Mentoring for Early Career Mathematicians Using the ONSIDE Mentoring Concept
If ONSIDE Mentoring conjures up a vision of two teams of 11 running up and down a football pitch, we are sorry to disappoint you. ONSIDE Mentoring has nothing to do with the beautiful game, but everything to do with mentoring early career professionals, including mathematicians embarking on their professional journeys.
Andy Hobson, Professor of Teacher Learning and Development and Head of Education Research at the University of Brighton, developed the ONSIDE model of mentoring in 2016. The model was based on five research studies of mentoring and professional learning, alongside a review of international research evidence. While initially designed with Early Career Teachers in mind, the principles of the ONSIDE model are widely applicable, including to early career mathematicians in academia, industry, and research.
The model aims to strike the right balance between supporting and challenging early career professionals. It is built on a foundation of trust and alternates between the mentor working alongside the mentee as an ally and directing them when necessary, providing valuable guidance. Effective mentoring requires a high degree of professional judgement, increasing opportunities for the mentee to grow by allowing them to take risks and learn from experience.
ONSIDE Mentoring consists of six core elements.
Each letter of the acronym represents a key aspect:
- Off-line – The mentoring relationship is separate from the mentee’s line management and supervision, ensuring a non-hierarchical dynamic. A mentee being mentored by their direct supervisor may be hesitant to share concerns or take risks, for fear of negative repercussions. In a mathematical context, this separation can allow mentees to explore new research ideas, career pathways, or industry applications without undue pressure.
- Non-judgemental and non-evaluative – The mentor does not impose rigid directives or make critical judgments but instead fosters open dialogue. Active listening, avoiding interruptions, and paying attention to non-verbal communication are essential skills for an effective mentor. In mathematics, where problem-solving and innovation require a degree of intellectual risk, this approach creates a safe space for mentees to explore new theories, proofs, or applications.
- Supportive of the mentee’s psycho-social needs and wellbeing – Mathematical research and professional work can be intellectually demanding and, at times, isolating. A strong mentoring relationship acknowledges that personal wellbeing impacts professional performance. A mentor should be attuned to the mentee’s challenges, including imposter syndrome, work-life balance, and the pressures of academic publishing or industry deadlines.
- Individualised – The mentoring relationship should be tailored to the unique needs of each mentee, recognising that circumstances and aspirations evolve over time. Mathematicians pursuing different career paths—whether in academia, finance, data science, engineering, or beyond—will require different forms of support and guidance. A mentor should continuously assess and adapt to these changing needs.
- Developmental and growth-oriented – The mentor serves as a sounding board, encouraging the mentee to take responsibility for their own learning and career decisions. This includes fostering a growth mindset, focusing on strengths and aspirations, and helping the mentee set clear goals. In mathematics, this might mean encouraging exploration of interdisciplinary applications, attending conferences, or pursuing collaborations that align with long-term career ambitions.
- Empowering – A successful mentoring relationship is one where the mentee gradually gains confidence and independence. As the relationship progresses, the mentor should adopt a progressively non-directive approach, supporting the mentee in becoming more autonomous. In the field of mathematics, this could mean guiding mentees towards developing their own research agenda, leading projects, or making strategic career decisions with greater self-assurance.
Whether you’re an early career mathematician seeking mentorship or an experienced professional considering mentoring, the ONSIDE model offers a structured, research-backed approach to foster growth and development.
The Institute of Mathematics and its Applications (IMA) provides mentoring opportunities. Explore our program to find or become a mentor and support the next generation of mathematicians.
