The college of business and technology's course embedded student outcomes assessment process

College Student Journal, June, 2002 by Edgar J. Manton, Donald E. English

4. The student will be able to calculate the mean for grouped data.

5. The student will be able to calculate the variance for grouped data.

6. The student will know the definition of probability.

7. The student will be able to calculate a probability using the general rule of addition.

8. The student will know how to determine the random variable of a normal distribution.

9. The student will be able to use the normal distribution table to solve a problem.

10. The student will be able to calculate the mean and the variance of a binomial distribution.

11. The student will be able to use the binomial distribution tables to solve a problem.

12. The student will be able to use the poisson distribution table to solve a problem.

13. The student will know the definition of a sampling distribution of means.

14. The student will know the central limit theorem.

15. The student will know the definition of a random sample.

16. The student will know the definition of a Type I and a Type II error.

17. The student will be able to calculate a confidence interval to estimate a population parameter.

18. The student will be able to test a statistical hypothesis.

19. The student will know how to test the hypothesis involving a small sample size.

20. The student will know the interpretation of the coefficient of determination.

21. The student will know the definition of correlation.

22. The student will know the definition of least squares.

23. The student will know how to calculate a correlation coefficient.

24. The student will know how to calculate a regression equation.

Then the instructor developed 24 objective type questions, which are intended to determine the student's knowledge relating to each of the competencies. For the first competency--"the student will know the definition of inferential statistics"--the following question was used:

The branch of statistics in which we draw conclusions about a population parameter from sample data is called:

a) descriptive statistics

b) central tendency measures

(x) c) inferential statistics

e) dispersion measures

Table 1, indicates the results for the course on all 24 items for the Spring 2000 term.

The class had 42 students. The vertical column tabulations indicate the numbers and percentages of students who answered each competency question correctly. For question # 1, thirty-five or 83% of the students responded correctly. The results on each question could be compared to a desired goal such as "at least 70% of the students will correctly answer each competency question". Of the 24 competency questions, the students achieved at least 70% on only 16 of the questions.

The horizontal tabulation indicates the numbers and percentages of the 24 competency questions that individual students answered correctly. These results could be compared to a course objective such as "at least 80% of the students will receive a score of 70% or higher on the major competency questions." In this course, 30 of the 42 or 71% of the students scored 70% or higher on the 24 questions indicating that a goal of 80% would not have been achieved.