Learning Persistence and Cessation in Kindergarten and College Students Annina Brendel - Department of Psychology, Heidelberg University Abbey Mirkin & Jeffrey Coldren, Ph.D., Department of Psychology, Youngstown State University Abstract This project identifies the conditions under which learners persist or cease in a laboratory task. Kindergarten children and college-aged students completed three perceptual discrimination learning problems. The first problem was solvable as learners attained a criterion of success; the second was solvable but with no criterion so learners achieved a highly accurate level of performance (overtraining); and the third problem was non-solvable as the correct answer was set randomly. Two distinct profiles were observed across the ages: Kindergarten students showed high rates of cessation across the problems even when they were making progress, whereas college students showed high rates of persistence even when learning had become futile. These experiments highlight that human learners at any age may demonstrate irrational learning performance. Learning Problems The first two problems were practice, followed by three experimental problems. The first problem was solvable (S) as learners attained a criterion of success of eight correct responses in a row; the second was solvable but with no learning criterion so learners achieved a highly accurate level of performance (overtraining - OT); and the third problem was non-solvable (NS) as the correct answer random. Conclusions & Future Directions   This project found that human learners at either age generally did not conform to the predictions of the neural net model. Both ages demonstrated irrational but different profiles of persistence and cessation. Kindergarten children generally did not persist long enough to solve learnable problems (even though they could), and did not persist in problems that yielded little payoff. On the other hand, college students persisted when making progress in a task, but failed to cease when either attaining mastery or reaching futility. Thus, college students are laudable, but irrational and inefficient, learners. The failure to persist when making progress in learning and to cease when no longer making progress is attributed to deficiencies in the self-regulation of learning, although the extent of these failures and their developmental and experiential mechanisms remain to be determined. Future directions for research include (a) generalization of these findings to other learning tasks; (b) extending the neural net model to cover these new data; (c) exploring ways to increase learning persistence in preschool and kindergarten children; (d) identifying individual differences and profiles of successful performance especially with regard to educational outcomes; and (e) determining relations to dispositional measures (Grit, ATQ). Experiment 1 (Kindergarten Learners)   The sample involved 32 typical kindergarten children (69% females; 25% non-Caucasian) with a mean age of 74.16 months. The primary measure is the percent of participants who attained each outcome on each problem. As shown in the graph below, kindergarten children showed high rates of cessation across all problems including those that were solvable. Previous experiments with this type of learning task have demonstrated that kindergarten children can solve such problems with ease. Introduction In most endeavors, persistence is regarded as a virtue. There is substantial evidence of the benefits of persistence. The issue of doggedness in education is especially important as “grit” has been found to predict success in educational attainment among individuals beyond IQ.   A glaring need is to identify processes that determine whether to persist or quit in learning a task. A key determinant in task persistence as specified by the information-processing model of self-regulated learning is how a learner sets goals, evaluates, and revises behavior. This model, however, is vague, imprecise, and outdated. Further, many studies about persistence are observational and correlational. Controlled laboratory studies likewise offer little insight as quitting may be considered “error”. The development of autonomous organisms, spurred by advances in machine learning and artificial intelligence, offers novel interpretations for the study of persistence. Shultz, Doty, and Dandurand (2012) developed a neural net model of human learning that simulated cessation. Learning cessation was operationalized as error reduction toward a goal. The neural net model was quite efficient as learning continued under 100% reinforcement conditions, but stopped quickly under a 50% learnable condition when error reduction stalled. The purpose of this project was to determine whether the laboratory learning performance at two ages conforms to predictions of the computational model. Specifically, do learners (1) persist when making progress toward a goal, and (2) cease upon either attaining mastery by solving the problem or reaching futility by never solving the problem? Our predictions were that kindergarten children would show high levels of persistence given their immature self-regulatory skills and poor inhibition, whereas college students would be more likely to cease when learning is no longer productive given their greater experience in educational tasks. For more information or reprints, please contact: J. T. Coldren, Ph.D. Department of Psychology Youngstown State University Youngstown, Ohio USA 44555 jtcoldren@ysu.edu Experiment 2 (College Learners)   This sample involved 67 college students (69% females; 33 % non-Caucasian) with a mean age of 22.22 years. The majority solved the learnable problem as expected, but there was a great deal of persistence as most participants did not quit the OT and NS problems. Method   At each age, participants solved three perceptual discrimination learning problems. Each problem contained a pair of abstract geometric stimuli that contained four co-varying perceptual dimensions (although the stimuli were more complex for the college students). Participants were told to pick the “correct” picture in the pair, with one consistently reinforced over trials, to attain as many correct responses in a row as possible. Participants pressed the left or right buttons to indicate their choice, and were given the explicit option to press the space bar on every trial to quit the problem.