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Test your basic knowledge |
Measuring And Evaluating Teaching
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Study First
Subject
:
teaching
Instructions:
Answer 50 questions in 15 minutes.
If you are not ready to take this test, you can
study here
.
Match each statement with the correct term.
Don't refresh. All questions and answers are randomly picked and ordered every time you load a test.
This is a study tool. The 3 wrong answers for each question are randomly chosen from answers to other questions. So, you might find at times the answers obvious, but you will see it re-enforces your understanding as you take the test each time.
1. The multiple dependent variables in a study with multiple independent variables.
Qualitative Data
Covariates
Split-half Reliability
Ordinal Data
2. Qualitative measures are more intangible - anecdotal - personal - and subjective - as in opinions - attitudes - assumptions - feelings - values - and desires. Qualitative data can't be objectified - and that characteristic makes this type of data val
Correlation
Interval Variables
Soft Data
Stratified Random Sampling
3. The range where something is expected to be.
Frequency Distributions
Significant
Confidence Interval
Correlation
4. Involves looking at participant's opinions - behaviors - and attributes and is often descriptive.
Experimental Design
Qualitative Analysis
Outlier
Experimental Group
5. A commonly used measure or indicator of the amount of variability of scores from the mean. The standard deviation is often used in formulas for advanced or inferential statistics.
Reliability
Nominal Data
Standard Deviation
Significant
6. Measures the success of the learner's ability to transfer and implement the learning back on the job.
Formative Evaluation
Variance
Criterion Validity
Training Transfer Evaluation
7. Each person in the population has an equal chance of being chosen for the sample. Choosing every tenth person from an alphabetical list of names - for example - creates a random sample.
Hard Data
Outlier
Interval Variables
Random Sampling
8. The extent to which an instrument agrees with the results of other instruments administered at approximately the same time to measure the same characteristics.
Criterion Validity
Covariates
Interval Variables
Concurrent Validity
9. Is a particular way in which observation tend to pile up around a particular value rather than be spread evenly across a range of values.
Inferential Statistics
Qualitative Data
Normal Distribution
Treatment (Experimental) Variable
10. Undesirable variables that influence the relationship between variables an evaluator is examining.
Regression Line
Extraneous Variables
Intervention
Dichotomous Variable
11. The process of assigning the sample that's drawn to different groups or treatments in the study.
Experimental Design
Correlation
Random Selection
Random Assignment
12. A way of quantifying the difference - using standard deviation - between two groups. For example - if one group (the treatment group) has had an experimental treatment and the other (the control group) has not - the effect size is a measure of the ef
Extant Data
Significant
Effect Size
Validity
13. A group of participants in an experiment that's equal in all ways to the experimental group - except the control group doesn't receive the experimental treatment.
Variance
Control Group
Ordinal Data
Program Evaluation
14. A variable in which the units are in the whole numbers - or 'discrete' units (for example - number of children - number of defects).
Mean Score
Qualitative Data
Discrete Variable
Soft Data
15. The process of drawing the sample of people for a study from the population.
Control Group
Smile Sheet
balanced Scorecard Approach
Random Selection
16. The most robust - or least affected by the presence of extreme values (outliers) - of the three types of central tendency because each number in the data set has an impact on its (mean) value.
Mean Score
Split-half Reliability
Significant
Hard Data
17. Dividing the population into constituent parts - and then choosing sample members randomly choosing people from each age group creates a stratified random sample.
Stratified Random Sampling
Independent Variable
Qualitative Analysis
Extant Data
18. The error of distorting a statistical analysis be pre-or post selecting the samples.
Dependent Variable
Selection Bias
Skewness
Random Assignment
19. A measure of how spread out a distribution is. It's calculated as the average squared deviation of each number from the mean of a data set
Extraneous Variables
Variance
Discrete Variable
Randomization
20. A nickname for the instructor and class training evaluation forms used in Level 1 evaluation.
Ordinal Variables
Nominal Data
Intervention
Smile Sheet
21. Numbers or variables used to classify a system - as in digits in a telephone number or numbers on a football player's jersey.
Nominal Data
Program Evaluation
Concurrent Validity
Validity
22. Is information that can be difficult to express in measures or numbers.
Qualitative Data
Selection Bias
Inferential Statistics
Outlier
23. Variable that make it possible to rank order items measured in terms of which has less and which has more of the quality represented by the variable.
Experimental Group
Ordinal Variables
Criterion Validity
Experimental Design
24. An assessment done when while its being formed.
Training Transfer Evaluation
Mean Score
Experimental Design
Formative Evaluation
25. The process of organizing an experiment properly to ensure that the right type of data - and enough of it - is available to answer questions of interest as clearly and efficiently as possible.
