Browsing by Author "Cox, Larry A., II"

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    Course Development Plan Template
    Williams, Daron; Cox, Larry A., II; Ofori, Eunice; Louvet, Matthew, Sr.; Nino, Miguel (Miko); Cui, Andy-Gouqiang (2020-01)
    The Course Development Plan (CDP) was designed as a job aid for faculty to use when working to revise or develop a technology-enhanced course. This document is used as part of a semester-long course (re)design with the aid of an Instructional Design unit. Many of the elements in this document were included to build a course that would pass a quality assurance review based on the Quality Matters Higher Education Rubric.
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    Examining Faculty and Student Perceptions of Generative AI in University Courses
    Kim, Junghwan; Klopfer, Michelle; Grohs, Jacob R.; Eldardiry, Hoda; Weichert, James; Cox, Larry A., II; Pike, Dale (Springer, 2025-01-24)
    As generative artificial intelligence (GenAI) tools such as ChatGPT become more capable and accessible, their use in educational settings is likely to grow. However, the academic community lacks a comprehensive understanding of the perceptions and attitudes of students and instructors toward these new tools. In the Fall 2023 semester, we surveyed 982 students and 76 faculty at a large public university in the United States, focusing on topics such as perceived ease of use, ethical concerns, the impact of GenAI on learning, and differences in responses by role, gender, and discipline. We found that students and faculty did not differ significantly in their attitudes toward GenAI in higher education, except regarding ease of use, hedonic motivation, habit, and interest in exploring new technologies. Students and instructors also used GenAI for coursework or teaching at similar rates, although regular use of these tools was still low across both groups. Among students, we found significant differences in attitudes between males in STEM majors and females in non-STEM majors. These findings underscore the importance of considering demographic and disciplinary diversity when developing policies and practices for integrating GenAI in educational contexts, as GenAI may influence learning outcomes differently across various groups of students. This study contributes to the broader understanding of how GenAI can be leveraged in higher education while highlighting potential areas of inequality that need to be addressed as these tools become more widely used.
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    Faculty & Student Panel Discussion: Issues in Course Materials Access and Use
    Walz, Anita R.; Cox, Larry A., II; Falls, Jonathan; Filer, Kimberly L.; Mantha, Anurag; Meinke-Lau, Billy; Poff, Ron (Virginia Tech. University Libraries, 2020-03-03)
    Faculty and student panelists will discuss the interplay of issues such as equity, cost, persistent access, customization, and pedagogical affordances in relation to open course materials, as well as implications for career advancement in academic contexts when creating and using such materials. We’ll consider a variety of perspectives on these considerations, challenging one another to engage with the complexities of championing openness in higher education.
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    Framing generative AI in education with the GenAI Intent and Orientation Model
    Pike, Dale; McGowin, Brooke; Bond, Mark Aaron; Williams, Daron; Cox, Larry A., II (Educause, 2024-06-06)
    The proposed model seeks to assist instructors and learners with a framing lens for how GenAI might be useful in educational settings.