SECCM Assessment Plan - Roger Williams University

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Section 3 <strong>Assessment</strong> <strong>Plan</strong> for the Computer Science Program Introduction The Computer Science Program is founded on an educational philosophy that encourages exploration and discovery in a dynamic discipline. Students study computer science in an environment which goes beyond disciplinary boundaries and enhances the development of the “whole” person. The curriculum is designed to develop the essential knowledge, skills and abilities needed for professional practice or graduate study. The curricular structure of the program, coupled with the strong influence of the liberal arts, equips our graduates with a “holistic” educational experience that prepares them to succeed in a world characterized by rapidly increasing technology, growing complexity and globalization. The computer science program is designed to encompass seven functional categories of courses: • Algorithms • Data Structures • Software Design • Concepts of Programming Languages • Computer Organization and Architecture • Mathematics and Science • General education. Each of these categories provides the student with an essential component of their overall educational experience. The interleaving of the courses provides a synergistic curriculum that ensures students are prepared for successful computer science practice. Curricular Functional Design As discussed above, the computer science curriculum is designed around seven functional categories of courses. Many of the courses are common to most undergraduate computer science programs. The program follows many of the tenets as set forth in the ABET/CAC criteria and the ACM Computing Curriculum 2001. There are a total of 121 credit hours required for the computer science degree broken down as depicted in Table 3.1. 47
Table 3.1 General Program Breakdown Category Credit Hours Algorithms 10.5 Data Structures 6.5 Software Design 9.5 Programming Languages 7.0 Computer Organization & Architecture 12.5 Computer Science Electives 9.0 Mathematics & Science 32.0 General Education 34.0 Total 121.0 1. Algorithms These courses focus on the step-by-step process of computing a solution to a problem. These courses cover basic as well as advanced topics. They provide a mix of practical application and theoretical foundations. The data communication course provides the opportunity to consider specialized algorithms. Table 3.2 lists the courses in this category. Table 3.2 Algorithm Courses Course Number Course Title Core Adv COMSC 110 Introduction to Computer Science & Lab 1.5 COMSC 111 Data Structures & Lab 1.0 COMSC 210 Principles of Computer Organization & Lab 0.5 COMSC 220 Analysis of Algorithms 2.0 COMSC 230 Principles of Programming Languages 0.5 COMSC 240 Theory of Computation 0.5 1.0 COMSC 310 Language Translation and Compiler Design 0.5 COMSC 320 Principles of Operating Systems 0.5 COMSC 492 Integrated Senior Design II 0.5 ENGR 445 Dynamic Modeling and Control 0.5 ENGR 455 Data Communications 0.5 ENGR 465 Network Analysis and Design 0.5 0.5 Total Credits 5.0 5.5 2. Data Structures These courses provide students with the basic, and then advanced, ways in which data are organized to best execute algorithms. The material presented complements the instruction provided in the algorithms courses. Table 3.3 lists the courses within this category. 48
Page 1 and 2: School of Engineering, Computing an
Page 3 and 4: Section 4 - Assessment Plan for the
Page 5 and 6: Correlation of SECCM’s Goals and
Page 7 and 8: Figure 1.1 Assessment Plan Interrel
Page 9 and 10: Program Educational Objectives and
Page 11 and 12: Table 1.2 Instruments and Materials
Page 13 and 14: • Course Assessment Report One of
Page 15 and 16: • Student enrollment trends • F
Page 18 and 19: Section 2 Assessment Plan for the E
Page 20 and 21: The Engineering program was origina
Page 22 and 23: 6. Core Education Courses These cou
Page 24 and 25: Table 2.7 RWU Engineering Program E
Page 26 and 27: Relationship between Engineering Cu
Page 28 and 29: Seminar Business elective Engineeri
Page 30 and 31: Bloom’s taxonomy and derived from
Page 33 and 34: Table 2.12 Course Mapping to Expect
Page 35 and 36: Outcome Courses ENGR 300 Mechanics
Page 37 and 38: Outcome Courses ENGR 424 Digital Si
Page 39 and 40: Outcome Courses CORE 103 Human Beha
Page 41 and 42: Metric Goals for Each a-k Engineeri
Page 43 and 44: Table 2.15 Outcome “c” Metrics
Page 45 and 46: Table 2.18 Outcome “f” Metrics
Page 47 and 48: Table 2.20 Outcome “h” Metrics
Page 49: Table 2.23 Outcome “k” Metrics
Page 53 and 54: Table 3.5 Concepts of Programming L
Page 55 and 56: Senior Capstone Sequence The hallma
Page 57 and 58: Computer Science Program Outcomes C
Page 59 and 60: Table 3.12 Sample of Outcomes Works
Page 61 and 62: Table 3.12b Sample of Outcomes Work
Page 63 and 64: Table 3.12e Sample of Outcomes Work
Page 65 and 66: Table 3.12g Sample of Outcomes Work
Page 67 and 68: Metric Goals for Each a-g Computer
Page 69 and 70: Table 2.16 Outcome “d” Metrics
Page 71 and 72: Table 2.19 Outcome “g” Metrics
Page 73 and 74: Table 4.1 General Education Courses
Page 75 and 76: Table 4.5 Construction Course Numbe
Page 77 and 78: Table 4.8 Alignment and Mapping of
Page 79 and 80: Table 4.9 Construction Management P
Page 81 and 82: Table 4.13 Outcome “b” Metrics
Page 83 and 84: Table 4.17 Outcome “f” Metrics
Page 85 and 86: Table 4.20 Outcome “i” Metrics
Page 88 and 89: Engineering Senior Exit Survey Scho
Page 90: Programs/Services/Individuals Extre
Page 93 and 94: 5. Were there any activities, progr
Page 96 and 97: Construction Management Senior Exit
Page 98: 7. What would you say is the greate
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SECCM Course Assessment Report Cont
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Student assessments of course objec
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e. Average Time Data ENGR 330 Time
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d. Development of a written assessm
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computers imaged the same as those
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18. How long did it take you to fin
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ROGER WILLIAMS UNIVERSITY SCHOOL OF
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ENGR 490 Skills Inventory School of
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School of Engineering, Computing, a
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Student ___________________________
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Student ___________________________
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