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Quantum mechanics is notoriously challenging, and research has found that students struggle with many common difficulties when learning it. It is also proving to be a critical piece of many exciting fields that are all but assured to see great development and expansion in the coming years; the Second Quantum Revolution is upon us. Quantum information science and engineering is a rapidly unfolding field, requiring talent from many disciplines, that aims to leverage the potential of quantum systems for many practical applications. To prepare students for the opportunities afforded by these advances, a strong foundation in quantum mechanics is essential. The work that I present in this dissertation is focused on helping students achieve this understanding. By investigating the common difficulties that students have in key concepts related to quantum mechanics and quantum computing, a guiding framework can be established and followed to develop research-validated, active-engagement instructional tools. These tools include Clicker Question Sequences (CQSs) on (1) the basics of two-state quantum systems, and changing basis in two-state systems; (2) time-development of two-state systems; (3) quantum measurement of two-state systems, and (4) measurement uncertainty in two-state systems. In addition to these, I have developed and validated Quantum Interactive Learning Tutorials (QuILTs) consisting of guided-inquiry teaching-learning sequences for (1) the Bloch sphere and (2) the basics of quantum computing. In each case, cognitive task analysis from both expert and student perspectives was either carried out directly or built upon from the results of prior investigations. I discuss the results of implementations of these learning tools in authentic classroom environments, which involves both online and in-person administrations and multiple instructors. In each case, student performance after engaging with the learning tools increased noticeably, and dramatically for some difficult concepts. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

Introductory computer programming (i.e. CS1) is the entry point into the computer science major at higher education institutions worldwide. It introduces foundational concepts to students that are then built upon in future courses. Computer science as a whole has struggled to attract and retain students in the major, particularly women and students from minority backgrounds. Researchers have explored reasons as to why students are struggling to complete their CS1 course and remain in the major. Current research has uncovered a wide range of different factors which have been studied mostly in isolation from each other, thus not being able to provide a full view of the CS1 student experience. This dissertation presents an (1) exploration of the current state of CS1 research and its organization into an existing theoretical framework, (2) a holistic view of student experiences in early computing courses, and (3) the benefits and role of pedagogical best practices in supporting student learning in CS1. Regarding exploration: we surveyed the current state of CS1 literature to gain an understanding of what factors related to student CS1 success have been studied and mapped the findings to an existing student learning framework: Biggs' 3P model. We find the factors explored included areas such as internal student factors, instructional practices, the student's learning process, and many more. Regarding holistic: we collected student experience surveys from students of the first four courses students at UCSD stake during their computer science program. We found lower performing students report higher levels of stress across multiple areas compared to their higher performing peers. Regarding pedagogy: we analyzed 12 years of longitudinal student data to understand how the implementation of a trio of best practices (peer instruction, pair programming, and media computation) in introductory programming courses at UCSD demonstrated improvement to student performance and retention within the program. Regression models and significance testing provide evidence that the presence of these best practices were significant in these positive outcomes. Despite these improvements, certain groups such as women and minorities were still failing and being retained at lower rates in the major than their peers. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

Despite efforts to increase representation among those enrolled, earning degrees, and working in the computing and technology industry, women across races/ethnicities and People of Color more broadly remain underrepresented in the field. Fortunately, extant literature has found that psychosocial factors like computing identity can help broaden participation for these groups by supporting their academic and career interests and persistence. However, a consistent and comprehensive measure of computing identity remains elusive. This quantitative dissertation draws on a conceptual framework developed for Women of Color in computing and uses longitudinal survey data from 1,036 undergraduate students from one of 15 research universities across the U.S. to: (a) develop a reliable measure of computing identity and assess the role of self-efficacy and sense of belonging in that measure; (b) validate the measure across time and gender and racial/ethnic groups; and (c) identify college-related factors influencing computing identity, considering variations across gender and racial/ethnic identities. This dissertation provides a nuanced account of what computing identity is and how it forms among undergraduate students, noting the unique facilitators and impediments across gender and racial/ethnic groups. In particular, findings highlight that computing identity is a multidimensional measure that incorporates a student's self-identity as a computing person, their sense that computing is a part of their core personal identity, and their sense of belonging in the greater computing community. Hence, it is distinct from related concepts--interest, self-efficacy (competence/performance), and social recognition. While the construct of the computing identity measure is consistent across gender, racial/ethnic, and intersectional gender and racial/ethnic identities, it does not necessarily hold over time during college. Further, while the baseline computing identity and academic major variables generally fostered greater computing identity scores, separate linear regression analyses revealed distinct predictors for different student groups, implying that a one-size-fits-all approach to fostering computing identity should be avoided. For instance, interest in computing was a salient predictor of men's computing identity but not women's, and self-efficacy was a positive predictor for underrepresented Students of Color but not for white students. This dissertation probes these and other findings, offering implications for enhancing practice and policy and advancing theory and research. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

This qualitative research used the tenants of phenomenological research to structure a study that begins to identify faculty coordinator's decision processes in selecting a general education mathematics course. In this study, I examined the question if a faculty member's experiences or beliefs had any influence on the decision process. The interviews occurred with faculty in degree programs grouped by the following a) no specific mathematics requirements (e.g., Humanities) degree programs, b) mathematics-light degree programs (e.g., Social Sciences) and c) mathematics-intensive degrees (e.g., Computer Science). The results of this study are varied but suggest that faculty tasked making decisions on mathematics should understand current recommendations and trends in mathematics selection. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

This dissertation investigates the issue of gender stratification within engineering and other STEM-related fields. The dissertation is divided into three articles that address different aspects of the problem and propose potential solutions. Article 1 explores the persistent gender imbalance within STEM fields, particularly in engineering and computer science. Several factors are identified that contribute to this disparity, including social and cultural pressures, self-efficacy, and the STEM possible self. To address these factors, the researcher proposes a conceptual framework that emphasizes early exposure to STEM, hands-on activities, and exposure to diverse role models. Article 2 describes a six-week intervention that aimed to improve the attitudes and interests of second-grade students towards engineering. The intervention involved the distribution of family STEM kits, which provided a variety of materials for both adults and children to engage with. The results suggest positive impacts of the intervention toward improving female engineering interest and attitudes. Article 3 provides recommendations that would support greater equity in course enrollment at Flagstaff High School based on the findings of Articles 1 and 2. These recommendations include identifying and implementing effective curriculum and instructional approaches within the classroom, establishing an elementary science curriculum coordinator for preK-5, and establishing a family and community partnership to support caregivers in their understanding of their child's developing interests and attitudes toward STEM. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

The education of students on existing and emerging technologies in higher education environments requires access to complex software. The rise of the Bring Your Own Device (BYOD) phenomenon in many postsecondary educational institutions, along with the increasing complexity of technological coursework, creates challenges for students needing school-mandated software within their own environment. Software containerization is a widely used method to alleviate similar challenges that complicate heterogeneous software deployments in enterprise computing and production environments. A literature review suggested a gap in research existed concerning the use of containerization for commercial off-the-shelf (COTS) software programs as an educational tool. This gap in research was addressed with a generic qualitative study to explore the perspectives of eight university faculty members who were aware of containerization and how it is applied in other environments. The participants were current instructors in postsecondary courses in computer science, information technology, and business. Semi-structured interview questions were posed to gather instructional experiences and solicit opinions on the potential benefits, limitations, and concerns associated with applying software containerization in an educational environment. Interview recordings were transcribed, and transcriptions were error-checked and subjected to manual thematic analysis with inductive coding. Four major themes emerged from the analysis related to containerization: lack of student access to required course software is a barrier to success; containerization of course software may improve student success; containerization has benefits for instructors; instructors must consider cost, resources, experience, and applicability when deciding whether to implement containerization of course software. The study findings provide a foundation from which further research into the application of software containerization in educational environments may be pursued and initial guidance for postsecondary instructors who are considering implementing a containerization strategy for their courses. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

Past efforts to teach novices programming through pair programming and project-based learning utilizing different low floors, high ceilings and wide walls platforms have been successful. Building from related work, this study investigates the effectiveness of Productive Failure (PF) pedagogical design in supporting youth and novices when learning programming and fundamental computational concepts. I report on finding from an online synchronous remote workshop for participants from federal programs from low-income families during the Covid-19 pandemic. Participants engaged in code debugging without scaffolding followed by a consolidation phase. Findings suggest that PF design can introduce frustration and complexity, but when well designed and reinforced, it can aid learners' comprehension and application of computational concepts and future troubleshooting skills. Students' interest, motivation, and self-efficacy in programming were positively impacted by the PF design. However, some students lacked confidence in their abilities and tended towards problem avoidance. The iterative solution generation and trial and error were effective in learning code block functionalities, sequencing of scripts, and improving application accuracy of some computational concepts. However, there is a need to design structured support structures in PF designs to manage failures, promote good programming practices, mitigate recurring error patterns and affective challenges, improve problem-solving approaches, and support interest and skill development in STEM, especially for vulnerable learners. Effective error location and debugging strategies may need to be modeled and scaffolded to support deeper conceptual engagement with fundamental computational concepts, ultimately improving their accuracy and efficiency in coding. The study suggests that PF design can be an effective approach to teach computational concepts when coupled with scaffolds and use of different debugging strategies. The study also provides insights into remote learning and delivery of online STEM focused workshops for vulnerable learners. Future work will explore how different designs can facilitate meaningful learning for marginalized learners, provide space for support, community building, and skill development in STEM fields. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

