4
engineering curricula have been adapted in recent years to
include industry application of gen-AI in mine planning,
operational optimization, scheduling maintenance, slope
stability and failure prediction models and mine automa-
tion, etc. Well defined policies on the appropriate use of
AI have simultaneously been developed to ensure students
are aware of the permissibility of the use and limits of these
technologies. Curtin University’s position on Gen-AI use
by students in academic submissions starts from the point
of non-permissibility. Permissions required for use of and
specific uses of AI tools like ChatGPT, Microsoft Copilot,
Gemini are well understood by students. Other software
like Quilbot, Grammarly etc. are often viewed as facilitat-
ing tools and the changes they suggest to the composition
of assessments, while also indicating non-original student
work, are often not seen as violating AI use rules. This can
lead to cases of academic misconduct lodged against stu-
dents and depending on the severity of the offence, can
present significant penalties on students. Students and aca-
demics have to stay on top of this evolving landscape and
stay informed about recent developments in both the tech-
nology and its appropriate use so that they may adequately
prepare students for the workforce.
Furthermore, concerns about cost, infrastructure, and
the readiness of both faculty and students to adapt to such
technological changes contribute to a more hesitant stance.
Meanwhile, the industry perspective is often driven by the
immediate potential for AI to enhance efficiency, safety, and
profitability in mining operations. Moreover, considering
the increasing demand on technological literacy required
and the accelerated adoption from the side of the indus-
try, the partial or improper development and implementa-
tion of AI skills in teaching and learning could exacerbate
inequalities and an educational divide.
Sustainability and ESG
Secondly, Sustainability and Environmental, Social, and
Governance (ESG) considerations take center stage, reflect-
ing the industry’s shift towards responsible and ethical
resource management. This involves integrating broader
concepts such as Humanitarian Engineering, Circular
Economy, Sustainable Mining, Environmental, Social and
Governance stewardship into the curriculum (1, 8, 14). The
first prioritizes community well-being and socio-economic
impacts encouraging students to consider how mining
operations affect local communities and to design projects
that foster positive social outcomes. Similarly, the principles
of Sustainable Mining emphasize the reduction of envi-
ronmental footprints, enhancing resource efficiency, and
ensuring long-term environmental balance. Furthermore,
integrating this along with fostering ESG stewardship in
mining engineering education prepares engineers to handle
challenges such as the impacts of climate change, resource
scarcity, and social equity, ensuring they can make informed
decisions that align with global sustainability goals.
Future technologies
The advancement of future technologies represents the third
stream, highlighting the need for innovation in extraction
methods and the adoption of cutting-edge technology such
as digitalization and automation to enhance efficiency and
safety at the workplace. As these technologies become more
integral to mining, they require the development of a mul-
tifaceted skillset that integrates technical expertise with a
deep understanding of advanced systems and data analytics
and mining engineering education must evolve to include
comprehensive training on these technologies. To achieve
this, stronger industry-academia collaboration is required.
This collaboration can enable educational institutions to
facilitate practical learning experiences that will prepare
students for technologically advanced mining environ-
ments. Moreover, the adoption of future technologies in
mining demands not only technical acumen but also skills
in communication, problem-solving, and systems thinking.
Engineers must be adept at working in multidisciplinary
teams, where they can leverage diverse perspectives to inno-
vate and solve complex challenges. As the industry con-
tinues to advance, equipping future engineers with these
comprehensive skills will be crucial, positioning them to
lead the way in implementing safe and efficient mining
practices that leverage the full potential of automation and
digital technologies.
Generational shift
Lastly, addressing generational shifts becomes essential, as
education must adapt to the evolving expectations and val-
ues of a new workforce eager to contribute to sustainable
and technologically advanced mining practices. Today’s
learners, often characterized by their digital nativity and
propensity for rapid information consumption, require
innovative delivery methods that resonate with their learn-
ing preferences. They anticipate interactive and adaptable
learning experiences that go beyond traditional lectures and
textbooks. Instead, there’s a need for dynamic, multimedia-
rich content that leverages technology in the classroom.
