Machine learning (ML) has become commonplace in educational research and science education research, especially to support assessment efforts. Such applications of machine learning have shown their promise in replicating and scaling human-driven codes of students' work. Despite this promise, we and other scholars argue that machine learning has…

Outlines a narrative method for the study of classrooms. The main feature of the method is the reconstruction of classroom meaning in terms of narrative unities in the lives of classroom participants. The work's theoretical character is introduced by comparison and contrast with Schon's "The Reflective Practitioner: How Professionals Think in…

Describes an introductory astronomy course for undergraduate students in which students use three-dimensional (3-D) modeling tools to model the solar system and develop rich understandings of astronomical phenomena. Indicates that 3-D modeling can be used effectively in regular undergraduate university courses as a tool to develop understandings…

Applies Kuhn's model of the structure of scientific revolutions, Popper's hypothetic-deductive model of science, and Lakatos' methodology of competing research programs to a historical biological episode. Suggests using Kuhn's model (emphasizing the nonrational basis of science) and Popper's model (emphasizing the rational basis of science) in…

Examines alternative evaluation models to expand the concept of process-product research in teaching training program evaluation. Figures represent these models discussed in the text: an education process-product research model, a conventional process-product teaching training program assessment model, and an expansion of that model. (CS)

A model of memory developed by information processing psychologists is described, illustrating how such a model could be used to guide science education research on learning and problem solving. (Author/SK)

Discusses a mathematical model for mastery learning. The model includes measures of a motivational factor and the specific ability of a learner with respect to content being learned. The model also contains a variable reflecting prior learning. Assumptions/limitations are discussed, and research questions raised. (Author/JN)

Discusses the science education research agenda from the viewpoints of learning theorists, political and social scientists, counseling psychologists, cognition psychologists, and pedagogical researchers. Indicates that a broader perspective of these areas helps to link the research agenda to science teachers' questions/concerns, and to such areas…

A model to illuminate and relate various twentieth-century philosophical perspectives on key questions about the nature of scientific theories and, therefore, aspects of the structure and development of postmodern science is described. The Scientific Theory Profile model then forms the basis for a course for science teachers in perspectives on the…

Speculates that physiological changes resulting from repeated, long-term stimulation in human and laboratory animal brains are related to short- and long-term memory processes. Describes a physiological-based model which may explain many current learning theory principles and can serve as a foundation for developing new learning theories based on…

Defines artificial intelligence (AI) in relation to intelligent computer-assisted instruction (ICAI) and science education. Provides a brief background of AI work, examples of expert systems, examples of ICAI work, and addresses problems facing AI workers that have implications for science education. Proposes a revised model of the Karplus/Renner…

Uses two studies to examine developmental and task effects in estimation problems. Results are discussed in terms of student and task characteristics and the implications of such variables on information processing model of learning. Implications for science teaching, learning problem diagnostics, and science curricula are also discussed. (TW)