I agree with most of his points (powerpoint lectures stink, presentation/podcastast/videos should be made available for students out-of-class, there is a lot of bad teaching, etc.), but have not experienced the same resistance by students to leave behind the “broadcast” model of lecturing. My impression is that the cause for student resistance is unrelated to technology or teaching styles. Too often, students don’t know why they are studying a particular topic, and how it relates to their degree and their lifes. In such a situation, where students don’t see the relevance and meaning of what they are supposed to learn, they rely on lecturers to break down the content in a way that — at least — let’s them succeed on the test. However, once the purpose is clear, students readily embrace opportunities to engage more actively. The resistance I have experienced comes mainly from lecturers, who are comfortable with a teaching style that is designed not to challenge their “expert” positions vis-a-vis the students. Admitting that there is something they don’t know is scary for many lecturers, but it’s the norm online – where every google search and visit to wikipedia is an acknowledgment that there is something we don’t know.

An important point that Jeff makes about half-way down the article (a little too late in my opinion) deals with Jose Bowen’s fundamental support for technology:

Mr. Bowen is part of a group of college leaders who haven’t given up on that dream of shaking up college instruction. Even though he is taking computers out of classrooms, he’s not anti-technology. He just thinks they should be used differently—upending the traditional lecture model in the process.

We know that when technology is used to alleviate bad teaching practices, it will often just compound the problems. The easy, and wrong, response is to blame the technology. Rather than point out examples where bad teaching was made worse, we should look at how the best use of technology is innovating learning. The problem is that these examples might be easy to overlook, because they take place outside of institutions, or because learning becomes a part of solving a problem or taking action, rather than exist as an activity per se. A friend recently pointed out the practices of knowledge sharing in the online poker communities, which seem perfectly in line with the ideals of academia. And it comes as no surprise that many smaller institutions, often colleges and technical universities or Art schools in the case of Professor Bowen, are able to move faster and innovate more rapidly than their larger more traditional (and sometimes more reputable) counterparts. Yet, unless we start looking at what’s happening outside of education institutions, we might miss a technology-enabled revolution in learning that takes place right in front of our eyes.

Apparently something similar is happening in cycling:

Licensed under a CC-BY 2.0 licensed by revolution_cycle

For some of these speed freaks, the videos are clearly repetition of materials that they have already learned, and they are just skimming through them in preparation for an exam. But many of the users in Taiwan did not even show up for the exam (the courses were not mandatory). Also, in Taiwan it turned out that all of the users who liked to go faster, lived in the same dorm – nobody who lived outside of the dorm had come up with the idea.

I would be interested to find out how self-learners that have no interest in assessment work with these videos – do they also find them too slow? And how do students feel about their professors (too slow)? Thanks to Telkom‘s bandwidth policies, I rarely download lecture videos, but I do listen to quite a lot of podcasts. And different from these OCW users, I usually find myself pausing and skipping back to listen to certain passages a second time, rather than wanting to go faster.

On the upside, this could also mean that using tools which develop collaborative practices and encourage the open sharing of ideas (such as wikis) will remap our brains in ways that will lead to more socially beneficial behaviour. So that the experience of sharing ideas might allow us to get better at sharing land, water, and oil? Let’s face it, those are important skills to learn!

Following is the complete letter to The Atlantic, that was sent in response to this article “Is Google making us stupid?” by Nicholas Carr (I underlined parts of it).

Nicholas Carr correctly notes that technology is changing our lives and our brains. The average young person spends more than eight hours each day using technology (computers, PDAs, TV, videos), and much less time engaging in direct social contact. Our UCLA brain-scanning studies are showing that such repeated exposure to technology alters brain circuitry, and young developing brains (which usually have the greatest exposure) are the most vulnerable. Instead of the traditional generation gap, we are witnessing the beginning of a brain gap that separates digital natives, born into 24/7 technology, and digital immigrants, who came to computers and other digital technology as adults.