This adjustment of teaching methods and materials partic-
ularly considers the shortening of attention spans and aims
for greater effectiveness. A proven way to respond to indi-
viduality and diversity is to design more agile methods that
shift from traditional frontal instruction to blended and
engineering curricula have been adapted in recent years to
include industry application of gen-AI in mine planning,
operational optimization, scheduling maintenance, slope
stability and failure prediction models and mine automa-
tion, etc. Well defined policies on the appropriate use of
AI have simultaneously been developed to ensure students
are aware of the permissibility of the use and limits of these
technologies. Curtin University’s position on Gen-AI use
by students in academic submissions starts from the point
of non-permissibility. Permissions required for use of and
specific uses of AI tools like ChatGPT, Microsoft Copilot,
Gemini are well understood by students. Other software
like Quilbot, Grammarly etc. are often viewed as facilitat-
ing tools and the changes they suggest to the composition
of assessments, while also indicating non-original student
work, are often not seen as violating AI use rules. This can
lead to cases of academic misconduct lodged against stu-
dents and depending on the severity of the offence, can
present significant penalties on students. Students and aca-
demics have to stay on top of this evolving landscape and
stay informed about recent developments in both the tech-
nology and its appropriate use so that they may adequately
prepare students for the workforce.
Furthermore, concerns about cost, infrastructure, and
the readiness of both faculty and students to adapt to such
technological changes contribute to a more hesitant stance.
Meanwhile, the industry perspective is often driven by the
immediate potential for AI to enhance efficiency, safety, and
profitability in mining operations. Moreover, considering
the increasing demand on technological literacy required
and the accelerated adoption from the side of the indus-
try, the partial or improper development and implementa-
tion of AI skills in teaching and learning could exacerbate
inequalities and an educational divide.
Sustainability and ESG
Secondly, Sustainability and Environmental, Social, and
Governance (ESG) considerations take center stage, reflect-
ing the industry’s shift towards responsible and ethical
resource management. This involves integrating broader
concepts such as Humanitarian Engineering, Circular
Economy, Sustainable Mining, Environmental, Social and
Governance stewardship into the curriculum (1, 8, 14). The
first prioritizes community well-being and socio-economic
impacts encouraging students to consider how mining
operations affect local communities and to design projects
that foster positive social outcomes. Similarly, the principles
of Sustainable Mining emphasize the reduction of envi-
ronmental footprints, enhancing resource efficiency, and
ensuring long-term environmental balance. Furthermore,
integrating this along with fostering ESG stewardship in
mining engineering education prepares engineers to handle
challenges such as the impacts of climate change, resource
scarcity, and social equity, ensuring they can make informed
decisions that align with global sustainability goals.
Future technologies
The advancement of future technologies represents the third
stream, highlighting the need for innovation in extraction
methods and the adoption of cutting-edge technology such
as digitalization and automation to enhance efficiency and
safety at the workplace. As these technologies become more
integral to mining, they require the development of a mul-
tifaceted skillset that integrates technical expertise with a
deep understanding of advanced systems and data analytics
and mining engineering education must evolve to include
comprehensive training on these technologies. To achieve
this, stronger industry-academia collaboration is required.
This collaboration can enable educational institutions to
facilitate practical learning experiences that will prepare
students for technologically advanced mining environ-
ments. Moreover, the adoption of future technologies in
mining demands not only technical acumen but also skills
in communication, problem-solving, and systems thinking.
Engineers must be adept at working in multidisciplinary
teams, where they can leverage diverse perspectives to inno-
vate and solve complex challenges. As the industry con-
tinues to advance, equipping future engineers with these
comprehensive skills will be crucial, positioning them to
lead the way in implementing safe and efficient mining
practices that leverage the full potential of automation and
digital technologies.
Generational shift
Lastly, addressing generational shifts becomes essential, as
education must adapt to the evolving expectations and val-
ues of a new workforce eager to contribute to sustainable
and technologically advanced mining practices. Today’s
learners, often characterized by their digital nativity and
propensity for rapid information consumption, require
innovative delivery methods that resonate with their learn-
ing preferences. They anticipate interactive and adaptable
learning experiences that go beyond traditional lectures and
textbooks. Instead, there’s a need for dynamic, multimedia-
rich content that leverages technology in the classroom.
This adjustment of teaching methods and materials partic-
ularly considers the shortening of attention spans and aims
for greater effectiveness. A proven way to respond to indi-
viduality and diversity is to design more agile methods that
shift from traditional frontal instruction to blended and