1. Chapter 7 Item Analysis In constructing a new test (or shortening or lengthening an existing one), the final set of items is usually identified through a process known as item analysis. —Linda Croker

2. Both the validity and the reliability of any test depend ultimately on the characteristics of its items.

3. Two Approaches of Item Analysis Qualitative Analysis Quantitative Analysis

4. Qualitative Analysis includes the consideration of content validity (content and form of items), as well as the evaluation of items in terms of effective item-writing procedures.

5. Quantitative Analysis includes principally the measurement of item difficulty and item discrimination.

6. §1 Item Difficulty 1. Definition The item difficulty for item i, p i, is defined as the proportion of examinees who get that item correct.

7. Though the proportion of examinees passing an item traditionally has been called the item difficulty, this proportion logically should be called item easiness, because the proportion increase as the item becomes easier.

8. 2. Estimation Methods Method for Dichotomously Scored Item Method for Polytomously Scored Item Grouping Method

9. Method for Dichotomously Scored Items (7.1) p is the difficulty of a certain item. R is the number of examinees who get that item correct. N is the total number of examinees.

10. Example 1 There are 80 high school students attending a science achievement test, and 61 students pass item 1, 32 students pass item 10. Please calculate the difficulty for item 1 and 10 separately.

11. Method for Polytomously Scored Items (7.2), the mean of total examinees’ scores on one item, the perfect scores of that item

12. Example 2 The perfect scores of one open- ended item is 20 points, the average score of total examinees on this item is 11 points. What is the item difficulty? Key:.55

13. Grouping Method (Use of Extreme Groups) Upper (U) and Lower (L) Criterion groups are selected from the extremes of distribution of test scores or job ratings. T. L. Kelley (1939) proposed that upper and lower 27% could lead to the optimal point when the total test scores are normally distributed.

14. is th proportion for examinees of upper group who get the item correct. (7.3) is the proportion for examinees of lower group who get the item correct.

15. Example 3 There are 370 examinees attending a language test. Known that 64 examinees of 27% upper extreme group pass item 5, and 33 examinees of 27% lower extreme group pass the same item. Please compute the difficulty of item 5. Key :.49

16. 3. Correct Chance Effects on Item Difficulty for Multiple-Choice Item (7.4), corrected item difficulty,uncorrected item difficulty, the number of choices for that item

17. Example 4 The diffuculty of one five-choice item is.50, the difficulty of another four-choice item is.53. Which item is more difficulty?

18. ANSWER So, the four-choice item is more difficulty.

19. 4. Item Difficulty and Discrimination Discrimination Difficulty

20. If there are 100 persons in one population, then,we can calculate the discriminations as following: P=.01, 1 × 99 = 99 P=.02, 2 × 98 = 196 P=.3, 30× 70 = 2100 P=.5, 50 × 50 = 2500

21. 5. Test difficulty and the Distribution of Test Scores How to Calculate the Test Difficulty ? Two Methods A calculate the mean of all item difficulties of the test B compute the ratio of mean of test scores to perfect test scores

22. Test difficulty and the Distribution of Test Scores (a) Positive Skewed Distribution (b) Negtive Skewed Distribution

23. §2 Item Discrimination When the test as a whole is to be evaluated by means of criterion-related validation, the items may themselves be evaluated and selected on the basis of their relationships to the external criterion. When we identify an item for which high scoring examinees have a high probability of answering correctly and low-scoring examinees have a low probability of answer correctly, we would say such an item can discriminates or differentiates the examinees.

24. 1.Interpretation Item discrimination refers to the degree to which an item differentiates correctly among test takers in the behavior that the test is designed to measure.

25. 2. Estimation Methods Index of Discrimination (used for dichotomously scored items) D = P H - P L (7.5) We need to set one or two cutting scores to divide the examinees into upper scoring group and lower scoring group. P H is the proportion in the upper group who answer the item correctly and P L is the proportion in the lower group who answer the item correctly. Values of D may range from -1.00 to 1.00.

26. Example 1 There are 140 students attending a world history test. (1) If we use the ratio 27% to determine the upper and lower group, then how many examinees are there in the upper and lower group separately? (2)If 18 examinees in upper group answer item 5 correctly, and 6 examinees in lower group answer it correctly, then calculate the discrimination index for item 5.

27. Example 2 50 Examinees’ Test Data on 8-Item Scale About Job Stress. Item 1 2 3 4 5 6 7 8 PHPLPHPL.54.81.47.32.51.18.63.56.32.56.11.05.10. 23.25.19 D.18.25.36.27.41 -.05.38.37

28. Guidelines for Interpretation of D Value D≥.40, the item is functioning quite satisfactorily.30≤ D≤.39, little or no revision is required.20 ≤ D≤.29, the item is marginal and needs revision D≤.19, the item should be eliminated or completely revised

29. Correlation Indices of Item Discrimination (1)Pearson Product Moment Correlation Coefficient This formula is commonly used to estimate the degree of the relationship between item and criterion scores

30. (2) Point Biserial Correlation If we use the total test score as the criterion, and test item is scored 0 to 1, then we can use the following formula: (7.6) is the mean test scores for those who answer the item correctly is the mean scores for the entire group is the standard deviation of test scores for entire group is the pass ratio of that item (difficulty ) is fail ratio of that item

31. Example 3 the Test Data of 15 Examinees Examinees 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Test score Item score 90 81 80 78 77 70 69 65 55 50 49 42 35 31 10 1 0 1 1 1 1 1 0 0 0 1 0 1 0 0 note:

33. Transformation of Formula 7.6 ( 7.7) is the mean test scores for those who answer that item incorrectly

34. (3) Biserial Correlation Coefficient or

35. (4) Correlation Between Items a) Tetrachoric Correlation Coefficient Each variable is created through dichotomizing an underlying normal distribution (7.8) A B CD Item i 0 1 Item j 1010 A+C B+D A+B C+D

36. b) PHI Coefficient (7.9)

37. Variance for item (7.10)

38. Difficulty and Discrimination P D 1.00 0.00 0.90 0.20 0.70 0.60 0.60 0.80 0.50 1.00 0.40 0.80 0.30 0.60 0.10 0.20 0.00 0.00

39. §3 Application Case of Item Analysis 1.Procedures Select a representative sample of examinees and administer the test; Differentiate the examinees into upper 27% (or 30% etc.) group and lower 27% group according to their test scores; Calculate P U and P L, then estimate P and D for each item; Compare the responses on different choices for each item between the upper group and lower group; ● Revise items.

40. 2. Analysis Case P D 0.71 0.42 0.52 0.42 0.32 0.33 0.31 -0.06 -0.04 0.12 0.04 0.08 ItemGroupNumber of Examinees on Each Choice Key ABCDOmit 1Upper592120 B Lower225012160 2Upper581015161 A Lower262115362 3Upper171528 12 D Lower2511193411 4Upper14414365 C Lower 15610285

41. Choice Analysis Whether the examinees who choose the correct choice is more than those who choose the wrong choices Whether a lot of examinees choose the wrong choices Whether the examinees of upper group who choose the correct choice is more than the examinees of lower group Whether the examinees of upper group who choose the wrong choice is more than those of lower group Whether there is any choice that few examinees choose Whether there is any item that quite a number of examinees make no choices