Intervention
Skewness
Smile Sheet
Experimental Design
26. The best-fitting straight line through all value pairs of correlation coefficients.
Split-half Reliability
Program Evaluation
Regression Line
Ordinal Data
27. Evaluators to make inferences about data from the sample to a compare the sixes of differences between them.
Frequency Distributions
Experimental Group
Stratified Random Sampling
Inferential Statistics
28. Assess the impact of a training program on learning.
Program Evaluation
Mean Score
Concurrent Validity
Significant
29. The extent to which the assessment can predict or agree with external constructs. Criterion validity is determined by looking at the correlation between the instrument and the criterion measure.
Confidence Interval
Criterion Validity
Confounding Variable
Random Sampling
30. A data point that's far removed in value from others in the data set.
Significant
Outlier
Independent Variable
Extraneous Variables
31. Archival or existing records - reports - and data that may be available inside or outside an organization. Examples include - job descriptions - competency models - benchmarking reports - annual reports - financial statements - strategic plans - miss
Standard Deviation
Extant Data
Treatment (Experimental) Variable
Dependent Variable
32. A type of test reliability in which one test is split into two shorter ones.
Dichotomous Variable
Nominal Data
Randomization
Split-half Reliability
33. A variable whose quantification can be broken down into extremely small units (for example - time - speed - distance).
Ordinal Variables
Continuous Variable
Criterion Validity
Discrete Variable
34. Involves measuring what the practitioner intended to measure.
Concurrent Validity
Control Group
Intervention
Validity
35. The variable that influences the dependent variable. Age - seniority - gender - shift - level of education - and so on may all be factors (independent variables) that influence a person's performance (the dependent variable).
Covariates
Independent Variable
Stratified Random Sampling
Split-half Reliability
36. Show the actual number of observations falling in each range or percentage of observations.
Continuous Variable
Frequency Distributions
Independent Variable
Dichotomous Variable
37. Make it possible to rank order the items measured and quantify and compare the sizes of differences between them.
Qualitative Data
Soft Data
Effect Size
Interval Variables
38. The treatment group; those participants who receive the 'treatment.'
Qualitative Data
Experimental Group
Validity
Mean Score
39. A model for measuring effectiveness through four perspectives: the customer perspective - the innovation and learning perspective - the internal business perspective - and the financial perspective.
balanced Scorecard Approach
Interval Variables
Covariates
Ordinal Data
40. Asymmetry in the distribution of sample data values.
Skewness
Mean Score
Ordinal Variables
Ordinal Data
41. A measure of the relationship between two or more variables; if one changes - the other is likely to make a corresponding change. If such a change moves the variables in opposite directions - it is a negative correlation.
Correlation
Smile Sheet
Regression Line
Variance
42. A variable that falls into one of two possible classifications (for example - number of children - number of defects).
Experimental Design
Dichotomous Variable
balanced Scorecard Approach
Regression Line
43. The ability to achieve consistent results from a measurement over time.
Experimental Design
Regression Line
Reliability
Interval Variables
44. Means probably true (not by chance) in statistics.
Confidence Interval
Significant
Randomization
balanced Scorecard Approach
45. Frequently thought of as the 'outcome.' Or treatment variable. The dependent variable's outcome depends on the independent variable and covariates.
Formative Evaluation
Criterion Validity
Discrete Variable
Dependent Variable
46. Another name for a solution or set of solutions - usually a combination of (outliners) - of the three types of central tendency because each number in the data set has an impact on its (mean) value.
Intervention
Significant
Qualitative Analysis
Extraneous Variables
47. Numbers or variables that make it possible to rank order items measured in terms of which has less and which has more of the quality represented by the variable.
Training Transfer Evaluation
Ordinal Data
Frequency Distributions
Qualitative Data
48. An unknown or uncontrolled variable that produces an effect in experimental setting. A confounding variable is an independent variable that the evaluator didn't somehow recognize or control. It becomes a variable that confounds the experiment.
Confounding Variable
Ordinal Variables
Ordinal Data
Effect Size
49. Objective and measurable quantitative measures - whether stated in terms of frequency - percentage - proportion - or time.
Ordinal Variables
Stratified Random Sampling
Soft Data
Hard Data
50. A method that helps diffuses the covariates across the experimental and control groups. Researchers in organizations often have multiple dependent variable with one independent variable (for example - performance
Criterion Validity
Random Selection
Randomization
Independent Variable