Thesis (M.S.)--Worcester Polytechnic Institute. / Keywords: cognitive model; model-tracing; intelligent tutoring system; tutoring; artificial intelligence. Includes bibliographical references (p. 55-57).

Thesis (Ph. D.)--University of Oregon, 2003. / Typescript. Includes vita and abstract. Includes bibliographical references (leaves 425-442). Also available for download via the World Wide Web; free to University of Oregon users.

Thesis (Ph. D.)--University of Missouri-Columbia, 2001. / Typescript. Vita. Includes bibliographical references (leaves 174-192). Also available on the Internet.

Thesis (Ph. D.)--University of Texas at Austin, 2001. / Vita. Includes bibliographical references (leaves 213-220). Available also in a digital version from Dissertation Abstracts.

Thesis (Ph. D.)--Ohio State University, 2003. / Title from first page of PDF file. Document formatted into pages; contains xii, 148 p.; also includes graphics (some col.). Includes abstract and vita. Advisor: Paul E. Post, College of Education. Includes bibliographical references (p. 122-126).

Computer-Assisted Instruction (CAI) offers the potential to deliver cognitive and meta-cognitive strategies in mathematical word problem-solving for students with mathematics difficulties. However, there is a lack of commercially available CAI programs with cognitive and meta-cognitive strategies for mathematical word problemsolving that pay particular attention to the critical design features for students with mathematics difficulties. Therefore, empirical evidence regarding the effects of CAI program with cognitive and meta-cognitive strategies on the word problem-solving of students with mathematics difficulties has not been found. Considering the imperative need for a CAI program with cognitive and metacognitive strategies for students with mathematics difficulties, an interactive multimedia software, ‘Math Explorer,’ was designed, developed, and implemented to teach one-step addition and subtraction word problem-solving skills to students with mathematics difficulties. Math Explorer incorporates: (a) four-step cognitive strategies and corresponding three-step meta-cognitive strategies adapted from the research on cognitive and meta-cognitive strategies, and (b) instruction, interface, and interaction design features of CAI identified as crucial for successful delivery of cognitive and metacognitive strategies for students with mathematics difficulties. The purpose of this study was to investigate the effectiveness of Math Explorer, which was designed to be a potential tool to deliver cognitive and meta-cognitive strategy instruction in one-step addition and subtraction word problem-solving. Three research questions guided this study: (a) To what extent does the use of Math Explorer affect the accuracy performance of students with mathematics difficulties in grades 2-3 on computer-based tasks with one-step addition and subtraction word problem-solving?, (b) To what extent does the use of Math Explorer generalize to the accuracy performance of students with mathematics difficulties in grades 2-3 on paper/pencil-based tasks with one-step addition and subtraction word problem-solving?, and (c) To what extent does the use of Math Explorer maintain the accuracy performance of students with mathematics difficulties in grades 2-3 on computer- and paper/pencilbased tasks with one-step addition and subtraction word problem-solving? A multiple probe across subjects design was used for the study. Four students with mathematics difficulties participated in the pre-experimental (i.e., introduction; screening test; and computer training I) and experimental (i.e., baseline, computer training II, intervention, and follow-up) sessions over an 18-week period. Each week of the intervention phase, the students received an individual 20- to 30-minute Math Explorer intervention, at most, five days. After each intervention, they took the 10-minute computer- or paper/pencil-based tests developed by the researcher. The intervention phase for each student lasted five to seven weeks. Two weeks after termination of the intervention phase, their accuracy performance on the computer- and paper/pencil-based tests were examined during the follow-up phases. The findings of the study revealed that all four of the students were able to use the cognitive and meta-cognitive strategies to solve the addition and subtraction word problems and improved their accuracy performance on the computer-based tests. Their improved accuracy performance found on the computer-based tests was successfully transferred to the paper/pencil-based tests. About two weeks after termination of the intervention phase, except for one student who had many absences and behavioral problems during the extended intervention phase, the three students successfully maintained their improved accuracy performance during the follow-up phase. Taken together, the findings of the study clearly provide evidence that Math Explorer is an effective method for teaching one-step addition and subtraction word problem-solving skills to students with mathematics difficulties and suggest that the instruction, interface, and interaction design features of CAI program is carefully designed to produce successful mathematical performance of students with mathematics difficulties. Limitations of the research and implications for practice and future research were discussed. / text

The purpose of this quasi-experimental study was to examine the comparative effects of multimedia anchored instruction (MAI) to analog video instruction (AVI) and to teacher-directed, lecture- and text-based instruction (TDI) on the knowledge, beliefs, and skills of preservice teachers. Previous teacher education research had raised important questions about the paucity of existing studies investigating whether video-based technologies such as MAI were more effective or efficient than other instructional practices, the lack of a theoretical foundation or supporting empirical evidence for most technology practices, and insufficient information identifying which instructional features of technology-based practices impact learning and in what ways. In this study, 6 university instructors who taught introductory coursework in behavior management from 5 schools across the country volunteered to participate and were randomly assigned to 1 of the 3 instructional conditions. Their preservice teacher students received MAI, AVI, or TDI instruction on the Functional Behavioral Assessment (FBA) process. Measures included a knowledge test, a beliefs survey, a performance test of skills, and a satisfaction survey. Results of the study confirmed previous findings that participants exposed to MAI learned more than with other methods, with students in the MAI group performing significantly better than students in the TDI group on a test of content knowledge. The MAI group also outperformed the AVI group, although results were not significant. Students in all groups significantly increased their self-efficacy, ableness, and willingness to manage challenging behavior. There were no significant differences between groups on the skills measure, although mean differences suggested the MAI group was better able to perform the FBA process. Instructor and student satisfaction surveys reported technical difficulties in the MAI module and video case study. Instructors found the content to be aligned with evidence-based practices and their own beliefs about managing challenging behavior. Students in the MAI condition reported finding the instruction most interesting and felt best prepared to conduct the case study. Overall, study findings suggest that MAI is an effective approach for increasing knowledge, developing beliefs, and promoting skills for preservice teachers. / text

