Daniel T. Willingham

Improving Students’ Learning With Effective Learning Techniques Promising Directions From Cognitive and Educational Psychology

Many students are being left behind by an educational system that some people believe is in crisis. Improving educational outcomes will require efforts on many fronts, but a central premise of this monograph is that one part of a solution involves helping students to better regulate their learning through the use of effective learning techniques. Fortunately, cognitive and educational psychologists have been developing and evaluating easy-to-use learning techniques that could help students achieve their learning goals. In this monograph, we discuss 10 learning techniques in detail and offer recommendations about their relative utility. We selected techniques that were expected to be relatively easy to use and hence could be adopted by many students. Also, some techniques (e.g., highlighting and rereading) were selected because students report relying heavily on them, which makes it especially important to examine how well they work. The techniques include elaborative interrogation, self-explanation, summarization, highlighting (or underlining), the keyword mnemonic, imagery use for text learning, rereading, practice testing, distributed practice, and interleaved practice. To offer recommendations about the relative utility of these techniques, we evaluated whether their benefits generalize across four categories of variables: learning conditions, student characteristics, materials, and criterion tasks. Learning conditions include aspects of the learning environment in which the technique is implemented, such as whether a student studies alone or with a group. Student characteristics include variables such as age, ability, and level of prior knowledge. Materials vary from simple concepts to mathematical problems to complicated science texts. Criterion tasks include different outcome measures that are relevant to student achievement, such as those tapping memory, problem solving, and comprehension. We attempted to provide thorough reviews for each technique, so this monograph is rather lengthy. However, we also wrote the monograph in a modular fashion, so it is easy to use. In particular, each review is divided into the following sections: General description of the technique and why it should work How general are the effects of this technique?  2a. Learning conditions  2b. Student characteristics  2c. Materials  2d. Criterion tasks Effects in representative educational contexts Issues for implementation Overall assessment The review for each technique can be read independently of the others, and particular variables of interest can be easily compared across techniques. To foreshadow our final recommendations, the techniques vary widely with respect to their generalizability and promise for improving student learning. Practice testing and distributed practice received high utility assessments because they benefit learners of different ages and abilities and have been shown to boost students’ performance across many criterion tasks and even in educational contexts. Elaborative interrogation, self-explanation, and interleaved practice received moderate utility assessments. The benefits of these techniques do generalize across some variables, yet despite their promise, they fell short of a high utility assessment because the evidence for their efficacy is limited. For instance, elaborative interrogation and self-explanation have not been adequately evaluated in educational contexts, and the benefits of interleaving have just begun to be systematically explored, so the ultimate effectiveness of these techniques is currently unknown. Nevertheless, the techniques that received moderate-utility ratings show enough promise for us to recommend their use in appropriate situations, which we describe in detail within the review of each technique. Five techniques received a low utility assessment: summarization, highlighting, the keyword mnemonic, imagery use for text learning, and rereading. These techniques were rated as low utility for numerous reasons. Summarization and imagery use for text learning have been shown to help some students on some criterion tasks, yet the conditions under which these techniques produce benefits are limited, and much research is still needed to fully explore their overall effectiveness. The keyword mnemonic is difficult to implement in some contexts, and it appears to benefit students for a limited number of materials and for short retention intervals. Most students report rereading and highlighting, yet these techniques do not consistently boost students’ performance, so other techniques should be used in their place (e.g., practice testing instead of rereading). Our hope is that this monograph will foster improvements in student learning, not only by showcasing which learning techniques are likely to have the most generalizable effects but also by encouraging researchers to continue investigating the most promising techniques. Accordingly, in our closing remarks, we discuss some issues for how these techniques could be implemented by teachers and students, and we highlight directions for future research.

Critical Thinking: Why Is It So Hard to Teach?

(2008). Critical Thinking: Why Is It So Hard to Teach? Arts Education Policy Review: Vol. 109, No. 4, pp. 21-32.

