Research Report – AI-Powered VR Learning

Research Paper Report

Reimagining the future of learning spaces in RMIT’s MBA and EMBA program with AI-powered VR for data analysis, adaptive learning and accelerated skill development.

Vincent Vu
Design Think for Business (Executive)
Executive Master of Business Administration

Table of Contents


Traditional learning spaces often limit students’ ability to engage with complex problems in a realistic setting. With a trend in innovation towards AI, for students studying RMIT’s Master of Business Administration (MBA) and Executive Master of Business Administration (EMBA) program, AI-driven Virtual Reality (VR) offers the potential for immersive learning environments that provide real-time performance tracking and adaptive learning aligning with RMIT’s emphasis on active, authentic and applied learning experiences. (RMIT University, 2023)

This research explores how AI-driven VR can create immersive learning experiences, evaluate student performance and create personalised learning trajectories within RMIT’s MBA program. It adopts a design thinking perspective, focusing on the “engage” and “evaluate” stages.

Secondary Research

Virtual Reality (VR) and Artificial Intelligence (AI) have demonstrated unprecedented potential in enhancing the future learning space, offering immersive learning experiences and personalised feedback technology. Research shows a general potential of VR and AI in education (Rong, Lian and Tang, 2022; Sharrab et al., 2023; Gandedkar, Wong and Darendeliler, 2021; Luckin and Cukurova, 2019), existing studies offer limited guidance on their application within the specific context of the MBA and EMBA program. However, more research is needed to explore how AI-driven VR simulation and feedback systems can target developing essential business skills like critical negotiation, strategic decision-making and leadership. The study aims to address this gap.

VR and AI in Education

VR and AI offer a powerful synergy for revolutionising education. VR excels in creating immersive environments that transcend the limitations of traditional classrooms, allowing students to actively engage with complex simulated scenarios (Makransky, Terkildsen and Mayer, 2019). VR and AI promote active learning, a “learning-by-doing” approach that can accelerate skill development (Gandedkar, Wong and Darendeliler, 2021). AI introduces data-driven personalisation, providing tailored feedback and adapting learning experiences to individual needs (Hwang and Chang, 2021). VR’s immersive experience and AI’s user-based personalisation have the potential to deepen learning objectives and foster opportunities for student success (Luckin and Cukurova, 2019).

VR and AI for MBA and EMBA

The MBA program requires learning experiences that extend beyond the traditional classroom. MBA and EMBA graduates are expected to be proficient in complex skills such as negotiation, strategic decision-making and leadership (Pepperdine University, 2018), often developed through real-world practice. Tang and Huang (2019) indicate the potential of VR-enhanced education for MBA and EMBA students by offering new ways to address limitations associated with traditional teaching methods. Research by Oyelere et al. (2020) and Hamilton et al. (2021) demonstrates VR’s potential to deliver immersive, personalised learning experiences with evidence of improved learning outcomes compared to traditional methods. AI-driven VR has the potential to offer immersive learning environments that align with RMIT’s emphasis on active, authentic and applied learning, offering a bridge between theory and practice.

VR Performance Tracking

VR environments can be integrated to collect real-time data on interactions, actions and behaviours within the simulated space. The data and information collected within the simulated space often exceed traditional assessments, providing rich insights into decision-making processes, problem-solving approaches and skill application under pressure (Radianti et al., 2020; Merchant et al., 2014). AI algorithms can process complex data in real-time, offering nuanced evaluations and identifying specific strengths and areas of improvement.

AI-Driven VR Adaptive Learning Experience

Analysing VR performance data with AI enables the creation of highly personalised learning pathways for MBA and EMBA students (Mohammed, 2023). Adaptive learning systems can adjust the difficulty of subsequent simulations, focus on targeted skill development and offer customised learning recommendations (Motejlek and Alpay, 2021; Mohammed, 2023). This approach ensures students are progressively challenged at the right skill level, with simulations adapting to address their specific needs or areas requiring additional attention.

