1. C H A P T E R 15 Standardized Tests and Teaching
© 2006 The McGraw-Hill Companies, Inc. All rights reserved. Santrock, Educational Psychology, Second Edition, Classroom Update
C H A P T E R Standardized Tests and Teaching

2. Learning Goals 1. Discuss the nature of standardized tests.
© 2006 The McGraw-Hill Companies, Inc. All rights reserved. Santrock, Educational Psychology, Second Edition, Classroom Update
Learning Goals
1. Discuss the nature of standardized tests.
2. Compare aptitude and achievement testing and describe current uses of achievement tests.
3. Identify the teacher’s role in standardized testing.
4. Evaluate some key issues in standardized testing.
15.2

3. Standardized Tests and Teaching
© 2006 The McGraw-Hill Companies, Inc. All rights reserved. Santrock, Educational Psychology, Second Edition, Classroom Update
Standardized Tests and Teaching
The Nature of
Standardized Tests
The Purposes of Standardized
Tests
What Is a
Standardized Test?
Criteria for
Evaluating
Standardized Tests
15.3

4. The Nature of Standardized Tests
© 2006 The McGraw-Hill Companies, Inc. All rights reserved. Santrock, Educational Psychology, Second Edition, Classroom Update
The Nature of Standardized Tests
Standardized Tests
Have uniform procedures for administration and scoring.
Allow comparison of student scores by age, grade level, local and national norms.
Attempt to include material common across most classrooms.
15.4

5. © 2006 The McGraw-Hill Companies, Inc. All rights reserved
© 2006 The McGraw-Hill Companies, Inc. All rights reserved. Santrock, Educational Psychology, Second Edition, Classroom Update
Enter the Debate
Should students have to pass a test to earn a high school diploma?
YES NO
During a slideshow, text may be written on the slides in the yes/no boxes, and then saved for later reference.
15.5

6. Purposes of Standardized Tests
© 2006 The McGraw-Hill Companies, Inc. All rights reserved. Santrock, Educational Psychology, Second Edition, Classroom Update
Purposes of Standardized Tests
Diagnose students’
strengths and
weaknesses
Provide information for
planning
and instruction
Provide information about
student progress and
program placement
Contribute to
accountability
Help in program
evaluation
15.6

7. The Nature of Standardized Tests
© 2006 The McGraw-Hill Companies, Inc. All rights reserved. Santrock, Educational Psychology, Second Edition, Classroom Update
The Nature of Standardized Tests
Standards-based tests assess skills that students are expected to have mastered before they can be permitted to move to the next grade or be permitted to graduate.
High-stakes testing is using tests in a way that will have important consequences for the student, affecting major educational decisions.
15.7

8. Evaluating Standardized Tests
© 2006 The McGraw-Hill Companies, Inc. All rights reserved. Santrock, Educational Psychology, Second Edition, Classroom Update
Evaluating Standardized Tests
Norms – Does the normative group represent all students who may take the test?
Reliability – Are test scores stable, dependable and relatively free from error?
Validity – Does the test measure what it is purported to measure?
15.8

9. (positive or negative)
Correlation
Indicates strength
of relationship
(0.00 to 1.00)
Correlation
coefficient
r = +
0.37
OBJECTIVE 3-4| Describe positive and negative correlations and explain how correlational measures can aid the process of prediction.
Correlation Coefficient is a statistical measure of relationship between two variables.
Indicates direction
of relationship
(positive or negative)
Psychology 7e in Modules

10. Pearson correlation coefficient
r = the Pearson coefficient
r measures the amount that the two variables (X and Y) vary together (i.e., covary) taking into account how much they vary apart
Pearson’s r is the most common correlation coefficient; there are others.

