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