Exam 6: Training Evaluation

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Evaluation designs without pre-test or comparison groups are most appropriate when ________.

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In the context of big data, ________ refers to the huge amount of data that is being generated and the speed with which it must be evaluated, captured, and made useful.

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In the context of big data, ________ refers to the large number of sources and types of data.

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Describe three ways to minimize threats to validity.

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The believability of study results refers to external validity.

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________ refers to the process of collecting the outcomes needed to determine whether training is effective.

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Which of the following statements is most true of comparison groups?

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Which of the following is an affective learning outcome?

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Evaluation designs without pre-test or comparison groups are most appropriate when companies are interested in determining how much change has occurred in trainees.

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Behavior and skill-based outcomes are best measured by ________.

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A reliable test includes items for which the meaning or interpretation does not change over time.

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It is important to conduct a return on investment (ROI) analysis for nearly all training programs.

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The Hawthorne effect refers to employees performing at a low level because of the attention they receive.

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ROI (return on investment) would be considered a Level-4 outcome in Kirkpatrick's model of training evaluation.

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A comparison group refers to a group of employees who participate in the evaluation study but do not attend the training program.

(True/False)
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A "pencil-and-paper" test is the best means for measuring skill-based outcomes.

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________ refers to concrete examples to show how learning has led to results that a company finds worthwhile and credible.

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Which of the following statements best differentiates formative evaluation from summative evaluation?

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Which of the following statements is true of Solomon four-group evaluation design?

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Formative evaluation usually involves collecting quantitative data through tests or objective measures of performance.

(True/False)
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