The landscape of education is continually evolving, particularly as we delve deeper into the implications of artificial intelligence (AI) across various sectors. One significant initiative in this realm comes from Aditya Johri, a prominent professor in Information Sciences and Technology and the Dr. Lawrence Cranberg Endowed Research Fellow at the College of Engineering and Computing at George Mason University. With a grant totaling $430,000 from the National Science Foundation (NSF), Johri aims to enhance AI literacy among undergraduate engineering and technology students through a pioneering approach centered around case-based instruction.
This innovative project seeks to bolster national interests by refining undergraduate education, ensuring that future professionals in engineering and computing are both proficient in utilizing and capable of developing AI tools. The urgency of this goal cannot be overstated, especially as AI technologies increasingly permeate every facet of society. By investing in the education of these students, we are effectively laying the groundwork for a workforce that is equipped to face the challenges and opportunities presented by AI advancements.
The project’s significance is underscored by its focus on situated case studies—an approach designed to demystify the complexities inherent in AI applications. These case studies not only elucidate the varying requirements of different stakeholders but also encourage students to engage in critical reasoning. The advantage of this early exposure, particularly in first-year courses, is that it fosters the development of transferable mindsets and competencies that students can utilize throughout their professional lives. This forward-thinking initiative promises to cultivate a generation of engineers and technologists who are not just consumers of AI but innovators capable of advancing the field.
In terms of specific objectives, the project plans to design and implement a series of six case studies centered on familiar AI applications. Areas of focus include essential topics such as career preparedness, campus sustainability initiatives, the development of autonomous vehicles, and advancements in mental health systems. Through the application of the Situated AI Literacy framework, these case studies will serve as a structured pathway for students to understand the implications of AI in diverse contexts.
The implementation of this project will occur across first-year engineering and computing curricula at both Youngstown State University and George Mason University. Over the project timeline running from October 2025 to September 2028, it is expected to benefit more than 500 students. Additionally, the project aims to extend its reach through a series of faculty development workshops, which will engage over ten external institutions and disseminate the innovative practices developed during the project.
Incorporating advanced educational methodologies, the project will leverage role-playing in case study discussions, thereby emphasizing three critical competencies: complex systems cognition, perspectival understanding, and critical thinking. This multifaceted approach promises to facilitate deeper engagement with the subject matter, allowing students to appreciate the nuanced and often multifarious nature of AI technologies and their societal impacts.
Evaluation will be a crucial component of this initiative; mixed-methods approaches will be employed to gauge student learning outcomes effectively. Tools such as pre- and post-surveys, concept maps, analysis of discussion transcripts, and focus group feedback will form the backbone of the assessment strategy. This comprehensive evaluation framework aims to measure students’ growth in multi-dimensional AI understanding, their ability to take perspectives from diverse stakeholders, and their aptitude for critically evaluating AI’s benefits and limitations.
Through careful scrutiny of how case studies nurture these competencies, the research will shed light on the pathways through which students develop a sophisticated understanding of AI. It will provide insights into the essential skills that future engineers and technologists must cultivate in an increasingly AI-driven world. The implications of this work extend beyond the classroom, as it contributes to groundbreaking efforts to prepare a competent workforce, equipped to partake in and lead AI innovations, thereby supporting the nation’s broader economic health.
Supported by the NSF IUSE: EDU Program, this initiative is part of a larger commitment to improve the effectiveness of STEM education for all students. Within the framework of Engaged Student Learning, the program recognizes the importance of fostering educational environments that embolden student engagement and creativity in problem-solving.
As we embark on this journey toward enhancing AI literacy amongst young scholars, we recognize the pivotal role that institutions like George Mason University play in cultivating a diverse and inclusive academic landscape. This university, known for its rapid growth and commitment to innovation, diversity, and accessibility, serves as a beacon for aspiring students from various backgrounds. By embracing cutting-edge pedagogical strategies, it stands poised to lead the charge in preparing the next generation of technologists and engineers.
In conclusion, as the realms of technology and education continue to intersect, initiatives like Aditya Johri’s project represent critical stepping stones towards building an informed and skilled workforce. By equipping students with the necessary tools and knowledge to understand and navigate the complexities of AI, we ensure that they are not only ready to engage with technology but are also empowered to shape its development for the future. The stakes are high as we forge ahead into a future defined by AI; thus, educational initiatives must evolve in tandem, preparing students to rise to the challenges and opportunities ahead.
Subject of Research: Developing Artificial Intelligence Literacy Among Undergraduate Engineering and Technology Students Through Case-Based Instruction
Article Title: Promoting AI Literacy: A Pioneer Initiative for Future Engineers and Technologists
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Keywords
Applied sciences, engineering, computer science, artificial intelligence
