Patricia E. Simmons

Expert and "novice" subjects’ approaches to genetic problem solving in a computer-based setting

A small group of subjects differing in levels of expertise in genetics undertook a problem-solving task in a computer-based setting. Transcripts of ‘think-aloud’ protocols were obtained. Data revealed contrasts between expert and novice subjects in their approaches to the problem, and differences both in inferred understanding of genetic concepts and procedural knowledge. Experts carried out prior planning by identifying suitable strategies; they displayed well developed content knowledge, and appropriate use of procedures in which sequences of procedures were grouped into single productions. In contrast, novices showed poor planning, used a ‘try-it-and-see’ approach to selection of crosses, and confused some basic concepts. Problem tasks of the type identified in this study complement other learning experiences, and have the potential to assist learners to enhance their understanding of genetic concepts.

A research method using microcomputers to assess conceptual understanding and problem solving

Important goals in science education include the elucidation of how students develop a world view, reason about new information, and solve problems. This paper focuses on a research strategy using microcomputers that is directed towards elucidating conceptual understanding and problem solving strategies used by subjects interacting with an open-ended genetics simulation. The field method employed in this study is termed “structured observations”. The use of this method facilitated the generation of data during problem solving sessions by subjects in a think aloud protocol. Three sets of synchronized information of subjects’ interactions with the software were obtained: a video image which provided the sequence and duration of computer screen displays, a video image of subjects, and an audio track of verbal commentaries. The verbal protocol data, complemented by synchronized visual data, were analyzed using software tools for qualitative analysis. The use of these kinds of software programs aided researchers in the analysis of complex, qualitative data. The data were subjected to codings as text files, searches for patterns, and retrievals of patterns among coded variables. Frequency tables of the codes and patterns were generated for further interpretation. By these means, patterns of operations can be identified and inferences made about problem solvers’ conceptual understanding.