Students demonstrate the Use Mathematics Core Ability by:
| Use Mathematics: | Course List | Rubric |
Fleming, G. C., Klopfer, M., Katz, A., & Knight, D. (2024). What engineering employers want: An analysis of technical and professional skills in engineering job advertisements. Journal of Engineering Education, 113(2), 251–279. https://doi.org/10.1002/jee.20581
This source examines how industry employer-sought professional and technical skills vary among engineering disciplines and levels of education. The core abilities Use Mathematics, Communicate Effectively, Work Cooperatively and Demonstrate Creative and Critical Thinking are among the professional skills included in this study. A large sample (n = 26,103) of mined job advertisements from the O*NET skills database is used to determine the frequencies of different professional and technical skills for biomedical, civil, chemical, electrical, environmental, and mechanical engineers with bachelor's, master's, and PhD degrees. A skill premium is determined by comparing the median starting salary for each engineering discipline and education level to the skills listed in the job description. Use Mathematics had the highest professional skill premium.
Torres-Peña, R. C., Peña-González, D., Chacuto-López, E., Ariza, E. A., & Vergara, D. (2024). Updating calculus teaching with AI: A classroom experience. Education Sciences 14(9), 1019. https://doi.org/10.3390/educsci14091019
This study explores the use of specific AI tools, including Chat-GPT, MathGPT, Gemini, and Wolfram Alpha, to deepen students’ understanding of key mathematical concepts such as derivatives and rates of change through continuous interaction with a virtual tutor. By employing well-designed prompts, these tools facilitated problem-solving exercises that were verified and refined by AI, fostering both precision in calculations and conceptual clarity. Observations from the classroom implementation reveal that students not only improved their accuracy in performing derivative calculations but also developed a clear understanding of the distinctions between average and instantaneous rates of change. The AI tools created a dynamic, adaptive learning environment, providing immediate feedback and simulations that significantly boosted student engagement and motivation. These findings underscore the potential of AI to transform mathematics education by making learning more personalized and accessible, ultimately enhancing educational outcomes and preparing students for future academic and professional challenges. Furthermore, this study introduces an innovative approach to refining AI prompts and interactions, highlighting the importance of iterative improvement to enhance the quality of AI feedback. This approach is crucial for developing better problem-solving skills and ensuring a comprehensive understanding of mathematical concepts.
