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Extracting Value From Post-course Evaluations Using Advanced Statistical Techniques
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| Presenter(s):
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| Michele Graham, KPMG LLP, magraham@kpmg.com
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| John Mattox, KPMG LLP, jmattox@kpmg.com
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| Heather Maitre, KPMG LLP, hmaitre@kpmg.com
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| Peter Sanacore, KPMG LLP, psanacore@kpmg.com
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| Abstract:
Is your learning organization swimming in a sea of unused training evaluation data? In his book 'Super Crunchers: Why Thinking-By-Numbers is the New Way to Be Smart' Ayers (2007) describes how massive data sets, powerful analytics tools and a keen statistical mind can turn data into action-oriented information for businesses. This thinking applies to training evaluation data. For instance, many organizations collect large amounts of Level 1 (Kirkpatrick, 1998) data, but do not take full advantage of the benefits these results can yield. By using advanced statistical techniques to analyze this data store, you can improve training, enhance job performance and gain competitive advantage. This paper presents the four key steps a learning organization should take when gathering and analyzing data to bring value to the business.
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It's a Beloved Part of Our Culture, But We Aren't Sure It Works: An Evaluation of a New Employee Orientation Program
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| Presenter(s):
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| Meghan Lowery, Southern Illinois University at Carbondale, mrlowery@siu.edu
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| Joel Nadler, Southern Illinois University at Carbondale, jnadler@siu.edu
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| Abstract:
A mid-sized national organization with a new employee orientation training program sought a combination needs assessment and process evaluation. The training program is a week-long, intensive experience that uses and hands-on activities. This practice is very costly, and organizational decision-makers wanted to know if the current training was effective and if the training could be shortened or even eliminated through the use of an e-training system. Decision-makers sought to determine not only if the training was effective, but also if the training could be shortened or even adapted to incorporate online portions as e-training. A pre-test post-test design measured improvement in general knowledge and understanding of learning objectives. Results indicated significant improvement in knowledge and understanding based on learning objectives. The evaluation process and the importance of considering organizational culture when assessing need for change will be discussed.
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Towards an Evaluative Model for Determining the Value of Faculty Diversity and Inclusion in Higher Education
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| Presenter(s):
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| Ray Haynes, Indiana University, rkhaynes@indiana.edu
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| Eric Abdullateef, Directed Study Services, eric.abdullateef@mac.com
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| Abstract:
This paper presentation offers a dynamic model for determining the value of diverse faculty in higher education. It rests on the assumption that the administrations of predominantly white higher education institutions continuously grapple with the dilemma of achieving racial and ethnic diversity among its faculties. The model proffered is evaluative because it could be used to evaluate existing higher education diversity programs. The model is transformative because it creates a paradigm shift from a socio-economic view of diversity to an expanded view that incorporates cultural and ecological dimensions that are rarely considered or appropriately valued when faculty-of-color are hired to diversify higher education institutions.
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