The problem that was addressed in this study was underrepresented minorities' low interest in pursuing computer science as a profession. The purpose of this quantitative, quasi-experimental study was to measure underrepresented youth's attitudes toward computer science. The issue remains a pressing challenge in the U.S. This study explored the disparity in interest among underrepresented minority youth, an issue contributing to the national shortage of skilled computer science professionals. Guided by the expectancy-value theoretical framework, this quantitative, quasi-experimental study assessed the impact of a computer science learning intervention on attitudes toward the discipline among these youth. Approximately 200 underrepresented minority youth from the United States, aged between 11 and 15 were invited to participate in the computer science learning intervention. Of this, there were 57 pre-test responses, and 46 post-test responses. Of those submitted, the pre/post-test data could be matched for 36 participants. After removing participants with missing data, the final sample included 33 participants. The research questions focused on the extent to which the intervention affected two dimensions of computer science attitudes: self-efficacy and outcome expectancy. Repeated measures MANOVA and ANOVA were employed to analyze the data. Significant elevations in self-efficacy and outcome expectancy post-intervention were observed (p < 0.001). Moreover, the enhancement in self-efficacy was found to be consistent with the growth in outcome expectancy over time (p = 0.648), suggesting the intervention had a comparable effect on both dimensions. These findings underscore the potential of hands-on computer science activities in positively influencing attitudes of underrepresented minority youth toward computer science. In light of these results, it is recommended that stakeholders prioritize such targeted interventions, especially those infused with cultural relevancy and imposter syndrome mitigation strategies, critical for increasing underrepresented minorities' interest in computer science. They help to instill a sense of confidence and belongingness in computer science among underrepresented minority groups. Collaborations between government agencies, educational institutions, industries, and community entities are encouraged to create a supportive ecosystem fostering sustained computer science interest among underrepresented minorities Future research directions include probing the lasting effects of these interventions and examining their applicability across diverse age brackets and educational backdrops. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

Many middle school students come to Computer Science (CS) classes without any previous CS instruction or any Computational Thinking (CT) skills that are needed to be successful. To overcome this, many curriculums and programming environments have been used to engage students and to instill a love of CS. Which curriculum should be used to develop CT skills that will also increase positive attitudes towards CS so students will continue in this field of study in higher grades? The purpose of this mixed method action research study was to evaluate how Code.org's block-based programming curriculum affects middle school CS students' CT skills, and their attitudes towards CT and CS. This study explored the following two research questions: (1) How and to what degree did Code.org's block-based programming curriculum in game design affect middle school students' CT skills? (2) How and to what degree were the differences in middle school students' attitudes towards CT and CS after participating in a unit in block-based programming? This study implemented a game design curriculum in Code.org's block-based programming environment over the course of 11 weeks. Participants included 16 eighth grade students at a middle school in South Carolina. The qualitative data collected were student interviews and the quantitative data were pre- and post-tests, surveys, and student artifacts. Qualitative data analysis included inductive thematic analysis. Quantitative data analysis included descriptive statistics and paired samples t-tests. Students' artifacts showed that students learned how to code in Code.org's block-based programming environment. There was a statistically significant increase in participants' algorithmic thinking, debugging, and pattern recognition skills. The increase in participants' abstraction skill was not statistically significantly different. Qualitative themes revealed that participants enjoyed block-based programming as evidenced by their references to the elements of game design during the interviews, but the quantitative findings revealed that students' attitudes towards CT and CS did not have any statistically significant increase. This may be due to the students' performance levels and that not all students perceive coding as easy. Future directions for research and practices are discussed. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

The rise in children's media use (Rideout & Robb, 2020) and the prioritization of STEM learning (Fayer et al., 2017) has led to the development of new STEM-related apps, TV shows, and other media for young children. One topic in this area gaining popularity is computational thinking (CT). Researchers refer to CT as an approach to problem solving based in computer science (Barr et al., 2011) that involves concepts such as sequencing and debugging (Grover & Pea, 2013). Research suggests that learning CT at a young age can be beneficial to children's analytical skills and provides them with new approaches to problem solving (Bers, 2018, 2020; Boticki et al., 2018).The television program of focus to this dissertation is "Work it Out Wombats!." This television program was created with an intentional focus on culturally relevant and inclusive approaches in an effort to support preschool viewers' computational thinking skills. Research has shown that educational media has the potential to support young children's STEM learning, however, there is little research on how to best meet the challenge of creating educational STEM media that effectively engages children of all races and ethnicities and positively impacts their learning. "Work It Out Wombats!" is the first attempt to try and accomplish this. This dissertation explores parents' and children's perception, understanding, and recognition of the culture and inclusion cues and the computational thinking cues embedded in the program. In this qualitative research study, 30 parent-child dyads were interviewed about their perceptions, understanding, and recognition of the culture and inclusion cues and the computational thinking cues embedded in the program. Interviews were conducted in person and completed in a University research space or community center in western and central Michigan. A semi-structured interview protocol was utilized to guide the discussion. The participants in our study shared rich and valuable insights about the "Wombats!" episodes they watched. Parents reported that they would encourage their child to watch the show, especially after learning about its focus on culture and inclusion and computational thinking. Parents identified and discussed the culture and inclusion themes unprompted when asked about their opinions about the show and its characters. Parents reacted positively to the characters and their portrayals, specifically the non-stereotypical portrayals and the non-traditional family structures. Although parents appreciated the culture and inclusion focus, some parents would have preferred for the cues to be more specific, particularly with the animal characters showing diversity and the language cues. Children, however, did not seem to noticed the culture and inclusion cues in these episodes. Regarding computational thinking, a majority of parents had never heard of it and when asked to try and define it, many parents did have aspects of computational thinking in their definitions however, their examples show that they did not have a full and complete understanding of the computational thinking curriculum. Parents believed that computational thinking is an important topic for their children to learn, however, some parents have reservations regarding the abstractness and age-appropriateness of the topic. "Work It Out Wombats!" is a first attempt at trying to create early STEM media that engages children of diverse race/ethnicities. Our results show that this show is an initial step in that direction, where early STEM media has diverse portrayals. More research should be done to measure the educational impact of this show, not only with computational thinking but also the culture and inclusion cues. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

Despite high scores and abilities, girls lose interest in science and math throughout middle school. According to the Bureau of Labor Statistics, jobs in the computer science research field will grow 19% by 2026; however, only 18% of the bachelor's degrees in computer science are earned by women in the United States (ComputerScience.org, 2021). New technology and inventions are being created without the benefit of more diverse perspectives and input from females. There is a need to engage girls and maintain their interest throughout middle school and beyond. Additional research needs to be conducted about the impact and best practices used during out-of-school time programs to encourage and motivate girls to stay engaged in STEM, including computer programming (Koch, 2014).This study investigated the relationship between middle school girls' interest in computer programming and the opportunities to collaborate, solve problems, and use their creativity while participating in computer programming activities led by female role models during the 4-H Girls Tech Challenge, an informal education program. Research questions are the following: 1) In what ways did the 4-H Girls Tech Challenge experience, which included components of problem solving, collaboration, creativity and female role models, affect the attitudes of middle school girls towards computer programming? 2) To what extent did the 4-H Girls Tech Challenge experience affect the attitude of middle school girls towards potentially pursuing careers related to computer science and technology? Evidenced by other studies, experiences in which collaboration, problem solving, and creativity are present have been shown to increase knowledge about computer programming and engagement in STEM (Cooper & Heaverlo, 2013; Wu-Rorrer, 2019; Hayden et al., 2011). A qualitative study employing interviews with previous participants was utilized to determine how the components of collaboration, problem solving, and creativity of the 4-H Girls Tech Challenge affected the attitudes of middle school girls towards computer programming and careers in computer science. Educators will benefit from learning more about best practices that engage, motivate, and retain more girls in STEM. An increase in the number of women in the STEM workforce will maximize innovation, creativity, and competitiveness (Hill et al., 2010). [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

Teenagers today are coming of age under unprecedented, pervasive networks of institutional mass surveillance technologies. Surveillance technologies spreading in youth spaces are impacting young people's prospects today and are expected to continue in the future. Additionally, today's teenagers will be tomorrow's decision-makers, tasked with managing and shaping future surveillance systems. Concerns that young people are being normalized to surveillance culture carry serious political implications for just and democratic futures with technology. How do teenagers view these systems? How can educators, researchers, and fellow learners support them to develop their own perspectives and sense of agency with these technologies? This dissertation examines how teenagers learn about surveillance technologies and opportunities for supporting their learning in line with justice-centered goals. Specifically, teenagers' views on institutional privacy and surveillance through an interview study, and learning about a specific institutional surveillance technology in "Drag vs AI" workshops through observational data analyses. "Drag vs AI" is a drag queen-led workshop created by the Algorithmic Justice League which engages teenagers in makeup use to subvert AI-powered facial recognition technologies (FRTs). We organized and studied four workshop enactments with two community partners, Out Boulder County and the Longmont Public Library. Article I, "Expectations vs reality: teenager views of institutional privacy," reveals how teenagers' complex views of institutional surveillance coexist with attitudes of surveillance realism, identifying implications for justice-centered surveillance education. The second article, "Taking Play and Tinkering Seriously in AI Education: Cases from Drag vs AI Teen Workshops," examines tinkering and play as modes of interaction with FRTs in "Drag vs AI" workshops, evidencing an alternative learning methodology termed embodied algorithmic tinkering. Finally, "Drag Pedagogy for CS Educational Work: Reflections from Drag vs AI Workshops," explores how drag pedagogical practices embodied in the design and facilitation of workshops supported playful and critical CS learning around FRTs. In my concluding chapter, I reflect on the relationship between privacy and criticism of surveillance, and examine how the limitations identified in the first study emerged in studies of "Drag vs AI" using a historical action analysis, synthesizing actionable takeaways for practitioners and possible directions for future designs and research. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

