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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. Objective and measurable quantitative measures - whether stated in terms of frequency - percentage - proportion - or time.
Covariates
Effect Size
Hard Data
Training Transfer Evaluation
2. Numbers or variables used to classify a system - as in digits in a telephone number or numbers on a football player's jersey.
Ordinal Data
Intervention
Nominal Data
Training Transfer Evaluation
3. A variable that falls into one of two possible classifications (for example - number of children - number of defects).
Normal Distribution
Training Transfer Evaluation
Program Evaluation
Dichotomous Variable
4. Involves looking at participant's opinions - behaviors - and attributes and is often descriptive.
Independent Variable
Confounding Variable
Qualitative Analysis
Criterion Validity
5. 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.
Experimental Group
Continuous Variable
Reliability
Mean Score
6. 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.
Dichotomous Variable
Randomization
Smile Sheet
Intervention
7. 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
Dichotomous Variable
Interval Variables
Frequency Distributions
Soft Data
8. 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
Dichotomous Variable
Normal Distribution
Confidence Interval
Effect Size
9. Make it possible to rank order the items measured and quantify and compare the sizes of differences between them.
Dichotomous Variable
Training Transfer Evaluation
Stratified Random Sampling
Interval Variables
10. The treatment group; those participants who receive the 'treatment.'
Regression Line
Effect Size
Standard Deviation
Experimental Group
11. The range where something is expected to be.
Qualitative Analysis
Confidence Interval
Covariates
Reliability
12. 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.
Interval Variables
Stratified Random Sampling
Program Evaluation
Ordinal Variables
13. The term researchers and statisticians use to define the 'manipulated' variable in an experiment. An 'experiment group' receives a treatment (for example - attends a training program) - and a control group does not.
Normal Distribution
Treatment (Experimental) Variable
Validity
Control Group
14. 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
Criterion Validity
Variance
Frequency Distributions
Standard Deviation
15. Assess the impact of a training program on learning.
Dependent Variable
Program Evaluation
Random Sampling
Continuous Variable
16. Undesirable variables that influence the relationship between variables an evaluator is examining.
Treatment (Experimental) Variable
Formative Evaluation
Normal Distribution
Extraneous Variables
17. The multiple dependent variables in a study with multiple independent variables.
Hard Data
Qualitative Data
Covariates
Continuous Variable
18. 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
Significant
Control Group
Random Sampling
19. 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.
Standard Deviation
Ordinal Variables
Random Sampling
Effect Size
20. 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
Validity
Ordinal Data
Interval Variables
21. Means probably true (not by chance) in statistics.
Variance
Dichotomous Variable
Significant
Interval Variables
22. The extent to which an instrument agrees with the results of other instruments administered at approximately the same time to measure the same characteristics.
Concurrent Validity
Randomization
Program Evaluation
Discrete Variable
23. The process of assigning the sample that's drawn to different groups or treatments in the study.
Confidence Interval
Random Assignment
Treatment (Experimental) Variable
Standard Deviation
24. The best-fitting straight line through all value pairs of correlation coefficients.
Qualitative Analysis
Experimental Group
Selection Bias
Regression Line
25. 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.
Hard Data
Formative Evaluation
Discrete Variable
Correlation
26. 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
Extant Data
Skewness
Confounding Variable
Treatment (Experimental) Variable
27. 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.
Extant Data
Confounding Variable
Experimental Design
Control Group
28. Frequently thought of as the 'outcome.' Or treatment variable. The dependent variable's outcome depends on the independent variable and covariates.
Hard Data
Variance
Mean Score
Dependent Variable
29. A model for measuring effectiveness through four perspectives: the customer perspective - the innovation and learning perspective - the internal business perspective - and the financial perspective.
Dichotomous Variable
balanced Scorecard Approach
Experimental Group
Ordinal Data
30. A nickname for the instructor and class training evaluation forms used in Level 1 evaluation.
Hard Data
Inferential Statistics
Smile Sheet
Split-half Reliability
31. The process of drawing the sample of people for a study from the population.
Effect Size
Covariates
Criterion Validity
Random Selection
32. 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.
Correlation
Ordinal Data
Variance
Split-half Reliability
33. 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.
Program Evaluation
balanced Scorecard Approach
Confounding Variable
Standard Deviation
34. Measures the success of the learner's ability to transfer and implement the learning back on the job.
Training Transfer Evaluation
Interval Variables
Selection Bias
Program Evaluation
35. A variable whose quantification can be broken down into extremely small units (for example - time - speed - distance).
Ordinal Data
Skewness
Stratified Random Sampling
Continuous Variable
36. 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
balanced Scorecard Approach
Normal Distribution
Control Group
Randomization
37. A variable in which the units are in the whole numbers - or 'discrete' units (for example - number of children - number of defects).
Experimental Group
Discrete Variable
Extant Data
Independent Variable
38. Show the actual number of observations falling in each range or percentage of observations.
Frequency Distributions
Inferential Statistics
Independent Variable
Continuous Variable
39. Is information that can be difficult to express in measures or numbers.
Nominal Data
Ordinal Variables
Confidence Interval
Qualitative Data
40. A type of test reliability in which one test is split into two shorter ones.
Experimental Group
Split-half Reliability
Mean Score
Intervention
41. 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.
Concurrent Validity
Random Sampling
Treatment (Experimental) Variable
Independent Variable
42. Evaluators to make inferences about data from the sample to a compare the sixes of differences between them.
Confounding Variable
Inferential Statistics
Random Selection
Dichotomous Variable
43. An assessment done when while its being formed.
Ordinal Variables
Reliability
Formative Evaluation
Independent Variable
44. 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.
Mean Score
Criterion Validity
Discrete Variable
Program Evaluation
45. The error of distorting a statistical analysis be pre-or post selecting the samples.
Random Sampling
Covariates
Frequency Distributions
Selection Bias
46. Asymmetry in the distribution of sample data values.
Skewness
Random Selection
Validity
Criterion Validity
47. A data point that's far removed in value from others in the data set.
Soft Data
Outlier
Stratified Random Sampling
Concurrent Validity
48. Involves measuring what the practitioner intended to measure.
Mean Score
Correlation
Validity
Significant
49. 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.
Random Sampling
Extraneous Variables
Normal Distribution
Control Group
50. 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).
Independent Variable
Intervention
Regression Line
balanced Scorecard Approach