AI Automated Feedback

AI-driven feedback systems integrated into VR experiences can provide timely, relevant and actionable guidance (Motejlek and Alpay, 2021; Mohammed, 2023). Natural Language Processing (NLP) techniques can analyse student interactions within the simulation and provide real-time context-specific feedback (Lester, Mott and Robison, 2022). Through generative AI, AI can generate feedback reports highlighting student performance patterns using data collected during the simulation to support self-reflection and instructor analysis for focused interventions and recommendations.

Ethical Considerations

Integrating AI-driven VR in RMIT’s MBA/EMBA program has proven potential but raises ethical concerns. Ethical considerations revolve around data protection, privacy of sensitive student performance, potential biases within AI algorithms, equity and accessibility (Zhuk, 2024)

Primary Research

A mixed-methods study investigated current MBA/EMBA students’ perspectives on AI-driven VR. The research sample included MBA and EMBA students from diverse career backgrounds to identify trends and differences in management styles and career pathways.

Current MBA and EMBA students were selected to identify and explore the gaps within our research topic. This research involved semi-structured interviews incorporating a questionnaire to capture qualitative insights and quantitative information on technology attitudes and learning preferences.

Participant Selection

Background: Current MBA/EMBA students from diverse career backgrounds.
Male, female and undefined groups.
Evenly dispersed age group.
Data Collection:
Semi-structured interview and structured questionnaire.

Quantitative Response

Participant 1
Participant 2
Participant 3
Participant 4
Participant 5
Previous Education
Bachelor’s Degree (Economics)
Master’s Degree (Engineer)
Bachelor’s Degree (Commerce)
Master’s Degree (Public Health)
Bachelor’s Degree (Computer Science)
Learning Style
Technology Comfort
Very Comfortable
Somewhat Comfortable
Somewhat Uncomfortable
Very Comfortable
VR Ownership
Yes (Gaming Headset)
Yes (High-End VR Setup)
AI-driven VR Interest
Very Interested
Somewhat Interested
Somewhat Uninterested
Very Interested

Affinity Map

Ai Drive Vr Research Report Affinity Map - Research Report - Ai-Powered Vr Learning


The following analysis highlights key themes and trends that emerged from this research.

Key Themes

Immersive Learning: Participants pursuing technology-based leadership embrace AI-driven VR’s immersive potential, while those inclined towards more traditional roles appreciate its focus on practical skill development. Students have indicated that current studies are too ‘theoretical’ and ‘abstract’, wanting ‘more focus on doing than just learning the theories.’ Students strongly desire immersive learning to be able to see what they’re being taught.

Theory and Practical: Participants from all backgrounds express a common theme of bridging the gap between theory and real-world application. Responses include a want to ‘try applying some of these concepts’ or how it can ‘connect the dots’ between study and work. Current learning structures struggle to effectively enable students to apply theoretical knowledge to practical learning. Students look to connect the dots between traditional classrooms and real-world experiences.

Human-Guided AI/VR: While open to AI and VR’s potential for skill development, participants expressed concerns about AI and VR replacing human interactions. Participants indicated they would want their feedback backed by ‘experienced mentors,’ with trust and transparency, questioning whether the AI’s feedback is ‘reliable’. Participants have concerns about whether the data used to train AI is trustworthy or from a reputable source. Students express that while AI/VR has potential, professional guidance is required to ensure the AI feedback is correct and just.

Personalisation: Participants express a requirement for personalised AI-driven VR experiences customised to the specific skills and real-world scenarios relevant to their career pathway. This means that the AI/VR learning experience should be relevant to them, including their current skill level and desired goals.

Accessibility and Equality: While tech comfort was generally high, only two participants owned VR equipment. This indicates a potential barrier and highlights the need to address accessibility.

Trust and Transparency: Participants require clarity on how AI can replicate the dynamics of a real-world environment. Data privacy was a common theme among participants. Participants indicate concerns about what or who the AI is being ‘trained on’, whether their data is collected and being ‘used for non-educational purposes’, and a general concern for ‘data protection’.