Neural Substrates of Response-based Sequence Learning using fMRI

Representation of sequential structure can occur with respect to the order of perceptual events or the order in which actions are linked. Neural correlates of sequence retrieval associated with the order of motor responses were identified in a variant of the serial reaction time task in which training occurred with a spatially incompatible mapping between stimuli and finger responses. After transfer to a spatially compatible version of the task, performance enhancements indicative of learning were only present in subjects required to make finger movements in the same order used during training. In contrast, a second group of subjects performed the compatible task using an identical sequence of stimuli (and different order of finger movements) as in training. They demonstrated no performance benefit, indicating that learning was response based. Analysis was restricted to subjects demonstrating low recall of the sequence structure to rule out effects of explicit awareness. The interaction of group (motor vs. perceptual transfer) with sequence retrieval (sequencing vs. rest) revealed significantly greater activation in the bilateral supplementary motor area, cingulate motor area, ventral premotor cortex, left caudate, and inferior parietal lobule for subjects in the motor group (illustrating successful sequence retrieval at the response level). Retrieval of sequential responses occurs within mesial motor areas and related motor planning areas.

Contributions of spatial working memory to visuomotor learning

Previous studies of motor learning have described the importance of cognitive processes during the early stages of learning; however, the precise nature of these processes and their neural correlates remains unclear. The present study investigated whether spatial working memory (SWM) contributes to visuomotor adaptation depending on the stage of learning. We tested the hypothesis that SWM would contribute early in the adaptation process by measuring (i) the correlation between SWM tasks and the rate of adaptation, and (ii) the overlap between the neural substrates of a SWM mental rotation task and visuomotor adaptation. Participants completed a battery of neuropsychological tests, a visuomotor adaptation task, and an SWM task involving mental rotation, with the latter two tasks performed in a 3.0-T MRI scanner. Performance on a neuropsychological test of SWM (two-dimensional mental rotation) correlated with the rate of early, but not late, visuomotor adaptation. During the early, but not late, adaptation period, participants showed overlapping brain activation with the SWM mental rotation task, in right dorsolateral prefrontal cortex and the bilateral inferior parietal lobules. These findings suggest that the early, but not late, phase of visuomotor adaptation engages SWM processes.

Neural correlates of encoding and expression in implicit sequence learning

In the domain of motor learning it has been difficult to separate the neural substrate of encoding from that of change in performance. Consequently, it has not been clear whether motor effector areas participate in learning or merely modulate changes in performance. Here, using a variant of the serial reaction time task that dissociated these two factors, we report that encoding during procedural motor learning does engage cortical motor areas and can be characterized by distinct early and late encoding phases. The highest correlation between activation and subsequent changes in motor performance was seen in the motor cortex during early encoding, and in the basal ganglia during the late encoding phase. Our results show that rapid encoding during procedural motor learning involves several distinct processes, and is represented primarily within motor system structures.

Neural substrates of intermanual transfer of a newly acquired motor skill

In healthy humans, the two cerebral hemispheres show functional specialization to a degree unmatched in other animals, and such strong hemispheric specialization contributes to unimanual skill acquisition [1, 2]. When most humans learn a new motor skill with one hand, this process results in performance improvements in the opposite hand as well [3-6]. Despite the obvious adaptive advantage of such intermanual transfer, there is no direct evidence identifying the neural substrates of this form of skill acquisition [7-9]. Here, we used functional magnetic resonance imaging (fMRI) to study brain regions activated during intermanual transfer of a learned sequence of finger movements. First, we found that the supplementary motor area (SMA) has more activity when a skill has transferred well than when it has transferred poorly. Second, we found that fMRI activity in the ventrolateral posterior thalamic nucleus correlated with successful future intermanual transfer, whereas activity in the ventrolateral anterior thalamic nucleus correlated with past intermanual transfer. Third, we found that repetitive transcranial magnetic stimulation applied over the SMA blocked intermanual transfer without affecting skill acquisition. These findings provide direct evidence for an SMA-based mechanism that supports intermanual transfer of motor-skill learning.

