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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 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.
Randomization
Treatment (Experimental) Variable
Experimental Design
Qualitative Data
2. A variable that falls into one of two possible classifications (for example - number of children - number of defects).
Qualitative Analysis
Random Selection
Skewness
Dichotomous Variable
3. A variable whose quantification can be broken down into extremely small units (for example - time - speed - distance).
Continuous Variable
Frequency Distributions
Covariates
Discrete Variable
4. Evaluators to make inferences about data from the sample to a compare the sixes of differences between them.
Confounding Variable
Inferential Statistics
Confidence Interval
Independent Variable
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.
Mean Score
Interval Variables
Discrete Variable
Frequency Distributions
6. Involves looking at participant's opinions - behaviors - and attributes and is often descriptive.
Discrete Variable
Stratified Random Sampling
Random Selection
Qualitative Analysis
7. Asymmetry in the distribution of sample data values.
Experimental Group
Skewness
Smile Sheet
Randomization
8. 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
Training Transfer Evaluation
Dichotomous Variable
Soft Data
balanced Scorecard Approach
9. 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
Extant Data
Confounding Variable
Intervention
10. A data point that's far removed in value from others in the data set.
Qualitative Analysis
Regression Line
Outlier
Inferential Statistics
11. 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
Random Sampling
Effect Size
Formative Evaluation
Qualitative Analysis
12. 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
Frequency Distributions
Skewness
Experimental Design
Extant Data
13. The process of assigning the sample that's drawn to different groups or treatments in the study.
Mean Score
Random Assignment
Random Selection
Reliability
14. Objective and measurable quantitative measures - whether stated in terms of frequency - percentage - proportion - or time.
Skewness
Smile Sheet
Covariates
Hard Data
15. Dividing the population into constituent parts - and then choosing sample members randomly choosing people from each age group creates a stratified random sample.
Smile Sheet
balanced Scorecard Approach
Continuous Variable
Stratified Random Sampling
16. 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
Control Group
Qualitative Analysis
Covariates
17. 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
Extraneous Variables
Intervention
Treatment (Experimental) Variable
18. The best-fitting straight line through all value pairs of correlation coefficients.
Reliability
Regression Line
Dichotomous Variable
Discrete Variable
19. Measures the success of the learner's ability to transfer and implement the learning back on the job.
Experimental Group
Training Transfer Evaluation
Standard Deviation
balanced Scorecard Approach
20. 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
Intervention
Randomization
Inferential Statistics
Split-half Reliability
21. The treatment group; those participants who receive the 'treatment.'
Dependent Variable
Nominal Data
Random Sampling
Experimental Group
22. 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.
Stratified Random Sampling
Random Selection
Experimental Design
Discrete Variable
23. Show the actual number of observations falling in each range or percentage of observations.
Significant
Mean Score
Frequency Distributions
Random Assignment
24. A type of test reliability in which one test is split into two shorter ones.
Extraneous Variables
Significant
Ordinal Variables
Split-half Reliability
25. The multiple dependent variables in a study with multiple independent variables.
Outlier
Frequency Distributions
Covariates
Random Sampling
26. 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.
Random Sampling
Confounding Variable
Extraneous Variables
Normal Distribution
27. 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.
Dichotomous Variable
Experimental Group
Confounding Variable
Random Selection
28. 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.
Frequency Distributions
Regression Line
Control Group
Independent Variable
29. Assess the impact of a training program on learning.
Continuous Variable
Covariates
Program Evaluation
Ordinal Data
30. The range where something is expected to be.
Confidence Interval
Inferential Statistics
Random Selection
Formative Evaluation
31. 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
Soft Data
Frequency Distributions
Outlier
32. The process of drawing the sample of people for a study from the population.
Random Selection
Independent Variable
Dependent Variable
Concurrent Validity
33. 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
Significant
Training Transfer Evaluation
Inferential Statistics
34. 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
Interval Variables
Stratified Random Sampling
Ordinal Data
35. 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.
Extraneous Variables
Criterion Validity
Ordinal Variables
Validity
36. A variable in which the units are in the whole numbers - or 'discrete' units (for example - number of children - number of defects).
Variance
Training Transfer Evaluation
Formative Evaluation
Discrete Variable
37. An assessment done when while its being formed.
Dependent Variable
Extant Data
Continuous Variable
Formative Evaluation
38. A nickname for the instructor and class training evaluation forms used in Level 1 evaluation.
Normal Distribution
Mean Score
Split-half Reliability
Smile Sheet
39. 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
Variance
Effect Size
Interval Variables
Soft Data
40. Is information that can be difficult to express in measures or numbers.
Qualitative Data
Criterion Validity
Independent Variable
Normal Distribution
41. 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.
Extant Data
Ordinal Data
Discrete Variable
Smile Sheet
42. Involves measuring what the practitioner intended to measure.
Correlation
Validity
Independent Variable
Dichotomous Variable
43. The extent to which an instrument agrees with the results of other instruments administered at approximately the same time to measure the same characteristics.
Qualitative Data
Confounding Variable
Covariates
Concurrent Validity
44. Frequently thought of as the 'outcome.' Or treatment variable. The dependent variable's outcome depends on the independent variable and covariates.
Covariates
Dependent Variable
Experimental Group
Hard Data
45. The ability to achieve consistent results from a measurement over time.
Reliability
Intervention
Random Selection
Selection Bias
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.
Random Selection
Ordinal Data
Nominal Data
Ordinal Variables
47. The error of distorting a statistical analysis be pre-or post selecting the samples.
Selection Bias
Soft Data
Ordinal Variables
Normal Distribution
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.
Extant Data
Standard Deviation
Normal Distribution
balanced Scorecard Approach
49. Undesirable variables that influence the relationship between variables an evaluator is examining.
Dichotomous Variable
Intervention
Stratified Random Sampling
Extraneous Variables
50. Make it possible to rank order the items measured and quantify and compare the sizes of differences between them.
Correlation
Interval Variables
Concurrent Validity
Variance