• Meini Su 
  • Lin Ma 
  • Dongda Zhang 
  • Akilu Yunusa-Kaltungo 
  • Clara Cheung 

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The integration of emerging technologies such as artificial intelligence (AI) and immersive systems including augmented/virtual/mixed realities (AR/VR/MR) into engineering education can significantly enhance student engagement through their personalized and self-paced learning capabilities. Their virtual laboratories also make it possible for students and tutors to replicate real-life and often complex engineering activities within hazardfree environments with high repeatability. Therefore, this  paper investigates the benefits of integrating digital tools into technical programmes delivered within higher education institutions (HEIs), with a focus on engineering programmes. The discussion covers student experiences, teaching quality and efficiency, feedback and comments, etc. Moreover, the challenges and concerns of using digital tools in HEIs are also considered, with an overarching aim of contributing to the ongoing discussions around the pros and cons of such tools on knowledge management.

Introduction

Digital tools for education are technologies designed to enhance teaching, learning, and administrative processes. Artificial intelligence (AI) and immersive systems such as augmented reality/virtual reality/mixed reality (AR/VR/MR) are examples of digital tools that are rapidly reshaping the engineering industry. It is therefore important for higher education institutions (HEIs) to equip students with the fundamentals of such tools mainstream engineering curriculum to help speed up their ability to implement similar skills and algorithms to real-world engineering challenges. The influence of digital tools in engineering education is not only being used as a tool for addressing specific engineering challenges, but also emphasizing the use of AI techniques and resources to enhance the teaching-learning process.

The integration of digital tools into engineering education has transformed traditional pedagogical approaches, enhancing teaching methodologies and fostering active learning (Chenet al., 2020; Tuomi, 2018). In this study, we focus on engineering programmes in higher education. Although there are examples of the implementation of AI for solving engineering problems and optimising design, studies that focus on the hybridisation of AI and immersive tools (AR/VR/MR) for engineering education are still limited.

Therefore, this study aims to explore the benefits of using digital tools such as AI and AR/VR to enhance curriculum planning, teaching, learning and assessment. Additionally, the challenges and concerns of using digital tools in higher education are also discussed, thereby leading to the generation of initial roadmaps for universal and more sustainable integration in the near future.

Benefits for Learning

Digital tools offer numerous benefits for enhancing learning by providing personalized, interactive, and accessible educational experiences. This section will discuss the benefits from students’ learning perspective.

Personalized Learning Experiences

AI-powered platforms have revolutionized education by offering tailored, dynamic, and accessible learning experiences. Platforms such as DreamBox and Knewton utilize real-time data to adjust the difficulty, type, and sequence of learning materials. These systems are particularly beneficial for engineering students, as they address knowledge gaps in foundational subjects.

Engineering students often discover gaps in their understanding of these foundational subjects during their higher education journey. AI-powered platforms provide personalized support to bridge these gaps and meet specialized learning needs. For instance, chemical engineering students may realise the need for additional knowledge in biology to succeed in bioengineering related courses, while others within the same field may require a stronger grasp of physics concepts to master flow dynamics analysis. In such cases, personalized learning mechanisms become invaluable, offering targeted resources and adaptive content.

Beyond foundational support, other AI-powered platforms, such as Coursera and EdX, expand the educational horizon by offering courses designed to supplement traditional classroom learning. These platforms provide specialized content in areas such as advanced machine learning, robotics, and structural engineering (Chandrasekaranet al., 2023). They support students seeking to gain advanced knowledge aligned with personal interests, career development goals, or future academic pursuits, such as doctoral (PhD) studies. It has been shown that an increased number of students applying for PhD studies have adequately enriched their CVs with certificates from Coursera (Esenet al., 2022).

By providing accessible, flexible, and high-quality content, these platforms equip students with cutting-edge skills and interdisciplinary insights. For example, students interested in robotics can explore courses on AI and programming, while those pursuing structural engineering may dive into advanced computational design. Additionally, certifications from these platforms enhance employability and academic credentials, making them an essential complement to formal education.

