The Structure and Use of Biological Knowledge about Mammals in Novice and Experienced Students

This study explored differences in the way novice and experienced students organize and use biological knowledge within the domain of mammals. Subjects were enrolled in a college-level, introductory biology course for nonscience majors (n=25) and an advanced course in mammalogy intended for upper-division and graduate-level students (n=25). Each subject constructed a concept map and then participated in a clinical interview, during which an exhaustive set of descriptive propositions about 20 mammals depicted in line drawings was generated. Subjects subsequently sorted the mammals into homogeneous groups. Results of concept mapping reveal that experienced students possess a substantially more extensive, complex, and integrated knowledge base characterized by significantly greater numbers of concepts, relationships, levels of hierarchy, branchings, and crosslinks. Results of clinical interviews and sorting task demonstrate that these differences are linked to the emergence of a new repertoire of implicit, superordinate concepts which orders students' understandings, the enhanced use of inferential reasoning strategies, and the development of a scientifically acceptable system of assigning class membership.

[1]  M. Chi,et al.  The Nature of Expertise , 1988 .

[2]  V. Patel,et al.  The relationship between comprehension and reasoning in medical expertise. , 1988 .

[3]  M. Chi.  Knowledge structures and memory development. , 1978 .

[4]  Mike U. Smith.  Knowledge Structures and the Nature of Expertise in Classical Genetics , 1990 .

[5]  Penny Rheingans,et al.  Visualizing structure in high-dimensional multivariate data , 1991, IBM J. Res. Dev..

[6]  H. Simon,et al.  Perception in chess , 1973 .

[7]  J. Mintzes,et al.  Students' Alternative Conceptions of Animals and Animal Classification. , 1985 .

[8]  H. Simon,et al.  Skill in Chess , 1988 .

[9]  Joel J. Mintzes,et al.  Children's Biology: A Review of Research on Conceptual Development in the Life Sciences. , 1984 .

[10]  M. Chi,et al.  Network representation of a child's dinosaur knowledge. , 1983 .

[11]  Mike U. Smith.  Successful and unsuccessful problem solving in classical genetic pedigrees , 1988 .

[12]  D. Gentner.  Expertise in Typewriting. , 1984 .

[13]  Joel J. Mintzes,et al.  Students' alternative conceptions of the human circulatory system: A cross-age study , 1985 .

[14]  Kate Ehrlich,et al.  Knowledge and processes in the comprehension of computer programs. , 1988 .

[15]  Allan Collins,et al.  A spreading-activation theory of semantic processing , 1975 .

[16]  Dorothea P. Simon,et al.  Expert and Novice Performance in Solving Physics Problems , 1980, Science.

[17]  R. E. Martin,et al.  A Manual of Mammalogy: With Keys to Families of the World , 2011 .

[18]  J. Mintzes,et al.  Alternative conceptions in animal classification: A cross‐age study , 1988 .

[19]  Ian M. Kinchin,et al.  Concept mapping in biology , 2000 .

[20]  Joseph D. Novak,et al.  Learning How to Learn , 1984 .

[21]  Michelene T. H. Chi,et al.  How knowledge is structured and used by expert and novice children , 1986 .

[22]  Mary W. Arnaudin,et al.  Biology from the Learner's Viewpoint: A Content Analysis of the Research Literature. , 1989 .

[23]  Mike U. Smith.  Expertise and the organization of knowledge: Unexpected differences among genetic counselors, faculty, and students on problem categorization tasks , 1992 .