Gabriele Wienhausen

Research

Our research is focused on (1) how to promote "meaningful learning" in college science teaching, i.e., how to assure that students store more information in a memorable, readily usable fashion, and (2) how to facilitate the development of effective problem solving skills. Specifically, we investigate what role interactive, computer-based multimedia packages can play and how effective they are as a tool to facilitate the understanding of complex biological/scientific processes and concepts. We study the impact of a systematic, computer-based representation of a scientific topic on a student's learning and recall of that topic.

To accomplish our goals, we develop multimedia modules which are being used as tools to improve science teaching in the laboratory setting and to integrate the process of scientific research and education. These modules have been designed on the premise that a deep understanding of biological and biomedical systems and processes depends on a meaningful inclusion of related knowledge from all the sciences. Our innovative methods of instruction address the dramatic changes in the pace of scientific learning exemplified in areas such as molecular biology or structural biochemistry. Scientific results are superseded quickly, and it is mandatory that students are familiarized with the know-how of information acquisition and its effective use. Students are taught that concepts and knowledge have to be applied across scientific disciplines. A key thesis of our research is that interactive, computer-based multimedia packages provide a potent vehicle for addressing many of the previously listed problems. We believe that the flexibility of multimedia, computer-based instructional systems allows for the provision of information in a way that more closely resembles the way research scientists think and acquire new knowledge; typically, both intellectual processes occur in a non-linear, interdisciplinary fashion where new pieces of information are fitted into an existing framework of knowledge.

For instance, in the software module titled "Spectrophoto-metry", students can explore the interaction of light and matter, follow the mathematical derivation of Beer's Law, and practice the operating of a UV-visible virtual spectrophotometer using an on-screen working model. At all times, students using the software are in control of the pace and the path. They determine the extent of interactivity, they determine the direction, and depth of their learning path.