Student Engagement and Interaction

Student engagement has been significantly increased with immersive technology (mainly AR/VR/MR) as they allow students to explore complex concepts in a safe and controlled environment. For example, engineering students can use simulations to design and test prototypes, analyze structural failures, or model fluid dynamics without requiring physical resources. Such experiences not only reinforce theoretical understanding but also enhance practical skills, making learning more tangible, self-paced, and applicable to real-world scenarios. Additionally, gamification in education integrates game-like elements such as leaderboards, badges, and rewards into assessments and activities. These features tap into students’ competitive instincts and foster intrinsic motivation. AI enhances this by personalizing challenges based on each student’s skill level, ensuring that tasks are neither too easy nor overly difficult (Suresh Babu & Dhakshina Moorthy, 2024). For instance, a gamified platform for coding might progressively introduce complex algorithms as students demonstrate mastery of simpler concepts, keeping them engaged and eager to advance.

Many AI-powered interactive platforms facilitate two-way communication and engagement, enabling students to ask questions, receive instant feedback, and collaborate with peers. For example, platforms like Piazza and Kahoot! foster active participation through quizzes, discussions, and live polls, transforming passive lectures into collaborative learning experiences (Ghannamet al., 2020). Kahoot!, widely used in HEIs, including engineering studies, enhances student engagement by introducing gamified elements, making complex topics like fluid dynamics or circuit analysis more interactive and enjoyable (Lashariet al., 2024). Furthermore, some AI platforms, such as Edmodo, integrate features that promote collaboration, including group projects, peer reviews, and virtual team exercises (Ryane, 2020). These tools create opportunities for students to engage in meaningful ways, fostering a sense of community even in remote or hybrid learning environments. Besides enhance learning, they also equip students with the communication and teamwork skills needed for success in their careers.

Wider Accessibility

Digital tools significantly improve accessibility, allowing students to access resources, collaborate with peers, and participate in remote learning, breaking barriers of location and time. These tools enable students to learn from home, campus, or anywhere with internet access, providing flexibility to obtain knowledge on subjects of interest. This is particularly supportive for students with disabilities and learning challenges, as these tools can be tailored to meet diverse needs. They also enhance accessibility for engineering students to gain hands-on experience in industrial applications, fostering inclusivity and innovation.

In many universities, most lectures are recorded and made available online via specialized virtual learning platforms such as Canvas, Moodle, and Blackborad, allowing engineering students to replay key sections of the recordings as needed (MacKay, 2019; Swerzenski, 2021). These resources make complex engineering topics, such as thermodynamics or circuit design, more accessible and easier to understand, thanks to the flexibility and interactivity provided by digital tools.

Digital tools are particularly transformative for students with physical, sensory, or learning disabilities. Features like screen readers, captions, and adjustable font sizes help create an inclusive learning environment. One example of such functionalities is JAWS (Job Access With Speech) which provides visually impaired students with voice guidance to navigate online resources, has been used in many engineering courses to provide wider accessibility (Ndlovuet al., 2023). Also, engineering students with motor impairments can use voice-to-text tools, such as Dragon Naturally Speaking, to write reports or codes for software related projects.

Benefits for Immersive Learning Experiences

With the help of AR/VR, immersive learning experiences are becoming a cornerstone of modern education. These technologies not only make learning more engaging and effective but also ensure that students are better prepared for real-world challenges in their respective fields.

For example, the integration of AR/VR/MR for immersive learning experiences in fields like medicine, engineering, and the arts can foster a deeper understanding of complex concepts, support diverse learning styles, and create more inclusive and effective learning environments (Takrouriet al., 2022).

Students studying mechanical engineering can also use VR to explore the internal workings of a jet engine, observing how components interact in real-time. Tools like EON Reality or VIVED Science enable students to virtually disassemble and reassemble machinery, offering hands-on experience without the need for physical equipment (Takrouriet al., 2022). These tools provide realistic environments where students can safely practice and refine their skills before applying them in real-world scenarios. In Civil engineering programmes, students can use VR platforms like InfraWorks to simulate bridge construction projects, experimenting with materials, designs, and environmental factors in a risk-free setting (Tuominen, 2024).

