Abstract:

The rapid development of artificial intelligence is reshaping the competencies required in the labour market, increasing the importance of adaptability, self-awareness, and lifelong learning. At the same time, Generation Z students expect more personalized, relational, and development-oriented forms of support in higher education. In this context, academic mentoring is gaining recognition as an effective approach to addressing these emerging needs and bridging the gap between formal education and future career demands.

The aim of this study is to explore which mentoring practices and relational mechanisms are perceived by Generation Z students as most valuable for their academic and professional development, and to identify barriers that limit the effectiveness of mentoring programmes in contemporary higher education.

Methodology:
The study adopts a qualitative approach and examines three editions of the Uni-Me mentoring programme implemented at Nicolaus Copernicus University in Toruń (Poland) as an example of a practice aligned with Generation Z expectations. Data were collected through semi-structured interviews with students and mentors, participant observation of mentoring sessions and mentor training, and document analysis. Additionally, open-ended expectation and evaluation surveys were used to support data triangulation and case profile development. The data were transcribed and analysed using thematic analysis with coding. Credibility was enhanced through triangulation and member checking.

Results and conclusions of the research:
The findings are expected to identify key mentoring practices (e.g. active listening, developmental tasks, career coaching), as well as underlying mechanisms of impact, such as increased self-awareness leading to changes in learning strategies and career decisions. The study will also highlight organisational and relational barriers, including mismatched expectations and limited institutional support. The comparison of expectations and post-programme evaluations provides further insight into perceived effectiveness.
The study offers practical implications for designing and scaling mentoring programmes that support Generation Z students in developing future-oriented competencies in the age of AI. The results are relevant for programme coordinators, academic staff, and educators seeking to enhance student support in higher education.

Keywords:

Academic mentoring, higher education, Generation Z, artificial intelligence (AI), soft skills, support, lifelong learning.