Assessing conceptual knowledge using similarity judgments

This study evaluates the validity of a similarity judgments test (SJT) for assessing conceptual knowledge. 89 high school seniors judged the semantic similarity of a set of concepts. The resulting scores are calculated using a correlational approach as well as the MDS and Pathfinder approaches, respectively. The validity of the SJT is estimated by comparing (a) the scores with the test scores resulting from a multiple-choice test, (b) the scores resulting from pre- and post-instruction, and (c) the scores of students with high vs. low expertise. Our results support the validity of the SJT and show that both the correlational and the Pathfinder approach outclass the MDS approach. Recommendations to evaluate the SJT are provided.     

How strongly does statistical reasoning influence knowledge and acceptance of evolution?

A large body of research has examined students' conceptions of evolution and their relationships to acceptance of evolution. Proficiency in statistical and probabilistic reasoning has long been considered to be an essential feature of evolutionary reasoning, yet almost no empirical work has explored these putative connections. The RaPro instruments have recently been developed to measure statistical reasoning in the contexts of mathematics (RaProMath) and evolution (RaProEvo). Our study provides additional validation of these instruments using Rasch analysis and quantifies the contribution of statistical reasoning to both understanding and accepting evolution. We recruited a large sample (N = 564) of undergraduate students enrolled in an introductory biology course at a large public research university in the United States. Students completed a suite of published instruments that assessed statistical reasoning, evolutionary understanding, and evolutionary acceptance. Our findings indicate that validity inferences derived from RaPro scores generalized to the new sample, and that proficiency in statistical reasoning explained 28% of the variance in evolutionary knowledge and 19% of the variation in evolutionary acceptance. The inclusion of demographic variables into the model significantly increased the explained variance in acceptance. Notably, the variance in evolution acceptance explained by statistical reasoning was comparable to that of thinking dispositions or evolutionary knowledge reported in the literature. This work provides the first large-scale evidence of the role of statistical reasoning in evolutionary knowledge and acceptance and motivates future work to explore how statistical literacy should be integrated into evolution education efforts.     

How effective is instructional support for learning with computer simulations?

The study examined the effects of two different instructional interventions as support for scientific discovery learning using computer simulations. In two well-known categories of difficulty, data interpretation and self-regulation, instructional interventions for learning with computer simulations on the topic “ecosystem water” were developed and tested using a sample of 124 eighth graders in science classes. The results demonstrate the effectiveness of instructional support for domain-specific factual, conceptual, and procedural knowledge acquisition. Students who received either only instructional support for data interpretation or only for self-regulation achieved the highest learning outcomes. However, a combination of instructional support for data interpretation and self-regulation seemed detrimental for knowledge acquisition. Students who received instructional interventions for both data interpretation and self-regulation also showed the highest values of perceived cognitive load. High cognitive load could be a reason for why a combination of particular instructional interventions does not lead to the expected positive learning outcomes.     

The Impact of Network Size and Financial Incentives on Adoption and Participation in New Online Communities

The success of online communities depends heavily on the providers' abilities to motivate potential users to adopt the service and to actively participate. Because research in this field of media economics is rare, especially with regard to newly established communities, this study analyzes what drives community adoption and how direct and indirect financial incentives influence user participation. Extending Ajzen's (1991) Theory of Planned Behavior, this article shows, in 2 empirical studies, that network size significantly affects adoption in newly established communities. The results of the first study indicate a strong effect of indirect financial incentives (saving money) on the intention to adopt. The second study indicates that direct financial incentives (earning money) may well help increase the network's size without altering user motivation through crowding-out effects. It is interesting to note that the presence of direct financial incentives attracts new users, but it does not increase usage.     

PUBLIC ATTITUDES TOWARD DATA SHARING BY FEDERAL AGENCIES

Because of the high cost of the 1990 census and the continuedundercoverage of some population subgroups, it has been suggestedthat administrative records be used to supplement or replaceconventional census-taking activities. Very little informationexists concerning public knowledge and attitudes on this topic.The most extensive information to date comes from questionsasked on several IRS surveys of taxpayers. In late 1993 an opportunitypresented itself to add a small number of questions about datasharing to national telephone surveys conducted by the WisconsinLetters and Sciences Survey Center. Here we report on an analysisof these data.     

Creativity,Complexity and Self‐similarity: The Vision of the Fractal University

Creativity and communication processes in engineering education have become more and more necessary in highly complex structures such as technological networks and ‘virtual’ reality. These issues also include an educational challenge for university: all education for the future has to be based on experiencing reality. A new socio‐technical approach describes the engineering profession in all aspects beside technology, such as tasks, views, organizational structures or cooperation. Therefore, university and higher education have to change into self‐similar structures to support the learning of complexity in real life. The experiences of the Department of Computer Science in Mechanical Engineering at the University of Technology in Aachen, as a socio‐technical, self‐similar and creative system, show such learning processes of students (and staff) in undergraduate education, research and organizational structures.