Appreciative Inquiry: An innovative approach to eliciting voices of Secondary School Leaders

PIF 6 February 2020

Gill Thomas is a post graduate doctoral student at ARU and her school experience includes posts as a Trust Educational Director in secondary and primary academies, an Executive Headship and two Secondary Headships. At our Participatory Inquiry Forum focused on doctoral research, Gill presented her findings and reflections from her Professional EdD using appreciative inquiry to hear the perspectives of Secondary School Leaders.

Gill conceptualised school leadership through a lens of change: school leaders are under huge pressure and face many challenges as a result of the unprecedented pace and extent of contemporary educational change (Hargreaves, 2014). Though research has demonstrated the need to develop leadership at all levels in schools (Harris, 2008), there is less evidence on how collaborative, distributed leadership impacts on student success, as perceived by Secondary School Leaders themselves.


School leaders ranging from middle leaders to head teachers, were recruited from three secondary academies from the South East of England, including one Outstanding, one Good, and one Requires Improvement as defined by the Office for Standards in Education (Ofsted, 2015). Through participant interviews, they offered new knowledge and possibilities as authors of their personal stories, creating new ‘worlds of meaning’ (Bushe, 2013).

Appreciative Inquiry (AI) represented an innovative way of eliciting the voices of Secondary School Leaders who aren’t always heard in the discourse on leadership (often dominated by head teachers and school governors). It also provides space to identify and build on successes rather than taking a deficit approach of focusing on problems (Bushe, 2013). Participants were empowered to reflect on their successes and promote their best practice (Shuayb, et al., 2009). Sharp et al. (2016) suggest that there is no single AI Inquiry method, but rather AI is formed around a set of core principles where voice, patterns of conversation and different perspectives to explore new possibilities are key.

Gill choose to adapt the 4D model of AI for her research, which comprises four phases: discovery, dream, design, and destiny (Cooperrider and Whitney, 2005). This enabled an exploration of current practice and identified areas of success to be developed into practice.



Distributed leadership characteristics that emerged across all three academies were trust, accountability, and collaboration. Further characteristics included collaboration, shared values, developing people, and a culture of success and honesty. Time constraints and an overarching value of moral purpose that were also prominent.

Dynamics of being trusted and trusting others had been established between leaders to enable a different way of working, that was distributed and collaborative – however participants emphasised that this had taken time. Trust was also influenced by an interdependency between collaboration and shared accountability. The participants identified a shift from individual accountability to shared accountability, underpinned by things like school standards, ethos and shared values around raising aspirations, engaging students and parents, and being more than just a school.

This interdependency of trust, collaboration and shared accountability was instrumental in how distributed leadership was able to influence student success. Student success was conceptualised broadly, from tackling gang culture to positive engagement with students and parents.

Adapting AI

Gill explained that she had intended to hold a group forum to share findings with the school leaders and discuss how they would take the learning forward; however the gatekeepers would not allow participants to spend any more time on the research. Accordingly, Gill adapted her approach to a 3D hybrid AI model (Crow, 2013). This was an ethical response to the challenge of participants’ time as there has to be a balance between the interests of the researcher and the interests of the institution (Kirsch, 1999).

In order to gain feedback for the design and destiny phases without taking up too much time, Gill developed and emailed feedback sheets that gave participants the opportunity to comment on the themes to generate a collective view from each school. This final phase identified evidence of a guiding sense of moral purpose that was an intrinsic part of their leadership, both in a practical way for example by keeping students engaged and away from gang culture, and in a broader context of social justice. Creating a climate of success was also identified, evident for example in the school with the highest levels of disadvantage being passionate about every single student.

Our discussions during the PIF included how the AI approach enabled a collection of voices – a choir of voices – where no one component is more or less important than another. This was also reflected in the community of leaders in each school who are sharing accountability for student success and all have a part to play, though they are not all doing the same things. We also talked about being able to be vulnerable as a leader in order to talk about where improvements are needed.

We also talked about the strengths and limitations of the AI approach. For example, though it is useful to identify and build on best practice, does this obscure problems? Gill concluded that with significant time constraints and other pressures on schools, the adapted AI approach may represent a meaningful way to engage school-based professionals and to support the participation of school leaders in considering successful practice.

Author: annadadswell

As a Research Fellow in Social Work and Social Policy at Anglia Ruskin University, I manage the Participatory Research Blog. Please feel free to contact me with questions and suggestions at

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