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