These findings suggest that MBA/EMBA participants see the potential of AI-driven VR enhancing their learning experience. From our user group, participants indicated a requirement for transparency around AI-generated feedback and trained datasets. While tech-savvy participants embrace data-driven insights, others prefer AI feedback coupled with mentors. Primary and secondary research reflects similar concerns on how VR can be implemented to tailor simulations that mirror real-world situations for different fields. Participants also expressed concerns about the balance between technology and human connection.

How Might We Statement

The ‘how might we’ statement is typically the problem statement that the proposed research aims to address.

Through this research on traditional MBA problem learning structure. Traditional MBA program learning structures often struggle to provide the immersive, practice-oriented experiences essential for skill development. As a result, the revised how might we statement:

How might we leverage AI-driven VR with real-time feedback to create immersive, personalised and practice-oriented environments that can enhance skill development, student engagement and learning outcomes within RMIT’s MBA program while considering costs, accessibility and ethical concerns?


This research explored how AI-driven VR could enhance the learning experience within RMIT’s MBA program. The literature review highlighted the potential of VR and AI in education while demonstrating a knowledge gap concerning their applications for skill development. Primary research involving current RMIT MBA students revealed a strong interest in the potential of AI-driven VR for personalised skill development. Themes include the desire for immersive, practice-oriented learning that bridges the gap between theory and real-world scenarios. Students also emphasised the importance of ethical considerations like data privacy and accessibility and the need for more precise guidance between human interaction and AI-driven systems.

These findings indicate the potential that AI-driven VR could bring to the MBA program while highlighting critical areas for further investigation. Questions remain about how VR simulations can effectively simulate the dynamic environment of a real-world situation, the balance between AI guidance and human mentorship, ethical concerns for responsible implantation and costs. Future research focused on these open questions will be crucial in determining the best ways to explore the full potential of AI-driven VR for enhancing the future classroom and MBA learning experience.


Chu, S.-T., Hwang, G.-J., & Tu, Y.-F. (2022). ‘Artificial intelligence-based robots in education: A systematic review of selected SSCI publications’. Computers and Education: Artificial Intelligence, 3, 100091.

Gandedkar, N.H., Wong, M.T. and Darendeliler, M.A. (2021), ‘Role of virtual reality (VR), augmented reality (AR) and artificial intelligence (AI) in tertiary education and research of orthodontics: An insight’, Seminars in Orthodontics, 27(2), 69-77. ISSN 1073-8746.

Hamilton, D., McKechnie, J., Edgerton, E. and Wilson, C. (2021). ‘Immersive virtual reality as a pedagogical tool in education: a systematic literature review of quantitative learning outcomes and experimental design’. Journal of Computers in Education, 8(1), 1-32.

Hwang, G.-J. and Chang, C.-Y. (2023) ‘A review of opportunities and challenges of chatbots in education’, Interactive Learning Environments, 31(7), 4099–4112.

Luckin, R., Cukurova, M. (2019), ‘Designing educational technologies in the age of AI: A learning sciences‐driven approach’, British Journal of Educational Technology, 50(6), 2824-2838.

Makransky, G., Terkildsen, T. S. and Mayer, R. E. (2019). ‘Adding immersive virtual reality to a science lab simulation causes more presence but less learning’. Learning and Instruction, 60, 225-236.

Merchant, Z., Goetz, E. T., Cifuentes, L., Keeney-Kennicutt, W., & Davis, T. J. (2014). ‘Effectiveness of virtual reality-based instruction on students’ learning outcomes in K-12 and higher education: A meta-analysis’. Computers & Education, 70, 29-40.

Mohammed, R. (2023). ‘Investigating AI-Powered Tutoring Systems that Adapt to Individual Student Needs, Providing Personalized Guidance and Assessments’. The Eurasia Proceedings of Educational and Social Sciences. 31. 67-73.

