Given current legislation to ensure education for students with disabilities and that institutions of higher education are required to use universal design for learning (UDL) principles, the purpose of this study was to explore the impact of video modeling on preservice teachers' knowledge, understanding and application of the three principles of UDL. Preservice teachers were randomly assigned to control or experimental groups to determine if video embedded with UDL principles impacted their thinking. Specifically, pre and posttest information of knowledge and understanding as well as self-perceived ability to teach students with disabilities using UDL was analyzed. In addition preservice teacher created lesson plans were analyzed for application of UDL principles after viewing the video intervention. Quantitative analyses were conducted to compare pre and posttest scores of the control group (n = 41) and experimental group (n =45). The quantitative analyses of knowledge, understanding

Because many general education teachers feel unprepared to provide students with disabilities with appropriate instruction, changes to teacher education programs are needed (Burdette, 2007; Smith et al., 2010). Teacher education programs need to integrate content regarding instructional methods for teaching and accommodating students with disabilities in secondary, general education classrooms (Burdette, 2007; Smith et al., 2010). The results of the research should provide insight (1) to determine if integrating instruction on UDL into preservice SGE students' instructional methods courses will increase students' knowledge of UDL and (2) to determine if integrating instruction on Universal Design for Learning (UDL) will affect how secondary social studies (SS) students design lesson plans, particularly, content delivery and student assessment, in regards to the three principles of UDL. The research design was a quantitative, quasi-experimental design. The participants in the research study were students enrolled in four content specific SGE instructional methods courses: Social Studies (SS), Language Arts (LA), Mathematics (M) and Science (S). Research question one's data were analyzed both within content area, Wilcxon test for matched pairs, and between content areas, Mann-Whitney U test for independent samples. The results from research question one indicated a significant difference (p < .05). between pre and post UDL Knowledge test scores within the SGE SS participants. Within the other three SGE content areas, M, LA, and S, subjects' UDL Knowledge pre to posttest scores did not significantly change. When each content area's difference score for the UDL knowledge pre and posttest were calculated and compared between content areas, only the SS and S pairing demonstrated a statistically significant difference score (p < .05). Data from research question two indicated no statistically significant difference (p > .05) between pre and post intervention UDL lesson plan rubric scores. The study provides impetus for future research regarding effective delivery of UDL content in teacher preparation programs. The study also provides suggestions for future researchers who may be interested in designing a similar research study. Finally, the study provides teacher education leadership with questions regarding how the three principles of UDL planning, instruction, and assessment align with the current teacher and student educational evaluation practice of standardized assessments.

In data science, machine learning methods, such as deep learning and other AI algorithms, have been widely used in many applications. These machine learning methods often have complicated model structures with a large number of model parameters and a set of hyperparameters. Moreover, these machine learning methods are data-driven in nature. Thus, it is not easy to provide a comprehensive evaluation on the performance of these machine learning methods with respect to the data quality and hyper-parameters of the algorithms. In the statistical literature, design of experiments (DoE) is a set of systematical methods to effectively investigate the effects of input factors for the complex systems. There are few works focusing on the use of DoE methodology for evaluating the quality assurance of AI algorithms, while an AI algorithm is naturally a complex system. An understanding of the quality of Artificial Intelligence (AI) algorithms is important for confidently deploying them in real applications such as cybersecurity, healthcare, and autonomous driving. In this proposal, I aim to develop a set of novel methods on the interface between experimental design and machine learning, providing a systematical framework of using DoE methodology for AI algorithms. This proposal contains six chapters. Chapter 1 provides a general introduction of design of experiments, machine learning, and surrogate modeling. Chapter 2 focuses on investigating the robustness of AI classification algorithms by conducting a comprehensive set of mixture experiments. Chapter 3 proposes a so-called Do-AIQ framework of using DoE for evaluating the AI algorithm’s quality assurance. I establish a design-of-experiment framework to construct an efficient space-filling design in a high-dimensional constraint space and develop an effective surrogate model using additive Gaussian process to enable the quality assessment of AI algorithms. Chapter 4 introduces a framework to generate continual learning (CL) datsets for cybersecurity applications. Chapter 5 presents a variable selection method under cumulative exposure model for time-to-event data with time-varying covariates. Chapter 6 provides the summary of the entire dissertation. / Doctor of Philosophy / Artificial intelligence (AI) techniques, including machine learning and deep learning algorithms, are widely used in various applications in the era of big data. While these algorithms have impressed the public with their remarkable performance, their underlying mechanisms are often highly complex and difficult to interpret. As a result, it becomes challenging to comprehensively evaluate the overall performance and quality of these algorithms. The Design of Experiments (DoE) offers a valuable set of tools for studying and understanding the underlying mechanisms of complex systems, thereby facilitating improvements. DoE has been successfully applied in diverse areas such as manufacturing, agriculture, and healthcare. The use of DoE has played a crucial role in enhancing processes and ensuring high quality. However, there are few works focusing on the use of DoE methodology for evaluating the quality assurance of AI algorithms, where an AI algorithm can be naturally considered as a complex system. This dissertation aims to develop innovative methodologies on the interface between experimental design and machine learning. The research conducted in this dissertation can serve as practical tools to use DoE methodology in the context of AI algorithms.