Real-Time Support

These tools enable immediate responses to students’ work, helping them identify mistakes or misconceptions at incipient stages of learning. Instant feedback allows students to make corrections and improve their understanding while the material is still fresh in their minds, leading to more effective learning. Real-time support, such as through AI-powered tutoring systems or chatbots, provides students with on-demand assistance, ensuring they don’t feel stuck or disengaged during the learning process. This continuous and personalized interactions foster a more dynamic learning experience that helps maintain student motivation, and promotes incremental growth.

Similarly, mathematical tools like ALEKS offer immediate responses to student inputs, helping them master foundational engineering mathematics concepts, such as differential equations or linear algebra, by correcting errors and offering alternative problem-solving approaches (Dean, 2016). Programming platforms like LeetCode and HackerRank provide instant feedback on coding exercises, showing errors in logic or syntax and suggesting optimized solutions, which is invaluable for software engineering students (Murai & Watanobe, 2023).

Some AI-driven tools analyze student performance in real-time and offer personalized suggestions, creating a tailored learning experience. Tools like Fusion 360 integrate AI assistants that guide students through CAD modeling, offering real-time tips on improving designs or correcting geometrical inconsistencies (Saorínet al., 2019). AI chatbots provide instant answers to student queries, reducing frustration and ensuring they remain engaged with their studies. Chatbots on platforms like Blackboard, Moodle, Edmodo, Coursera and edX can answer questions about course content, such as thermodynamics laws or structural analysis methods, helping students continue their work uninterrupted (Saqret al., 2023). Furthermore, some HEIs, such as Georgia Tech, have implemented AI chatbots like Jill Watson to assist students with course-related inquiries and administrative processes, streamlining their learning journey (Goel & Polepeddi, 2018).

Real-time support tools are transforming education by offering immediate, personalized guidance that empowers students to learn actively and confidently, by fostering a more dynamic and engaging learning environment, which in turn equips students with the skills and mindset needed to excel in their fields. Immediate support keeps students motivated by reducing the time spent feeling stuck and increasing their confidence as they progress. By addressing errors promptly and constructively, real-time support tools encourage students to view mistakes as learning opportunities rather than failures.

Benefits for Teaching

Digital tools significantly enhance teaching and administration by improving efficiency, organisation, and overall effectiveness. This section examines their benefits from an academic teaching perspective.

Incorporation of Multimedia, Simulations, and Collaborative Platforms

The integration of multimedia, simulations, and collaborative platforms has profoundly transformed teaching and learning in engineering education (Abdulrahamanet al., 2020). In chemical engineering, videos and animations are particularly effective in illustrating complex concepts, such as nature-inspired optimisation algorithms. Animations visually demonstrate how these algorithms identify optimal solutions for intricate chemical process design problems, enabling students to quickly grasp theoretical foundations, practical applications, and inherent limitations. This engaging and digestible format enhances students’ understanding significantly.

Beyond traditional in-person sessions, the availability of tutorial recordings and audio-visual materials provide students with multiple complementary learning mechanisms and opportunities that are deployable at their own pace. This flexibility proves especially valuable when revisiting challenging topics or accommodating varied schedules, particularly during periods of overlapping coursework deadlines. In the classroom, digital tools such as polls and surveys are utilised to gauge students’ progress and comprehension in real time (Grazuleviciuset al., 2021). By gathering immediate feedback, lecturers can adjust their teaching pace, revisit complex topics, or provide additional case studies and tutorials to strengthen understanding. These tools were indispensable during the COVID-19 pandemic and remain highly beneficial for distance learners (Robertson, 2023), such as students on industrial placements or part-time students, ensuring effective planning and personalised support despite the absence of physical classroom interaction.

VR further enriches the educational experience by immersing students in realistic simulations of chemical plant environments (Kumaret al., 2021). These tools enable students to replicate plant operations, explore decision-making outcomes, and practise teamwork in addressing real-world challenges, such as ensuring safety or managing operational disruptions. Such hands-on, interactive learning not only deepens understanding but also prepares students for the complexities of real-world engineering, making the teaching experience more dynamic and impactful.

