Part of the problem stems from the fact that the report is about e-learning systems that are not yet here. The authors coin the phrase Interactive Learning Online (ILO) to differentiate such a system from our current, poorly used and poorly performing, learning management systems. An ILO system, or platform, is different in that it would use largely machine-guided learning, data-driven, adaptive and customized to individual students, that would also assist instructors in delivering targeted guidance. One of the report’s recommendations is for a national, system-wide initiative to develop such a platform. Instead of a new initiative, I think it would be much wiser to support the open source communities around Moodle and Sakai in order to capitalize on their vast experience with systems that have been actually deployed for some time now.

Also, the authors call for educational content that can easily be customized and adapted by faculty. We used to call that the not-invented-here syndrome, ten years ago, and of course the argument is still valid and the obstacle is a very real one. As with the software development issue, I would at least have expected the authors to mention Open Educational Resources as a possible solution to this problem.

Big data in education

The US Department of Education just released a draft version of a brief titled Enhancing Teaching and Learning through Educational Data Mining and Learning Analytics.

One of the old promises of e-learning has been to use data generated in online learning systems to guide student learning, as well as to help instructors and designers, and managers to continually improve the online learning system. In practice most institutions do very little with the data they have, simply because they lack the skills to handle the data, or just don't know what to do with the data. After all, you can only make data work for you when you know which questions you'd like to see answered.

Technology to deal with big data has been developing rapidly lately, and the DoE thinks we might be at a tipping point, so it released this timely brief.

The report starts off with some familiar scenarios, think Netflix applied to education, before making an interesting, and useful distinction between educational data mining and learning analytics:

Educational data mining (EDM) develops methods and applies techniques from statistics, machine learning, and data mining to analyze data collected during teaching and learning. EDM tests learning theories and informs educational practice.

Learning analytics applies techniques from information science, sociology, psychology, statistics, machine learning, and data mining to analyze data collected during education administration and services, teaching and learning. Learning analytics creates applications that directly influence educational practice.

The Journal of Educational Data Mining started in 2009. In 2011 both the International Educational Data Mining Society and the Society for Learning Analytics Research were founded. New societies and journals usually mark the birth of new academic fields.

There is much more good information in the 57 pages report and it will be interesting to see how the response to the brief develops.

E-learning, who’s in control?

Interesting story in yesterday’s New York Times about teachers (and also parents and students) in Idaho resisting the introduction of computers and online courses in high schools. In a sense it rehashes the ongoing debate (since the end of the 1990s) about e-learning.

One quote stands out for me: “Teachers are resisting, saying that they prefer to employ technology as it suits their own teaching methods and styles”. This perfectly illustrates Larry Cuban’s famous observation "When teachers adopt technological innovations, these changes typically maintain rather than alter existing class room practices." (Cuban 2001, p. 71).  Time and again we see that without redesigning courses the introduction of e-learning does not make much sense, but just adds costs, in terms of hardware and software licenses and teacher time, without producing better results. Why is it so hard for teachers to change their dominant practice of lecturing?

Also yesterday I came across this story about physics teachers that gave up on traditional lecturing because they found that students were not grasping fundamental concepts. Instead, they ask students to go over the material before meeting in class and posting questions in a learning management system that the teacher uses to prepare for class. In the classroom clickers are used to probe students understanding, as well as students discussing with each other, and, more importantly, learning from each other. The simple observation, in a related article is that a student who has just learned something might be better than an expert into explaining a new concept to a fellow student. As one of the physics teachers observes: “That''s the irony of becoming an expert in your field, Mazur says. "It becomes not easier to teach, it becomes harder to teach because you''re unaware of the conceptual difficulties of a beginning learner."

It’s not only important for teachers to understand their own limitations as experts, the hard part,I think, is also giving up control. I had an interesting experience in my own teaching career in the 1980s. One day I came to class unprepared and felt both bad and nervous about it. So I started asking students questions and letting them discuss among themselves solutions to those questions. It went wonderful, for the first time I had the feeling that students were really engaged and actively learning. Giving up control turned out to be fun as well.

Larry Cuban (2001), Oversold and Underused, Computers in the Classroom, Harvard University Press