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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
11

Maximizing Information: Applications of Ideal Point Modeling and Innovative Item Design to Personality Measurement

Leeson, Heidi Vanessa January 2008 (has links)
Recent research has challenged the way in which personality and attitude constructs are measured. Alternatives have been offered as to how non-cognitive responses are modeled, the mode of delivery used when administrating such scales, and the impact of technology in measuring personality. Thus, the major purpose of the studies in this thesis concerns two interrelated issues of personality research, namely the way personality responses are best modeled, and the most optimal mode by which personality items are presented and associated modal issues. Three studies are presented. First, recent developments using an ideal point approach to scale construction are outlined, and an empirical study compares modeling personality items based on an ideal point approach (generalized graded unfolding model; GGUM) and a dominance approach (graded response model: GRM). Second, an extensive review of literature pertaining to the mode effect when transferring paper-and-pencil measures to screen was conducted, in addition to a review of the various types of computerized and innovative items and their associated psychometric information. Finally, nine innovative items were developed using various multimedia features (e.g., video, graphics, and audio) to ascertain the advantages of these methods to present items constructed to elicit response behavior underlying ideal point approaches, namely, typical response behavior. It was found that the dominance IRT model continued to produce superior model-data fit for most items, more attention needs to be placed on developing principles for constructing ideal point type items, the web-based version supplied 20% more construct information than the paper version, and innovative items seem to provide more data-model fit for students with lower personality attributes. While the innovative items may require more initial outlay in terms of time and development costs, they have the capacity to provide more information regarding test-takers’ personality levels, potentially using fewer items.
12

Maximizing Information: Applications of Ideal Point Modeling and Innovative Item Design to Personality Measurement

Leeson, Heidi Vanessa January 2008 (has links)
Recent research has challenged the way in which personality and attitude constructs are measured. Alternatives have been offered as to how non-cognitive responses are modeled, the mode of delivery used when administrating such scales, and the impact of technology in measuring personality. Thus, the major purpose of the studies in this thesis concerns two interrelated issues of personality research, namely the way personality responses are best modeled, and the most optimal mode by which personality items are presented and associated modal issues. Three studies are presented. First, recent developments using an ideal point approach to scale construction are outlined, and an empirical study compares modeling personality items based on an ideal point approach (generalized graded unfolding model; GGUM) and a dominance approach (graded response model: GRM). Second, an extensive review of literature pertaining to the mode effect when transferring paper-and-pencil measures to screen was conducted, in addition to a review of the various types of computerized and innovative items and their associated psychometric information. Finally, nine innovative items were developed using various multimedia features (e.g., video, graphics, and audio) to ascertain the advantages of these methods to present items constructed to elicit response behavior underlying ideal point approaches, namely, typical response behavior. It was found that the dominance IRT model continued to produce superior model-data fit for most items, more attention needs to be placed on developing principles for constructing ideal point type items, the web-based version supplied 20% more construct information than the paper version, and innovative items seem to provide more data-model fit for students with lower personality attributes. While the innovative items may require more initial outlay in terms of time and development costs, they have the capacity to provide more information regarding test-takers’ personality levels, potentially using fewer items.

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