The purpose of this paper is to develop a conceptual model which integrates the well-established US-based occupational information network (O*Net) into a competence perspective. Taking serious claims about lifelong learning, one of the biggest challenges is the assessment of tacit knowledge and competences. To tackle this challenge, we depart from four well-established competences (personal competence, social competence, methodic competence and domain competence), and integrate descriptors from the O*Net. We argue that learning outcomes (what a person should be able to do) can be made comparable and accessible when linking them with the descriptors from the O*Net. This approach is in line with the European Qualification Framework (EQF), that aims at establishing comparability of learning outcomes within the European Union and relies on theories linking individual to organizational learning.

The video game industry is a billion dollar industry with an ever-growing fan base. Massachusetts, along with other states, has begun to take an interest in further developing this dynamic industry. A problem facing many policy makers and economic developers is accurately defining the video game industry, determining the types of workers that form of human capital within its workforce and where these businesses are located. This study helps to solve this problem by converting video game credits, found in all video games, into Standard Occupational Codes to identify the types of workers who comprise the industry and by conducting spatial analysis using Public Use Microdata Samples (PUMS). It also uses the Occupational Information Network to evaluate what forms of human capital comprises the video game industry. The results show the video game workforce comprises both creative workers such as artists and musicians, but also computer programmers, engineers, and business management and marketing professionals. This workforce tends to be concentrated not only in larger U.S. metropolitan areas but also in regions with a significant high-technology workforce, college towns, and government laboratories. Also, as this diverse workforce contains a wide variety of skills and abilities, a common theme is being able to work together as a team to develop a product. This study is part of a growing body of research and initiatives to identify and to locate new, creative industries within metropolitan regions. This research will contribute to future research using occupational analysis to identify new and growing industries.

The O*NET was built to replace the Dictionary of Occupational Titles (DOT) and form a highly accessible, on-line (through the World Wide Web), common language occupational information center (Dye & Silver, 1999). This study tested the relevance of the self-rating choice and unconventional BARS format to be used by the O*NET system for occupational ratings. In addition, a new rating scale format named NBADS, was tested for improved ratings. Fifty three Incumbent raters in two occupations (Graduate teaching assistants and Secretaries) and 87 laypeople raters who have never worked in these occupations, rated 21 item-pairs (Importance and Level type questions) picked randomly from the 52 items on the original O*NET Ability questionnaire. Participants rated each of the 21 item-pairs three times, with the Level question being presented in the O*NET BARS, a Likert GRS and the NBADS formats; The importance type question was always rated using a 1-5 Likert scale. Hypothesis 1a was supported, showing a significant leniency bias across formats for self-ratings. Hypothesis 1b was mostly supported, failing to show significant leniency, elevation error or interrater agreement improvement over laypeople ratings; only the overall-error measure showed a significant improvement for incumbent raters. Hypothesis 2 was not supported, failing to show that the GRS format had any improvement on leniency, accuracy or interrater agreement over the O*NET BARS format. Hypothesis 3a was supported, showing significant leniency reduction, accuracy error reduction and higher interrater agreement using the NBADS format over the GRS format. In a similar sense, hypothesis 3b was partially supported, showing reduction in leniency effect and higher agreement using the NBADS format over the O*NET BARS format. Finally, hypothesis 4 was mostly supported, showing hardly any significant differences in the ratings of the Importance type question across the three format sessions, strengthening the idea that no other interfering variables have caused the format sessions' differences. Implications of the results are discussed. / Master of Science

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