Game construction learning approaches have seen increased interest for computational learning and digital literacy in K-12 education, but the paucity of research on game text-based scripting skill development identifies a gap in the literature. This case study investigated text-based scripting skill development and intrinsic motivation with a class of eighth grade students who were engaged in game construction. The study participants were 20 students and their teacher. The case involved the open-ended, project-based game construction class. Data sources included classroom observations, teacher and student interviews, survey responses, and student game scripts. The findings showed that engaging in game construction with peer collaboration and teacher support helped the students develop scripting skills. Game scripting skill development involved the use of language arts and mathematic skills. Challenges in game scripting included student debugging difficulties, as well as technology issues that distracted the students from their work with battery charging problems, Wi-Fi connectivity drops, and broken computers. The students showed moderate intrinsic motivation toward text-based scripting in game construction and appeared to prefer design artwork to scripting. Implications suggest that developing game scripting skills promoted the practice of language arts literacy and mathematics concepts. Game scripting was an engaging self-directed autonomous learning experience. Text-based scripting development is suggested to be a distinct digital literacy.

Informal learning experiences have become increasingly effective in enhancing self-efficacy and interest in the fields of science, technology, engineering, and mathematics (STEM).This study investigated the impact of access to informal STEM learning experiences on student self-efficacy and interest in STEM before and after participating in the 2018 See Blue See STEM Summer Experience. Pre-survey results indicated that middle school students who had previous access to informal STEM learning experiences are 3.21 times as likely to demonstrate high self-efficacy in STEM as those who had no previous access. After engaging in the 2018 summer experience, post-survey results showed a statistically significant increase in student self-efficacy in STEM and indicated that students who had previous access to informal STEM learning experiences are 4.13 times as likely to manifest interest in STEM as those who had no previous access. These results suggest that increasing exposure to informal STEM learning experiences enhances both self-efficacy and interest in STEM.

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<div>Information security practitioners and researchers who possess sufficient depth of conceptual understanding to reconstitute systems after attacks or adapt information security concepts to novel situations are in short supply. Education of new information security professionals with sufficient conceptual depth is one method by which this shortage can be reduced. This study reports research that instructed two groups of ten undergraduate, pre-cryptography students majoring in Computer Science in cryptography concepts using representational understanding first and representational fluency first instructional treatment methods. This study compared learning results between the treatment groups using traditional paper-based measures of cognitions and fMRI scans of brain activity during cryptography problem solving. Analysis found no statistical difference in measures of cognitions or in cognitive processing, but did build a statistical model describing the relationships between explanatory variables and cryptography learning, and found common areas of cognitive processing of cryptography among the study’s twenty subjects.</div>

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STEM (Science, Technology, Engineering, and Mathematics) academic programs and career fields continue to lack representation among females and minorities. STEM learning programs that engage youth in culturally relevant and personally meaningful experiences in STEM have been shown to develop participant self-concept as a scientist, as well as increase interest in related careers. This study uses the Draw-a-Scientist Checklist (DAST-C) instrument, as well as the Draw-a-Scientist Growth (DAST-G) instrument, which was developed and implemented by the author as part of this research. The DAST-C and DAST-G instruments were used to examine the science-related perceptions of youth before and after participation in a residential STEM geosciences program. An analysis found that the program produced statistically significant (p<.05) reductions to the DAST-C scientist stereotype scores in all twelve cycles of the program between 2018 and 2019, and statistically significant gains to the DAST-G scientist perception growth scores in eleven of the cycles.

This dissertation presents a series of neuroimaging investigations and achievements that strive to deepen and broaden our understanding of human problem solving and physics learning. Neuroscience conceives of dynamic relationships between behavior, experience, and brain structure and function, but how neural changes enable human learning across classroom instruction remains an open question. At the same time, physics is a challenging area of study in which introductory students regularly struggle to achieve success across university instruction. Research and initiatives in neuroeducation promise a new understanding into the interactions between biology and education, including the neural mechanisms of learning and development. These insights may be particularly useful in understanding how students learn, which is crucial for helping them succeed. Towards this end, we utilize methods in functional magnetic resonance imaging (fMRI), as informed by education theory, research, and practice, to investigate the neural mechanisms of problem solving and learning in students across semester-long University-level introductory physics learning environments. In the first study, we review and synthesize the neuroimaging problem solving literature and perform quantitative coordinate-based meta-analysis on 280 problem solving experiments to characterize the common and dissociable brain networks that underlie human problem solving across different representational contexts. Then, we describe the Understanding the Neural Mechanisms of Physics Learning project, which was designed to study functional brain changes associated with learning and problem solving in undergraduate physics students before and after a semester of introductory physics instruction. We present the development, facilitation, and data acquisition for this longitudinal data collection project. We then perform a sequence of fMRI analyses of these data and characterize the first-time observations of brain networks underlying physics problem solving in students after university physics instruction. We measure sustained and sequential brain activity and functional connectivity during physics problem solving, test brain-behavior relationships between accuracy, difficulty, strategy, and conceptualization of physics ideas, and describe differences in student physics-related brain function linked with dissociations in conceptual approach. The implications of these results to inform effective instructional practices are discussed. Then, we consider how classroom learning impacts the development of student brain function by examining changes in physics problem solving-related brain activity in students before and after they completed a semester-long Modeling Instruction physics course. Our results provide the first neurobiological evidence that physics learning environments drive
the functional reorganization of large-scale brain networks in physics students. Through this collection of work, we demonstrate how neuroscience studies of learning can be grounded in educational theory and pedagogy, and provide deep insights into the neural mechanisms by which students learn physics.