Initiatives geared toward broadening participation in computing research have addressed the longstanding underrepresentation of various populations - including women, Black people, Latinx people, and persons with disabilities. Although there has been an increase in underrepresented populations participating in computing, building upon these efforts is still necessary. While previous research has investigated broadening participation in computing for women and underrepresented racial and ethnic groups, there is limited research on the participation of Black boys. My dissertation work aimed to investigate pedagogies to increase the interest and persistence of Black male adolescents in computer science in the United States. My research identified factors behind retention rates of Black male adolescents in computer science through existing literature. It also examined strategies for Black male adolescents participating in computer science and conducted case studies centered on understanding strategies and pedagogies for increasing the participation of Black male adolescents in computer science. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

The purpose of this transcendental phenomenological study was to describe the lived experiences of Black women with a bachelor's, master's, or doctoral degree in computer science, currently employed in the United States. The theory guiding this study was Krumboltz's social learning theory of career decision-making, as it provides a foundation for understanding how a combination of factors leads to an individual's educational and occupational preferences and skills. This qualitative study answered the following central research question: What are the lived experiences of Black women with a bachelor's, master's, or doctoral degree in computer science, currently employed in the United States? Purposeful criterion sampling was used to select between 12 to 15 participants from the Society of Women Engineers who met the following criteria: a female, Black or African American, with a bachelor's, master's, or doctoral degree in computer science, graduated from an accredited college, university, or vocational program, and currently employed in the United States. Data collection methods included individual interviews, letter writing, and focus groups. Data analysis followed Moustakas modified approach: setting aside personal experiences and prejudgments, organizing data and conducting horizonalization, developing clusters of meaning into common themes, generating and combining textural and structural descriptions, and generating a composite description of the phenomenon experienced by all participants. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

Though efforts have been made for centuries, how concepts are represented in the brain is still elusive. The embodiment view claims that the sensory, motor and other brain areas through which people acquire concept information during life experiences represent this information during concept retrieval. Some compelling neurobiological evidence supports the view. However, this evidence has mainly focused on the study of object concepts and less on the representation of event concepts and their underlying neural mechanisms. Componential models for concept representation were developed in the psychological and computer science field. However, the applications of these models gave limited insight into how concepts are represented in the brain since the information represented by each component is unknown. A high-dimensional componential model inspired by the embodiment view was developed by Binder et al. that provides the opportunity to probe the characteristics of neural signature for each component. We hypothesize that the preferential representation of the event category in the brain is the result of natural constraints on the representation of specific experiential features associated with event knowledge. In this work, this was approached by following experiments and analyses. First, we investigated the neural signature of event concept representation using a large dataset spanning 8 subcategories consisting of 320 nouns and a relatively large number of participants, which provided more power. We contrasted the activation of event and object conditions to show the areas preferentially representing event concepts. This analysis identified several regions involved in the event representation in previous studies, for example, the left posterior superior temporal sulcus extending into the inferior parietal cortex, and the left anterior superior temporal sulcus. In addition, we found multiple regions that were not shown in previous studies, for example, the left inferior frontal gyrus, the right inferior frontal gyrus, and the right anterior superior temporal sulcus. We leveraged the categorical structure of the stimuli to implement a classification study to investigate the performance of classifiers in classifying the concepts into a priori categories. This analysis identified overlapping regions for event and object representation across the brain surface, with regions for representation of event concepts being more extensive than that of object concepts. The contrast between accuracies of classifiers from event and object conditions identified left inferior frontal gyrus pars opercularis and supramarginal gyrus.Second, the same set of experiential features is hypothesized to be involved in the representation of event and object concepts in the brain. We investigated whether an encoding model trained to predict the similarity structure of the neural activation patterns elicited by object concepts would also predict the similarity structure of event concepts, and vice versa. Both encoding models significantly predicted the neural similarity structures across categories in areas where event or object concepts are preferentially represented. Next, the difference in activation between event and object concepts on the brain surface should reflect the difference in representation of experiential information in the underlying brain region. We used ridge regression to find the linear combination of experiential features that best predicted the activation amplitude for event trials. The weighted model was then used to predict the average object activation amplitude for each vertex. The predicted t-map from the vertex-wise encoding analysis closely resembles the pattern observed in the original univariate contrast between event and object conditions. These results indicate that event and object concepts rely on a shared representational code based on experiential information, suggesting that differences in neural activation between object and event concepts arise from quantitative differences in the experiential content of these concept categories. Third, we hypothesized that the event-salient experiential features may give rise to differences in activation between the event and object concepts in the brain areas where event concepts are preferentially represented. We tested this hypothesis with an encoding model composed of similarity structures of event-salient features or object-salient features, defined by feature important analyses on ratings, in the brain areas where event (the event network ROI) or object (the object network ROI) concepts are preferentially represented. We found that in the event network ROI, the encoding model composed of the similarity structure of event-salient features had the best performance in predicting left-out neural similarity structures of event concepts. Conversely, in the object network ROI, the encoding model composed of similarity structures of object-salient features had the best performance in predicting left-out neural similarity structures of object concepts. These results suggest that the difference in activation in these networks may arise from the difference in the experiential information. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

Language is central to education, being the core medium of instruction. Researchers and practitioners have long used manual methods to analyze instructional language like classroom discourse and instructional texts, with the goal of facilitating student-centered instruction. In this dissertation, I offer three studies demonstrating how natural language processing (NLP) can expand the possibilities for student-centered educational research and practice. First, I illustrate how computational methods can help analyze textbook content. Applying lexicons, word embeddings and topic models, I study the depiction of historically marginalized groups in U.S. history textbooks. I find that Latinx individuals are rarely discussed and African Americans are described with low agency and power. The quantification of these inequities can aid researchers, teachers, publishers and other stakeholders make informed decisions when developing and choosing textbooks. Second, I demonstrate how NLP can identify teachers' student-centered talk moves in classroom discourse. I develop an unsupervised machine learning measure for teachers' uptake of student contributions, a high-leverage teaching practice that supports dialogic instruction and makes students feel heard. I extensively validate this measure by analyzing the linguistic phenomena it captures, such as repetition and elaboration, and by demonstrating its correlation with positive educational outcomes across three datasets of student-teacher interaction. Third, I demonstrate how computational research on classroom discourse can be translated into improving educational practice. Building on my uptake measure, I develop a web application that provides teachers with consistent, individualized feedback on their uptake of student contributions. In a large-scale randomized controlled trial in an online computer science course, Code in Place (n=1,136 instructors), I find that the tool improves instructors' uptake of student contributions by 27% and I present suggestive evidence that it also improves students' satisfaction with the course and assignment completion. Together, these studies demonstrate the possibilities for natural language processing methods to measure and to improve key aspects of student-centered instruction. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

The vision of Smart Connected Community (SCC) is to integrate technology to improve economy, safety, education, health and provide equity in the society. Human factor plays a vital role in the SCC in human societal, psychological, physical factors in the technology uses from various aspects. In this research, first, we have studied the impact of the COVID-19 pandemic on smart cities through analyses of 311 data of cities and the residents in the United States. We have compared various aspects of municipal governments' service platforms and citizens' requests during pre-COVID, the lockdown, and the rest of the pandemic duration. Among multiple observations from the data, we discover the noticeable changes in the digital transformation of citizens' voices during the COVID-19 pandemic. We also find that various aspects of divides of residents, such as economic, COVID-related health, and demands are closely related to each other. We have built a comprehensive website that dynamically collects 311 data from municipal open data of cities in the United States that other researchers or urban planners can use to understand citizens' voices better and draw insights. In the second part, we have discussed the effect of COVID-19 in transition of learning in higher education. Two years ago in Spring 2020, a stay-at-home order was issued in the United States and other countries, due to the Pandemic. The education system has to adopt online classes in the middle of the semester. Not many institutions were prepared at that time. We did survey research at the beginning of the pandemic, more than 300 students in computing and engineering and other departments have participated in that survey [1]. After two years of the pandemic we all understood, online classes are very crucial to continue the education system. In some departments, it was easy to transform the classes online but in some lab-based departments, it was difficult. We did another two surveys of over 138 students in spring 2021 and over 379 students in spring 2022, to see how the opinion of the students have changed, what difficulties they have faced in the pandemic, what opportunities online education has presented, how students are comfortable with online classes and different online platforms (like, Canvas, Zoom, Proctorio and so on) and any suggestions to improve the online education system. In the last part, our multi-disciplinary research team has conducted empirical research as part of technology education offered to women-in-transition in the Midwest. In this study, we report results from our interviews with 75 women-in-transition in the Midwest that were conducted to develop a tailored technology education program for the women in the beginning. More than half of the participants in our study are women of color and face precarious housing and financial situations. Then we discuss principles that we adopted in developing our education program for the marginalized women and participants' feedback on the program. Our team launched in-person sessions with women-in-reentry at public libraries in February 2020 and had to move the sessions online in March due to COVID-19. Our research-informed educational program is designed primarily to support the women in enhancing their knowledge and comfort with technology and nurturing computational thinking. Our study shows that low self-efficacy and mental health challenges, as well as lack of resources for technology access and use, are some of the major issues that need to be addressed in supporting technology learning among women-in-transition. This research offers scholarly and practical implications for computing education for women-in-transition and other marginalized populations. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

