Problem-Based Approach for Bioinformatics
Chu, Yen-Wei, Sun, Chuen-Tsai, International Journal of Instructional Media
The human genome project has attracted a large number of information science researchers to work in the area of bioinformatics. Of particular interest to these researchers is the development and refinement of algorithms for culling meaningful information from large bodies of data. However, information science experts have little understanding of biology, and only a handful of biologists understand information algorithm requirements.
In this paper, we will propose a problem-based learning approach that makes use of concept maps for bioinformatics learning. Our goals are to a) create a process through which information specialists can easily identify the core issues of biology problems, and b) reduce research costs associated with applying information theory to biology problems.
In 1989, the U.S. National Institutes of Health invited James D. Watson-best known for describing the double-helix structure of DNA-to establish a human genome research center. The guiding objective for researchers from the United States and 17 other countries has been to identify over 3 billion DNA sequences that make up the human genetic code. The project has generated an enormous amount of data that needs to be organized and analyzed. This has lead to an explosion in research in the field of bioinformatics, which combines the domains of information science and biology. Communication among researchers in the two fields is critical to achieving research success.
Problem-based learning-an idea that originated in medical education in the 1960s-is learner-centered rather than instructor-centered (LaPlaca et al., 2001; Maskell & Grabau, 1998; Ronteltap & Eurelings, 2002; Soderberg, 2003). It is considered not only a curriculum organizing method, but also an instructional strategy and learning process for dealing with poorly structured real world problems (Barrows & Kelson, 1998; Trop & Sage, 1998). According to Wegner et al. (1998), the process involves a) defining the problem, b) determining whether information is lacking, c) collecting and categorizing related information, d) identifying content and learning targets, e) examining methods for solving the problem, and f) finding optimal solutions.
Learners must train themselves in problem solving and communication skills in order to manage and apply learning information (Illinois Mathematics and Science Academy, 2004). Instructors are viewed as partners, consultants, advisors, or trainers.
Novak (1972, 1990) used the meaningful learning theory of American cognitive psychologist David Ausubel to establish a concept map instructional strategy. The method emphasizes the integration of old and new concepts into newer concept skeletons.
The five categories of bioinformatics applications are a) establishing and integrating databases, b) analyzing sequences, c) analyzing structure and function, d) analyzing experimental data, and e) managing knowledge (Academia Sinica Computing Center, 2003). Bioinformatics knowledge has four properties: a) a database for storing raw or processed data from a biology experiment, b) a simulation that embodies molecules for easy observation and analysis, c) one or more tools for solving specific problems, and d) a package in which related tools are integrated.
The primary goal of a problem-based learning approach is actively transmitting information in a manner that encourages knowledge construction. It is an approach that is well suited to teaching scientific principles and properties (Gallagher et al., 1995). Learners construct meaningful knowledge on their own. Cognition helps in terms of adaptability-the integration of new data with previous experiences instead of the discovery of specific entities. In other words, individuals build knowledge through an adaptation process (Lennan, 1989; vonglasersfeld, 1989). …