Learning Management Systems (LMS), such as Blackboard, enhance collaboration by providing platforms for discussion boards where students can pose questions, engage in group projects, and interact with lecturers and teaching assistants (Dobre, 2015). This fosters a supportive, dynamic learning environment, encouraging peer-to-peer collaboration and strengthening connections between students and academics. The combined use of multimedia resources, VR tools, real-time feedback mechanisms, and collaborative platforms creates a flexible, interactive, and inclusive educational experience. These technologies equip students with the critical skills and understanding necessary for modern engineering challenges.

Reduce Faculty Workload

Digital tools such as ChatGPT streamline the feedback process, saving time and allowing lecturers leading computationally intensive engineering modules to focus on critical intended learning outcomes (ILOs), such as fundamental domain knowledge (Wanget al., 2024). At the same time, these tools ensure students receive the support they need to excel in practical tutorials and assessments. The integration of generative AI tools, like ChatGPT, into engineering education has revolutionised how students acquire coding skills (Rajabiet al., 2024), particularly in chemical engineering programmes where advanced optimisation and modelling are integral to the undergraduate curriculum.

Traditionally, the teaching of programming/coding through platforms such as MATLAB posed considerable challenges, especially for junior undergraduate students with limited prior coding experience. Bridging this skills gap often required in-person tutorial sessions led by graduate teaching assistants (GTAs), necessitating extensive preparation and delivery time. For instance, in teaching first/second-year students in aerospace, civil, mechanical, and chemical engineering programmes the concepts of process optimisation, intensive sessions were typically required at the start of the semester to revise foundational MATLAB concepts through various examples. Despite these efforts, students frequently sought additional clarification during weekly drop-in sessions, slowing progress and increasing the workload for GTAs and lecturers.

The introduction of ChatGPT has markedly alleviated these challenges by providing instant feedback and real-time troubleshooting for programming-related issues. Students can now independently identify and resolve errors, fostering a more autonomous and interactive learning environment. This immediacy not only maintains their learning momentum but also strengthens their understanding through iterative problem-solving without needing to wait for external assistance. By addressing routine coding challenges, ChatGPT has reduced the reliance on lengthy in-person tutorial sessions. This shift enables lecturers and GTAs to dedicate more time to explaining mathematical concepts underlying optimisation theory and their practical applications in engineering. Similarly, weekly drop-in sessions are now less strained, as many common issues are resolved independently by students using ChatGPT. This adjustment not only optimises resource allocation but also enhances the overall efficiency of the teaching process.

The use of AI tools like ChatGPT exemplifies how digital innovations can transform education by providing on-demand, personalised support (Hashmi & Bal, 2024; Rajabiet al., 2024). These tools empower students to take greater ownership of their learning while significantly reducing the workload for teaching staff. As generative AI becomes increasingly integrated into educational strategies, tools like ChatGPT are poised to play a vital role in improving learning outcomes, enhancing the student experience, and optimising faculty resources in engineering education.

Tracking Student Progress

AI-driven analytics for tracking student success and preventing dropout are revolutionising how educational institutions identify and support at-risk students (Attaranet al., 2018). By analysing data such as grades, attendance, engagement levels, and behavioural patterns, AI can detect early warning signs of students struggling academically or emotionally (Al Yousufiet al., 2023). This data-driven approach allows educational support offices to intervene proactively, providing tailored support and resources before students fall behind or drop out.

In engineering programmes, where certain modules are particularly demanding, AI systems offer valuable insights into attendance and engagement patterns. Modules such as fluid dynamics, thermodynamics, advanced mathematics, and programming are often cited as particularly challenging. AI systems can monitor attendance rates for these critical courses and automatically alert unit leads if attendance falls below a specified threshold. This early identification enables unit leads to address potential issues, whether related to module content, teaching methods, or external factors, and adjust their strategies to re-engage students. For example, lecturers might introduce additional case studies, restructure tutorials, or create smaller, interactive discussion groups to foster a more supportive learning environment.