The purpose of this qualitative research study was to investigate and interpret the influence of the lived experiences of women who have successfully pursued and persisted in a computer science career. The planned study utilized the Interpretive Phenomenological Analysis research method consistent with Smith et al. (2012). The research methods, described by Merriam and Tisdell (2016) and Creswell and Poth (2018), provided additional guidance for conducting ethical, reliable qualitative research. Social Cognitive Career Theory guided the analysis of the recalled lived experiences of eight women with bachelor's degrees in computer science. Social Role Theory was applied as a secondary framework to guide the subjective interpretation of societal influences on career preparation and work environment. Five significant themes emerged from the subjective hermeneutic interpretations of the meaning of the participants' lived experiences: 1) Computer science career pathways were influenced by objective and contextual supports, 2) Computer science careers have motivational rewards, 3) Women perceived barriers in computer science careers related to gender, culture, working conditions, and self-efficacy, 4) Women displayed positive self-efficacy characteristics to overcome challenges, and 5) Women utilized and valued informal and formal support systems. Information from the study may enhance literature and understanding of the experiences of women who navigate the STEM pipeline to enter and remain in computer science careers. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

This correlational, quantitative dissertation in practice explored the influence of the timing of algebra 1, taking advanced math courses, taking AP math courses, math credits earned, math self-efficacy, math identity, and socioeconomic status (SES) on the decision by girls to choose computer science education or career pathway at the post-secondary level. The variables of SES, race/ethnicity, region, locale, and school control were also included as controls in the analyses. Data from the publicly available, nationally representative High School Longitudinal Study of 2009 (HSLS:09) was used to explore the strength and directions of relationships between the predictor variables and the outcome variable. Three research questions were explored through examining the bivariate correlations between variables, and multivariate regression models. The statistical software IBM SPSS v 28.0 was used to filter and analyze the data. The overall findings suggest math self-efficacy and math identity play a key role in girls choosing to participate in computer science. Race/ethnicity is also significant as the data suggests the predictor variables have varying effects by race/ethnicity. Proposed solutions highlight the importance of seeing students as individuals and of educators crafting strategies to increase the participation by girls in computer science (CS) that are respectful and understanding of the influence of race/ethnicity and of the culture of the individual school and community. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

This phenomenological study investigates the narratives of six Black women faculty to ascertain how their experiences contributed to their retention and persistence in Computing. This study, which incorporates Anti-Deficit Achievement Framework, Critical Race Theory, and Intersectionality Theory, is guided by phenomenology and the following key research question: What are the lived experiences of Black Women Faculty in Computing that have aided their academic persistence and capacity to overcome internal and external barriers? Given the dearth of research in this area, this study employed a qualitative research approach to elucidate and understand the factors that contributed to these Black women faculty's academic and professional success in Computing. The study collected data through in-depth semi-structured interviews. The research explored three sub-questions: (1) What experiences influenced each participant's decision to begin and continue their education in Computing?, (2) What factors influenced the participant's ability to persist as a faculty member in computing sciences?, (3) What impact does each participant believe they have had on computing education, and what impact do they wish to have? At the study's conclusion, the researcher gave results and recommendations to enhance Black women faculty in Computing's perseverance and career success. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

The "Computer Science for All" (CS for All) movement launched in 2016, following a decade of increasing support for broadening access to computer science education in K-12. In the years since, it has grown into a broad-based effort to equip all students with the skills they need to thrive in a digital society. CS for All follows a long line of educational initiatives that have attempted to achieve broad social and political aims through curriculum reform. The wide range of rationales for CS for All, including workforce development, personal empowerment, and creative expression, have implications for designs for curricula and strategies for teacher professional learning. This dissertation considers the CS for All movement from three perspectives: historical context, curricular approaches, and the experiences of classroom teachers who are learning to teach computer science. The successful scaling of CS for All will depend upon a coherent approach supported by a strong theory of action linking classroom activities to the broad array of intended outcomes. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

Educational reform in the United States is often focused on upgrading school curricula in response to evolution in science, technology, and society. Wyoming is no exception. A 2001 Wyoming Supreme Court decision granted constitutional protection to every K-12 student in the state for a "fair, complete, and equal education, appropriate for the times." Based on that decision, in 2015 Governor Matt Mead initiated an executive action to make computer science education available in every Wyoming school. Such a new mandate caught many Wyoming schools off guard in that their in-service teachers were required to obtain education and certification to provide computer science education. To support the state's schools, several of Wyoming's institutions of higher education began delivering professional development to teachers needing qualifications to teach modern computer science. The research presented in this dissertation focuses on describing, documenting, and evaluating the origin story and system processes utilized to bring this initiative to implementation. The study describes the experiences of an initial group of in-service teachers seeking to complete a K-12 computer science teaching endorsement program in rural Wyoming by focusing on three overarching research questions: How does systems theory provide a model to deeply understanding Wyoming's K-12 computer science education effort? What are the challenges of delivering multi-age computer science in the rural, mountain regions of the western U.S.? and What differences might exist between teachers' perceived needs for computer science based professional development before and after their actual classroom teaching experience? Using a combination of standard quantitative and qualitative methods, the results suggest that the process could be analyzed using systems theory and that substantive differences exist in the suitability of various programming languages for in service teachers compared with the needs of traditional computer science students. Moreover, the data reveal a discrepancy between the participants' expectations of their preparedness to teach computer science after completing the endorsement program (but before teaching) and after using the information gained in their professional development to actually teach computer science. At the same time, results suggest that teachers who are novice computer science teachers would perhaps benefit greatly from being trained on classroom-ready instructional materials more so than only having an enhanced understanding of fundamental computer science principles. Taken together, the results of this study create a foundation for other states developing similar initiatives to provide K-12 computer science in their own settings. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

This research explores the emerging field of data science from the scientometric, curricular, and altmetric perspectives and addresses the following six research questions: 1.What are the scientometric features of the data science field? 2.What are the contributing fields to the establishment of data science? 3.What are the major research areas of the data science discipline? 4.What are the salient topics taught in the data science curriculum? 5.What topics appear in the Twitter-sphere regarding data science?6.What can be learned about data science from the scientometric, curricular, and altmetric analyses of the data collected? Using bibliometric data from the Scopus database for 1983-2021, the current study addresses the first three research questions. The fourth research question is answered with curricular data collected from U.S. educational institutions that offer data science programs. Altmetric data was gathered from Twitter for over 20 days to answer the fifth research question. All three sets of data are analyzed quantitatively and qualitatively. The scientometric portion of this study revealed a growing field, expanding beyond the borders of the United States and the United Kingdom into a more global undertaking. Computer Science and Statistics are foundational contributing fields with a host of additional fields contributing data sets for new data scientists to act, including, for example, the Biomedical and Information Science fields. When it comes to the question of salient topics across all three aspects of this research, it was revealed that a large degree of coherence between the three resulted in highlighting thirteen core topics of data science. However, it can be noted that Artificial Intelligence stood out among all the other groups with leading topics such as Machine Learning, Neural Networks, and Natural Language Processing. The findings of this study not only identify the major parameters of the data science field (e.g., leading researchers, the composition of the discipline) but also reveal its underlying intellectual structure and research fronts. They can help researchers to ascertain emerging topics and research fronts in the field. Educational programs in data science can learn from this study about how to update their curriculums and better prepare students for the rapidly growing field. Practitioners and other stakeholders of data science can also benefit from the present research to stay tuned and current in the field. Furthermore, the triple-pronged approach of this research provides a panoramic view of the data science field that no prior study has ever examined and will have a lasting impact on related investigations of an emerging discipline. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

The purpose of this study was to explore how elementary school teachers think about equity in relation to their goals in their computer science instruction, and to explore the strategies they articulated to make their practice more equitable. States are mandating computer science standards and instruction and requiring schools to teach the content (2020 State of CS). Parents want students to be taught the content, and students in affluent and predominantly white communities have greater access to computer science opportunities than their low-SES and minority counterparts (Margolis, 2020). In addition, teachers are not formally trained or prepared to teach computer science (2020 State of CS). This study adds to the limited body of research that focuses on computer science instruction at the elementary school level. The current study used documents and interviews of 20 respondents. These respondents self-identified as elementary school teachers that teach computer science in some capacity. This sample of 20 teachers included teachers across the United States, as they self-selected to participate in the study through snowball sampling. The focus of this study was to explore computer science education at the elementary school level. The study explored the two questions: 1. How do elementary CS teachers think about equity in relation to their goals for their computer science instruction? 2. What strategies do elementary computer science teachers articulate to make their practice equitable? This study found that elementary computer science teachers think about equity in two ways: opportunity and differentiation, and listed their goals as: providing access to opportunity, promoting positive identification with computer science, empowering students to use computer science for social change, as well as increasing academic achievement, and provided strategies for making their practices more equitable. This study added to the growing body of research on the topic of elementary computer science education, and supported and extended extant research. From these conclusions, recommendations for current implementation and practice and future research were shared. These recommendations included providing teachers training in integrating ideas around who holds the power in technology, expanding teachers' views on what constitutes equity in computer science education, and supporting teachers in leveraging computer science instruction to promote academic achievement. Teachers in this study expressed their interest in supporting students to acquire computer science skills and create equitable computer science educational pathways. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

