Frederick Reif

Understanding and teaching important scientific thought processes

This article analyzes the cognitive processes and kinds of knowledge needed to work in a scientific domain like physics. In particular, it discusses the processes needed to interpret properly scientific concepts and principles, complementary uses of quantitative and qualitative descriptions, useful hierarchical ways of organizing scientific knowledge, and description and decision processes facilitating effective problem solving. The importance of these processes is illustrated by some experimental evidence and by specific instructional implications. It has been possible to design a physics course where these thought processes are explicitly taught and where students learning is correspondingly improved. However, there remain practical implementation problems—particularly students naive conceptions about the nature of science and the very limited amount of individual guidance and feedback that students receive in ordinary classroom situations.

Beyond command knowledge: identifying and teaching strategic knowledge for using complex computer applications

Despite experience, many users do not make efficient use of complex computer applications. We argue that this is caused by a lack of strategic knowledge that is difficult to acquire just by knowing how to use commands. To address this problem, we present efficient and general strategies for using computer applications, and identify the components of strategic knowledge required to use them. We propose a framework for teaching strategic knowledge, and show how we implemented it in a course for freshman students. In a controlled study, we compared our approach to the traditional approach of just teaching commands. The results show that efficient and general strategies can in fact be taught to students of diverse backgrounds in a limited time without harming command knowledge. The experiment also pinpointed those strategies that can be automatically learned just from learning commands, and those that require more practice than we provided. These results are important to universities and companies that wish to foster more efficient use of complex computer applications.

Strategy-Based Instruction: Lessons Learned in Teaching the Effective and Efficient Use of Computer Applications

Numerous studies have shown that many users do not acquire the knowledge necessary for the effective and efficient use of computer applications such as spreadsheets and Web-authoring tools. While many cognitive, cultural, and social reasons have been offered to explain this phenomenon, there have been few systematic attempts to address it. This article describes how we identified a framework to organize effective and efficient strategies to use computer applications and used an approach called strategy-based instruction to teach those strategies over five years to almost 400 students. Controlled experiments demonstrated that the instructional approach (1) enables students to learn strategies without harming command knowledge, (2) benefits students from technical and nontechnical majors, and (3) is robust across different instructional contexts and new applications. Real-world classroom experience of teaching strategy-based instruction over several instantiations has enabled the approach to be disseminated to other universities. The lessons learned throughout the process of design, implementation, evaluation, and dissemination should allow teaching a large number of users in many organizations to rapidly acquire the strategic knowledge to make more effective and efficient use of computer applications.

How can we help students acquire effectively usable physics knowledge

What are essential requirements enabling flexible use of acquired scientific knowledge? Cognitive considerations indicate that these requirements include the following: (a) Methods for interpreting properly scientific concepts or principles, and methods for making the judicious decisions needed for problem solving; (b) forms of knowledge description and organization facilitating inferences and search; and (c) active student processing needed for learning, with adequate individual guidance and feedback ensuring that such processing is effectively carried out. The preceding requirements are often inadequately heeded in prevailing physics instruction, but could be addressed by some suggested instructional approaches. Centrally important cognitive functions (deciding, implementing, and assessing) might also be explicitly taught by exploiting the instructional strategy of “reciprocal teaching” and using computers to implement it in practice.

El conocimiento científico y el cotidiano: comparación e implicaciones para el aprendizaje

La ciencia que se ensena en la escuela suele ser muy distinta de la ciencia real. Tambien de los conocimientos correspondientes empleados en la vida cotidiana. Partiendo de tan desalentadora situacion, el autor propone alternativas practicas para cambiarla, llevando a la conciencia del estudiante esas distintas caracteristicas en los objetivos y medios cognitivos de cada una de estas «tres ciencias».

Better instruction with lower costs: Some practical suggestions

We discuss some general guidelines and practical suggestions for systematically allocating limited resources so as to improve instruction, lower its costs, or both. Our main guideline consists of separating goals and assigning to each those resources which serve it best. We apply this procedure to selecting instructional goals, to dividing labor between human instructors and instructional materials (e.g., printed booklets, audio tapes), and to assessing student achievement. Our own experience with both PSI and conventional physics courses provides illustrations for these comments, which are generally applicable to both innovative and traditional course formats.

Physically important integrals without calculus

Many physically important spatial integrals, such as those needed for finding electric or magnetic fields, can be calculated by a simple method based on elementary geometry, without the need to use the techniques of the calculus or advanced theorems (such as Gauss’s or Ampere’s laws). The method is practically useful, can provide physical insights, and is suitable for mathematically unsophisticated students in introductory courses. We explain this method by applying it to calculate the electric fields due to a uniformly charged plane, line, and spherical surface.