Motejlek, J. and Alpay, E. (2021). ‘Taxonomy of Virtual and Augmented Reality Applications in Education’. IEEE Transactions on Learning Technologies, 14(3), 415-429.

Oyelere, S.S., Bouali, N., Kaliisa, R., Obaido, G., Yunusa, A.A. and Jimoh, E.R. (2020). ‘Exploring the trends of educational virtual reality games: a systematic review of empirical studies’. Smart Learning Environments, 7, 1-22.

Pepperdine University. (2018). ‘The importance of soft skills development’. (Accessed: 25 March 2024).

Radianti, J., Majchrzak, T. A., Fromm, J. & Wohlgenannt, I. (2020). A systematic review of immersive virtual reality applications for higher education: Design elements, lessons learned, and research agenda. Computers & Education, 147, 103778.

RMIT University (2023). ‘RMIT’s Education Plan to 2025: Learning through Life and Work’. (Accessed: 25 March 2024).

Rong, Q., Lian, Q. and Tang, T. (2022). ‘Research on the Influence of AI and VR Technology for Students’ Concentration and Creativity’. Frontiers in Psychology, 13, 767689.

Sharrab, Y., Almutiri, N.T., Tarawneh, M., Alzyoud, F., Al-Ghuwairi, A.R. and Al-Fraihat, D. (2023). ‘Toward Smart and Immersive Classroom based on AI, VR, and 6G’. International Journal of Emerging Technologies in Learning, 18(2), 4-16.

Tang, X. and Huang, J. (2019). ‘Research on MBA Educational Practice Innovation Based on VR in 2019 3rd International Conference on Data Science and Business Analytics (ICDSBA)’. Istanbul, Turkey, 20-23 November 2019, IEEE, 33-38.

Zhuk, A. (2024). ‘Ethical implications of AI in the Metaverse’. AI Ethics,


Quantitative Survey

Technology and VR

How comfortable are you using technology?

▢ Very comfortable
▢ Somewhat comfortable
▢ Neutral
▢ Somewhat uncomfortable
▢ Very uncomfortable

Do you currently own any Virtual Reality (VR) equipment?

▢ Yes
▢ No

If so, how frequently do you use your VR equipment?

▢ Very frequent
▢ Frequent
▢ Neutral
▢ Rarely
▢ Never

Attitudes Towards AI-driven VR

How interested are you in the potential of AI-driven VR for learning and development?

▢ Very interested
▢ Somewhat interested
▢ Neutral
▢ Somewhat uninterested
▢ Very uninterested

What are your thoughts on the potential of AI-driven VR for developing critical business skills (e.g., negotiation and decision-making) in an MBA program?

▢ Very valuable
▢ Somewhat valuable
▢ Neutral
▢ Somewhat not valuable
▢ Not valuable at all

Experience with MBA Programs

What aspects of the MBA teaching environment have been particularly effective or less effective for you?

What are the biggest strengths and weaknesses you’ve observed in the MBA teaching environment?

How important is developing practical skills (e.g., negotiation, decision-making) in your MBA program experience?

What is your reasoning for studying for an MBA or EMBA program?

What are your career goals after completing your MBA/EMBA?

Attitudes Towards VR Learning

What potential benefits or drawbacks do you see in using VR for an immersive learning experience in your MBA program?

AI-driven Feedback

Do you find personalised and real-time feedback valuable during your learning process, and if so, why?

How comfortable would you be receiving performance feedback from AI in a VR simulation environment?

Learning Preferences

How does a traditional classroom foster active participation and engagement in your learning process?

How do you think VR simulations could enhance your learning experience and engagement?

Ethical Considerations

What, if any, ethical concerns do you see with using AI-driven VR for learning in an MBA program?

How important is ensuring data privacy and security when using VR simulations for educational purposes?

Interest and Adoption

Would you be interested in participating if offered an AI-driven VR learning experience within your MBA program? Why or why not?