11. Computing the Pearson correlation coefficient
To put it another way: Or

12. Sum of Products of Deviations
Measuring X and Y individually (the denominator):
compute the sums of squares for each variable
Measuring X and Y together: Sum of Products
Definitional formula
Computational formula
n is the number of (X, Y) pairs

13. Correlation Coefficent:
the equation for Pearson’s r:
expanded form:

14. Example
What is the correlation between study time and test score:

15. Calculating values to find the SS and SP:

16. Calculating SS and SP

17. Calculating r

18. Correlation Coefficient Interpretation
Range
Strength of
Relationship
Practically None
Low
Moderate
High Moderate
Very High

19. © 2006 The McGraw-Hill Companies, Inc. All rights reserved
© 2006 The McGraw-Hill Companies, Inc. All rights reserved. Santrock, Educational Psychology, Second Edition, Classroom Update
Reliability
Test-retest: The extent to which a test yields the same score when given to a student on two different occasions
Alternate-forms: Two different forms of the same test on two different occasions to determine the consistency of the scores
Split-half: Divide the test items into two halves; scores are compared to determine test score consistency
15.19

20. Methods of Studying Reliability
Interrater Reliability- The consistency of a test to
measure a skill, trait, or domain across examiners.
This type of reliability is most important when
responses are subjective or open-ended.
Copyright ©2006 by Pearson Education, Inc. Upper Saddle River, New Jersey All rights reserved.
Terry Overton Assessing Learners with Special Needs, 5e

21. © 2006 The McGraw-Hill Companies, Inc. All rights reserved
© 2006 The McGraw-Hill Companies, Inc. All rights reserved. Santrock, Educational Psychology, Second Edition, Classroom Update
Types of Validity…
Content: Test’s ability to sample the content that is being measured
Criterion-related:
Concurrent: The relation between a test’s score and other available criteria
Predictive: The relationship between test’s score and future performance
Construct: The extent to which there is evidence that a test measures a particular construct
15.21

22. Factor Analysis
statistical technique which uses the correlations between observed variables to estimate common factors and the structural relationships linking factors to observed variables. The diagram below illustrates how two observed variables can correlate because of their relationships with a common factor.

23. Standardized Tests and Teaching
© 2006 The McGraw-Hill Companies, Inc. All rights reserved. Santrock, Educational Psychology, Second Edition, Classroom Update
Standardized Tests and Teaching
Aptitude and
Achievement Tests
Comparing
Aptitude and
Achievement Tests
District and
National
Tests
Types of
Standardized
Achievement Tests
High-Stakes
State-Mandated
Tests
15.23

24. Aptitude vs. Achievement Tests
© 2006 The McGraw-Hill Companies, Inc. All rights reserved. Santrock, Educational Psychology, Second Edition, Classroom Update
Aptitude vs. Achievement Tests
Aptitude Tests
Predict a student’s ability to learn a skill
or accomplish a task.
(Stanford Binet,
Wechsler, SAT when
used to predict success)
Achievement Tests
Measure what the
student has learned
or mastered.
(California Achievement,
IOWA Basic Skills,
SAT when used to
determine what has been learned)
15.24

25. High-Stakes State-Mandated Tests
Possible
Advantages
Criticisms
- Improved student performance
- More teaching time
- Higher student expectations
- Identification of poor-performing
schools/teachers
- Improved confidence in schools
- “Dumbing down” and more emphasis on rote memorization
- Less time for problem-solving and critical thinking skills
- Teachers “teaching to the test”
- Discrimination against low-SES and ethnic minority children

26. National Assessment of Educational Progress
© 2006 The McGraw-Hill Companies, Inc. All rights reserved. Santrock, Educational Psychology, Second Edition, Classroom Update
National Assessment of Educational Progress
A federal “census-like” exam of students’ knowledge,
skills, understanding, and attitudes
Reading 1992– th grade no improvement
1992– th and 12th no improvement
Math 1990– th and 8th improvement
1990– th decline
Science 1996– th and 8th no change
1996– th decline
15.26