There are many concerns from early childhood educators regarding allowing children to use technology, pointing to the adverse effects of screen time and barriers such as lack of resources. To support advocating CT in early childhood settings using technology, this dissertation proposes solutions and resources for early childhood educators by highlighting the best practices in using technology as a medium for children to grow and learn while working through the adverse effects. The contribution of this work developed a "bes-T-ech" framework that has been used to develop two programs created based on the gaps in literature reviews. The first one relates to integrating CT into non-CS disciplines, namely drama. The lesson learning objective was delivered using robotic activities with the aim to create a template that can be used as a sample for other educators to align their lessons with CT standards. The second program teaches CT using our suggested Computational Thinking Pedagogical + Framework. The chosen environment is a virtual world (VW) due to the few studies or resources linking early childhood education and VW. Accordingly created a CT VW blueprint. By the same token, three reinforcement experiments were executed to advocate CT into Kuwaiti society. The reinforcements were complemented with a developed STEM model designed to meet the needs of Arabic/Persian Gulf region learners. The first reinforcement investigates the educators' CT awareness and proposes a plan for implementing CT into the Kuwaiti education system. The second reinforcement transferred a successful CT outreach program from a Western country into Kuwait, which brought insight into the CT ability of the young Kuwaiti educators. Compared to U.S. students, they carry a similar trend and gains in CT concepts and program knowledge. The third reinforcement investigates the ability and preferences between males and females, showing that society and maturity factors are the leading two influencers over Kuwait students' STEM choices, reversing the gender stereotype in Kuwait. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

Nationally, a shortage exists of qualified cybersecurity persons entering the field, posing challenges for higher education institutions in locating qualified educators to help fill the gap. A wealth of literature discusses the needs of students, yet literature outlining qualities of attracting graduates to become educators is lacking. The purpose of the qualitative phenomenological study was to examine, recognize, and describe the lived experiences that influenced cybersecurity graduates to the field of higher education. The study was guided by Lent, Brown, and Hackett's social cognitive career theory and Mezirow's transformative learning theory, as each focus on the awareness of self and motivating behaviors in choosing an occupational career path. The research questions that directed the study were created to examine the experiences that prompted cybersecurity graduates to become educators in the field of higher education. Seventeen postsecondary educators from Texas completed a video-conferencing interview and member-checking review. The data revealed three emergent themes and eight subthemes from the participants' experiences regarding how the decision was made to enter the field of higher education. Findings from the study can benefit stakeholders in the fields of academic advising and admissions, and human resources guiding the recruitment process of future cybersecurity educators. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

This dissertation conducted a science classroom intervention using two instructional approaches, computational modeling and paper-based pictorial modeling, in the context of food webs. A series of research papers were written on the impact of the intervention on students' attitudes and learning, and on teachers via professional development and teaching. The first study employed quasi-experimental design, examining the impacts of computational modeling and paper-based pictorial modeling on students' systems thinking and CT skills. A total of 365 seventh-grade students were involved in week-long online learning activities. The students were purposefully assigned to either synchronous computational modeling condition (n = 224) or asynchronous paper-based pictorial modeling condition (n = 141). Students modeled the interrelation between concepts and components of a food web in both conditions. The students took CT and systems thinking-embedded food web assessments before and after the activity and formative assessment after each activity to gather their perceptions of what they thought they learned from the activities. Multilevel modeling and Epistemic Network Analysis were used to analyze the data. The findings indicated a significant increase in students' systems thinking skills regardless of the conditions. Students in computational modeling condition had a substantial increase in their CT scores, while such a result was not detected in the paper-based pictorial modeling condition. ENA results supported this finding, showing that students in computational modeling condition expressed that they learned both science and CT concepts. The second study explored the predictors of students' interests in computationally intensive (or AI-informed) science careers and the impact of computational modeling activity on middle school students' interests in such careers. In parallel, an instrument to measure students' career interests called the Computationally Intensive Science Career Interest (CISCI), was developed and validated. A combination of classical test theory and item response theory was used to validate the CISCI instrument using a sample N = 934. Multiple linear regression and paired-sample "t"-tests were performed to analyze the data. The results showed that the CISCI is a valid and reliable instrument consisting of five constructs. Results from regression tests revealed that students' science attitudes, computer science attitudes, CT skills, and prior computer science-related activities significantly predicted students' career interests. Furthermore, a significant increase in students' perceptions of intensity of discussing computationally intensive careers with their parents was detected after participating in a computational modeling activity. The third study employed a mixed-methods design to investigate the changes in, and sources of, middle school teachers' self-efficacy for teaching science in a computationally rich environment. A total of eleven middle school teachers participated in this study. They took two questionnaires four times--before and after training and teaching--measuring their self-efficacy for teaching science and CT. The teachers were also either interviewed or asked to provide written reflections after taking the questionnaires. Non-parametric Skillings-Mack tests and thematic analysis were used to analyze the data. The results revealed a significant increase in teachers' self-efficacy for teaching science and CT after training and teaching. These changes in self-efficacy were tied to three sources, namely: (1) exposure to computer programming, (2) students' interests and responses to a computationally rich science environment, and (3) teaching repetition and field experience. Results from the three studies highlight the potential benefit of engaging students with learning science in a computationally rich environment to positively influence both their CT and systems thinking skills as well as content knowledge. The study also highlighted the challenges and possibilities for preparing science teachers to teach computational modeling with little or no background in programming or computer science. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

This dissertation presents a novel theory of event memory along with an associated computational model that embodies the claims of view which is integrated within a cognitive architecture. Event memory is a general-purpose storage for personal past experience. Literature on event memory reveals that people can remember events by both the successful retrieval of specific representations from memory and the reconstruction of events via schematic representations. Prominent philosophical theories of event memory, i.e., causal and simulationist theories, fail to capture both capabilities because of their reliance on a single representational format. Consequently, they also struggle with accounting for the full range of human event memory phenomena. In response, we propose a novel view that remedies these issues by unifying the representational commitments of the causal and simulation theories, thus making it a hybrid theory. We also describe an associated computational implementation of the proposed theory and conduct experiments showing the remembering capabilities of our system and its coverage of event memory phenomena. Lastly, we discuss our initial efforts to integrate our implemented event memory system into a cognitive architecture, and situate a tool-building agent with this extended architecture in the Minecraft domain in preparation for future event memory research. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

Computer Science (CS 1) offerings in most universities tend to be notoriously difficult. Over the past 60 years about a third of students either fail or drop out of the course. Past research has focused on improving teaching methods through small changes without changing the overall course structure. The premise of this research is that restructuring the CS 1 course using a Spiral pedagogy based on principles for improving memory and recall can help students learn the information and retain it for future courses. Using the principles of Spacing, Interleaving, Elaboration, Practiced Retrieval, and Reflection, CS 1 was fundamentally redesigned with a complete reordering of topics. The new pedagogy was evaluated by comparing the students with those coming from a traditional offering in terms of: (1) CS 1 performance; (2) CS 2 performance; and (3) retention of students between CS 1 and 2. Additionally, students were tracked on the individual outcome / topic level of their performance, and students filled out surveys measuring learning motivation and self-regulation. The Spiral pedagogy helped students outperform those who learned via the traditional pedagogy by 9% on final exam scores in CS 1 with a significant difference. Furthermore, 23% of students taught using the Spiral pedagogy mastered greater than 90% of the outcomes, where those taught with the traditional method only mastered 5% of the learning outcomes. Students who were taught with the Spiral pedagogy showed a greatly increased interest in Computer Science by the end of the course, with women showing the greatest increase in interest towards Computer Science. Retention is increased between CS 1 and CS 2 with a 19.2% increase for women, and a 9.2% increase overall. Five weeks later, students were given the same final exam by way of a review exam in CS 2. With the gap in time to forget, those taught with the Spiral pedagogy scored 10-12.5% higher than their peers taught using the traditional method. The change in pedagogy showed an influence with Cohen's d = 0.69. Furthermore, students continued to do better in CS 2 with increased grades across all assessments, including programming capabilities. By the end of CS 2 only 65% of students who learned by the traditional method passed CS 2 with a C or above while students who learned via the Spiral pedagogy had 80% pass with a C or above. The framework for the Spiral Design is presented along with implementation suggestions if others wish to duplicate the pedagogy for their course along with future research suggestions; including building a Spiral Curriculum to enhance performance across courses and interactive tools to act as a means of intervention using techniques proven to improve recall of past content. Overall the Spiral Design shows promising results as the next generation in course design for supporting student achievement and provides additional pathways for future research. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

