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