Document Type
Article
Publication Title
SSRG International Journal of Recent Engineering Science
Abstract
Generative Artificial Intelligence (GAI) is revolutionizing education, echoing historic shifts such as the emergence of the codex and the printing press. GAI automates complex tasks and personalizes learning to individual needs, enhancing interdisciplinary collaboration and bolstering critical thinking and ethical reasoning skills. Initiatives in new, innovative programming illustrate the benefits of embedding these generative technologies to foster cultural competence and innovative problem-solving. Research indicates that intelligent tools significantly enhance learner engagement and access to quality education, enriching learning environments. However, integrating these tools introduces challenges, including ethical dilemmas, academic integrity issues, and resource disparities. These challenges necessitate comprehensive policy development, robust faculty training, and inclusive design practices. Future research should focus on the longitudinal impacts of GAI, develop frameworks to support lifelong learning and establish ethical guidelines to ensure accountability. Advancing interdisciplinary research and prioritizing social inclusion, educational systems can align machines with human values and global educational goals. This strategy prepares learners for participation in increasingly knowledge-driven economies, ensuring that technological advancements remain ethically and socially responsible and equipping learners to excel in evolving professional landscapes.
DOI
https://doi.org/10.14445/23497157/IJRES-V11I6P117
Publication Date
12-2024
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Recommended Citation
Hutson, James; McMaken, W. Travis; and Vosevich, Kathi, "From Codex to Code: Pedagogical Transformations in the Age of Technological Innovation" (2024). Faculty Scholarship. 713.
https://digitalcommons.lindenwood.edu/faculty-research-papers/713