Achievement Motivation Goals in Relation to Academic Performance in Traditional and Nontraditional College Students

This study extended Dweck's model of achievement motivation to the collegiate level, and it is the first to apply this model to nontraditional students. We examined the relationship between goal orientations and academic performance in 262 undergraduate students grouped by nontraditional vs. traditional status. Although both groups rated themselves higher on learning goals than on performance goals, non-traditional students endorsed learning goals even more strongly than their traditional peers. Goal orientations were a better predictor of academic success than student status. Consistent with Dweck's model, a learning goal orientation was positively related to successful academic performance for both groups. The relationship between performance goals and academic success was less straightforward, but students who rated both goal orientations as relatively weak had the lowest cumulative GPAs. Traditional and nontraditional students differed on variables that were inversely related to academic performance. Less successful traditional students endorsed irrational beliefs (a possible index of learned helplessness), while less successful nontraditional students worked more hours at a paid job.     

I Remember You: Independence and the Binomial Model

We focus on the problem of ignoring statistical independence. A binomial experiment is used to determine whether judges could match, based on looks alone, dogs to their owners. The experimental design introduces dependencies such that the probability of a given judge correctly matching a dog and an owner changes from trial to trial. We show how this dependence alters the probability of a successful match of dog to owner, and thus alters the expected number of successful matches and the variance of this expected quantity. Finally, we show that a false assumption of independence that results in incorrect probability calculations changes the probability of incorrectly rejecting the null hypothesis (i.e. the Type I error).     

Surveillance of school violence,injury, and disciplinary actions

The safety of America's schools is a major issue. Yet, the magnitude of the problem cannot be accurately assessed because some of the data concerning incidents and disciplinary actions come from reporting systems that are seriously flawed. In this article we examine how data from student self‐report surveys and other sources can be used to assess the weaknesses in current school incident‐reporting systems and improve the validity of surveillance data on school violence. Particular attention is paid to assessing the validity of data from Gun‐Free Schools Act (GFSA) reports on the number of guns in schools in light of nationally representative student survey data. We also discuss the difficulties of obtaining accurate surveillance data and suggest changes in surveillance systems that could produce more valid estimates of violence and injury in our nation's schools. © 2001 John Wiley & Sons, Inc.     

Learning via mnemonic pictures: Analysis of the presidential process

In three experiments, junior high school students learned the numerical order of 14 U.S. presidents according to either a complex mnemonic strategy or their own techniques. Reliable performancepattern differences between the two groups were detected, both in the presence and absence of overall level-of-recall differences. Chief among the pattern differences were the classic serial-position profiles produced by control subjects, but not by those using mnemonic strategies, and the slower response times (suggesting a more complex retrieval process) of subjects using mnemonic strategies.     

Toward a computational model of tutoring

This article addresses several issues around successful integration of instructional science and computer science. It addresses issues of building computational models of tutoring and incorporating instructional principles into them. The first barrier to overcome in working toward this integration is development of principled programs in which cognitive principles about learning and teaching are realized at a level of granularity consistent with building computational models. Such cognitive studies would facilitate fine-grained modeling of learning and teaching. The second barrier to overcome is the gap between the two disciplines in terms of goals, motivations, literature, and even definitions of concepts. This situation suggests that effort should be concentrated on two areas: research on understanding basic principles behind learning and teaching, and the establishment of clearer lines of communication between instructional and computer scientists. This article addresses both these issues. An earlier version of this article will appear as a chapter in the NATO Workshop volumeFoundations and Frontiers in Instructional Computing Systems, P. Winne and M. Jones, Eds., Springer-Verlag, NY.     

Introduction to the special issue on the appraisal and prediction of school violence

This article provides an overview of a special issue of Psychology in the Schools that critically examines issues related to the appraisal of the risk for violence among students. It is argued that school psychologists can assume the important role of informing communities about the limitations of school violence screening and assessment procedures and can implement student‐appraisal techniques that focus on long‐term student development. They can also work toward more accurate measurement of general school violence trends and intervention needs. © 2001 John Wiley & Sons, Inc.