C. M. Crowe

Bio: C. M. Crowe is an academic researcher from McMaster University. The author has contributed to research in topics: Higher education & Statistical hypothesis testing. The author has an hindex of 20, co-authored 44 publications receiving 2122 citations. Previous affiliations of C. M. Crowe include McMaster-Carr & University of Sydney.

Developing Problem Solving Skills: The McMaster Problem Solving Program

Abstract: This paper describes a 25-year project in which we defined problem solving, identified effective methods for developing students' skill in problem solving, implemented a series of four required courses to develop the skill, and evaluated the effectiveness of the program. Four research projects are summarized in which we identified which teaching methods failed to develop problem solving skill and which methods were successful in developing the skills. We found that students need both comprehension of Chemical Engineering and what we call general problem solving skill to solve problems successfully. We identified 37 general problem solving skills. We use 120 hours of workshops spread over four required courses to develop the skills. Each skill is built (using content-independent activities), bridged (to apply the skill in the content-specific domain of Chemical Engineering) and extended (to use the skill in other contexts and contents and in everyday life). The tests and examinations of process skills, TEPS, that assess the degree to which the students can apply the skills are described. We illustrate how self-assessment was used.

A geometric approach to steady flow reactors: the attainable region and optimization in concentration space

Abstract: Probleme du choix optimal du systeme de reacteurs en ecoulement permanent pour une serie de reactions ayant chacune une cinetique donnee. On s'interesse aux systemes isothermes sans changement de volume sur la reaction et le melange. On ne peut pas combiner ensemble les reacteurs parfaitement agites, les reacteurs piston ou les reacteurs a recyclage pour etendre la region accessible. On examine plusieurs exemples a deux dimensions

Reconciliation of process flow rates by matrix projection. Part II: The nonlinear case

Abstract: Flow rate measurements in a steady-state process are reconciled by weighted least squares so that the conservation laws are obeyed. A projection matrix is constructed which can be used to decompose the linear problem into the solution of two subproblems, by first removing each balance around process units with an unmeasured component flow rate. The remaining measured flow rates are reconciled, and the unmeasured flow rates can then be obtained from the solution of the conservation equations. The basic case contains constraints which are linear in the component and the total flow rates. The method is extended to cases with bilinear constraints, involving unknown parameters such as split fractions. Chi-square and normal statistics are used to test for overall gross measurement errors, for gross error in each node imbalance which is fully measured, and for each measurement adjustment.

Detection of gross erros in data reconciliation by principal component analysis

Abstract: Statistical testing prouides a tool for engineers and operators to judge the validity of process measurements and data reconciliation. Uniuariate, maximum power and chisquare tests haue been widely used for this purpose. Their perJormance, however, has not always been satisfactory. A new class of test statistics for detection and identification of gross errors is presented based on principal component analysis and is compared to the other statistics. It is shown that the new test is capable of detecting gross errors of small magnitudes and has substantial power to correctly identify the uariables in error, when the other tests fail.

Inductive Teaching and Learning Methods: Definitions, Comparisons, and Research Bases

Abstract: Traditional engineering instruction is deductive, beginning with theories and progressing to the applications of those theories Alternative teaching approaches are more inductive Topics are introduced by presenting specific observations, case studies or problems, and theories are taught or the students are helped to discover them only after the need to know them has been established This study reviews several of the most commonly used inductive teaching methods, including inquiry learning, problem-based learning, project-based learning, case-based teaching, discovery learning, and just-in-time teaching The paper defines each method, highlights commonalities and specific differences, and reviews research on the effectiveness of the methods While the strength of the evidence varies from one method to another, inductive methods are consistently found to be at least equal to, and in general more effective than, traditional deductive methods for achieving a broad range of learning outcomes

Toward a design theory of problem solving

Abstract: Problem solving is generally regarded as the most important cognitive activity in everyday and professional contexts. Most people are required to and rewarded for solving problems. However, learning to solve problems is too seldom required in formal educational settings, in part, because our understanding of its processes is limited. Instructional-design research and theory has devoted too little attention to the study of problem-solving processes. In this article, I describe differences among problems in terms of their structuredness, domain specificity (abstractness), and complexity. Then, I briefly describe a variety of individual differences (factors internal to the problem solver) that affect problem solving. Finally, I articulate a typology of problems, each type of which engages different cognitive, affective, and conative processes and therefore necessitates different instructional support. The purpose of this paper is to propose a metatheory of problem solving in order to initiate dialogue and research rather than offering a definitive answer regarding its processes.

Understanding Student Differences

Abstract: Students have different levels of motivation, different attitudes about teaching and learning, and different responses to specific classroom environments and instructional practices. The more thoroughly instructors understand the differences, the better chance they have of meeting the diverse learning needs of all of their students. Three categories of diversity that have been shown to have important implications for teaching and learning are differences in students' learning styles (characteristic ways of taking in and processing information), approaches to learning (surface, deep, and strategic), and intellectual development levels (attitudes about the nature of knowledge and how it should be acquired and evaluated). This article reviews models that have been developed for each of these categories, outlines their pedagogical implications, and suggests areas for further study.

Inductive Teaching and Learning Methods: Definitions, Comparisons, and Research Bases

Abstract: Traditional engineering instruction is deductive, beginning with theories and progressing to the applications of those theories. Alternative teaching approaches are more inductive. Topics are introduced by presenting specific observations, case studies or problems, and theories are taught or the students are helped to discover them only after the need to know them has been established. This study reviews several of the most commonly used inductive teaching methods, including inquiry learning, problem-based learning, project-based learning, case-based teaching, discovery learning, and just-in-time teaching. The paper defines each method, highlights commonalities and specific differences, and reviews research on the effectiveness of the methods. While the strength of the evidence varies from one method to another, inductive methods are consistently found to be at least equal to, and in general more effective than, traditional deductive methods for achieving a broad range of learning outcomes.