Differential Effect of Reward and Punishment on Procedural Learning

Reward and punishment are potent modulators of associative learning in instrumental and classical conditioning. However, the effect of reward and punishment on procedural learning is not known. The striatum is known to be an important locus of reward-related neural signals and part of the neural substrate of procedural learning. Here, using an implicit motor learning task, we show that reward leads to enhancement of learning in human subjects, whereas punishment is associated only with improvement in motor performance. Furthermore, these behavioral effects have distinct neural substrates with the learning effect of reward being mediated through the dorsal striatum and the performance effect of punishment through the insula. Our results suggest that reward and punishment engage separate motivational systems with distinctive behavioral effects and neural substrates.

Failure to engage spatial working memory contributes to age-related declines in visuomotor learning

It is well documented that both cognitive and motor learning abilities decline with normative aging. Given that cognitive processes such as working memory are engaged during the early stages of motor learning [Anguera, J., Reuter-Lorenz, P., Willingham, D., & Seidler, R. Contributions of spatial working memory to visuomotor learning. Journal of Cognitive Neuroscience, 22(9), 1917–1930, 2010], age-related declines in motor learning may be due in part to reductions in cognitive ability. The present study examined whether age-related declines in spatial working memory (SWM) contribute to deficits in visuomotor adaptation. Young and older adult participants performed a visuomotor adaptation task that involved adapting manual aiming movements to a 30° rotation of the visual feedback display as well as an SWM task in an fMRI scanner. Young adults showed a steeper learning curve than older adults during the early adaptation period. The rate of early adaptation was correlated with SWM performance for the young, but not older, adults. Both groups showed similar brain activation patterns for the SWM task, including engagement of the right dorsolateral prefrontal cortex and bilateral inferior parietal lobules. However, when the SWM activation was used as a limiting mask, younger adults showed neural activation that overlapped with the early adaptation period, whereas older adults did not. A partial correlation controlling for age revealed that the rate of early adaptation correlated with the amount of activation at the right dorsolateral prefrontal cortex. These findings suggest that a failure to effectively engage SWM processes during learning contributes to age-related deficits in visuomotor adaptation.

Three problems in the marriage of neuroscience and education

Whether neuroscience can be informative to educational theory and practice is not debatabledit has been. For example, behavioral data were not decisive in determining whether dyslexia was primarily a visual perceptual disorder, or whether phonology was the more fundamental problem (for a review, see McCardle et al., 2001). Brain imaging data (e.g., Rumsey et al., 1992) showed reduced activation in left temporoparietal cortex, a region known from other studies to support phonology, thus strongly supporting the phonological theory. The question is just how enthused and optimistic should researchers, educators, and parents be? It is wise to remember that there have been at least two other brief pulses of excitement over a possible marriage between these two fieldsdone in the mid 1960s (e.g., Gaddes, 1968) and the other in the early 1990s (e.g., Vellutino et al., 1991). Will the recent reigniting of the romance lead to a long-term commitment, or will it be another passing infatuation? Here I highlight three problems in bringing neuroscientific data and theory to bear on educational practice. Before I describe those three problems it will be useful to draw a distinction between natural and artificial sciences (Simon, 1996). Natural sciences, like neuroscience, are descriptive; the aim is to discover principles that describe neural structure and function and in so doing to bring order and comprehensibility to data. Artificial sciences are normative. Their aim is not the description of the natural world as it exists, but the creation of an artifact, designed to serve a specified goal, within a particular environment. Examples of artificial sciences include urban planning, economics, engineering, and education. The artifact to be created in education is a set of pedagogic strategies and materials. The goal is usually some version of ‘‘instilling skills and knowledge in children,’’ although the goal changes over time and across cultures.

What Neuroimaging and Brain Localization Can Do, Cannot Do, and Should Not Do for Social Psychology

Interest in bridging social psychology and neuroscience has seen a significant upsurge. Much of this interest has centered on brain localization--the attempt to relate psychological events to locations of brain events. Although many articles have sought to localize brain activity that supports social behavior, scant attention has been paid to the specific methods to be used in integrating brain localization data into psychological theory. The authors describe 4 strategies psychologists can use to integrate brain localization data and psychological theory, and they consider whether social psychology presents special considerations in the use of these strategies. They conclude that brain localization offers a useful tool for some but not all problems in social psychology, and they discuss the types of problems for which it may and may not prove useful.