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Collection: Carnegie Mellon University
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- Abstract: This introductory course in "Modern Biology" covers topics found in the fields of cellular biology, molecular biology, biochemistry, and genetics. It does not cover organismal biology or taxonomy. This course is a requirement for biology majors at Carnegie Mellon University. The course is carefully planned to provide the background biology students will need for advanced biology classes. Non-biology majors will also find this course useful as it explains many of the concepts and techniques currently discussed in the popular press. Plans for a complete on-line Biology course are under development. This Modern Biology course is built around six Key Concepts that provide unifying explanations for how and why structures are formed and processes occur throughout your study of biology. Because it is not possible to cover the breadth of modern molecular biology in one semester, an understanding of these Key Concepts will provide a basis for extension of your knowledge to biological systems beyond the specifics covered in this course. One of the major goals of the course therefore is for you to not only learn the definitions of the concepts but also learn to recognize when they are operating the process being studied. The Key Concepts are: Bioselectivity, Energy, Equilibrium, Ionic State, Rate Control, Solubility.
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- Abstract: Does excessive exposure to violent video games cause violent behavior? Does increased gun availability cause more crime or less? Causal claims permeate everyday life and are constantly the subject of "studies" reported in the newspaper. The material in Causal and Statistical Reasoning examines the nature of causal claims and the statistical sorts of evidence used to support them. The material is contained in: approximately 20 content modules, a repository of over 100 short case studies, and a "Causality Lab" that allows students to simulate the work a social scientist does in trying to discover what causes what from data. The material is meant to be used for three related purposes. One, it is meant for students who will only take one such overview of research methods course in service of consuming the newspaper intelligently and critically. Two, it is meant for students who will take a few statistics courses in order that they have an appropriate qualitative conceptual framework within which to learn statistical ideas, and three, it is meant for students interested in the foundations of quantitative causal models: called Bayes Networks. By adjusting the set of modules, cases, and causality lab exercises covered, professors and students can tailor the experience accordingly. The OLI project teaches annual summer workshops for faculty who are interested in learning how to integrate the material into their courses.
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- Abstract: The Introductory Economics course is a collection of online experiments and related on-line workbooks which can be used by individual learners or to supplement an instructor lead course. In each experiment a student is an active participant attempting to make deals with other traders in a market. After each experiment, the data the students generated is stored and the student will use this data to complete an online workbook. The workbook guides the student through the analysis and much of the economic theory needed to understand the related experiment. In these experiments the student is both a participant and an observer.
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- Abstract: Regression analysis is an enormously popular and powerful tool, used ubiquitously in the social and behavioral sciences. Most courses on the subject immediately dive into the mathematical aspects of the subject and illustrate the technique on problems that are already highly structured. As a result, most students come away with little idea of the wide range of problems to which regression analysis can be applied and how to represent those problems in a way that cleverly utilizes readily available data. Few understand, at a conceptual level, the limitations of regression analysis. The OLI Empirical Research Methods course bridges the gap between the mathematical foundations of regression and its practical application. We teach students how to move from an interesting question about the world to a regression model that, when estimated, meaningfully addresses the question asked. It emphasizes causal analysis as the main research goal and multivariate linear regression as the main statistical tool. We teach a process that involves: Formulating a research problem, Developing and formalizing hypotheses, Collecting data relevant to these hypotheses, Analyzing the data using an appropriate regression model, and Critically interpreting the results of these analyses.
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- Abstract: Statics is a sophomore level engineering course, offered in all mechanical and civil engineering programs. Statics forms the essential pre-requisite to a number of follow-on courses, such as dynamics and mechanics of materials, and lays the foundation for design of mechanical systems. In most institutions, Statics is taught in a traditional way with an emphasis on the mathematical operations that are useful in its implementation, but without enough emphasis on modeling the interactions between real mechanical artifacts. Unfortunately, students who learn Statics in the traditional way do not generally gain the ability to apply concepts of Statics in the analysis and design of mechanical systems and structures which they confront in their subsequent education. Prior to beginning work on the OLI Statics course, the authors undertook the development of a concept inventory for Statics which included identification of key concepts in Statics and the construction of a testing instrument to measure a student's ability to use these concepts in isolation. The authors also combined a variety of instructional techniques known to increase learning - such as active learning, collaboration, integration of assessment and feedback, and use of concrete physical manipulatives - to devise a sequence of learning modules for the Statics classroom. These practical instructional tools, which reflect a more organized, sequential approach to addressing concepts in Statics, have been presented at conferences and described in the engineering education literature. The OLI Statics course implements this sequential, object-centered instructional approach and seeks to address the educational challenge of improving conceptual understanding and fostering improved ability to apply concepts to real mechanical systems.
