Module Title

Module Objectives

• assess the strengths and weaknesses of corporate reactionnaires; and,
• edit corporate reactionnaires to include appropriate assessment guidelines.

• define five statistical terms (correlation, mean, standard deviation, t-test and statistical significance); and,
• provide an example of how each of the five terms can be used in training evaluations.

• name, define and illustrate 5 types of validity; and,
• name, define and illustrate 4 types of reliability.

• define an attitudinal object;
• generate an item pool;
• create a draft attitudinal instrument;
• select a scoring format;
• collect data on the draft attitudinal instrument;
• load data into a statistical software package;
• complete an item analysis; and,
• refine an attitudinal instrument based upon the item analysis results.

• examine the objective and determine the level of performance needed based on Bloom's Taxonomy;
• decide which testing format is best for your exam questions;
• create a content valid multiple choice exam; and,
• employ sixteen guidelines for creating effective multiple-choice exams.

• describe how on-the-job behavior is viewed from both the traditional and new training evaluation models;
• name three types of data collection methods used to measure on-the-job behavior;
• list the benefits and limitations of the three data collection methods;
• apply the information from modules two and three (i.e., basic statistics and reliability/validity) to measure on-the-job behavior;
• define intra and inter rater reliability; and,
• calculate intra and inter rater reliability.

• create a list of costs and benefits;
• develop criteria;
• determine a dollar value for all data;
• determine if the data fits the criteria;
• calculate the total costs and the total benefits;
• calculate a cost-benefit ration; and,
• calculate return on investment.

• name the five tiers of the new training evaluation model;
• explain the benefit of using the new model's instruments;
• create a reactionnaire with a built-in self-efficacy instrument;
• explain how the self-efficacy section of a reactionnaire aids evaluators in gathering more information than a traditional reactionnaire;
• create an attitudinal instrument;
• create a subjective norms instrument;
• create a self-efficacy instrument;
• create an external control instrument;
• create a behavioral intentions instrument;
• create an actual behavior instrument;
• prove content validity;
• explain what is a multiple regression analysis;
• prove predictive validity;
• support internal consistency reliability;
• support test-re-test reliability; and,
• analyze training effectiveness via pre and post training results.

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