UNT Theses and Dissertations - Browse


Students' Criteria for Course Selection: Towards a Metadata Standard for Distributed Higher Education

Description: By 2007, one half of higher education students are expected to enroll in distributed learning courses. Higher education institutions need to attract students searching the Internet for courses and need to provide students with enough information to select courses. Internet resource discovery tools are readily available, however, users have difficulty selecting relevant resources. In part this is due to the lack of a standard for representation of Internet resources. An emerging solution is metadata. In the educational domain, the IEEE Learning Technology Standards Committee (LTSC) has specified a Learning Object Metadata (LOM) standard. This exploratory study (a) determined criteria students think are important for selecting higher education courses, (b) discovered relationships between these criteria and students' demographic characteristics, educational status, and Internet experience, and (c) evaluated these criteria vis-à-vis the IEEE LTSC LOM standard. Web-based questionnaires (N=209) measured (a) the criteria students think are important in the selection of higher education courses and (b) three factors that might influence students' selections. Respondents were principally female (66%), employed full time (57%), and located in the U.S. (89%). The chi square goodness-of-fit test determined 40 criteria students think are important and exploratory factor analysis determined five common factors among the top 21 criteria, three evaluative factors and two descriptive. Results indicated evaluation criteria are very important in course selection. Spearman correlation coefficients and chi-square tests of independence determined the relationships between the importance of selection criteria and demographic characteristics, educational status, and Internet experience. Four profiles emerged representing groups of students with unique concerns. Side by side analysis determined if the IEEE LTSC LOM standard included the criteria of importance to students. The IEEE LOM by itself is not enough to meet students course selection needs. Recommendations include development of a metadata standard for course evaluation and accommodation of group differences in ...
Date: August 2000
Creator: Murray, Kathleen R.
Partner: UNT Libraries

Detecting the Presence of Disease by Unifying Two Methods of Remote Sensing.

Description: There is currently no effective tool available to quickly and economically measure a change in landmass in the setting of biomedical professionals and environmental specialists. The purpose of this study is to structure and demonstrate a statistical change-detection method using remotely sensed data that can detect the presence of an infectious land borne disease. Data sources included the Texas Department of Health database, which provided the types of infectious land borne diseases and indicated the geographical area to study. Methods of data collection included the gathering of images produced by digital orthophoto quadrangle and aerial videography and Landsat. Also, a method was developed to identify statistically the severity of changes of the landmass over a three-year period. Data analysis included using a unique statistical detection procedure to measure the severity of change in landmass when a disease was not present and when the disease was present. The statistical detection method was applied to two different remotely sensed platform types and again to two like remotely sensed platform types. The results indicated that when the statistical change detection method was used for two different types of remote sensing mediums (i.e.-digital orthophoto quadrangle and aerial videography), the results were negative due to skewed and unreliable data. However, when two like remote sensing mediums were used (i.e.- videography to videography and Landsat to Landsat) the results were positive and the data were reliable.
Date: May 2002
Creator: Reames, Steve
Partner: UNT Libraries