Big data analytics also tracks individual students’ patterns across attendance, academic performance, and engagement with course materials (Baiget al., 2020). For instance, if a student exhibits a noticeable decline in attendance across multiple modules combined with a drop in grades, the system can flag them as potentially at risk. Academic tutors can then receive automated alerts, enabling timely one-on-one meetings to discuss the student’s challenges. These personalised interventions not only support students academically but also provide opportunities to address underlying issues such as stress, anxiety, or other mental health concerns, ensuring a holistic approach to student well-being.

Additionally, AI tools enhance performance tracking in practical and computational aspects of engineering education. For example, systems monitoring student work on simulation-based assignments (Dai & Ke, 2022), such as MATLAB, Aspen Plus, or ANSYS, can identify recurring errors or areas of misunderstanding. These insights enable lecturers and teaching assistants to offer personalised resources, such as targeted tutorials or guided problem-solving exercises, addressing specific learning gaps. AI systems can also identify common difficulties across cohorts, informing curriculum improvements and adjustments.

By integrating attendance monitoring, academic performance analysis, and collaborative activity tracking, AI-driven tools provide a comprehensive framework for fostering student success. These systems not only enhance academic outcomes but also support students’ mental health and well-being through timely and proactive interventions. As AI analytics become an integral part of educational strategies, they promise to reduce dropout rates, improve learning experiences, and contribute to a more inclusive and supportive environment within engineering programmes.

Effective Communication

Digital tools significantly enhance lecturers’ ability to communicate effectively with students and colleagues, streamlining interactions and fostering a more connected and responsive educational environment. These tools save time while ensuring communication remains clear, accessible, and well-organised.

One practical example is the use of Learning Management Systems (LMS) (Dobre, 2015) such as Blackboard, which serve as centralised platforms for sharing instructions, updates, and feedback. For instance, Blackboard is often used to disseminate detailed coursework instructions, weekly learning plans, and reminders about important deadlines in engineering programmes. These regular communications help students stay informed and organised, reducing confusion and ensuring they remain on track with course requirements.

Real-time communication tools like Zoom and Microsoft Teams are indispensable for facilitating group-based design projects, especially for senior students in various engineering programmes. These platforms support virtual office hours, enabling students to consult with unit leads, teaching assistants, or peers from any location (Katz & Kedem-Yemini, 2021). This flexibility is particularly beneficial for collaborative engineering tasks, where team members often require immediate feedback on design concepts, simulation results, or project deliverables. During group meetings, Teams and Zoom allow seamless sharing of documents, diagrams, and project updates, thereby enhancing both communication and collaboration. For large classes, particularly during the pandemic (Sobaihet al., 2021) or in online learning environments, anonymous surveys have proven invaluable (Grazuleviciuset al., 2021). For example, in challenging modules such as advanced mathematics or programming, anonymous surveys can assess students’ understanding and identify areas requiring additional support. These insights enable lecturers to adapt their teaching strategies in real time, better addressing student needs and improving overall engagement.

Beyond student interactions, digital communication tools facilitate collaboration among faculty members and engagement with educational support administrators (Diffinet al., 2010). For instance, platforms like SharePoint and Microsoft Teams enable co-authoring of departmental documents and the coordination of teaching plans and learning resources. By integrating tools such as Blackboard, Zoom, and anonymous surveys into daily practices, universities create a responsive, flexible, and interactive learning environment. These tools not only enhance communication but also improve the overall efficiency and inclusivity of educational operations, ensuring that students and staff can engage meaningfully regardless of location or circumstances.

Challenges and Concerns

While digital tools, generative AI techniques and big data analytics offer transformative benefits for engineering education, their implementation presents significant challenges and concerns that must be addressed to ensure equitable and effective adoption.