With the large demand for technology workers all around the world, more people are learning programming. Studies show that human tutoring is the most effective way to learn for novice programmers. However, problems such as the inaccessibility to physical classes, prohibitive costs, and the lack of educators may limit students' opportunities to learn from these resources. Additionally, because programming is a skill requiring continuous practice and immediate feedback, simply listening to lectures may not be sufficient to learn effectively. This increases the inconvenience of learners who use online learning tools such as Massive Open Online Courses (MOOCs). In recent years, a particular type of MOOC that teaches programming in an interactive manner has become popular among programming learners, such as Codecademy and Treehouse. These systems are described as "interactive computer tutors" (ICTs) in this dissertation. ICTs provide an efficient solution for programming learners to practice the idea of learning-by-doing. The commercial application of ICTs has been growing rapidly in recent years and has gained a broad user base. However, despite their success, there is limited research in the literature that addresses the users of ICTs. For example, who are the learners, what do they think of these ICT based MOOCs, and how can we improve their learning experience? This dissertation examines how learners interact with ICT based MOOCs and what design features improve their experience. Four studies were conducted to answer these questions. The results from these studies indicate that learners' level of autonomy require different needs from ICTs, which are not addressed by current ICT designs. In addition, an autonomous feature is tested on an interactive computer tutor that teaches programming, and the effects for different learners are examined. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

Efforts to increase the participation of groups historically underrepresented in computing studies, and in the computing workforce, are well documented. It is a national effort with funding from a variety of sources being allocated to research in broadening participation in computing (BPC). Many of the BPC efforts are funded by the National Science Foundation (NSF) but as existing literature shows, the growth in representation of traditionally underrepresented minorities and women is not commensurate to the efforts and resources that have been directed toward this aim. Instead of attempting to tackle the barriers to increasing representation, this dissertation research tackles the underrepresentation problem by identifying what has worked (leveraging existing real-world data) to increase representation. This work studies the educational pathways of persons who have successfully transitioned into the computing workforce and identifies the common roadmaps that have contributed to retention, persistence, and success in attaining computing employment. Descriptive statistics, Logistic regression, Classification algorithms, Clustering, and Predictive analytics were employed, using the Stata statistical tool and Orange Data Mining tool on real-world data, to identify educational pathways that have resulted in successful employment outcomes for women and blacks in computing. The results of this analysis have highlighted key information that is capable of informing future "Broadening Participation in Computing" (BPC) efforts. This is because the information will enable researchers and decision makers to have a clearer picture of what educational choices have resulted in favorable outcomes for underrepresented minorities and women in computing; and consequently, researchers and decision makers would be able to more accurately target their BPC efforts to achieve optimal results. This knowledge can also be applied in career advising for young students who are trying to chart their path into computing, providing insight into alternative pathways. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

Machine learning has achieved state-of-the-art performance in many areas, including image recognition and natural language processing. However, there are still many challenges and mysteries attracting numerous researchers. This dissertation comprises a series of works concerning problems at the intersection of computer science theory, adversarial robustness, generalization theory, and social science. The first part is to understand adversarial robustness from two perspectives: the efficiency of popular defense mechanisms against adversarial attacks and to understand how adversarial training trade-offs prediction accuracy to robustness. Specifically, in the first perspective, we investigate the popular defense mechanism that formulates adversarial training as robust optimization and trains with projected gradient descent. We study the non-concave landscape of the adversarial loss of a two-layer neural network. Our main result proves that the projected gradient ascent finds a local maximum of this non-concave problem in a polynomial number of iterations with high probability. In the second perspective, we introduce the Adversarial Influence Function (AIF) as a tool to investigate the solution produced by robust optimization. The proposed AIF enjoys a closed-form and can be calculated efficiently and is useful in quantifying the trade-off between accuracy and robustness. The second part is devoted to understanding generalization in modern learning. We investigate how a popular data augmentation scheme helps generalization and also develop a new notion of stability tailored for modern machine learning. Specifically, for data augmentation, we provide theoretical analysis to demonstrate how using Mixup in training helps model robustness and generalization. For robustness, we show that minimizing the Mixup loss corresponds to approximately minimizing an upper bound of the adversarial loss. This explains why models obtained by Mixup training exhibit robustness to several kinds of adversarial attacks such as the Fast Gradient Sign Method (FGSM). For generalization, we prove that Mixup augmentation corresponds to a specific type of data-adaptive regularization that reduces overfitting. Our analysis provides new insights and a framework to understand Mixup. For a new type of stability, we propose "locally elastic stability" as a weaker and distribution-dependent stability notion, which still yields exponential generalization bounds. We further demonstrate that locally elastic stability implies tighter generalization bounds than those derived based on uniform stability in many situations by revisiting the examples of bounded support vector machines (SVM), regularized least square regressions, and stochastic gradient descent (SGD). The final part is about fairness, where we initiate the study of the construction of "scaffolding sets," a small collection "C" of sets with the property that multi-calibration with respect to "C" ensures recovering predictors of individual probabilities accurately, and not just calibration, of the predictor. Our approach is inspired by the folk wisdom that the intermediate layers of a neural net learn a highly structured and useful data representation. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

Since near the very beginning of electronic computing, Monte Carlo particle transport has been a fundamental approach for solving computational physics problems. Due to the high computational demands and inherently parallel nature of these applications, Monte Carlo transport applications are often performed in the supercomputing environment. That said, supercomputers are changing, as parallelism has dramatically increased with each supercomputer node, including regular inclusion of many-core devices. Monte Carlo transport, like all applications that run on supercomputers, will be forced to make significant changes to their designs in order to utilize these new architectures effectively. This dissertation presents solutions for central challenges that face Monte Carlo particle transport in this changing environment, specifically in the areas of threading models, tracking algorithms, tally data collection, and heterogenous load balancing. In addition, the dissertation culminates with a study that combines all of the presented techniques in a production application at scale on Lawrence Livermore National Laboratory's RZAnsel Supercomputer. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

This study explores the phenomenon of computational thinking indicated by the use of Bloom's taxonomy's cognitive domain verbs in the Scratch community, the online, collaborative environment for the Scratch Visual Programming Language (VPL). A corpus of 660,984 words from three Scratch community sub-forums provide the data for this study. By semantically aligning cognitive domain verbs of Bloom's revised taxonomy to computational thinking (CT) dimensions, the occurrences of the verbs in Scratch community sub-forums are used to indicate instances of computational thinking. The methodology utilizes qualitative coding and analysis with R® and RStudio®. The findings show language attributes such as expressions of imagination, sharing of creative details, collaborative development ideas, teaching, modeling, innovating, solutions focused, and technical support to be indicative of computational thinking and CT dimensions. The computational thinking dimension referred to as computational perspectives occurs most frequently within Scratch community participant discourse. The environmental factors found to contribute to computational thinking and the CT dimensions are supporting tools, personalized learning, supportive organizational culture, social learning, and organizational support. Common among the three computational dimensions is the contributing environmental factor described as supportive organizational culture, with the computational perspectives dimension prevailing among the corpora. The characteristics of computational perspectives and supportive organizational culture suggest a desire for human connection in the attainment of technological skills and knowledge. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

This action research study explored how women perceived the influences of collaborative software development methodologies on workplace culture at one financial technology firm. While collaborative software development methodologies were not designed to increase gender diversity, the transformational shifts in the way technology teams work together illustrated the potential for an improved fit with preferred work styles and strengths of women. Thus, the adoption of collaborative methodologies may lead to attracting, retaining, and advancing women in the field of technology. Through semi-structured interviews, this research study described the lived experiences of women in technology roles. The findings highlighted unconscious bias resulting in stereotype threat and imposter syndrome. The recommendations include specific areas of potential improvement targeting team construction, leadership development, and education. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

No doubt exists that literacy and mathematics are the primary foci of early childhood education. Children have limited exposure to computer science-related topics, including robotics, coding, and engineering design. This study is based on prior research evidence indicating that early childhood teachers' confidence and competence can be enhanced with professional development in computer science-related areas, which in turn can enhance the exposure of children and increase their interest and skills in computer science. In this record of study using both quantitative and qualitative methods, I address early childhood teachers' lack of knowledge and experience in coding, engineering design, and robotics, and by conducting three, six-hour workshops focused on these concepts. Participants engaged in hands-on activities and discussions and were provided resources to support learning and classroom integration. Participants completed two pre- and two identical post-assessments measuring (a) competence levels in engineering design, robotics, computational thinking, and coding and (b) their confidence levels in using coding, engineering design, and robotics in their classrooms. Positive gains were made in both confidence and competence levels of the teachers. The artifact created is a framework that can be used to design and deliver focused professional development. The key factors within the framework include reflective practice, providing appropriate and timely resources, and building a personal network. Designing sustained professional development that includes the key factors may lead to an increase in confidence and competence in integrating computer science concepts across the early childhood curriculum. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

