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_objectives.Rmd
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**Chapter 1: Introduction**
1. Identify and use statistical notation for variables, sample size, mean, standard deviation, variance, and correlation.
2. Calculate and interpret frequencies, proportions, and percentages.
3. Create and use frequency distribution plots to describe the central tendency, variability, and shape of a distribution.
4. Calculate and interpret measures of central tendency and describe what they represent, including the mean, median, and mode.
5. Calculate and interpret measures of variability and describe what they represent, including the standard deviation and variance.
6. Apply and explain the process of rescaling variables using means and standard deviations for linear transformations.
7. Calculate and interpret the correlation between two variables and describe what it represents in terms of the shape, direction, and strength of the linear relationship between the variables.
8. Create and interpret a scatter plot, explaining what it indicates about the shape, direction, and strength of the linear relationship between two variables.
**Chapter 2: Measurement, Scales, and Scoring**
1. Define the process of measurement.
2. Define the term *construct* and describe how constructs are used in measurement, with examples.
3. Compare and contrast measurement scales, including nominal, ordinal, interval, and ratio, with examples, and identify their use in context.
4. Compare and contrast dichotomous and polytomous scoring.
5. Describe how rating scales are used to create composite scores.
6. Explain the benefits of composites over component scores.
7. Create a generic measurement model and define its components.
8. Define norm referencing and identify contexts in which it is appropriate.
9. Compare three examples of norm referencing: grade, age, and percentile norms.
10. Define criterion referencing and identify contexts in which it is appropriate.
11. Describe how standards and performance levels are used in criterion referencing with standardized state tests.
12. Compare and contrast norm and criterion score referencing, and identify their uses in context.
**Chapter 3: Testing Applications**
1. Provide examples of how testing supports low-stakes and high-stakes decision making in education and psychology.
2. Describe the general purpose of aptitude testing and some common applications.
3. Identify the distinctive features of aptitude tests and the main benefits and limitations in using aptitude tests to inform decision-making.
4. Describe the general purpose of standardized achievement testing and some common applications.
5. Identify the distinctive features of standardized achievement tests and the main benefits and limitations in using standardized achievement tests to inform decision-making.
6. Compare and contrast different types of tests and test uses and identify examples of each, including summative, formative, mastery, and performance.
**Chapter 4: Test Development**
*Cognitive*
1. Describe the purpose of a cognitive learning objective or learning outcome statement, and demonstrate the effective use of learning objectives in the item writing process.
2. Describe how a test outline or test plan is used in cognitive test development to align the test to the content domain and learning objectives.
3. Compare items assessing different cognitive levels or depth of knowledge, for example, higher-order thinking such as synthesizing and evaluating information versus lower-order thinking such as recall and definitional knowledge.
4. Identify and provide examples of SR item types (multiple-choice, true/false, matching) and CR item types (short-answer, essay).
5. Compare and contrast SR and CR item types, describing the benefits and limitations of each type.
6. Identify the main theme addressed in the item writing guidelines, and how each guideline supports this theme.
7. Create and use a scoring rubric to evaluate answers to a CR question.
8. Write and critique cognitive test items that match given learning objectives and depths of knowledge and that follow the item writing guidelines.
*Noncognitive*
9. Define affective measurement and contrast it with cognitive measurement in terms of applications and purposes, the types of constructs assessed, and the test construction process.
10. Compare affective test construction strategies, with examples of their use, and the strengths and limitations of each.
11. Compare and contrast item types and response types used in affective measurement, describing the benefits and limitations of each type, and demonstrating their use.
12. Define the main affective response sets, and demonstrate strategies for reducing their effects.
13. Write and critique effective affective items using empirical guidelines.
**Chapter 5: Reliability**
*CTT reliability*
1. Define reliability, including potential sources of reliability and unreliability in measurement, using examples.
2. Describe the simplifying assumptions of the classical test theory (CTT) model and how they are used to obtain true scores and reliability.
3. Identify the components of the CTT model ($X$, $T$, and $E$) and describe how they relate to one another, using examples.
4. Describe the difference between systematic and random error, including examples of each.
5. Explain the relationship between the reliability coefficient and standard error of measurement, and identify how the two are distinguished in practice.
6. Calculate the standard error of measurement and describe it conceptually.
7. Compare and contrast the three main ways of assessing reliability, test-retest, parallel-forms, and internal consistency, using examples, and identify appropriate applications of each.