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BACKGROUND: The mandate to provide inclusive education in Canadian schools means that Speech-Language Pathologists (SLPs) need to be well-versed in frameworks such as Universal Design for Learning (UDL) that support learning among students with diverse backgrounds and abilities. To be responsive, professional graduate programs need resources that support teaching SLP students about UDL. PURPOSE: 1) To use an instructional design model and Knowledge Translation (KT) theory to develop educational resources about UDL for SLP graduate students; and 2) to assess feasibility of the resources and SLP students’ perceived and actual UDL knowledge change after resource implementation. METHODS: First, educational resources about UDL were created for SLP students using a process in which the first three phases of the Analysis, Design, Development, Implementation, Evaluation (ADDIE) instructional design model were combined with the Diffusion of Innovations (DOI) KT theory and supported by engagement of key SLP stakeholders. Stakeholder feedback about their involvement in the resource development process was assessed through a focus group and analyzed using conventional content analysis. Next, the last two phases of the ADDIE model were conducted in which the developed resources were implemented and evaluated with 19 SLP students over a three-hour session; resource feasibility and UDL knowledge were measured before and after the session using anonymous, web-based questionnaires. RESULTS: The novel process for developing resources was deemed suitable for creating high-quality theory-informed resources tailored to SLP students. SLP students perceived the resources to be practical and acceptable. There was a statistically significant improvement in students’ perceived UDL knowledge as well as improvements in actual UDL knowledge. CONCLUSION: Health educators could consider the described methodology when developing content-specific resources for health professional students. This thesis introduces a new set of resources that could be used to address an important gap in SLP training. / Thesis / Master of Science Rehabilitation Science (MSc) / Inclusive education in which students with diverse abilities learn together is an expectation within Canadian schools. People who work in schools, like Speech-Language Pathologists (SLPs), need to know about frameworks such as Universal Design for Learning (UDL) that identify specific strategies for supporting inclusive education. However, many SLPs do not know about UDL or how to apply this framework when they work with teachers. In this thesis, I used a new resource development process involving a rigorous resource design method with a theory that helps people use new ideas, to make educational resources about UDL for SLP graduate students. Next, I implemented and evaluated the resources with 19 SLP students at McMaster University. Students felt the resources were suitable and taught them new information about UDL. This thesis provides new teaching resources for SLP students to increase their knowledge about UDL and better prepare them for working in schools.

Students with special needs are often placed in agriculture and other CTE classes. Literature has shown that teachers often feel unprepared to deal with this population of students. The Theory of Planned Behavior framed this case study of an exemplar agriculture teacher. Evidence of the teacher's planned behavior was supported by triangulation of interviews with the teacher, special education coordinator, special education aide, and lesson plans. This triangulation also showed that the teacher is an exemplar agriculture teacher in his work with students with special needs. Multiple themes emerged from the analysis of the interviews. An important theme was the need for agriculture teachers to participate in IEP meeting either by attending in person or by providing feedback prior to the meeting. Another important theme was the need for materials to be adapted for students with special needs both within lesson plans and as needed while the teacher is teaching the lesson. Recommendations for practice include providing information about special education laws, disabling conditions, and information on utilizing Universal Design for Learning (UDL) to pre-service and in-service teachers. It is also recommended that teacher preparation programs include having pre-service teachers work with students with special needs. Professional development workshops that discuss best practices for teachers when working with students with special needs can be beneficial. It is important for teachers to realize that not all students are the same but that everyone is better served if all teachers do their best at helping students achieve their highest potential. Because in the end, we all just want to be accepted for who we are. / Doctor of Philosophy / Students with special needs are often placed in agriculture and other CTE classes. This dissertation was a case study of a model agriculture teacher. It looked at the teacher's behavior to determine if his work with students with special needs was planned. The importance of a teacher planning their behavior towards students with special needs is important from both a lesson planning viewpoint and also while the teacher is teaching. Multiple recommendations came out of the study. One recommendation included the need for programs that prepare agriculture teachers to have these individuals work with students with special needs while they are still in their teacher preparation program. Professional development workshops for current agriculture teachers should include information on best practices for working with students with special needs. It is important for teachers to realize that not all students are the same but that everyone is better served if all teachers do their best at helping students achieve their highest potential. Because in the end, we all just want to be accepted for who we are.

