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Thesis (Ph. D.)--University of Texas at Austin, 2008. / Vita. Includes bibliographical references.

Thesis (Ph. D.)--Rutgers University, 2010. / "Graduate Program in Education." Includes bibliographical references (p. 104-108).

Thesis (Ph. D.)--University of Texas at Austin, 2006. / Vita. Includes bibliographical references.

The research reported in this thesis investigated issues relating to the use of computer-assisted assessment in Higher Education through the design, implementation and evaluation of a computer-adaptive test (CAT) for the assessment of and provision of feedback to Computer Science undergraduates. The CAT developed for this research unobtrusively monitors the performance of students during a test, and then employs this information to adapt the sequence and level of difficulty of the questions to individual students. The information about each student performance obtained through the CAT is subsequently employed for the automated generation of feedback that is tailored to each individual student. In the first phase of the research, a total of twelve empirical studies were carried out in order to investigate issues related to the adaptive algorithm, stakeholders’ attitude, and validity and reliability of the approach. The CAT approach was found to be valid and reliable, and also effective at tailoring the level of difficulty of the test to the ability of individual students. The two main groups of stakeholders, students and academic staff, both exhibited a positive attitude towards the CAT approach and the user interface. The second phase of the research was concerned with the design, implementation and evaluation of an automated feedback prototype based on the CAT approach. Five empirical studies were conducted in order to assess stakeholders’ attitude towards the automated feedback, and its effectiveness at providing feedback on performance. It was found that both groups of stakeholders exhibited a positive attitude towards the feedback approach. Furthermore, it was found that the approach was effective at identifying the strengths and weaknesses of individual students, and at supporting the adaptive selection of learning resources that meet their educational needs. This work discusses the implications of the use of the CAT approach in Higher Education assessment. In addition, it demonstrates the ways in which the adaptive test generated by the CAT approach can be used to provide students with tailored feedback that is timely and useful.

The Armed Services Vocational Aptitude Battery (ASVAB) is a test that approximately 700,000 students in 12,000 high schools take each year to determine military occupation placement. Form Assembly for the ASVAB refers to the selection of 20-35 questions, known as items, from an item pool of approximately 300 items to create a paper and pencil test in one of its ten topics. Previous research formulates form assembly as an Integer Linear Program (ILP). The current ASVAB mostly uses a Computer Adaptive Test (CAT), which estimates an examinee's ability after the examinee answers each item and selects the next item based on prior performance. The current CAT-ASVAB implementation does not control the number of items selected from each subject (taxonomy group) for a test. This thesis introduces ILPs, previously used for form assembly, that impose taxonomy restrictions and applies them to the CAT-ASVAB. We create four ILP variations and test them against the current method of item selection, by simulating 3,500 examinees (500 examinees each for seven given ability levels). The results show that all of the ILPs have acceptable solution times for CAT use, and taxonomy restrictions can be imposed while also having more even exposure rates (the number of times an item is administered divided by the number of examinees) than the current implementation of the CAT-ASVAB. A variation that relaxes most of the binary variables and constrains the difficulty of each item to be within a predetermined magnitude of the current ability estimate, performs the best in terms of item exposure (for both under and over-utilized items) and error between an examinee's estimated ability level and actual ability level. / Defense Manpower Data Center author (civilian).

Chi-Keung Leung. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2001. / Includes bibliographical references (p. 138-146). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Mode of access: World Wide Web. / Abstracts in English and Chinese.

Thesis (Ph. D.)--University of North Texas, Aug., 2009. / Title from title page display. Includes bibliographical references.

Thesis (Ph. D.)--University of Texas at Austin, 2003. / Vita. Includes bibliographical references. Available also from UMI Company.

A multi-stage test (MST) design is an alternative design for the delivery of automated tests. While computerized adaptive tests (CAT) have dominated testing for the past three decades, increasing interest has been focused on the MST because it offers two advantages that CAT does not: Test sponsors and test developers can see an entire test before administration because it is pre-constructed from sets of modules of test items, and within a module examinees may skip forward and back through test items and make changes to previously answered items. Due to the dominance of CAT, little research has been devoted to differing MST designs with regard to the number of items per stage and routing rules that direct the selection of the next module after a previous module has been completed. This research used simulated response data for a large national test and the generalized partial credit model to compare a CAT to one of three MST designs that had either decreasing numbers of items per stage, increasing number of items per stage, or the same number of items per stage, and one of three routing rules, maximum information, fixed [theta], or number-right routing. As anticipated, CAT had the best performance with respect to estimating proficiency and item pool use. Among the MSTs, the MST with increasing numbers of items per stage performed the best with respect to estimating proficiency, followed by the MST with decreasing number of items per stage, and equal numbers of items per stage. By routing rule, maximum information performed the best and number-right routing performed the worst. Only one panel was constructed per MST design, so only limited comparisons of item pool use could be made. Although the MST designs did not perform as well as CAT, the differences in estimating proficiency were not large, implying that the MST design is a viable alternative to CAT. / text