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- Abstract: French Online is an interactive video-based course intended for use by university students and independent learners on the Internet. The first-semester course is divided into five thematic modules, with three lessons within each module. Each lesson is designed to take approximately one week to complete so working through the entire course will take the average learner approximately fifteen weeks. Each lesson opens with a video dramatization that sets the context for the lesson. Parts of the video are then replayed in a variety of interactive activities and tutors. Each video in the course was written specifically to serve as the foundation for the lesson in which it is used. These high quality videos were produced with French actors on location in France so the speech and movements and contexts are authentic. The beginning of each lesson is always a set sequence, from simple recognition of language in a video dialogue, through explicit learning of grammar and pronunciation, to written and spoken production of variations on that language. After this ordered beginning, a number of activities are offered to the student in which the language learned is used in understanding new texts, sounds or videos or in creative production (conversation or writing).
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- Abstract: Our on-line Chemistry course covers stoichiometry and demonstrates our scenario based approach to teaching chemistry. Traditional courses tend to follow a bottom-up approach to learning chemistry. This traditional approach teaches abstract concepts and tools before discussing their practical application, which results in students learning bits of unconnected knowledge that are rarely usable let alone memorable. In our approach, scenarios are used both to motivate the material and provide a framework in which students can organize their knowledge. In our current OLI chemistry course, stoichiometry is situated in the real world problem of arsenic contamination in Bangladesh's water supply. This learning experience is constructed from the following types of components: Scaffolded homework activities provide students with hints and feedback on an as-needed basis, and fade this help appropriately such that students remain challenged but not floundering. Structured dialogues help students analyze a complex problem, identify an appropriate approach, and build on that approach for a broader understanding of chemistry. Virtual labs couple the mathematics of the course with authentic chemistry experiments, helping students see how their calculations relate to chemistry practice. The Virtual Laboratory is a simulation-based learning environment for aqueous chemistry. It allows students to select from hundreds of standard reagents and manipulate them in a manner that resembles that of a real lab.
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- Abstract: Logic and Proofs is an introduction to modern symbolic logic. It provides a rigorous presentation of the syntax and semantics of sentential and predicate logic. However, the distinctive emphasis is on strategic argumentation. Students learn effective strategies for constructing natural deduction proofs. This learning is supported by the Carnegie Proof Lab: it provides a sophisticated interface, in which students can give arguments by strategically guided forward and backward steps.
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- Abstract: A comparison of an expert human tutor with a real student and Ms. Lindquist's ability to match that closely.
We video-taped a expert teacher for one hour. This page shows that what the expert tutor did is very similar to what "Ms. Lindquist, The Tutor" is able to do.
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- Abstract: The current online Andes Physics course is intended to be used with most physics textbooks. It supplements the textbook by providing problems for students to solve with the aid of Andes, an intelligent tutoring system developed at the University of Pittsburgh and the United States Naval Academy with funding from the Cognitive Science program of the Office of Naval Research. Students solve typical textbook problems just as they would with pencil and paper, by entering vectors, coordinate systems, equations, variable definitions, etc. Students are free to make as many entries as they want in order to solve a problem. After they make each entry, they receive immediate feedback on its correctness. They can also ask why an entry (e.g., an equation) is wrong, and they can request hints on what to do next in order to solve the problem. Their score on a problem can be based mostly on the entries made while deriving the answer, and not just on the answer itself. The Andes Physics course currently provides over 350 problems that are suitable for both calculus and non-calculus introductory physics courses at the college or advanced high school level. For instance, in recent sections of the introductory physics course at the US Naval Academy, 80% of the assigned homework problems during the fall Mechanics course were done on Andes, and 50% of the assigned homework problems during the spring Electricity and Magnetism course were done on Andes. More problems are being added to Andes with each release.
(Complete Item Description)
- Abstract: This course introduces students to the basic concepts, logic, and issues involved in statistical reasoning. Major topics include exploratory data analysis, an introduction to research methods, probability, and statistical inference. The objectives of this course are to give students confidence in manipulating and drawing conclusions from data and provide them with a critical framework for evaluating study designs and results. An important feature of the course is the use of an intelligent tutoring system developed at Carnegie Mellon called "StatTutor." StatTutor aims to facilitate understanding of statistical ideas and analytical techniques by helping students construct useful knowledge representations and thereby develop effective problem-solving skills. It uses a specified outline of steps to follow in solving problems, or "scaffolding". StatTutor will use scaffolding and immediate feedback flexibly, tracking and responding to individual students as they navigate the learning environment.
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