Department of Computer Science Bachelor of Science

Master of Science

Doctoral of Philosophy

I. Assessment Procedures	III. Changes to Procedures or Curriculum Based on Assessment
II. Achievement of Departmental Objectives for Students A. Undergraduate--	IV. Changes in Department’s Assessment Goals

Part 1. Assessment Procedures:

As described in our assessment plan, the Computer Science program was assessed by examining learning outcomes, testing instruments, and student performance in selected courses from the curriculum. The data that was used was collected from the faculty for all courses taught during the academic year.

The original plan did not describe a data reduction strategy, which we now describe. The average assessment of the goal was evaluated by a weighted average of the professor’s assessment of the learning outcomes for each course. The weights were the predicted profile or prior estimate of emphasis for each course described in the super matrix of learning outcomes. In order to control for the effects of the assessment method on the scores the most representative score was chosen for each goal.

The weighted average is defined by: where W is the a-priori estimate of emphasis from the learning outcome and G is the instructor’s assessment of achieving the learning outcomes in the course. This average will be maximized when the assessment is strongly correlated with the a-priori estimate of emphasis.

Part 2. Achievement of Departmental Student Learning Objectives:

The data used for our analysis to describe achievement of our learning outcomes are given in the appendix. The undergraduate assessment is based on the 2000, 3000, and 4000 level courses.

The data in the appendix consist of the individual course assessments provided by the faculty.

The results given in the table below show how closely our overall program meets the expected learning outcomes. This is derived from the individual instructor’s assessments given in the appendix and by the process described in Part 1 of our report. From this, we can conclude that the program is meeting most of its expected learning outcomes. However, we are able to identify weaknesses in the following student learning outcomes: Discrete Mathematics, Hardware Systems, and Computer Organization and Programming.

Learning Outcomes	Weighted average (perfect score is 1.0)
Communication	0.913
Collaboration	0.874
Critical Thinking	0.998
Contemporary Issues	0.827
Quantitative Literacy	0.877
Technology	0.991
Algorithm Design and Analysis	0.892
Discrete Mathematics	0.735
Computer Systems Development	0.850
Programming Skills	0.917
Hardware Systems	0.750
Computer Organization and Programming	0.784

Part 3. Changes to Procedures or Curriculum Based on Assessment:

Changes to procedures:

1. We propose to adjust the weights to produce an a-posteriori estimate of the relative contributions to the learning outcomes of each course and thus improve the accuracy of the assessment.

2. We propose to use a sampling of representative courses for our assessment analysis. These courses will cover any path of course selections that a student may follow. We will still collect assessment data from faculty for all courses taught.

3. We propose to modify the course assessment data sheet. The revised form is given on the next page:

Assessment Report for a Classroom Taught Course

Course Number:

Course Title:

Term Taught:

Fill in chart with numeric score 1- 4 and N/A as defined

1 - Poor 2 - Satisfactory 3 - Good 4 - Excellent

Communication

Collaboration

Critical Thinking

Contemporary Issues

Quantitative Literacy

Technology

Algorithm Design & Analysis

Discrete Mathematics

Computer Systems Development

Programming skills

Hardware Systems

Computer Organization and Programming

Assessment Methods

1

2

3

4

5

6

7

8

9

10

11

12

Examinations

Best

Avg

Written Assignments, Lab Reports, or Research Reports

Best

Avg

4000 Level Course Oral/Written Presentations

Best

Avg

Professor’s assessment of the course:

Professor’s suggestions to modify course or its assessment:

Evidence of student weakness in learning outcomes and proposed changes to curriculum addressing these problems:

1. There is a general weakness in discrete mathematics, hardware systems, and computer organization and programming, resulting in more class time spent on compensating weaknesses. (See correlation scores in the table on page 2 of this report.) The low values for hardware systems and computer organization are reflective of the low values for discrete mathematics.

Proposed changes to curriculum:

1. Incorporate more real-world examples (at least more than in textbooks) in teaching allowing better student comprehension in hardware systems and computer organization.

2. Explore possibilities to modify the curriculum that will supplement the deficiencies students have in discrete mathematics. This includes either introducing a new course at the 3000 level or modifying existing 3000 level courses.
3. Textbook choice should be revised for certain courses since they do not contain sufficient number of examples.
4. Certain courses (like Windows programming) should be frequently (almost each year) updated in order to be synchronized with changes in the best programming practices.

2. Professors’ comments suggest that students’ communications skills need improvement.

Proposed changes to curriculum:

1. Encourage faculty to change syllabi to include group student projects in their courses.
2. Also encourage faculty to have students in 4000 level courses submit written reports and oral presentations.
3. Encourage students to turn the class projects into paper submissions/publications.

Part 4. Changes in Department’s Assessment Goals:

There are no proposed changes at this time.