What additional information or assurances would be needed for you to feel comfortable integrating AI-driven VR into your MBA learning journey?



▢ 20-25
▢ 26-30
▢ 31-35
▢ 35-40
▢ 41-45
▢ 45-50

▢ Male
▢ Female
▢ Non-binary
▢ Prefer not to answer

Highest level of education completed:

▢ Bachelor’s Degree
▢ Master’s Degree
▢ Doctoral Degree
▢ Other (please specify)

Career Focus:
(Economics, Technology, Engineering, Marketing, Communication, Health, etc)

What is your preferred learning style:

▢ Lectures
▢ Classroom
▢ Online
▢ Readings
▢ Internship

Student Response

Participant 1:

  • Age: 26-30
  • Gender: Female
  • Highest level of education: Bachelor’s Degree (Economics)
  • Preferred learning style: Internship
  • Technology comfort: Very comfortable
  • VR ownership: No
  • AI-driven VR interest: Very interested
  • AI-driven VR for business skills: Very valuable

Participant Summary:

  • Traditional MBA experience: I enjoy the program but find some material too theoretical; I am eager to apply concepts practically.
  • Practical skills importance: Essential. He wants to use the MBA for career advancement, so actionable skills are important.
  • Reason for MBA: Transition from an analyst role into management.
  • Career goals: Leadership position at a tech-adjacent company.
  • VR benefits: Immersive scenarios for practising decision-making and negotiation under pressure. Visualising complex data.
  • VR challenges: Cost, concerns about it replacing valuable human interaction in the learning process.
  • AI Feedback: Very important. I love data-driven insights. I’m comfortable with AI as long as it’s explained clearly.
  • Learning Preferences: Classroom learning can be passive. She craves more hands-on, experiential learning and thinks VR could be excellent.
  • Ethical concerns: Data privacy is a big one. She worries about how her VR performance might be stored and potentially used by the university or companies.
  • Interest and Adoption: Absolutely, but it needs transparency. She wants to know how the AI is trained, what data is collected and how it will be used.

Participant 2:

  • Age: 36-40
  • Gender: Male
  • Highest level of education: Master’s Degree (Engineering)
  • Preferred learning style: Classroom
  • Technology comfort: Somewhat comfortable
  • VR ownership: Yes (Gaming headset)
  • AI-driven VR interest: Somewhat interested, but with reservations.
  • AI-driven VR for business skills: Somewhat valuable

Participant Summary:

  • Traditional MBA experience: Good for the theory but struggles to bridge it to his engineering background.
  • Practical skills importance: Very important. Looking for tools to become a better engineering manager.
  • Reason for MBA: To move into a leadership role at his current company.
  • Career goals: Head a large-scale product development project.
  • VR benefits: Potential to ‘try out’ scenarios, but worries business is more nuanced than what a simulation can provide.
  • VR challenges: Will it truly be engaging or just a novelty? He is concerned about the ‘human element’ of leadership.
  • AI Feedback: Critical but prefers feedback that combines AI analysis with input from a mentor with industry experience.
  • Learning Preferences: He likes classroom discussion but finds it limited by a lack of ‘real-world’ practice. He wants more immediate feedback on his decisions.
  • Ethical concerns: He is not as worried about privacy but more about AI’s potential to be biased or miss the soft skills he needs to succeed.
  • Interest and Adoption: He might try it but needs a strong pilot program to convince him. He also needs to see a direct application to his engineering management context.