One of the main challenges is the potential impact on inequalities due to different access and affordability in different countries, which comes from both the availability of advanced facilities and readiness of skills. The high costs associated with software licences, hardware requirements, and ongoing maintenance can hinder the adoption of technologies such as AI-driven analytics, virtual reality (VR) systems, and specialised engineering simulation platforms (Smutny, 2022). A lack of infrastructure and resources in certain institutions limits the accessibility of advanced technologies (U.S. Department of Education, 2023). Additionally, there is a need for faculty training to effectively implement these tools in curricula (Bermejoet al., 2023). Institutions with limited funding may struggle to provide adequate resources for students and educators, exacerbating existing disparities in educational quality. This issue is especially pronounced in regions where reliable internet access, a prerequisite for most digital tools, is not universally available.

Secondly, adopting digital tools often necessitates a shift in established teaching methodologies, which can encounter resistance from lecturers and administrative teams accustomed to traditional approaches (Johnsonet al., 2016). Concerns about the reliability and efficacy of AI-based systems, or scepticism regarding their long-term benefits, may further slow adoption. Additionally, the rapid pace of technological advancement can lead to hesitation, as academics may fear investing time and effort into tools that could quickly become obsolete.

Thirdly, the effective integration of AI tools into curricula also requires lecturers and teaching assistants to develop new technical skills, which can demand considerable time and effort (Nget al., 2023). Many educators are accustomed to traditional teaching methods and may resist new technologies that disrupt established routines (Jansen & Merwe, 2015). There is a clear need for upskilling educators to effectively use digital tools in their teaching. For instance, utilising AI-driven platforms for student progress tracking or implementing VR systems in teaching not only requires familiarity with the tools but also an understanding of how to apply them effectively in a pedagogical context (Strielkowskiet al., 2024) Many academics, already burdened with teaching, research, and administrative responsibilities, may struggle to find time for professional development. Furthermore, institutions often lack structured training programmes to upskill staff, further limiting the successful deployment of these technologies.

Finally, there is also significant concerns about data privacy and ethical considerations. Because AI often relies on large amounts of personal or sensitive data to function effectively, the use of AI may require the status quo of privacy protection to be revisited.

Future Plan

To enhance the quality of engineering education in Higher Education, it is important to integrate the innovative digital tools into teaching and learning process, which would be beneficial to personalized learning, instant feedback and immersing learning experience. This integration will better prepare students for the evolving demands of the engineering industry for digitalization. To start with, some initials can be taken at the university level and educator perspective. For example, educators should gain a better understanding on the pros and cons of various digital tools, and carry out comparative analysis of traditional teaching approach and digital tools–aided approach. Select one or two digital tools to apply to the course as trial and collect students feedback for data analysis. HEIs should also invest infrastructure and facilities to allow the use of advanced tools such as cloud computing services and AR/VR labs. New programmes should also be developed to incorporate AR/VR, such as mechanical engineering designs or civil engineering projects. HEIs should also offer continuous professional development programs and workshops for educators on the effective use of digital tools in the classroom. It will also be of great important to invite industrial partners to the advisory boards, ensuring the programmes align well with the current industry needs and technological trends.

Conclusions

This paper discussed the benefits, concerns and potential plans to initiate the use of advanced digital tools and AI-powered platforms in engineering programme at higher education. From a learning perspective, these tools have revolutionized education by offering personalized, interactive, accessible, and immersive learning experiences, enhancing engagement, fostering collaboration, and providing real-time support to empower students with the skills, confidence, and inclusivity needed to excel in their academic and professional pursuits. Meanwhile, they enhance teaching by streamlining multimedia integration, reducing faculty workload, tracking student progress, and improving communication, while addressing challenges like accessibility, resistance to change, and the need for upskilling to ensure effective and equitable adoption in engineering education. However, there are various ways to leverage the digital tools, both from the university and educator levels. Lecturers must be better prepared for the integration of AI and digital tools, and universities need to provide structured training and support to facilitate this transition. By conducting more deeper discussions on the use of digital tools in education, we will all have a better picture and clearer goals for using digital tools. Some pioneering examples and positive feedback from students will be rather encouraging.

In summary, the trend of digitalization has expanded to engineering and a series of policies, such as “Industry 4.0” has been introduced for the transformation of productive industries. It is no doubt that our students need to equip with advanced technologies for efficient management, optimised design, complex data analysis and long-term decisions in the future engineering industries.

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