This perpetual exposure to technology is leading to the next major milestone in brain evolution. More than 300,000 years ago, our Neanderthal ancestors discovered handheld tools, which led to the co-evolution of language, goal-directed behavior, social networking, and accelerated development of the frontal lobe, which controls these functions. Today, video-game brain, Internet addiction, and other technology side effects appear to be suppressing frontal-lobe executive skills and our ability to communicate face-to-face. Instead, our brains are developing circuitry for online social networking and are adapting to a new multitasking technology culture.

Gary Small, M.D.
Director, UCLA Memory & Aging Research Center
Los Angeles, California

She argued that part of the reason we are lacking more generally
accepted ways to describe effectiveness of open educational resources
is that the OER movement was founded on a belief — sharing knowledge is a good thing — and not much more.
There was no clearly defined goal, not even a clearly defined problem
that this movement was created to address. What the community is
lacking is a shared goal, why we are developing all this stuff. If we
had a shared goal and then some smaller goals to support the overall
one, we would have a better idea what we are doing this for.

She went on to suggest one (actually two) such goals: Increasing the
amount of knowledge in the world, and more equitably distributing it.
As a result there would be more that we know about the world and how to
make it a good place, and more people know it and have access to the
power that comes from knowing it. I am paraphrasing her – she was more
eloquent than my typing was able to keep up with.

While I like the way she describes the goals, I do not agree that they
have been absent. Maybe they haven’t been as clearly expressed as the
goals of the free software movement were laid out by Richard Stallman
early on — but many of the projects that are part of the OER movement
do in fact increase the amount of knowledge in the world and more equitably distribute it.
The OER movement has many facettes, and different people and
organisations participate for very different reasons. There are first
efforts to identify a shared narrative — for example through the Cape
Town Open Education Declaration — and these will provide a map of the
landscape that projects can relate to, but we have seen that the belief
in a powerful idea — that sharing knowledge is a good thing — can
provide enough common ground (or is it shared ground) for many
incredible things to happen. 10 years ago, who would have thought that
there would be over 6000 courses published openly online, that there
would be an online encyclopedia that reaches beyond the size and
quality of traditional encyclopedias, and that we would be using
software developed by open communities of volunteer contributors to
make it all happen? All of these things increase the amount of
knowledge in the world and help to more equitably distribute it. Maybe
it took a empiricist like Candice to take a hard look at the movement,
and verbalise what the community had been doing all along, without
being fully aware of it.

Jon makes a sound argument that top teachers need better compensation and incentives, but in South Africa it is not just the top teachers, but all teachers. Only focusing on the top 1%, and by proxy the top few% of graduates that are taught by these teachers, is not enough. My sense is that many developing countries have a small group (maybe 1%?) of highly-educated and skilled people, but what is needed is a broader middle-class of professionals; and the teachers to educate them.

It’s exciting to see different voices bringing different perspective to the argument for breaking down boundaries, and increasing innovation!

The workshop wiki is online and we would love to get feedback and comments for improvement. Some participants already asked us to run the event in their universities and we are planning to build a workshop blueprint/model that others can use as well.

The current version is a preview that we want to share with a broader community to get initial feedback and comments. Along with the declaration text we have compiled an extensive list of FAQs, which go into much more detail and allow more flexibility than the declaration.

Please, have a look at both, and if you disagree or you feel we are missing an important aspect, send your feedback here. If you really like it, please tell us as well (and keep you pen ready to sign up when it launches in January).

It seems like a useful model to think about rip-mix-learn practices, which are all further towards the “active” side of the triangle than the traditional lecture style of teaching and learning.