Participant 3:

  • Age: 30-35
  • Gender: Female
  • Highest level of education: Bachelor’s Degree (Communications)
  • Preferred learning style: Classroom
  • Technology comfort: Neutral
  • VR ownership: No
  • AI-driven VR interest: Somewhat uninterested
  • AI-driven VR for business skills: Somewhat not valuable

Participant Summary

  • Traditional MBA experience: She has mixed feelings. She enjoys networking but finds some of the material very dry and numbers-focused.
  • Practical skills importance: Important, but focused on ‘soft skills’ like communication, client relationship management, etc.
  • Reason for MBA: To transition her career into management within a creative agency.
  • Career goals: She wants to lead a team and eventually start her own agency.
  • VR benefits: She struggles to see its relevance for her. She worries that VR might make learning too impersonal, removing the collaborative classroom element she enjoys.
  • VR challenges: Cost and accessibility. Her tech background is limited, and she is concerned about a steep learning curve.
  • AI Feedback: She is very wary. She fears AI couldn’t evaluate her creativity or nuanced communication style. She prefers feedback from a human mentor.
  • Learning Preferences: She loves group discussions and brainstorming and wants the MBA program to focus more on ‘people skills’.
  • Ethical concerns: AI bias is a big worry. She is concerned that VR data might be used to rank students or make decisions about their performance.
  • Interest and Adoption: She is unlikely to participate. She needs to see a compelling case about how VR can help her develop skills unique to her field.

Participant 4:

  • Age: 40-45
  • Gender: Female
  • Highest level of education: Master’s Degree (Public Health)
  • Preferred learning style: Internship
  • Technology comfort: Somewhat uncomfortable
  • VR ownership: No
  • AI-driven VR interest: Neutral, potential, but needs convincing.
  • AI-driven VR for business skills: Somewhat valuable

Participant Summary:

  • Traditional MBA experience: Participant 4 is an experienced healthcare administrator. The MBA is broadening her perspective, but some concepts feel abstract.
  • Practical skills importance: Extremely important. She wants to immediately apply her MBA knowledge to improve her organisation’s efficiency.
  • Reason for MBA: Advance into a role with more influence on the strategic direction of her organisation.
  • Career goals: Wants to utilise her clinical background and new business knowledge to streamline healthcare delivery systems.
  • VR benefits: Could help visualise complex processes, making financial concepts more intuitive.
  • VR challenges: Worried about accessibility and user-friendliness. Doesn’t have time for a complicated learning curve.
  • AI Feedback: Very valuable, but from a trusted source. Wants feedback grounded in healthcare expertise, not just general algorithms.
  • Learning Preferences: Classroom learning is fine, but she wants to focus more on simulations tailored to her industry.
  • Ethical concerns: Patient data privacy and informed consent are paramount in her field, so she has similar concerns about VR data collection.
  • Interest and Adoption: She is interested but needs a pilot program to see VR work well in healthcare. It needs to be easy to use.

Participant 5:

  • Age: 20-25
  • Gender: Male
  • Highest level of education: Bachelor’s Degree (Computer Science)
  • Preferred learning style: Online
  • Technology comfort: Very comfortable
  • VR ownership: Yes (high-end VR setup)
  • AI-driven VR interest: Very interested
  • AI-driven VR for business skills: Very valuable

Participant Summary:

  • Traditional MBA experience: Fresh out of undergrad, he’s finding it a bit slow-paced. He loves the ‘big picture’ business thinking but wants to prototype his ideas sooner.
  • Practical skills importance: Essential. Ben’s goal isn’t just theoretical knowledge; he wants to build a company.
  • Reason for MBA: To round out his technical skills and build a network for potential co-founders and investors.
  • Career goals: Launch his tech startup.
  • VR benefits: There is huge potential. VR is seen as a way to test market reactions, iterate on products and fail safely before going live.
  • VR challenges: Cost is a factor, and how accurately VR can replicate complex real-world market dynamics.
  • AI Feedback: He wants this. He is used to getting data-driven feedback in coding and believes it will elevate his business skill development.
  • Learning Preferences: The classroom is okay, but he wants more ways to apply knowledge in a fast-paced, experimental setting. He thinks VR could be great for this.
  • Ethical concerns: Less focused on privacy, more excited about the potential of AI to accelerate his learning.
  • Interest and Adoption: He is very enthusiastic. He would likely advocate for VR integration and provide extensive feedback to improve the experience.


Google Rating
Based on 18 reviews