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Home Page Class Times 9:30 - 10:45 TT Rm 231E Mad Office Hours: 2-3 Mon, 8:30-9:30 TT, 11-12, 1-2 Th Rm 209 Mad (Other times by appointment) Office Phone: 4493 Home Phone: 289-2126
This course concerns the study of certain mathematical theories and procedures used in the allocation of scarce resources (optimization). It is designed to help you understand, develop and analyze deterministic mathematical models, identify the assumptions underlying these models, and interpret the results from using these modeling techniques in practical terms. You will be using the computer for analysis and will be expected to prepare well-written reports describing your results. The course will involve problem-solving in cooperative groups as well as the more traditional methods.
Other important course goals are to increase awareness of and to develop your learning and problem solving skills, and to become eficient working in project groups. By the end of the course, you should be able to learn faster than you do now. You will be conscious of and able to assess your level of the learning skills for life listed in the attached taxonomy of process education. We will use cooperative group learning, discovery learning, applied critical thinking, problem solving, and self assessment in each class and lab. You will also be expected to keep a learning journal to help you assess your progress.
The primary theme of this course is the improvement of the learning process by practicing learning skills in the mastery of mathematical programming concepts and methods. You will be assigned team projects to which you will apply these skills. During each class you will work with your team on the following tasks: (1) quiz/problem solving session using information from the reading assignment, (2) minilecture or problem solution presentation, (3) a learning activity (involving concept models to manipulate, critical thinking questions about the models, and skill development exercises to apply the concept to new situations), (4) consulting session (you ask me questions), and (5) assessment of how well you worked as a team to learn the concepts and solve the problems. There will be very little "lecturing." Thus, it is essential that you do the reading for every class.
The reason why we emphasize collaborative learning as described in the preceding paragraph is that employers seek individuals who excel as:(1)
Attendance: A student is expected to attend every class. If you miss a class, it is your responsibility to make up the work and turn in any missed assignments. If you miss an exam or a homework or project deadline, you receive a grade of zero unless you have an official excuse from Mrs. Marcy's office or have made previous arrangements with me. A student who misses more than five classes without valid excuses will be required to withdraw from the class. The reason for this policy is that you have a responsibility to contribute to your team's efforts. If you aren't there your team is severely handicapped since each team member has a specific role to play.
Course Assignments: There will be regular reading assignments to be completed before each class, and regular (individual) written homework assignments due each Tuesday. In addition, you will be assigned a mini-project, and a major modeling project. These will be group projects for which the entire group receives the same grade. They will be graded on how well they are written as well as on their technical content. You must hand in a rough draft of your projects on specified dates - at least three classes before the project is due. Failure to hand in the rough draft will result in loss of 5 points on the project grade. Failure to hand in the project on time will result in loss of all credit. Late homework will be corrected but you will receive no points for it.
Project Participation: The focus in this course is on working in teams. You will be expected to work an average of 6-8 hours a week outside of class on the course and a good portion of this time will be spent in team meetings and group work on the projects. You are expected to attend all sessions scheduled by your team. With each project report each team should include an effort report detailing each team member's actual contributions.
I will select the team participants. If someone just does not work out on a team for any number of reasons, the two teams can arrange a trade (before the assignment of the mini-project). The two people to be traded must agree and at least one other member of each team must also agree before a trade can take place.
Honesty Policy: See the statement in the student handbook and the attached sheet on academic honesty. In this course, dishonesty will result in a grade of zero for the work involved. Continued infractions will be referred to the Office of Academic Affairs for disciplinary action. You are encouraged to compare ideas with other students but you should write up your own homework without using notes made during joint sessions until you get stuck. Copying someone else's work or using their computer files or programs is never allowed. Failure to adhere to this policy will cause loss of all credit for the work in question. Homework is to be completed on your own. Since most of the course work is in groups, this may be hard to remember.
The general grade letter equivalents: A 92-100; A- 88-91; B+ 84-87; B 80-83; B- 76-79; C+ 72-75; C 68-71; C- 64-67; D+ 60-63; D 56-62; F below 56. To figure final grade break points, multiply the above break points by ___ (to be determined by the class)
Two tests (Sept. 24, Nov. 12) 100 points each Homework * points Daily Quiz/Problem solution 10 points each Daily Class Assessment 10 points each Major Project (due 12/8) * points Mini-Project (due 10/8) * points Learning Journal * points Final Exam (Dec 18, 10:30am) 100 points * To be determined by the class
Week Topic 1 Learning Process Models 2 Review of Linear Algebra 3 Modeling Linear Programming Problems 4 Geometry of Rn 5 Linear Programming - Graphical Solutions 6 Review and Test 7 Linear Programming - Algebraic Solutions 8,9 Linear Programming - Simplex Method 10 Post Optimality Analysis 11 Review and Test 12 Non-Linear Programming - unconstrained problems 13,14 Non-Linear Programming - constrained problems 15 Search Methods
Reading assignments and the learning activity for each class will be given during the preceding class. When you read mathematics you must keep your critical thinking skills honed. Always ask why a particular step is valid and how a new concept relates to those previously learned. It helps to memorize definitions and to be familiar with examples that illustrate each definition and theorem.
Each student must keep a learning journal and bring it to every class. I will collect the reflector's learning journal the first class following the week in which she is the reflector. Each day the class meets you are expected to complete a Self Assessment form in your Learning Assessment Journal and record (as a minimum) the most valuable thing learned, two of your greatest strengths and two most important areas for improvement with a plan of action to address the most critical area for improvement. You should complete the weekly reflector's or recorder's report forms in the Learning Assessment Journal for each week in which you are the team reflector/recorder. The team captain should complete an Activity Assessment form for the Tuesday activities and the spokesperson should complete an Activity Assessment Form for the Thursday activities. You should also complete the critical thinking questions in each day's activity and hand these in with your learning journal. Depending on the weight that the class gives the journal, you will also be expected to use the reading, collection point and free writing sections.
1. 1 D. K. Apple, S. W. Beyerlein, M. A. Schlesinger, Learning Through Problem Solving, Pacific Crest Software, Corvallis, OR (1992), p. vii.
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