Introduction
Work-Integrated Learning (WIL) programs are increasingly recognized as essential components of higher education curricula, bridging the gap between academic learning and professional practice (Jackson & Bridgstock, 2021). Within the Bachelor of Information Technology (BIT) program, the ITEC320 WIL unit provides a platform for final-year students to apply disciplinary knowledge in real-world contexts, refine employability skills, and develop professional competencies. However, challenges persist—students often struggle with securing timely, personalised feedback on their résumés, practicing for interviews, and managing the logistics of job preparation. In response, this initiative introduced ChatGPT, a generative AI tool, to support ITEC320 students. By offering accessible, adaptive, and round-the-clock guidance, the project aimed to enhance students’ readiness for the workforce, reinforce their confidence, and foster more equitable learning outcomes.

Context and Rationale

Traditional WIL approaches frequently rely on external internships, mentorship, or limited workshop sessions that may not fully cater to the diverse schedules and backgrounds of undergraduate students (James & Casidy, 2018). Students can benefit from flexible learning tools that provide immediate feedback, help them craft professional documents, and simulate industry interactions. Emerging literature on digital learning tools suggests that AI-driven platforms can enhance student engagement, provide personalized support, and improve the quality of learning experiences (Holmes, Bialik, & Fadel, 2019).

By incorporating ChatGPT into ITEC320, the project aligns with calls for more innovative, learner-centered pedagogies. Drawing on principles of andragogy and experiential learning, the initiative encouraged students to learn actively—through refining their CVs, generating tailored interview questions, and scheduling their preparation time more effectively—thus developing digital literacy and adaptive thinking skills essential for the modern workforce (Knowles, Holton III, & Swanson, 2014; Kolb, Kolb, Passarelli, & Sharma, 2014).

Project Implementation

The project unfolded over a six-month period, beginning with a pilot phase where the lecturer introduced ChatGPT as a supplementary resource rather than a prescriptive solution. Training sessions guided students in effective “prompt engineering,” enabling them to pose queries that elicited high-quality, contextually relevant responses from the AI tool. This skill allowed learners to maximise the platform’s potential for a range of activities:

1. CV Enhancement: Students drafted their résumés and iteratively improved them with ChatGPT’s suggestions on structure, language, and industry-aligned terminology. This iterative feedback loop helped refine professional documents quickly and effectively.
2. Interview Preparation: By prompting ChatGPT to simulate interview scenarios, students practiced articulating their technical knowledge, communicating their personal brand, and rehearsing responses to common and role-specific questions. Two students who had previously struggled in interviews reported success in subsequent attempts after leveraging ChatGPT’s guidance. This is a true positive impact of the study.
3. Company Research and Scheduling: Students employed ChatGPT to gather information about prospective employers (placement providers), understand the company background, and generate strategic questions for interviews aligned with particular role and organisation. We observed that the tool also offered tips on time management strategies, helping students schedule their preparation activities more efficiently—one student described this as a “game changer.”

Throughout implementation, the lecturer emphasised the importance of critically evaluating ChatGPT’s outputs, ensuring learners integrated AI-generated feedback thoughtfully rather than accepting it at face value.

Pedagogical Framework

The initiative’s pedagogical underpinnings draw from Constructivist and Experiential Learning Theories, which prioritise active participation, reflective practice, and the construction of understanding through meaningful tasks (Kolb et al., 2014). By interacting with ChatGPT, students were not passive recipients of information but engaged problem-solvers who learned to refine their prompts, assess the relevance of the AI’s suggestions, and iteratively improve their professional materials.

Andragogy principles also played a vital role, recognising that adult learners benefit from self-directed, goal-oriented tasks closely tied to real-world applications (Knowles et al., 2014). The AI’s on-demand nature supported this paradigm by allowing students to seek guidance whenever required, regardless of time zones or resource limitations.

Academic Integrity and Ethical Considerations

Upholding academic integrity remained a priority. Educators provided explicit guidelines to distinguish between leveraging AI for idea generation, drafting assistance, and practice versus relying on it as a direct source of final content. To reinforce authenticity, faculty employed AI-detection tools and conducted spot checks to ensure students’ final submissions reflected their true capabilities (Dawson & Searle, 2023). This balanced approach promoted ethical use of technology while capitalising on the platform’s educational benefits.

Outcomes and Impact

Preliminary feedback indicated high levels of student engagement and improved confidence in navigating professional challenges. Informal surveys suggested that a majority of participants found ChatGPT helpful for enhancing their CVs and interview techniques. Notably, previously underprepared students reported increased comfort and success in real-world job application scenarios. Such outcomes align with broader research underscoring the benefits of technology-mediated learning interventions in skill development and employability (Holmes et al., 2019; Jackson & Bridgstock, 2021).

Data collection and research is ongoing, with qualitative interviews, surveys, and performance metrics capturing both student perspectives and educator evaluations. Early results suggest that, when integrated thoughtfully and ethically, AI tools can enrich WIL experiences, support diverse learners, and strengthen the bridge between academic theory and professional practice.

Challenges and Future Directions

A significant challenge encountered during the pilot phase was the substantial variability in students’ ability to formulate effective prompts for ChatGPT. While some readily adapted, others struggled to produce queries that elicited meaningful, context-specific guidance. To address this, the subject coordinator / lecturer organised two particular sessions, providing exemplars and structured exercises to help students refine their prompt engineering skills. Lecturer also showed various LinkedIn videos and other sources to help students with this. Another concern emerged from the potential overreliance on AI-generated content—some learners risked relying too heavily on the tool’s suggestions. In response, the lecturer integrated reflective tasks and peer feedback sessions, encouraging students to critically evaluate ChatGPT’s outputs rather than accepting them at face value.

Conclusion
Integrating ChatGPT into the ITEC320 WIL unit represents an innovative step in harnessing AI’s potential to enhance professional readiness. By providing continuous, personalised guidance, the initiative helps students refine essential employability skills, from crafting CVs to excelling in interviews. Grounded in established learning theories and supported by ongoing evaluation, this case study demonstrates the promise of generative AI to complement traditional instruction, foster inclusive learning environments, and ultimately prepare graduates to thrive in an increasingly complex and dynamic job market.

References

Dawson, P., & Searle, S. (2023). Artificial Intelligence and Academic Integrity. Higher Education Research & Development, 42(1), 150–154.

Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial Intelligence in Education: Promises and Implications for Teaching and Learning. Center for Curriculum Redesign.

Jackson, D., & Bridgstock, R. (2021). What Actually Works to Improve Graduate Employability? A Systematic Review of the Evidence. Higher Education Research & Development, 40(5), 1111–1126.

James, L. T., & Casidy, R. (2018). Authentic Assessment in Business Education: Its Effects on Student Satisfaction and Promoting Behaviour. Studies in Higher Education, 43(3), 401–415.

Knowles, M. S., Holton III, E. F., & Swanson, R. A. (2014). The Adult Learner: The Definitive Classic in Adult Education and Human Resource Development. Routledge.

Kolb, A. Y., Kolb, D. A., Passarelli, A., & Sharma, G. (2014). On Becoming an Experiential Educator: The Educator Role Profile. Simulation & Gaming, 45(2), 204–234.