Human Learning and Memory

Dr. Daniel Kimball

Research Description

My research explores basic human memory mechanisms, particularly those underlying forgetting, false memories, memory enhancement, and metamemory (self-assessment of memory). In my research, I use both behavioral techniques and computational modeling approaches.

Goal-Directed Forgetting

Forgetting can serve important goals, such as promoting efficient updating of memory by reducing interference from information that is no longer relevant (e.g., one's former telephone number). The prevailing view is that such goal-directed forgetting involves active suppression of to-be-forgotten information. However, the evidence supporting this suppression hypothesis is surprisingly sparse. My research seeks to provide more rigorous tests of this view and of alternative hypotheses, including selective rehearsal of to-be-remembered information and enhanced contextual segregation of to-be-remembered and to-be-forgotten information.

Forgetting and False Memories

Most research on forgetting has focused on the loss of access to previously learned information. Although that issue is important, I am also interested in establishing the manner in which forgetting affects false memories—that is, memories for events that never occurred, or that did occur but not as remembered. My research has shown that the effect of forgetting on false memories depends critically on what causes the forgetting—for example, whether the forgetting is intentional and goal-directed or whether the forgetting is instead a byproduct of enhancing memory for other events or facts. I am also interested in exploring other conditions that affect memory distortions, as well as the extent to which such distortions affect other cognitive processes, such as inferencing and reasoning. More generally, I am interested in exploring the ways that prior experience and knowledge affect our memory for episodes and events.

Metamemory Versus Memory

Another line of my research involves acquiring a better understanding of the workings of metamemory—that is, one's ability to assess the state and contents of one's own memory. A critical part of this research is designed to tease apart behavior that reflects memory processes from behavior that reflects metamemory processes. A key example of this issue involves the finding that, when people are asked to judge which words from a list they are likely to remember, they are more accurate if they can test themselves after a delay and then make the judgment. This finding is widely regarded as evidence of more accurate metamemory. However, my research has shown that this effect is actually attributable to memory phenomena, and not to better metamemory, in that the words they recall when testing themselves receive a boost in memorability from being recalled that the unrecalled words do not—that is, the self-testing affects the memorability of the words themselves—thus rendering the judgments that follow this self-testing appear more accurate (Kimball & Metcalfe, 2003). This finding underscores the importance of distinguishing between memory and metamemory processes when attempting to understand how our metamemory works.

Metamemory in the Learning Process

I am also interested in exploring the widely held assumption that better metacognitive accuracy leads to better decisions regarding allocation of study effort, which in turn leads to better memory performance. Surprisingly little evidence has been reported supporting this causal chain. A related area of interest involves developing methods to train learners to use metacognitive judgments to enhance learning—training which has been largely neglected in schools and training programs. I am also interested in exploring the intriguing scarcity of evidence for a strong relationship between metacognitive skill and memory performance.

Memory Enhancement

Another area of interest is optimization of memory performance, for both theoretical and practical reasons. One line of my research has explored interactions among the effects of various memory enhancement techniques—generation, spacing, levels of processing, and variation (Kimball & Bjork, manuscript in preparation). Our evidence indicates that combining techniques does not always result in recall that one would expect by simply adding the numbers of items recalled using the techniques separately. This line of research can inform us about the mechanisms underlying these various techniques—and it also has important applications to the classroom and to training programs, where the cost effectiveness of adding techniques is an issue.

Computational Modeling

In addition to continuing to use behavioral research techniques in pursuing these research interests, I have recently begun to apply computational modeling approaches. Such approaches can help in addressing the issues of interest in these lines of research. Modeling false memories could help discriminate between various mechanisms that have been offered to explain memory distortions, particularly those emphasizing encoding versus retrieval factors, and could help identify the boundary conditions separating the beneficial and distortive effects of prior experience and knowledge on episodic memory. Modeling goal-directed forgetting could help determine whether a suppression mechanism is necessary to explain the data or whether excitatory mechanisms are sufficient. Modeling metacognitive processes could be particularly helpful in ascertaining the extent to which phenomena that have been attributed to metamemory processes are actually attributable instead to memory processes. Modeling could also help identify the mechanisms that underlie various memory enhancement techniques and help explain the interactions among their effects.

For more information about applying to work with Dr. Daniel Kimball, contact him at dkimball@uta.edu (817-272-3179) or contact the graduate advisor, Dr. Martha Mann, at mann@uta.edu.