27. Standardized Tests and Teaching
© 2006 The McGraw-Hill Companies, Inc. All rights reserved. Santrock, Educational Psychology, Second Edition, Classroom Update
Standardized Tests and Teaching
The Teacher’s Role
Using Standardized
Test Scores to Plan
and Improve
Instruction
Preparing Students
to Take
Standardized
Tests
Understanding and
Interpreting
Test Results
Administering
Standardized
Tests
15.27

28. The Don’ts of Standardized Testing
© 2006 The McGraw-Hill Companies, Inc. All rights reserved. Santrock, Educational Psychology, Second Edition, Classroom Update
The Don’ts of Standardized Testing
DON’T
Teach to the test
Use the standardized test format for classroom tests
Describe tests as a burden
Tell students that important decisions will be made solely on the results of a single test
Use previous forms of the test to prepare students
Convey a negative attitude about the test
15.28

29. Counting the Data-Frequency
Look at the set of data that follows on the next slide.
A tally mark was made to count each time a score occurred
Which number most likely represents the
average score?
Which number is the most frequently
occurring score?
Descriptive statistics are the mathematical procedures that are used to describe and summarize data.

30. Frequency Distribution
Scores
100 99 98 94 90 89 88 82 75 74 68 60
Tally 1 11
1111
1111 1
Frequency 1 2 5 7 10 6
Average
Score?
Most 88
Most Frequent
Score? 88

31. This frequency count represents data that
closely represent a normal distribution.
1111 1
Tally
1111 1 11

32. Descriptive Statistics
© 2006 The McGraw-Hill Companies, Inc. All rights reserved. Santrock, Educational Psychology, Second Edition, Classroom Update
Descriptive Statistics
15.32

33. Frequency Polygons 60 68 74 75 88 89 90 94 98 99 100 Data 100 89 99 89 5 4 3 2 1
Scores

34. Measures of Central Tendency
© 2006 The McGraw-Hill Companies, Inc. All rights reserved. Santrock, Educational Psychology, Second Edition, Classroom Update
Measures of Central Tendency
Measures of central tendency provide information about the average or typical score in a data set
Mean: The numerical average of a group of scores
Median: The score that falls exactly in the middle of a data set
Mode: The score that occurs most often
15.34

35. Mean- To find the mean, simply add the
Central tendency = representative or typical value in a distribution
Mean
Same thing as an average
Computed by
Summing all the scores (sigma, )
Dividing by the number of scores (N)
Mean- To find the mean, simply add the
scores and divide by the number of scores
in the set of data.
= 355
Divide by the number of scores: 355/4 = 88.75

36. Mean

37. Measures of Central Tendency
Steps to computing the median
1. Line up scores from highest to lowest
2. Count up to middle score
If there is 1 middle score, that’s the median
If there are 2 middle scores, median is their average
Aron, Aron, & Coups, Statistics for the Behavioral and Social Sciences: A Brief Course (3e), © 2005 Prentice Hall

38. Median-The Middlemost point in a set of data
Data Set 1
100 99 98 97 96 90 88 85 80 79
Data Set 2
100 99 98 97 86 82 78 72 70 68
The median is
84 for this set.
84 represents
the middle
most point in
this set of
data.
Median 96

39. Mode-The most frequently occurring score in a set of data.
Find the modes for the following sets of data:
88 and 87 are both
modes for this
set of data. This is
called a bimodal
distribution.
Data Set 3 99 89 75
Data set 4 99 88 87 72 70
Mode: 89

40. Measures of Variability (Dispersion)
Range- Distance between the highest
and lowest scores in a set of data. 35 =
35 is the range in this set of scores.

41. Variance - Describes the total amount
that a set of scores varies from the
mean.
1. Subtract the mean from each score.
When the mean for a set of data is
87, subtract 87 from each score.

43. 2. Next-Square each difference- multiply each difference by itself.
= 13
= 11
= 8
= 4
= -2
= -7
= -27
3. Sum these
differences
1,152
Sum of
squares

44. 4. Divide the sum of squares by the number of scores.
1,152 divided by 7 =
This number
represents the variance for this set of data.

