Individual Differences

An individual difference that we have focused on in our laboratory is derived from Gernsbacher’s (1990) Structure Building Framework. The major assertion of this framework is that readers have a working mental model of what they are reading and are constantly updating it whenever they come across new information. This new information could either be incorporated into the existing structure or if it is deemed irrelevant, depending on the reader, the information is inhibited or a new substructure is constructed. It is posited that poor structure builders have a difficult time (a) inhibiting irrelevant information and (b) limiting the number of substructures constructed. Thus, poor structure builders end up shifting and constructing a lot of unnecessary substructures. Good structure builders, on the other hand, do a better job at inhibiting irrelevant information and develop a more coherent, organized mental model of what the text is about. The Structure Building framework originated in considering text comprehension of narratives, and little research has examined whether it is a significant predictor of learning from technical passages.

To this end, Martin, Nguyen, and McDaniel (2013) examined whether differences in structure building abilities influenced the effectiveness of the meta-3R strategy. All participants engaged in the 3R study strategy and also took the Revised Multi-Media Comprehensive Battery (MMCB-R), which is a measure of structure building (Gernsbacher & Varner, 1988). Consistent with the theoretical assumptions of the structure building framework, high structure builders outperformed low structure builders on a wide range of assessments that included free recall, inference multiple-choice, and problem-solving tests. Further, another difference between high and low structure builders was identified: High structure builders were able to guide their restudy more effectively than low structure builders. According to the Discrepancy-Reduction (DR) self-regulated learning framework, learners should spend less time

restudying material judged as well-learned than material judged as less well-learned (Thiede & Dunlosky, 1999). Martin et al. found that high structure builders were more likely to follow this self- regulated study policy than low structure builders. This difference in metacognitive strategy played a vital role in helping high structure builders recall significantly more new information (non-recited idea units) on a final free recall test than low structure builders.

More pertinent to the present chapter, structure building has also been found to moderate the effectiveness of study strategies designed to improve text comprehension. Callender and McDaniel (2007) found that placing embedded questions throughout the text improved test performance for low but not high structure builders relative to a rereading group (see Figure 4). The authors interpreted these results as indicating that embedded questions help provide low structure builders with anchors around which to build their mental model of the text’s meaning. Because high structure builders are

already adept at building an organized and coherent representation, answering embedded questions was superfluous for improving their comprehension.

Figure 4. Final test performance as a function of condition and level of structure building ability. Adapted from Callender & McDaniel (2007).

Bui and McDaniel (2013) also found structure building to moderate the effectiveness of outlines on learning. They instructed participants to take notes while listening to an audio lecture. Some learners were provided with an outline of the lecture while others received no learning aid. Following a short delay, learning was assessed with both a free recall test and an inference-based short-answer test. Providing outlines helped all learners on free recall but only improved performance on inference tests for high structure builders. These results suggest that low structure builders do not have the cognitive capability to develop a coherent mental model of the lecture despite the assistance of an outline. Taken together, these findings suggest that structure building is a particularly important individual difference that should be taken into account when assessing the efficacy of a technique aimed at improving text comprehension. Because of the vital role that structure building plays in moderating the effectiveness of some of these study strategies, we suggest that instructors become mindful of

individual differences (especially structure building) when trying to implement them, as benefits may not accrue for all students.

Conclusion

In the present chapter, we have endorsed text learning techniques that are especially useful in classes in which active learning is not an inherent part of the course. For instance, in classes such as chemistry or physics, active problem-solving is an essential part of the class no matter how the course is structured. Accordingly, students may be more likely to actively interrogate the textbook materials in the service of solving problems. However, with classes like introductory psychology or history, it is perhaps natural that students are less able to find active approaches for learning from the textbook. Thus, the techniques introduced in this chapter are particularly important for these classes in which passive learning from textbooks may be the norm. Our hope is that these techniques will help promote more active learning from textbooks than most students would otherwise typically engage.

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The techniques introduced in this chapter fall under a broader umbrella called desirable difficulties, the idea that learning perceived to be difficult and challenging in the moment tend to yield greater benefits later on (Bjork, 1994; McDaniel & Butler, 2011). While researchers and instructors may understand the value of these techniques, it is important to remember that students may perceive them to be less worth their while than reading (and rereading) through the text. Even though our data suggest that these techniques are not any more time-intensive than simply rereading or taking notes, it is essential to consider that students’ levels of motivation may decrease in the beginning when they do not see

immediate benefits. Consider the experience of Young, a medical student who was having a difficult time learning the material in his classes before he came across retrieval practice as a learning technique. Below is an excerpt taken from Brown, Roediger, and McDaniel (in press) that exemplifies the difficulty that Young experienced at first when trying to implement retrieval practice:

“It makes you uncomfortable at first. If you stop and rehearse what you’re reading and quiz yourself on it, it just takes a lot longer. If you have a test coming up in a week and so much to cover, slowing down makes you pretty nervous…You just have to trust the process, that was really the biggest hurdle for me, was to get myself to trust it. And it ended up working out really well for me.” (pp. 213-214)

Indeed, implementing retrieval practice worked out well for Young. He went from the bottom of his class to the top 10-15%. This is a real-life example of a student who persevered and kept implementing retrieval practice despite the frustration he encountered when first implementing the strategy.

However, the average student’s knowledge of effective study strategies is already poor so continued practice of a technique that is perceived as being difficult is less likely to occur (McCabe, 2011). Thus, it is important for instructors to reinforce students’ motivation to continue using the technique by

demonstrating the benefits of the strategy. Einstein, Mullet, and Harrison (2012) had students study one text using a study-study strategy and another text using a study-test strategy. Not surprisingly, they found the standard testing effect with students performing better on the text in which they used a study-test strategy. More importantly, they had students analyze their results to see first-hand how they performed on the respective tests. Following this demonstration, students reported that they were more likely to engage in a testing strategy during future study. These results suggest that students can be motivated to use a particular technique if they experience the benefits first-hand.

Attempts to apply cognitive principles to improve educational practices have picked up steam lately. One area that would benefit is text comprehension, given the considerable amount of time students spend learning from textbooks. In the present chapter, we have discussed several techniques that show great promise in producing effective learning from texts. In addition, we have also attempted to tackle the important question of translating laboratory findings to the classroom. Although we have made some practical recommendations, our hope is that instructors will use these recommendations as a starting point and adapt them to fit the constraints of their classes. Because of the easy to learn and time-efficient nature of these techniques, we are hopeful that they would be well-received by students and thus implemented routinely while studying texts. Nevertheless, instructors still play a vital role in augmenting these techniques by constructing an environment that encourages students to apply these techniques.