Deep Processing – Conveying Structure with Lectures

I was happy to discover that “Four things lecture is good for” by Robert Talbert comes to the defense of lectures. I’ve observed in the past that traditional lectures are very often dogged on, almost to the point of being unfair. Perhaps I’ve just wanted to play Devil’s advocate, but maybe the traditional lecturing style was the best we could do with what we knew in the past. Many learning theories are relatively young disciplines, with learning sciences and engineering education being younger still. Further, lecturing had to have some capabilities or it wouldn’t have been practiced. In fact, there might be certain fields or topics for which it is very useful.

As Talbert points out, there are some purposes for which lectures are useful. Of the four purposes listed as being “well-suited” to lectures, the sharing of “cognitive structures” stuck out to me. The Cambridge Handbook of Engineering Education Research provides a set of principles for three learning theories, or what it calls “conceptual frameworks” of learning and knowing. In the cognitivist framework, one of the principles in designing instruction is to aim for “deep processing” of information:

The general idea of deep processing is that learners should understand the structure of information to be learned, such as the main ideas and how they relate to one another and to sub-ideas that might derive from them…

The more organized information is, the easier it is to remember and understand. In “Successful Lecturing: Presenting Information in Ways That Engage Effective Processing”, it is also presented that the provision of structure in lectures results in better learning. Providing students with outlines or knowledge maps (concept maps) of the lecture material results in better notes, better testing results, and better memorization (sidenote: if you’re interested in knowledge maps, you should check out The Book of Trees: Visualizing Branches of Knowledge). Even as sparse as a title can be beneficial. At the other end of the spectrum, if outlines become too full and veer towards content, their benefits become negated:

Outlines containing only headings and subheadings are maximally effective in that they encourage note taking, whereas outlines that provide too much detail inhibit note taking

2 thoughts on “Deep Processing – Conveying Structure with Lectures”

  1. I also liked Talbert’s defense of lecturing, even though I thought it was a little ironic that he offers these really great points and still refers to himself as “firmly anti-lecture”. The thing that I find a little confusing is that he refers to these 4 purposes as if they are really specific situations within a course that might warrant lecturing, whereas I think many, many course subjects fall entirely within these four categories. For example, “modeling thought processes” seems like the goal of many math, physics, programming, and engineering courses, so it seems like lecture would be a really effective way to approach the course, rather than a tool to pull out of the teaching tool belt only on certain occasions.

    1. I think you have a very thoughtful comment that some classes seem to fit entirely within Talbert’s purposes of lectures. When I first started to become aware of non-traditional learning concepts such as connected learning, it was difficult for me to get away from this. For example, it seemed difficult to add something like blogging to a freshman math class. As I’ve learned more techniques and innovative ways to non-traditional teaching I think I’ve struggled less with this.

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