Team Research at the Biology–Mathematics Interface: Project Management Perspectives

The success of interdisciplinary research teams depends largely upon skills related to team performance. We evaluated student and team performance for undergraduate biology and mathematics students who participated in summer research projects conducted in off-campus laboratories. The student teams were composed of a student with a mathematics background and an experimentally oriented biology student. The team mentors typically ranked the students'' performance very good to excellent over a range of attributes that included creativity and ability to conduct independent research. However, the research teams experienced problems meeting prespecified deadlines due to poor time and project management skills. Because time and project management skills can be readily taught and moreover typically reflect good research practices, simple modifications should be made to undergraduate curricula so that the promise of initiatives, such as MATH-BIO 2010, can be implemented.     

University drop-out: an Italian experience

University students’ drop-out is a crucial issue for the universities’ efficiency evaluation and funding. In this paper, we analyze the drop-out rate of the Economics and Business faculty of Sapienza University of Rome. We use administrative data on 9,725 undergraduates students enrolled in three-years bachelor programs from 2001 to 2007 and perform a Generalized Linear Mixed Model. Our aim is to improve the general understanding of the students’ withdrawing focusing on personal characteristics of students rather than on institutional aspects of the university. The empirical analysis unveils the statistically significant effect of students’ characteristics, like citizenship and income, while the main findings relate a high drop-out probability to a high secondary school final mark and a low individual students’ performance.     

Using concept maps to assess student learning in the science classroom: Must different methods compete?

This yearlong study was implemented in seventh-grade life science classes with the students' regular teacher serving as teacher/researcher. In the study, a method of scoring concept maps was developed to assess knowledge and comprehension levels of science achievement. By linking scoring of concept maps to instructional objectives, scores were based upon the correctness of propositions. High correlations between the concept map scores and unit multiple choice tests provided strong evidence of the content validity of the map scores. Similarly, correlations between map scores and state criterion-referenced and national norm-referenced standardized tests were indicators of high concurrent validity. The approach to concept map scoring in the study represents a distinct departure from traditional methods that focus on characteristics such as hierarchy and branching. A large body of research has demonstrated the utility of such methods in the assessment of higher-level learning outcomes. The results of the study suggest that a concept map might be used in assessing declarative and procedural knowledge, both of which have a place in the science classroom. One important implication of these results is that science curriculum and its corresponding assessment need not be dichotomized into knowledge/comprehension versus higher-order outcomes. © 1998 John Wiley & Sons, Inc. J Res Sci Teach 35: 1103–1127, 1998.     

Equity and Excellence in Research Funding

The tension between equity and excellence is fundamental in science policy. This tension might appear to be resolved through the use of merit-based evaluation as a criterion for research funding. This is not the case. Merit-based decision making alone is insufficient because of inequality aversion, a fundamental tendency of people to avoid extremely unequal distributions. The distribution of performance in science is extremely unequal, and no decision maker with the power to establish a distribution of public money would dare to match the level of inequality in research performance. We argue that decision makers who increase concentration of resources because they accept that research resources should be distributed according to merit probably implement less inequality than would be justified by differences in research performance. Here we show that the consequences are likely to be suppression of incentives for the very best scientists. The consequences for the performance of a national research system may be substantial. Decision makers are unaware of the issue, as they operate with distributional assumptions of normality that guide our everyday intuitions.