A survey of pre/post-test data using the Halloun–Hestenes Mechanics Diagnostic test or more recent Force Concept Inventory is reported for 62 introductory physics courses enrolling a total number of students N=6542. A consistent analysis over diverse student populations in high schools, colleges, and universities is obtained if a rough measure of the average effectiveness of a course in promoting conceptual understanding is taken to be the average normalized gain 〈g〉. The latter is defined as the ratio of the actual average gain (%〈post〉−%〈pre〉) to the maximum possible average gain (100−%〈pre〉). Fourteen “traditional” (T) courses (N=2084) which made little or no use of interactive-engagement (IE) methods achieved an average gain 〈g〉T-ave=0.23±0.04 (std dev). In sharp contrast, 48 courses (N=4458) which made substantial use of IE methods achieved an average gain 〈g〉IE-ave=0.48±0.14 (std dev), almost two standard deviations of 〈g〉IE-ave above that of the traditional courses. Results for 30 (N=3259) of the a...

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Interactive-engagement versus traditional methods: A six-thousand-student survey of mechanics test data for introductory physics courses

Conceptual change models of student learning are useful for explicating the role of prior knowledge in students’ learning and are very popular in the research on learning in the subject areas. This article presents an analysis of a conceptual change model for describing student learning by applying research on student motivation to the process of conceptual change. Four general motivational constructs (goals, values, self-efficacy, and control beliefs) are suggested as potential mediators of the process of conceptual change. In addition, there is a discussion of the role of classroom contextual factors as moderators of the relations between student motivation and conceptual change. The article highlights the theoretical difficulties of a cold, or overly rational, model of conceptual change that focuses only on student cognition without considering the ways in which students’ motivational beliefs about themselves as learners and the roles of individuals in a classroom learning community can facilitate or h...

Beyond Cold Conceptual Change: The Role of Motivational Beliefs and Classroom Contextual Factors in the Process of Conceptual Change

Understanding how science students respond to anomalous data is essential to understanding knowledge acquisition in science classrooms. This article presents a detailed analysis of the ways in which scientists and science students respond to such data. We postulate that there are seven distinct forms of response to anomalous data, only one of which is to accept the data and change theories. The other six responses involve discounting the data in various ways in order to protect the preinstructional theory. We analyze the factors that influence which of these seven forms of response a scientist or student will choose, giving special attention to the factors that make theory change more likely. Finally, we discuss the implications of our framework for science instruction.

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The Role of Anomalous Data in Knowledge Acquisition: A Theoretical Framework and Implications for Science Instruction

Inquiry experiences can provide valuable opportunities for students to improve their understanding of both science content and scientific practices. However, the implementation of inquiry learning in classrooms presents a number of significant challenges. We have been exploring these challenges through a program of research on the use of scientific visualization technologies to support inquiry-based learning in the geosciences. In this article, we describe 5 significant challenges to implementing inquiry-based learning and present strategies for addressing them through the design of technology and curriculum. We present a design history covering 4 generations of software and curriculum to show how these challenges arise in classrooms and how the design strategies respond to them.

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Addressing the Challenges of Inquiry-Based Learning Through Technology and Curriculum Design

Self-regulated learning: a new concept embraced by researchers, policy makers, educators, teachers, and students

An analysis and comparison of everyday life and the domain of science reveals significant differences in their goals and in the cognitive means used to attain these goals. Students' lack of awareness of these differences can lead to pervasive learning difficulties in their study of science. Thus many students (a) have erroneous conceptions of scientific goals, (b) import goals and ways of thinking which are effective in everyday life but inadequate in science, and (c) devise ways of thinking ill suited to science. Additional complications arise because science taught in schools often differs both from actual science and from everyday life. Students' learning difficulties are thus increased because scientific goals are distorted and scientific ways of thinking are inadequately taught. The preceding analysis suggests some empirical investigations and instructional improvements.

Cognition in Scientific and Everyday Domains: Comparison and Learning Implications.

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.

https://www.jstor.org/stable/pdfplus/40186365.pdf

Understanding and teaching important scientific thought processes

Our attempts to improve physics instruction have led us to analyze thought processes needed to apply scientific principles to problems—and to recognize that reliable performance requires the basic cognitive functions of deciding, implementing, and assessing. Using a reciprocal-teaching strategy to teach such thought processes explicitly, we have developed computer programs called PALs (P_ersonal A_ssistants for L_earning) in which computers and students alternately coach each other. These computer-implemented tutorials make it practically feasible to provide students with individual guidance and feedback ordinarily unavailable in most courses. We constructed PALs specifically designed to teach the application of Newton’s laws. In a comparative experimental study these computer tutorials were found to be nearly as effective as individual tutoring by expert teachers—and considerably more effective than the instruction provided in a well-taught physics class. Furthermore, almost all of the students using the PALs perceived them as very helpful to their learning. These results suggest that the proposed instructional approach could fruitfully be extended to improve instruction in various practically realistic contexts.

Teaching Scientific Thinking Skills: Students and Computers Coaching Each Other

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

http://www.skbhavnani.com/DIVA/papers/Bhavnani_et_al-CHI-2001.pdf

Frederick Reif

Papers

Cognition in Scientific and Everyday Domains: Comparison and Learning Implications.

Understanding and teaching important scientific thought processes

Teaching Scientific Thinking Skills: Students and Computers Coaching Each Other

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

Analysis and Teaching of a General Skill For Studying Scientific Text.