However, I am wondering to what extend the model has been tested and how much empirical evidence exists for the statements implicit in the triangle. It makes specific statements about a “2
week” timeframe, and assigns percentages (we remember x % of something) to different types of learning (reading, hearing about something, speaking about it, etc.). I wonder how reliable those percentages are, and how they were arrived at.

http://freecourseware.uwc.ac.za/dokuwiki/doku.php?id=rml:rimor_summary

Here is the summary:

Learners’ Reflections in Technological Learning Environments: Why to Promote and How to Evaluate
Rimor, R. and Kozminsky, E.
Proceedings of SITE 2000, February 8-12, 2000, San Diego, California, USA

This paper introduces the concept of metacognitive processes as a driver of learning, and uses a case-study of grade 9 learners working with electronic information (the paper confusingly refers to “data-base environment”) as an example. The underlying argument is that successful learners practice metacognition more efficiently and more frequently than less successful learners, or in other words: students who engage in metacognitive activity learn more and better.

Metacognition is defined as the ability to reflect upon one’s own thinking (and action) going back to Flavell (1976). It is connected to learning as an important contribution to Self-Regulated Learning SRL (Butler & Winne, 1995). In SRL the “teacher’s role has changed from being an infallible expert responsible for a final product, to being a guide who is more responsive to the context in which learning is occurring” and is thus directly based to the Constructivist theory. “This approach encourages learners to control their learning processes, reflect upon them and evaluate their results and progress in an open debugging procedure, which entails self reflection and peer dialogue.” (Note: that sounds just like what we mean by rip-mix-learn)

Students were asked to keep journals (personal reflection notes) over a period of 5 months. The journal content was then analysed and categorised into the authors’ tool for evaluating metacognitive components of students reflection (MCSR), which is based on Flavell’s three components of metacognition:
1 personal characteristics (P) (for example referring to preferences one has in regards to a way of learning)
2 task requirements (T) (for example, evaluating the relevance of the task in comparison to goals and objectives)
3 strategies for accomplishing the task (S) (for example, referring to results of data search)

Where the paper seems weak, is connecting data to the model and making a clear connection between type and frequency of personal reflection and learning progress. The authors are not examining which types of reflections are correlated with certain learning outcomes. As such, the tool remains a useful guide for categorising content, but lacks predictive or analytical power. What does it “mean” if one student shows more (or different types of) metacognition compared to other students?

For example, the authors do not go further as the following statement: “… Analysis of three [journal entries] suggest that [student 1's] explanations are better articulated, detailed and explicit that [student 2's]…Based on this analysis we can claim that [student 1's] articulation is qualitatively richer than [students 2's].” What this means in terms of actual learning is not explained – student 2 might well be learning more?

Notes on rip-mix-learn:

One thread that seems to be emerging is the issue of students’ awareness of what they are doing and why they are doing it. It could be interesting to investigate if students that can make sense of the practices used in their course will learn more than those who are questioning them. For example in Richard’s/Jay’s course, are students that are familiar with blogs and believe they are a useful tool learning more (and enjoying the learning more?) than those who do not see the value of using these ICTs for biology. The understanding of their own learning and the process they are going to could be described using the model developed in this paper. The connection to the quality of learning would be our contribution (and given that the authors did not attempt it – might be quite a challenge).

Full article is here: http://www.canada.com/nationalpost/news/story.html?id=aebf03b8-2d32-4fe1-a467-5e7f1f5a27a0&k=93169&p=1

Just over a year ago, a professor at the University of Prince Edward Island made his overcrowded History of Christianity class a stunning offer: He would give a grade of 70% to anyone who stopped showing up for the rest of the semester and didn’t bother to complete any of the course work. About 20 students took him up on the offer and the veteran academic was ultimately forced into premature retirement by an embarrassed administration.

David Weale made national headlines and garnered notoriety for his seemingly cynical act, but he was also lauded by many who shared his frustrations for daring to expose some unpalatable truths about Canada’s postsecondary education system.

Prof. Cote has since employed the UPEI test on his own classes — as a hypothetical exercise. When he offers 68% to anyone who quits, the only takers are those who failed the mid-term. As he edges the freebie higher, more students are willing to take the bargain.

“At 80%, virtually the whole class would walk out,” he said. “A lot of students react to it like ‘I got an 80 — that’s mine.’ They’re very egocentric about it. It’s almost like a possession to them.”