The goal of this study was to examine the use of a technological and engineering design based learning (T/E DBL) challenge as a strategy for facilitating student comprehension of nonfiction/informational text inclusive of graphical devices. The data for this mixed methods exploratory case study were collected using a variety of instruments which assessed the prior knowledge, general graphical device comprehension, and reading comprehension of both familiar and unfamiliar texts in order to form a detailed picture of the six participants throughout the study. The six participants were examined as whole group and as reading level dyads (below, on, and above grade level) as they progressed through three T/E DBL challenges that were developed to support graphical device comprehension instruction. T/E DBL was found to increase reader text interactions and graphical device usage, support the development of general graphical device comprehension for diagrams and tables, improve comprehension of unfamiliar science texts, and provide particular benefit to below grade level readers. The results of this study demonstrate the need for further research into the benefits of T/E DBL for reading instruction, particularly of graphical devices. This research should include a further exploration of the potential benefits for graphical device comprehension and comprehension of unfamiliar science and engineering texts that include graphical devices, as well as the curricular, training, and implementation needs. / Doctor of Philosophy / This study examined how challenging fifth grade students to design a technology to meet an engineering need can support student understanding of nonfiction/informational texts which include informational graphics (graphical devices). The participants of this study were asked to create designs of different types of technology which would benefit from the information in the provided informational texts and graphics. A variety of data were gathered on six fifth grade participants as they worked through a serious of design challenges that were paired with reading passages that included graphics (graphical devices). Graphical device instruction using design challenges was found to increase readers' interactions with texts and their usage of graphical devices, support the development of comprehension for diagrams and tables, improve comprehension of unfamiliar science texts, and provide particular benefit to below grade level readers. The results of this study demonstrate the need for further research into the benefits of using design challenges for reading instruction, particularly of graphical devices.

Computer Science (CS) is among the fastest-growing fields. To fill the abundance of positions in Computer Science, early learning experiences should be implemented to promote interest in the field. This research aims to observe the impact of a design-based computer science treatment on 5th-grade students' interest in computer science careers. The treatment consisted of nine one-hour lessons in which the researcher introduced computer science content to students. At the end of the treatment, participants developed an application to study for a state-wide science assessment. To measure a change in students' career interests following the treatment, an adapted version of the STEM Career Interest Survey (STEM-CIS), grounded by Social Cognitive Career Theory (SCCT), was implemented using a pre-survey-post-survey design. Qualitative data was collected using focus groups to explain quantitative findings further. The samples' post-survey (39.62) mean was greater than the pre-survey mean (37.17), but the paired t-test was just above the statical significance level of 0.05, t(28)= -2.04, p =.051. There was a statistically significant increase for the survey items that align with the SCCT aspects Interest (t(30)= -2.30, p =.028) and Contextual Support (t(30)= -2.25, p =.032). The researcher identified several themes related to a positive perception toward the treatment and computer science and general during qualitative data analysis. These findings indicate a design-based computer science treatment can increase 5th-grade students' interest in computer science careers. / Doctor of Philosophy / Learning experiences influence an individual's career development. This dissertation observes the impact of a design-based computer science project in a 5th-grade classroom. The researcher implemented a pre-survey-post-survey design to measure change following the treatment. The researcher calculated the difference between survey means and ran a matched paired t-test to determine the statistical significance. The results of the paired t-test were not statistically significant. Still, the survey items that aligned with interest and contextual support had a statistically significant increase following the treatment. Additionally, the researcher conducted focus groups to collect qualitative data to explain quantitative findings further. Content analysis of the qualitative data revealed participants had a positive perception of the treatment and computer science in general. These results imply that a design-based computer science treatment can increase 5th-grade students' interest in computer science careers.

Technological/engineering design based learning (T/E DBL) provides a context in which students may utilize content knowledge and skills to develop prototype solutions to real-world problems. In science education, design based science (DBS) utilizes technological/engineering design based approaches in science education as a means for enhancing the purpose of and relevance for scientific inquiry by contextualizing it within the goal of developing a solution to a real-world problem. This study addressed the need to investigate the ways in which students utilize higher order thinking skills, demonstrated through the use of knowledge associated with declarative, schematic, and strategic cognitive demand when in engaged in DBS activities. The purpose of this study was to determine what relationships exist between engagement in DBS and changes in students' depth of understanding of the science concepts associated with the development of design solutions. Specifically, the study determined how students' abilities to demonstrate an understanding of the science concepts, required by assessments of different cognitive demand, change as they were engaged in a design-based science unit associated with heat transfer. Utilizing two assessment instruments, a pre/post-1/post-2 test and content analysis of student design portfolios based on Wells (2012) and utilizing Li's (2001) system to code student responses, the following research question was addressed: What changes in students' science concept knowledge (declarative, schematic, and strategic demand) are evidenced following engagement in design based learning activities? Although the results are not generalizable to other populations due to the limitations associated with the study, it can be concluded that design based learning activities incorporated in science courses can foster higher order thinking. Results from the study suggests that students' abilities to demonstrate their understanding of certain science concepts through higher order thinking, including utilizing concept knowledge strategically in open-ended problem solving, increased following engagement in design based learn activities. Results have implications in technological/engineering design education, in science education, and in integrative STEM education. Implications include the utility of design portfolios as both an assessment instrument and learning tool to ensure that concept knowledge is explicitly connected to and used in the design activity. / Ed. D.