Article Review #2

Butcher, K. R. (2006). Learning from text with diagrams: Promoting mental model development and inference generation. Journal of Educational Psychology, 98(1), 182-197.

Butcher (2006) starts with this primary observation: most educational materials rely on pictures, diagrams, and text to communicate information. Given this fact, Butcher identifies two gaps in the literature. First, while many studies have found a positive relationship between the use of pictures and recall or memorization, it is less clear if pictures have a similar impact on deeper levels of learning. Secondly, while principles like the coherence principle can help guide multimedia choices, the ideal format of individual learning materials has not been as consistently identified by the literature. Butcher chooses to focus her study on diagrams. (This includes schematic diagrams like flowcharts or Venn diagrams, and more simple iconic diagrams). Butcher makes a strong argument that this specific topic is under-addressed in the literature, despite the fact that visual elements are such a critical part of course instruction (even more so in online education, I would add).

According to Mayer (2001), the coherence principle states that “learning materials should include only relevant multimedia and should avoid irrelevant pictures, sounds, or words” (4). Applying the coherence principle to diagrams means that we would get rid of any parts of a diagram that are not necessary. Simplifying the diagram can reduce the demands placed on students’ working memories. However, simplifying can also mean an increase in abstraction, so which will be more useful to students? A realistic diagram that is more complex? Or a simple diagram that is more abstract? This is the question the author seeks to explore as she compares functional/simple diagrams and detailed/structural diagrams.

Butcher sets up two experiments. In Experiment 1, she tests the hypothesis that high knowledge learners benefit from detailed diagrams while low knowledge learners benefit from simpler diagrams. Students were provided with a pre-test, and then information in one of three formats (text only, text and simple diagram, and text and detailed diagram). A detailed post-test (including student drawings and explanations, memory questions, and inference questions) was then administered. The author found that both types of diagrams helped students develop a mental model of the concept, but simplified diagrams were best. Contrary to expectations, higher knowledge students didn’t benefit more from detailed diagrams.

Experiment 2 added an element of self-explanation in order to identify why simplified diagrams were effective. Butcher found that simplified diagrams created “more integration inferences” than complex diagrams or text-only instructions. In other words, diagrams helped students generate correct inferences, which is a key marker of deeper comprehension. In my opinion, experiment 2 was more abstract and the results less useful than experiment 1. However, as Butcher points out, many other studies stop once they identify a relationship between multimedia and recall, and so experiment 2 does provide evidence that diagrams/pictures can also influence deeper understanding by encouraging inference generation.

Butcher’s work has specific practical applications for instructors and designers, even though the article itself is quite technical and thus not as accessible as it could be. In particular, the recommendation to favor simple diagrams over “realistic” diagrams could be met with some resistance (I think we all have a tendency to assume is “more is better” from time to time). Being able to point to the research conducted by Butcher can help inform and justify best practices in those instances.

Lastly, I appreciate Butcher’s nuanced overall conclusion, which is that we cannot make a blanket recommendation to always choose simple diagrams or always choose complex diagrams. Instead, we should choose diagrams that make the key functional relationships within the diagram the most clear. In other words, consider the learning outcomes and ensure that the diagram only has what is necessary (no more, no less) to achieve those learning outcomes. Even though this is not an unexpected conclusion in the world of instructional design, it is nuanced nonetheless and strongly supported by the experiments conducted in Butcher’s study.

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Article Review #1

Sung, E., and Mayer, R. E. (2012). When graphics improve liking but not learning from online lessons. Computers in Human Behavior, 28, 1618-1625.

In this study by Sung and Mayer (2012), the authors explore the impact of graphics on learning. According to the multimedia principle, “People learn better from words and pictures than from words and pictures alone” (1618). This principle has been supported by numerous studies (see this article review). Adding graphics to a lesson can improve (1) performance, and (2) motivation.

The authors divide graphics into three distinct categories:

  1. Instructive graphics. These types of graphics are relevant to an instructional goal. According to the authors, an instructive graphic “Primes appropriate cognitive processing such as attending to the relevant information, organizing it, and integrating it with relevant prior knowledge” (1619).
  2. Seductive graphics. These graphics are interesting or attention-grabbing, but not relevant to the lesson content. This type of graphic requires learners to expend cognitive energy to process a graphic that is irrelevant to learning goals.
  3. Decorative graphics. These graphics are “neutral in cognitive impact.” They are pleasant but not very distracting.

In order to study the impact of each of these three types of graphics on performance and motivation, the authors performed a short experiment with 200 college students. They divided the students into 4 groups (instructive graphics, seductive graphics, decorative graphics, and no graphics), and administered a pretest, recall test, and satisfaction survey. They then performed a quantitative analysis to draw conclusions. The authors found that instructive graphics improve performance, while seductive graphics harm performance. Decorative graphics and no graphics yield basically the same level of performance. Interestingly, students indicated higher levels of satisfaction when any type of graphic was used. Satisfied students are more motivated students, so logically, adding even irrelevant graphics can improve student motivation.

While I find the results of this study interesting and quite useful, as the authors themselves point out: “The lessons used in this study were short, the material was simple, the test was immediate, the learners were college students, and only one lesson was involved” (1624). In other words, there are some nuances to this question that are not fully captured by this particular research design. We cannot make blanket recommendations to always use any type of graphic because it increases enjoyment, because perhaps the distraction from a seductive graphic would counteract the benefit of the increased motivation. I also concur with the authors’ that the study failed to precisely quantify “relevance” or “interestingness.” These factors could surely influence the findings but are difficult to accurately measure (especially in a small scale study as this).
Despite these shortcomings, I found this article to be very useful. The literature review was succinct but thorough, and showed all sides of the issue: when graphics help, hurt, or have no effect on learning. The three easy-to-understand categories of graphics (and the helpful examples provided by the authors) represent an easy way for designers and teachers to categorize graphics they are using or intend to use in their course. In turn, this could lead to better designed courses that not only use graphics intended to increase student enjoyment, but relevant graphics that increase performance as well.

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