Women remain underrepresented in Science, Technology, Engineering, and Math (STEM) disciplines. A lot of research has examined individual-level impacts of their absence, such as women's lack of interest in STEM, their lack of sense of belonging, and low math confidence. In this dissertation, I use Acker's theory of gendered organizations as a theoretical foundation to conceptualize STEM disciplines as multi-layered gendered organizations. In three quantitative studies, I test hypotheses based on components of Acker's theory, specifically, organizational culture and organizing processes. I use Acker's idea of gendered subtext to justify using text data to measure organizational culture in STEM programs. The text, program, and institutional data come from 1,758 STEM programs in six STEM disciplines: biology, chemistry, computer science, mathematics, physics, and psychology. The data sources are texts from each STEM program's "about us" or other introductory webpage, the Integrated Postsecondary Data System (IPEDS), and the IPEDS Completions Survey. In Study 1, I examine the extent to which the cultures of STEM disciplines are gendered using social network analyses of mental models. In Study 2, I explore how organizational cultures in programs differ across STEM fields using machine learning, multinomial logistic regression, and multivariate regression. In Study 3, I examine how organizational culture and organizing processes are related to the proportion of female bachelor's graduates in each discipline. I find the largest difference in organizational culture between the most female-dominated STEM fields (biology and psychology) and the most male-dominated field in the sample (computer science). I also find that feminine organizational culture does not distinguish the cultural differences between male-dominated versus female-dominated STEM disciplines, but that the presence of masculine organizational concepts (such as expectations of brilliance and competition) distinguish the cultures in these disciplines. While I am not able to link organizational culture and the proportion of female graduates, at least in the way I hypothesize, I do find that programs housed in certain interdisciplinary departments in computer science, chemistry, and psychology have higher proportions of female graduates than programs in single-disciplinary departments. I discuss this dissertation's contributions, limitations, and implications, as well as avenues for future research. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

In order to achieve broadening participation in computer science and other careers related to computing, middle school classrooms should provide students opportunities (tasks) to think like a computer scientist. Researchers in computing education promote the idea that programming skill should not be a pre-requisite for students to display computational thinking (CT). Thus, some tasks that aim to deliberately elicit students' CT competency should be stand-alone tasks rather than coding fluency-oriented tasks. Guided by this approach, this assessment design process began by examining national standards in CT. A Q-matrix (i.e., item-attribute alignment table) was then developed and modified using (a) literature in CT, (b) input from subject-matter experts, and (c) cognitive interviews with a small sample of students. After multiple-choice item prototypes were written, pilot-tested, and revised, 15 of them were finally selected to be administered to 564 students in two middle schools in the Mid-western US. Through cognitive diagnostic modeling, the estimation results yielded mastery classifications or subscores that can be used diagnostically by teachers. The results help teachers facilitate students' "mastery orientations," that is, to address the gap between what students know and what students need to know in order to meet desired learning goals. By equipping teachers with a diagnostic classification based assessment, this research has the capacity to inform instruction which, in turn, will enrich students' learning experience in CT. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

Where are the women in computing? This dissertation explores the underrepresentation of women in computing as a cultural issue. After considering the role of women in the history of computing, it examines contemporary interventions to address gender bias and promote gender diversity in the tech sector and Silicon Valley. Not for profit organizations operate as intermediaries that work to raise awareness of gender bias and facilitate institutional alignment on diversity policy and practice across corporate, academic, and the public sectors. This research used a multi-method approach that included critical discourse analysis, participant observation, and qualitative method. Moments of discourse were analyzed to reveal and illuminate dilemmas such as the phenomenon of unconscious bias and the prospect and dilemma of male allies for culture change. Also explored was the tension between focusing on diversity metrics vs. mounting intervention to produce durable culture change the face of deeply entrenched attitudes and practices that push back overt and subtle ways. Gendered occupational identities and biased institutional practices reverberate through the tech sector and more broadly in the structures of society. The conclusion raises uncomfortable questions, such as whether the work on gender diversity is ever "done," and who will continue to put pressure on companies to reconcile tensions between business performance and social justice. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

The possibility of improving employability skills through cooperative education and tech prep was examined in an action research project involving high school students from two neighboring suburban communities in northern Illinois. The extent to which the schools were currently teaching employment and career development skills was examined by surveying the following groups: 106 current students; an unspecified number of graduates of both schools; 23 local employers; and 86 vocational and academic teachers. The surveys established that students and graduates lacked critical employability skills. A probable cause analysis was conducted. The results were used to develop an intervention emphasizing relevance to the real world and use of cooperative learning strategies to facilitate development of skills in the following areas: job search, communication, technological literacy, work ethics, critical thinking, work safety, teamwork, and career exploration. Postintervention surveys indicated that the intervention increased the students' confidence in their employability skills. (The bibliography lists 14 references. Appended are the following: high school student, high school graduate, employer, and teacher surveys; checklist listing workplace skills and career development competencies adopted by the Illinois State Board of Education as part of the Illinois Learning Standards; and a cooperative education evaluation form.) (MN)

STEM (Science, Technology, Engineering and Math) education creates critical thinkers, increases science literacy, and enables the next generation of innovators, which leads to new products and processes that sustain our economy (Hossain & Robinson, 2012). We have been hearing the warnings for several years, that there simply are not enough young scientists entering into the STEM professional pathways to replace all of the retiring professionals (Brown, Brown, Reardon, & Merrill, 2011; Harsh, Maltese, & Tai, 2012; Heilbronner, 2011; Scott, 2012). The problem is not necessarily due to a lack of STEM skills and concept proficiency. There also appears to be a lack of interest in these fields. Recent evidence suggests that many of the most proficient students, especially minority students and women, have been gravitating away from science and engineering toward other professions. (President's Council of Advisors on Science and Technology, 2010). The purpose of this qualitative research study was an attempt to determine how high schools can best prepare and encourage young women for a career in engineering or computer science. This was accomplished by interviewing a pool of 21 women, 5 recent high school graduates planning to major in STEM, 5 college students who had completed at least one full year of coursework in an engineering or computer science major and 11 professional women who had been employed as an engineer or computer scientist for at least one full year. These women were asked to share the high school courses, activities, and experiences that best prepared them to pursue an engineering or computer science major. Five central themes emerged from this study; coursework in physics and calculus, promotion of STEM camps and clubs, teacher encouragement of STEM capabilities and careers, problem solving, critical thinking and confidence building activities in the classroom, and allowing students the opportunity to fail and ask questions in a safe environment. These themes may be implemented by any instructor, in any course, who wishes to provide students with the means to success in their quest for a STEM career. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

Women are underrepresented in technology careers because they pursue technology degrees less frequently and leave technology careers at greater numbers than do men. By analyzing a representative dataset of college graduates with degrees in computer science, computer engineering, and management information systems, this study identified correlations between specific college experiences of female technologists and long-term career success. Exposure to role models and opportunities to apply classroom learning to real world problems were found to increase the likelihood of long-term career success for female technology graduates while participation in campus life was not found to be significantly correlated with such success. These findings were used to create evidence-based recommendations for degree-granting universities to improve career outcomes for their female technology graduates, which included hiring professors that engage students in learning and make them feel cared for as individuals, creating peer and professional mentoring programs, establishing internship programs, and celebrating diversity. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

The lack of diversity in the technology workforce in the United States has proven to be a stubborn problem, resisting even the most well-funded reform efforts. With the absence of computer science education in the mainstream K-12 curriculum, only a narrow band of students in public schools go on to careers in technology. The problem persists because computer science reforms often focus resources primarily on high schools rather than on elementary school students. Studies show that computer science in elementary grade levels provides students not only with fundamental skills in computer science but also with valuable thinking, problem solving, and social skills that help them succeed in other subjects. The purpose of this research is to examine how teachers use a collaborative lesson study process of professional development to develop computer science content knowledge and teaching skills. This qualitative action research study examined an approach to professional development in computer science based on lesson study, a teacher-led form of professional development that originated in Japan. This study examined how third grade teachers, working with a computer science professor from a local university, worked collaboratively over a twelve-week timeframe to teach computer science and computer programming lessons to over one hundred students. The study took place in an urban elementary school serving students from minority groups underrepresented in the technology workforce. Results of this study suggest that professional development in computer science, based on lesson study, provided an effective approach to introduce computer science to the elementary school curriculum. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

This thesis addresses problems from two areas of theoretical computer science. The first area is that of computational learning theory, which is the study of the phenomenon of concept learning using formal mathematical models. The goal of computational learning theory is to investigate learning in a rigorous manner through the use of techniques from theoretical computer science. Much of the work in this field is in the context of "probably approximately correct" (PAC) model of learning, which is carried out in a probabilistic environment. Of particular interest are the questions of determining for which classes of concepts the PAC-learning problem is tractable and discovering efficient learning algorithms for such classes. The second area from which topics are drawn is that of online algorithms for graph-theoretic problems. Many problems in such fields as communications, transportation, scheduling, and networking can be reduced to that of finding a good graph algorithm. After an introduction in Chapter 1, some background information is provided in Chapter 2 on the field of computational learning theory. In Chapter 3 it is shown that for any concept class having a particular closure property, the existence of a graph algorithm implies that the class is PAC-learnable. Chapter 4 defines a variation on the standard PAC model of learning called semi-supervised learning, a model which permits the rigorous study of learning situations where the teacher plays only a limited role. Chapter 5 deals with the problem of prediction as performed by deterministic finite automata, counter machines, and deterministic pushdown automata. Chapter 6 investigates the power and the performance of online algorithms for a certain class of graph problems, referred to as vertex labeling problems. (77 references) (JJK)