8. Compare and contrast the four reliability study designs, based on 1 to 2 test forms and 1 to 2 testing occasions, in terms of the sources of error that each design accounts for, and identify appropriate applications of each.
9. Use the Spearman-Brown formula to predict change in reliability.
10. Describe the formula for coefficient alpha, the assumptions it is based on, and what factors impact it as an estimate of reliability.
11. Estimate different forms of reliability using statistical software, and interpret the results.
12. Describe factors related to the test, the test administration, and the examinees, that affect reliability.
*Interrater reliability*
13. Describe the purpose of measuring interrater reliability, and how interrater reliability differs from traditional reliability.
14. Describe the difference between interrater agreement and interrater reliability, using examples.
15. Calculate and interpret indices of interrater agreement and reliability, including proportion agreement, Kappa, Pearson correlation, and g coefficients.
16. Identify appropriate uses of each interrater index, including the benefits and drawbacks of each.
17. Describe the three main considerations involved in using g coefficients.
**Chapter 6: Item Analysis**
1. Explain how item bias and measurement error negatively impact the quality of an item, and how item analysis, in general, can be used to address these issues.
2. Describe general guidelines for collecting pilot data for item analysis, including how following these guidelines can improve item analysis results.
3. Identify items that may have been keyed or scored incorrectly.
4. Recode variables to reverse their scoring or keyed direction.
5. Use the appropriate terms to describe the process of item analysis with cognitive vs noncognitive constructs.
6. Calculate and interpret item difficulties and compare items in terms of difficulty.
7. Calculate and interpret item discrimination indices, and describe what they represent and how they are used in item analysis.
8. Describe the relationship between item difficulty and item discrimination and identify the practical implications of this relationship.
9. Calculate and interpret alpha-if-item-deleted.
10. Utilize item analysis to distinguish between items that function well in a set and items that do not.
11. Remove items from an item set to achieve a target level of reliability.
12. Evaluate selected-response options using option analysis.
**Chapter 7: Item Response Theory**
1. Compare and contrast IRT and CTT in terms of their strengths and weaknesses.
2. Identify the two main assumptions that are made when using a traditional IRT model, regarding dimensionality and functional form or the number of model parameters.
3. Identify key terms in IRT, including probability of correct response, logistic curve, theta, IRF, TRF, SEM, and information functions.
4. Define the three item parameters and one ability parameter in the traditional IRT models, and describe the role of each in modeling performance with the IIF.
5. Distinguish between the 1PL, 2PL, and 3PL IRT models in terms of assumptions made, benefits and limitations, and applications of each.
6. Describe how IRT is utilized in item analysis, test development, item banking, and computer adaptive testing.
**Chapter 8: Factor Analysis**
1. Compare and contrast the factor analytic model with other measurement models, including CTT and IRT, in terms of their applications in instrument development.
2. Describe the differing purposes of exploratory and confirmatory factor analysis.
3. Explain how an EFA is implemented, including the type of data required and steps in setting up and fitting the model.
4. Interpret EFA results, including factor loadings and eigenvalues.
5. Use a scree plot to visually compare factors in an EFA.
6. Explain how a CFA is implemented, including the type of data required and steps in setting up and fitting the model.
5. Interpret CFA results, including factor loadings and fit indices.
**Chapter 9: Validity**
1. Define validity in terms of test score interpretation and use, and identify and describe examples of this definition in context.
2. Compare and contrast three main sources of validity evidence (content, criterion, and construct), with examples of how each type is established, including the validation process involved with each.
3. Explain the structure and function of a test outline, and how it is used to provide evidence of content validity.
4. Calculate and interpret a validity coefficient, describing what it represents and how it supports criterion validity.
5. Describe how unreliability can attenuate a correlation, and how to correct for attenuation in a validity coefficient.
6. Identify appropriate sources of validity evidence for given testing applications and describe how certain sources are more appropriate than others for certain applications.
7. Describe the unified view of validity and how it differs from and improves upon the traditional view of validity.
8. Identify threats to validity, including features of a test, testing process, or score interpretation or use, that impact validity. Consider, for example, the issues of content underrepresentation and misrepresentation, and construct irrelevant variance.
**Chapter 10: Test Evaluation**
1. Review and critique the documentation contained in a test review, test manual, or technical report, including:
a. Data collection and test administration designs,
b. Reliability analysis results,
c. Validity analysis results,
d. Scoring and reporting guidelines,
e. Recommendations for test use.
2. Compare and contrast tests using reported information.
3. Use information reported for a test to determine the appropriateness of the test for a given application.