Department: Interdisciplinary Studies
Course: IDS233 Computers in the Sciences
Semester and Year: Spring, 2013
Time and Location: 9:00 A.M. Wednesday & Friday, Krehbiel Science Center Room 121Laboratory: 4:00-6:00 p.m. or 7:00-9:00 p.m. Tuesday, Will Academic Center Room 101
Instructor: Dwight Krehbiel
Location and Hours: Krehbiel Science
Center Room 105; Office hrs: 4:00 - 5:00 p.m. MWF, 9:00 - 11:00 a.m. and 1:00 - 4:00 p.m.Tuesday
Course Description: Primary emphasis is on learning to use software for searching and storing scientific literature and other resources, data acquisition, data graphics, scientific presentation, and modelling. Software introduced here is employed in a variety of other courses. All of us have been using some these methods, but in this course we will attempt to develop a level of knowledge and skill that will support our routine everyday use of these computing resources.
Objectives: Numerous excellent resources for scientific research and for science education are now available on the World Wide Web. The National Science Digital Library (NSDL) is a very large and rapidly growing repository of these resources, which we will learn to use. Scholarly journals are now usually published on the Web, and an important subset of these are freely available to anyone with a Web browser, a movement known as "open access." We will learn about the open access movement and develop skills for finding the open access scientific literature that is relevant to our interests. We will also learn to create our own collections of these resources and create properly formatted bibliographies using software called Zotero. The open access movement will also naturally lead us to a discussion of the open source software movement, which has given birth to many of the software packages we will use, such as R, Firefox, Moodle, Mahara, Zotero, and Scribus.
Data analysis usually involves statistical procedures and graphical displays. A widely used general-purpose data-analysis tool is the programming environment called R, along with various add-on packages, such as R Commander. We will study some of the basic statistical procedures available in this software but will concentrate our efforts on its use for creating graphs, both to analyze and to display our data.
Techniques for gathering data vary widely among disciplines, but the computer is used in many of them. Data collection in the natural sciences often involves the measurement of an electrical voltage signal or the detection of a dichotomous (digital) signal. These measurements can be readily accomplished by means of a computer equipped with an interface device, usually a USB port. Programming these measurements in a wide variety of situations, from the electrical signals generated by the human brain to those generated by a physical instrument, can be done in a package called LabVIEW, even by persons without computer programming experience. One can also use LabVIEW to implement questionnaires in the social sciences. We will be learning some of the basics of programming in LabVIEW as well as how to run experiments that others have programmed using LabVIEW.
Modeling is a process of trying to construct a system that behaves in a fashion similar to that of the phenomena we are studying. In constructing such a system we begin to understand and explain the phenomena. Models range from very informal intuitions to highly precise mathematical theories. Precise models are always sought after since they make specific, testable predictions. However, it is often difficult to attain such precision, either because we have not learned the necessary mathematics or because the phenomena in question are not very mathematically tractable. NetLogo and Vensim will allow us to turn even our informal intuitions into precise models. We will use these methods to explore existing models and create some of our own.
Presentation of scientific findings may involve poster or oral presentations, the latter usually complemented by computer-based visual aids, in addition to written reports. The issues involved in such presentations will be discussed, and the page-layout software package Scribus will be introduced for poster creation.
We will try to gain some independence from particular computer operating systems so as to become more flexible computer users, capable of adapting to a variety of teaching, learning, and work environments. Thus, while we may most often be working in some flavor of the Windows operating system, we will also gain familiarity with other operating systems -- Linux, and MacOS X. We will learn to transfer data from one computing package to another and to pay close attention to file formats. We will also devote some time to the scientific uses of standard office software (word processors, spreadsheet programs, and presentation software).
It is hoped that through this course students will master these various tools in order to use them competently in advanced courses and to understand how students from other disciplines are using them. Students from different disciplines may even find it interesting to collaborate on individual research projects using these tools.
Robbins, N. (2005). Creating more effective graphs. New York: Wiley.
Course Requirements. There will be 2 hours of lecture and 2 hours of laboratory per week. The weekly lectures will be designed to introduce students to topics and procedures that will be conducted in the laboratory and to explore some related issues in scientific computing. There will be some assigned readings in addition to those in the required text; these assignments will be made well in advance of the session when these readings are to be discussed. It is assumed that students will take careful notes over lectures and discussions; students cannot expect to perform well on quizzes and examinations without such notes.
A rough schedule of the various topics to be studied is shown below:
Zotero, open access, NSDL, open source software
Weeks 4-8 (week of Feb. 18) R
Weeks 9-11 (week of Apr. 1) LabVIEW
Weeks 12-15 (week of Apr. 29) NetLogo and Vensim
We will be studying examples from different disciplines as we learn to use this software. You should expect periodic quizzes over the material covered in lectures and laboratories. A midterm examination is scheduled for the week of March 11.
Attendance at all lecture and laboratory sessions is required, and any absences and tardy arrivals to class will be noted.
Evaluation. Any absences must have an acceptable, documented, written excuse (e.g. illness, death in the family, college activity that requires you to be elsewhere); unexcused absences and tardy arrivals to class will count against the student's grade. Grading will be based upon the exercises, quizzes, and projects (about 30% of the grade) and midterm and final examinations (70% of the grade). These examinations will consist of computer exercises and of essay questions pertaining to lectures and assigned readings.
Special needs: If you are a student with a physical or learning disability and need accommodations, please contact the instructor or Dan Quinlin, ext. 333, in the Center for Academic Development during the FIRST TWO WEEKS of class.