Career Preparedness Survey Outcomes of Food Science Graduates—A Follow‐Up Assessment

Abstract: Fifty‐eight recent graduates (1998–2008) from the joint Washington State University (WSU) and University of Idaho (UI) BiState School of Food Science program and 27 of their employers participated in a survey assessing learning outcomes based on the 2001 Institute of Food Technologists (IFT) core competencies for undergraduate food science programs. Parallel web‐based survey instruments for the graduates and employers using the WSU Skylight Matrix Survey System^© were employed to assess the attitudes of the respondents to the frequency of usage of IFT defined skills and the adequacy of the graduates’ preparation from the program. Graduates responded that they were generally satisfied with their education; however, they reported lower rates of adequate or better preparation in Success Skill involving group dynamics, processing and engineering skills, and government regulations. Most of these skills were also the least frequently used by graduates in their careers. Success Skills were the most frequently performed competencies, while food microbiology and safety, and some engineering and processing skills were used less frequently by graduates of the Food Science program. Greater than 80% of the employers reported that the graduates’ performance was adequate or better in all skill areas. The assessment suggested program improvement since a similar survey in 2004, but also illuminated areas for improvement in teaching and learning, particularly in light of the revised IFT 2011 Guidelines. Specifically, graduates and employers emphasized the need for more course work that weaves critical thinking skills, group dynamics, and government regulations into the classroom. Graduates also highlighted the importance of internships and extracurricular activities for career preparation.     

Automatically structuring domain knowledge from text: An overview of current research

This paper presents an overview of automatic methods for building domain knowledge structures (domain models) from text collections. Applications of domain models have a long history within knowledge engineering and artificial intelligence. In the last couple of decades they have surfaced noticeably as a useful tool within natural language processing, information retrieval and semantic web technology. Inspired by the ubiquitous propagation of domain model structures that are emerging in several research disciplines, we give an overview of the current research landscape and some techniques and approaches. We will also discuss trade-offs between different approaches and point to some recent trends.     

Warranted uncertainty and students' knowledge and use of drugs

The ability to recognize when it is warranted to be uncertain was developed effectively in 167 elementary school students through daily 15-min lessons over a 5-week period. This initial training did not deal with drug use in any way. A 3-year follow-up evaluation measured retention of these warranted-uncertainty skills, and assessed the effects of these skills on students' use of hard and soft drugs. In comparison with the matched control subjects, there was evidence of some retention after 3 years: the trained subjects were slightly better able to recognize when it is warranted to be uncertain about the effects of drugs. There was also strong evidence that many of the controls had acquired, somehow, the ability to generate warranted uncertainty, and that warranted uncertainty functioned as a stable construct (irrespective of how it was acquired) and was related to drug use. It appeared to produce a skepticism or an analytic attitude that allowed the student to ignore peer and parental dogma about drugs.