45. Standard Deviation-Represents the typical
amount that a score is expected to vary
from the mean in a set of data.
5. To find the standard deviation, find the
square root of the variance. For this
set of data, find the square root of
The standard deviation for this set of data is or 13.

50. Ceiling and Floor Effects
Ceiling effects
Occur when scores can go no higher than an upper limit and “pile up” at the top
e.g., scores on an easy exam, as shown on the right
Causes negative skew
Floor effects
Occur when scores can go no lower than a lower limit and pile up at the bottom
e.g., household income
Causes positive skew

51. Skewed Frequency Distributions
Normal distribution (a)
Skewed right (b)
Fewer scores right of the peak
Positively skewed
Can be caused by a floor effect
Skewed left (c)
Fewer scores left of the peak
Negatively skewed
Can be caused by a ceiling effect

52. Understanding Descriptive Statistics
© 2006 The McGraw-Hill Companies, Inc. All rights reserved. Santrock, Educational Psychology, Second Edition, Classroom Update
Understanding Descriptive Statistics
The Normal Distribution: A “bell-shaped” curve in which most of the scores are clustered around the mean; the farther from the mean, the less frequently the score occurs.
15.52

53. Bell Curve

54. Commonly Reported Test Scores Based on the Normal Curve
© 2006 The McGraw-Hill Companies, Inc. All rights reserved. Santrock, Educational Psychology, Second Edition, Classroom Update
Commonly Reported Test Scores Based on the Normal Curve
15.54

55. Z Scores
When values in a distribution are converted to Z scores, the distribution will have
Mean of 0
Standard deviation of 1
Useful
Allows variables to be compared to one another even when they are measured on different scales, have very different distributions, etc.
Provides a generalized standard of comparison
Aron, Aron, & Coups, Statistics for the Behavioral and Social Sciences: A Brief Course (3e), © 2005 Prentice Hall

56. Z Scores
To compute a Z score, subtract the mean from a raw score and divide by the SD
To convert a Z score back to a raw score, multiply the Z score by the SD and then add the mean
Aron, Aron, & Coups, Statistics for the Behavioral and Social Sciences: A Brief Course (3e), © 2005 Prentice Hall

57. Standardized Tests and Teaching
© 2006 The McGraw-Hill Companies, Inc. All rights reserved. Santrock, Educational Psychology, Second Edition, Classroom Update
Standardized Tests and Teaching
Issues in Standardized
Testing
Standardized Tests,
Alternative Assessments,
High-Stakes Testing
Diversity and
Standardized
Testing
15.57

58. Issues in Standardized Testing
© 2006 The McGraw-Hill Companies, Inc. All rights reserved. Santrock, Educational Psychology, Second Edition, Classroom Update
Issues in Standardized Testing
Alternative Assessments
Assessments of oral presentations
Real-world problems
Projects
Portfolios
Diversity and Standardized Tests
Gaps on standardized tests have been attributed to environmental rather than hereditary factors
Special concern in creating culturally unbiased tests
15.58

59. Crack the Case Standardized Tests
© 2006 The McGraw-Hill Companies, Inc. All rights reserved. Santrock, Educational Psychology, Second Edition, Classroom Update
Crack the Case Standardized Tests
What are the issues involved in this situation?
Examine Ms. Carter’s testing procedures. What does she do incorrectly? How might this reduce the validity of the students’ scores?
How would you answer each of the parents’ questions?
This case is on page 513 of the text.
15.59

60. Reflection & Observation
© 2006 The McGraw-Hill Companies, Inc. All rights reserved. Santrock, Educational Psychology, Second Edition, Classroom Update
Reflection & Observation
Reflection:
What standardized tests have you taken?
How have these tests affected your perceptions of competence?
Observation:
What are some of the mother’s concerns regarding her son’s standardized test scores?
What error does the teacher make in interpreting one of the test scores? How would you explain this score?
Classroom Observation Video: “Interpreting Test Scores”
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