Computational Science and Engineering (CSE) has been denominated as the third pillar of science and as a set of important skills to solve the problems of a global society. Along with the theoretical and the experimental approaches, computation offers a third alternative to solve complex problems that require processing large amounts of data, or representing complex phenomena that are not easy to experiment with. Despite the relevance of CSE, current professionals and scientists are not well prepared to take advantage of this set of tools and methods. Computation is usually taught in an isolated way from engineering disciplines, and therefore, engineers do not know how to exploit CSE affordances. This dissertation intends to introduce computational tools and methods contextualized within the Materials Science and Engineering curriculum. Considering that learning how to program is a complex task, the dissertation explores effective pedagogical practices that can support student disciplinary and computational learning. Two case studies will be evaluated to identify the characteristics of effective worked examples in the context of CSE. Specifically, this dissertation explores students explanations of these worked examples in two engineering courses with different levels of transparency: a programming course in materials science and engineering glass box and a thermodynamics course involving computational representations black box. Results from this study suggest that students benefit in different ways from writing in-code comments. These benefits include but are not limited to: connecting xv individual lines of code to the overall problem, getting familiar with the syntax, learning effective algorithm design strategies, and connecting computation with their discipline. Students in the glass box context generate higher quality explanations than students in the black box context. These explanations are related to students prior experiences. Specifically, students with low ability to do programming engage in a more thorough explanation process than students with high ability. This dissertation concludes proposing an adaptation to the instructional principles of worked-examples for the context of CSE education. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

This research study investigated the effectiveness of pair programming as a pedagogical tool measured by final course grades. It also aims to examine the experience perceptions of students regarding its implementation in an introductory computer programming course at a community college. In this study, a quantitative and qualitative approach was utilized. The quantitative data were collected by means of historical data for all 271 students enrolled in the introductory computer programming course during the Fall 2012 to Fall 2015 semesters. The final grade was the dependent variable for the research study. The independent variable was the instruction type: solo and pair programming. The qualitative data, using participant interviews, were collected from students that enrolled in the introductory computer programming course sections that implemented pair programming. The qualitative data were analyzed using a case study approach. When tested if students exposed to pair programming achieved higher final grades than students who were not, a chi-square test of independence resulted to a p-value of 0.368. The p-value suggested that at a 5% level of significance, the relationship between pair programming and student success, achieving a final course grade of C or higher, is statistically independent. In addition, the relationship between pair programming and retention, with student receiving a final course grade, was tested using a chi-square test and found to statistically independent, p = 0.698. This means that pair programming did not have a significant effect on students' final course grade and retention. Personal interviews conducted with seven computer science students that enrolled in the introductory programming course revealed that students have a positive perception of pair programming. The four major themes that emerged from the qualitative data were Productivity and Ability, Pairing and Partnering, Pairing and Learning, and Pairing Environment with an overarching theme of Collaboration. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

The fields of engineering, computer science, and physics have a paucity of women despite decades of intervention by universities and organizations. Women's graduation rates in these fields continue to stagnate, posing a critical problem for society. This qualitative grounded theory (GT) study sought to understand how robotics programs influenced young women's career decisions and the program's effect on engineering, physics, and computer science career interests. To test this, a study was mounted to explore how the FIRST (For Inspiration and Recognition of Science and Technology) Robotics Competition (FRC) program influenced young women's college major and career choices. Career theories suggested that experiential programs coupled with supportive relationships strongly influence career decisions, especially for science, technology, engineering, and mathematics careers. The study explored how and when young women made career decisions and how the experiential program and its mentors and role models influenced career choice. Online focus groups and interviews (online and face-to-face) with 10 female FRC alumnae and GT processes (inductive analysis, open coding, categorizations using mind maps and content clouds) were used to generate a general systems theory style model of the career decision process for these young women. The study identified gender stereotypes and other career obstacles for women. The study's conclusions include recommendations to foster connections to real-world challenges, to develop training programs for mentors, and to nurture social cohesion, a mostly untapped area. Implementing these recommendations could help grow a critical mass of women in engineering, physics, and computer science careers, a social change worth pursuing. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

Although a great deal of work has been done to develop new educational innovations, in the field of engineering, few innovations have found widespread acceptance in the classroom. Therefore, frameworks that conceptualize the interactions among the variables that influence successful dissemination are critical. In this dissertation, dissemination is defined as a process of first creating an awareness of an educational innovation, then influencing the intention to adopt, the actual adoption, and finally the routine use of that innovation (Fincher, 2000; Gravestock, 2002; Hutchinson & Huberman, 1994; King, 2003). This dissertation establishes the importance of achieving three research goals: (1) developing a framework that describes the interrelationships among the characteristics of educational innovations and an organizations' readiness to disseminate, (2) having an expert panel rank the characteristics of the educational innovations and readiness of faculty members, administrators, and students to disseminate, and (3) testing whether important characteristics of educational innovations and readiness of faculty members variables are significant predictors of successful dissemination. Three papers using different methodologies were sequentially developed to achieve the research goals: (1) a systematic literature review of recent dissemination literature, (2) a Delphi study of grant recipients who had disseminated educational innovations, and (3) a survey of electrical engineering and computer science faculty members. Analysis of the results from these papers led to the following findings: (1) Ease of use of an educational innovation and care about student learning outcomes were significant predictors of intention to adopt that innovation; (2) Efficacy of faculty members toward change and valence moderated the relationship between ease of use and intention to adopt educational innovations; (3) Attitude to educational innovation moderated the relationship between ease of use and intention to adopt educational innovations and moderated the relationship between intention to adopt and adoption; and (4) Awareness of others using an educational innovation was a significant predictor of adopting an educational innovation. The results of this dissertation may be leveraged by developers, faculty members, department chairs, college deans, and grant program managers, to successfully disseminate educational innovations in engineering and technology disciplines. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

The scalability of CMOS technology has driven computation into a diverse range of applications across the power consumption, performance and size spectra. Communication is a necessary adjunct to computation, and whether this is to push data from node-to-node in a high-performance computing cluster or from the receiver of wireless link to a neural stimulator in a biomedical implant, interconnect can take up a significant portion of the overall system power budget. Although a single interconnect methodology cannot address such a broad range of systems efficiently, there are a number of key design concepts that enable good interconnect design in the age of highly-scaled CMOS: an emphasis on highly-digital approaches to solving "analog" problems, hardware sharing between links as well as between different functions (such as equalization and synchronization) in the same link, and adaptive hardware that changes its operating parameters to mitigate not only variation in the fabrication of the link, but also link conditions that change over time. These concepts are demonstrated through the use of two design examples, at the extremes of the power and performance spectra. A novel all-digital clock and data recovery technique for high-performance, high density interconnect has been developed. Two independently adjustable clock phases are generated from a delay line calibrated to 2 UI. One clock phase is placed in the middle of the eye to recover the data, while the other is swept across the delay line. The samples produced by the two clocks are compared to generate eye information, which is used to determine the best phase for data recovery. The functions of the two clocks are swapped after the data phase is updated; this ping-pong action allows an infinite delay range without the use of a PLL or DLL. The scheme's generalized sampling and retiming architecture is used in a sharing technique that saves power and area in high-density interconnect. The eye information generated is also useful for tuning an adaptive equalizer, circumventing the need for dedicated adaptation hardware. On the other side of the performance/power spectra, a capacitive proximity interconnect has been developed to support 3D integration of biomedical implants. In order to integrate more functionality while staying within size limits, implant electronics can be embedded onto a foldable parylene ("origami") substrate. Many of the ICs in an origami implant will be placed face-to-face with each other, so wireless proximity interconnect can be used to increase communication density while decreasing implant size, as well as facilitate a modular approach to implant design, where pre-fabricated parylene-and-IC modules are assembled together on-demand to make custom implants. Such an interconnect needs to be able to sense and adapt to changes in alignment. The proposed array uses a TDC-like structure to realize both communication and alignment sensing within the same set of plates, increasing communication density and eliminating the need to infer link quality from a separate alignment block. In order to distinguish the communication plates from the nearby ground plane, a stimulus is applied to the transmitter plate, which is rectified at the receiver to bias a delay generation block. This delay is in turn converted into a digital word using a TDC, providing alignment information. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

Authorship attribution of source code is the task of deciding who wrote a program, given its source code. Applications include software forensics, plagiarism detection, and determining software ownership. A number of methods for the authorship attribution of source code have been presented in the past. A review of those existing methods is presented, while focusing on the two state-of-the-art methods: SCAP and Burrows. The primary goal was to develop a new method for authorship attribution of source code that is even more effective than the current state-of-the-art methods. Toward that end, a comparative study of the methods was performed in order to determine their relative effectiveness and establish a baseline. A suitable set of test data was also established in a manner intended to support the vision of a universal data set suitable for standard use in authorship attribution experiments. A data set was chosen consisting of 7,231 open-source and textbook programs written in C++ and Java by thirty unique authors. The baseline study showed both the Burrows and SCAP methods were indeed state-of-the-art. The Burrows method correctly attributed 89% of all documents, while the SCAP method correctly attributed 95%. The Burrows method inherently anonymizes the data by stripping all comments and string literals, while the SCAP method does not. So the methods were also compared using anonymized data. The SCAP method correctly attributed 91% of the anonymized documents, compared to 89% by Burrows. The Burrows method was improved in two ways: the set of features used to represent programs was updated and the similarity metric was updated. As a result, the improved method successfully attributed nearly 94% of all documents, compared to 89% attributed in the baseline. The SCAP method was also improved in two ways: the technique used to anonymize documents was changed and the amount of information retained in the source code author profiles was determined differently. As a result, the improved method successfully attributed 97% of anonymized documents and 98% of non-anonymized documents, compared to 91% and 95% that were attributed in the baseline, respectively. The two improved methods were used to create an ensemble method based on the Bayes optimal classifier. The ensemble method successfully attributed nearly 99% of all documents in the data set. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]