published_or_final_version / Linguistics / Doctoral / Doctor of Philosophy

Critical thinking is widely acknowledged as crucial for 21st century learners to be able to tackle the complex tasks arising every day in a rapidly changing world. Earlier critical thinking research has mostly focused on the related micro-skills, which have been criticized as inadequate. Recent studies have placed more emphasis on nurturing the dispositions towards critical thinking. Another trend in critical thinking research is the realization that good performance on generic critical thinking skills tests does not guarantee critical thinking performance in the real world. In line with the recent trends in critical thinking development, educators have shown growing interest in fostering critical thinking skills and dispositions in students through collaborative inquiry in authentic problem-solving contexts. However, empirical research that examines students’ critical thinking behavior while they engage in extended collaborative inquiry is rare. Further, it is not clear whether differences in students’ critical thinking abilities contribute to differences in their engagement and learning outcomes in collaborative inquiry. This study aims to investigate the relationship between students’ critical thinking and the quality of their collaborative inquiry. The study involved a class of secondary two students studying a humanities module through collaborative inquiry involving the use of an online platform. Given the debates over the value of different methods of measuring critical thinking, this study first seeks to explore the relationship between three different critical thinking tests: two standardized surveys on generic skills and dispositions, and a constructed-response test on context-specific skills. Second, this study examines whether students with higher critical thinking scores are better able to apply critical thinking to real-life situations. This is done through analyzing students’ critical thinking behaviors exhibited in the context of authentic problem solving. Third, this study explores the relationship between students’ critical thinking behavior and their knowledge building engagement in the learning process. Finally, this study uses the standardized tests to determine whether there is any significant change in the students’ critical thinking ability after a sustained engagement in collaborative inquiry to tackle an authentic problem. The analysis revealed a number of interesting findings. First, the three critical thinking tests are related but measure different aspects of critical thinking. Second, compared with traditional standardized surveys, the context-specific critical thinking test is a better indicator of the likelihood of the students to autonomously apply critical thinking in authentic problem-solving contexts. Third, critical thinking behaviors exhibited by students contributed to their engagement in knowledge building. Fourth, there was a statistically significant increase in students’ critical thinking dispositions after the extended collaborative inquiry of an authentic problem. The study has both theoretical and methodological implications. The study has both theoretical and educational implications. It deepens our understanding of the relationship between critical thinking and computer-supported collaborative inquiry. This study has provided strong evidence that traditional measures of critical thinking cannot predict the quality of students’ critical thinking engagement in authentic problem-solving contexts. Further, it also provides empirical support the theoretical claim that engaging students in knowledge building activities will enhance their critical thinking skills and dispositions. / published_or_final_version / Education / Doctoral / Doctor of Philosophy

This study aims to investigate the automated question detection and classification methods to support teachers in monitoring the progression of discussion in Computer-Supported Collaborative Learning (CSCL) discourse of Hong Kong students. Questioning is an important component of CSCL. Through the analysis of question types in CSCL discourse, teachers may probably get a general idea of how an inquiry is constructed. This study is an attempt to take up this time-consuming task of question classification with the techniques developed from machine learning. In general, the performance of machine learning algorithms will improve by increasing the amount of empirical data for training. The amount of training data is a determining factor for the performance of machine learning algorithms. The machine learning based question classification algorithms may not able to detect those question types with a small amount of training data. In order not to miss out those questions, an extra step to detect the occurrence of all question types might be needed. One Chinese and one English datasets are collected from an online discussion platform. These datasets are selected for comparing the performance of question detection and classification in the two languages, and a sentence is defined as the unit of analysis. Question detection is a process to distinguish questions from other types of discourse act. A hybrid method is proposed to combine the rule-based question mark method and machine-learning-based syntax method for question detection. This method achieves 94.8% f1-score and 98.9% accuracy in English question detection and 94.8% f1-score and 93.9% accuracy in Chinese question detection. While question detection focuses mainly on the identification of questions, question classification concentrates on the categorization of questions. The literature showed that the tree kernel method is almost a standardized method for question classification. The classification of English verification and reason questions using tree kernel method can both attained f1-score above 80%. Though the precision of Chinese question classification using the same settings remains at a similar level, the recall drops greatly. This result indicates that the syntax-based tree kernel method may not be appropriate for classifying questions in Chinese languages. In order to improve on the Chinese question classification result, Case-Based Reasoning (CBR) is introduced. CBR is a method to retrieve example case(s) which shares the maximum percentage of similarity with the test case from a database. In this study, the similarity is measured by the lexemes that composed a question. Although the implementation of the CBR method can improve the recall, it also causes the great drop of precision. Considering the high precision of tree kernel method and wide coverage of CBR method, a hybrid method is proposed to combine the two methods. The experiment result shows that f1-score of the hybrid method for multi-class classification surpasses the tree kernel and CBR methods. This indicates that the implementation of hybrid method can generally improve the result of Chinese question classification. / published_or_final_version / Education / Master / Master of Philosophy