OILSEED ECONOMICS

Crop Production/Industries,

TAXATION AS A MEANS OF REDUCING NITROGEN FERTILIZER USE IN MINNESOTA CORN PRODUCTION

Crop Production/Industries, Environmental Economics and Policy,

Embedded Intergroup Relations in Interdisciplinary Teams

Many organizations are making a deliberate effort to use teams to carry out work as an alternative to more traditional, hierarchical approaches to defining jobs or supervising employees. The authors posit that structure and composition of work teams are likely to systematically affect group dynamics of such teams. Using the related frameworks of social identification theory and embedded intergroup relations theory, they examine the proposition that greater diversity of team member characteristics and larger team size negatively affect members' perceptions of team integration. Hypotheses were tested on 1,004 individuals working on 105 interdisciplinary treatment teams in a national sample of 29 Department of Veterans Affairs psychiatric hospitals. Five of six hypotheses received support for at least one of three dimensions of team integration examined in this article. The strongest support was found for the effects of diversity on perceptions of team functioning. Results are generally consistent with the basic premise of the embedded intergroup relations model: As teams become more diverse along most identity group and organizational group characteristics, intergroup relations among team members suffer and perceived level of team integration declines. The authors offer several suggestions about how managers and team leaders might use these findings to improve team integration.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/67673/2/10.1177_0021886397334001.pd

The Motivational Assessment Tool (Mat) Development And Validation Study

The purpose of the present research is to validate a measure of motivation collimated from an individual’s motivational, affective, and personality traits. The Motivational Assessment Tool (MAT) is being developed to assess multiple variables for an Intelligent Tutoring System (ITS) to deploy individualized adaptations through various levels of learner profiling. This first study factor analyzed a pool of 303 questions aimed at reducing, refining, and developing scales. Overall, the results of the first factor analysis shows that the MAT is composed of 28 factors. The produced scales are supported by correlations with other factors identified in psychology. The MAT is envisioned to provide inputs into an intelligent tutor’s pedagogical strategy to adapt its learning methods to support the learner’s motivational type