Session: Government Agency Student Posters

Paper Number: 173370

From Foundation to Future: Revisiting Ai Integration in Mining Engineering Education Through Current Perspectives of Students, Educators, and Industry 

The mining industry is undergoing a profound transformation, driven by advancements in artificial intelligence (AI) that are fundamentally enhancing operations through automation, robotics, machine learning, and data analytics. However, current mining engineering curricula are not adequately equipping students with AI-related competencies essential for success in today’s rapidly evolving mining sector. To remain relevant and responsive, educational programs must rise to the challenge and evolve to meet emerging technological and workforce demands.  

The purpose of this study is to guide curriculum development that not only reflects advancements in technology in the mining sector but also fosters workforce readiness. This ensures that graduates are equipped to make meaningful contributions to the future of mining. The research examines how mining engineering education can evolve to meet the demands of an AI-driven industry. By gathering insights from students, educators, and industry professionals. The study identifies stakeholder views on AI familiarity, perceived importance, relevant applications and skills, current curricular limitations, and preferred approaches for integrating AI into mining engineering education.   

This study followed a pragmatic, mixed methods approach using a structured survey that included (16-18) in its final version. The survey which employed Likert-type questions and one open-ended question had addressed eight domains: Needs; Familiarity, Confidence and preparedness in understanding AI; Interest in mining course that integrates AI; Resources and Obstacles for learning about AI applications in mining; Teaching and learning methods; Curriculum flexibility, Career-related awareness; and Benefits and ethical issues regarding using AI in mining industry). Participants were recruited through multi-site convenience sampling as the survey dissemination took place in the three major mining academic conferences between February and June 2025, taking 7–10 minutes to complete per participant. The sample included (263) participants in total; 118 from industry, 106 graduate mining engineering students, 31 educators in mining courses, and 8 government representatives.  

The survey revealed a strong consensus on the need to integrate AI into mining engineering education. Industry professionals rated the importance of acquiring AI skills highest (M = 4.74) but perceived students as having low preparedness (M = 2.87), highlighting a gap between workforce expectations and current educational outcomes. Students showed strong interest in AI-fused mining course (M = 4.14) but only moderate confidence in their understanding (M = 3.65). All groups agreed that AI knowledge enhances career prospects, while students expressed greater ethical concerns, particularly, regarding job displacement (M = 3.43) compared to educators (M = 2.71). There was broad support for flexible, hands-on, problem-based curricula, with industry showing the strongest endorsement (M = 4.68), underscoring the need for adaptive educational reform. 

Presenting Author: Rana Alhaj Bedar University of Kentucky

Presenting Author Biography: Rana is a current PhD student in STEM education at the university of Kentucky and a Graduate Research Assistant at Mining Engineering Department at the University of Kentucky. Hew work focused=s on modernizing mining engineering education through AI integration.

Authors:

Rana Alhaj Bedar University of Kentucky
Sarah Wilson University of Kentucky
Ali Moradi University of Kentucky
Zach Agioutantis University of Kentucky
Steven J. Schafrik University of Kentucky
Pedram Roghanchi University of Kentucky