Conducting inclusive research

In order for educational research to understand and represent a diverse range of experiences from different groups, it is important that educational research practices are inclusionary. InclusionAn approach where a school aims to ensure that all children are educated together, with support for those who require it to access the full curriculum and contribute to and participate in all aspects of school life is an important consideration at every stage of the research process (research design, data collection, analysis and reporting) to ensure that the voices of underrepresented groupsThe diversity of research participants should reflect the educational community for whose benefit the research is taking place. When this is not the case, some groups are underrepresented in particular are heard. The long-held view that quantitative researchQuantitative research usually emphasises quantification in the collection and analysis of data., with its emphasis on measurement and empirical data, is more rigorous and robust than qualitative researchQualitative research usually emphasises words rather than quantification in the collection and analysis of data. is starting to be challenged (Santoro, 2023). Statistical practices such as eliminating outliers when cleaning the data (where data points that lie outside of the normal distribution are deleted) perpetuate structural inequity by silencing voices from the research (Arellano, 2022). In comparison, qualitative research, with its focus on lived experiences, can deepen our understanding of the educational experiences of historically marginalised groups. 

This is not to say that the status quo is simply being, or should be, reversed. Quantitative and qualitative data can often complement each other, so having a breadth of methodological tools at our disposal when seeking to conduct inclusive research is valuable. These guidelines are aimed to support anyone who would like to learn more about inclusive research as well as anyone who would like to take a more inclusive approach in their own research design, data collection, analysis and write-up.

Guidelines for conducting inclusive research

This guidance is adapted from the Government Social Research (GSR) Inclusive Research Guidance, available at: A guide to inclusive social research practices – GOV.UK (www.gov.uk)

The guide to inclusive social research practices includes the following recommendations: 

• it is important to allocate sufficient time and resources to the design stage of the research process to ensure that the project can accurately capture the views of all relevant groups from the beginning
• using a range of data collection methods and approaches will help to reach underrepresented groups. The additional costs associated with these methods need to be factored into research plans
• analysis needs to consider equalities issues and should be taken on disaggregated dataDisaggregated data is data that has been broken down into detailed sub-categories, for example by sex, age, disability. Disaggregated data can reveal inequalities that may not be fully reflected in aggregated data. where possible
• when reporting research, the voice of underrepresented groups needs to be heard, with the diversityThe recognition of individual differences in terms of race, ethnicity, gender, sexual orientation, socio-economic status, physical ability, religious beliefs and other differences of participants reflected in the final report.

The guide also suggests the following questions for researchers to consider:

Research design

Designing inclusive research means taking time to understand different groups or subgroups within the research. For example, the design of the research question(s) may inherently and inadvertently exclude some groups. Engaging with communities to co-produce research questions may help to ensure that decisions about what is measured and prioritised are fair and equitable.

It is also important to consider the barriers and enablers of different research designs. The research question(s) can be addressed using qualitative methods, quantitative methods, or a combination of the two approaches. Using a mixed methods or qualitative approach can provide the researcher with a deeper level of insight. Individuals are simultaneously members of multiple interconnected social categories that interact and intersect to influence lived experiences. Qualitative research approaches are valuable to understanding this complexity, which can often be lost in quantitative studies alone.

Sampling techniques and sample sizes will vary according to whether you are conducting quantitative or qualitative research. For more detailed information on this, please see the ‘Further reading’ section.

Data collection

When engaging with underrepresented groups, consideration for their needs must be embedded in all aspects of data collection. However, developing suitable data collection practices can take time. 

To ensure that the research materials are as accessible as possible, consider the format and length of the materials as well as the language used. Keeping materials short will help to make your study more accessible. If English is not the first language for all participants, you may need to consider translating research materials. It is good practice to pre-test research materials to ensure language is accessible. Consent forms must also be written in accessible language, clearly stating why, how, and when personal data and research data will be used. All content should be made accessible according to the needs of different users, such as those using screen readers. Furthermore, not all materials have to be written. You could also consider producing materials in different formats, such as audio or video. Additional guidance on designing for different groups is provided in the ‘Further reading’ section below.

When collecting demographic data, a balance will need to be struck between ensuring that questions are not overly burdensome and collecting equalities dataEqualities data refer to all types of disaggregated data used to assess the comparative situation of a specific group at risk of discrimination or exclusion. that will be specific to each individual research project. Researchers should always try to use the most disaggregated taxonomy where possible, to help avoid cultural sensitivities arising from using higher level group options (for example, the category Asian encompasses a diverse population). However, whilst having lower-level categories will enable more detailed data analysis to be undertaken, it is important to ensure that you do not use low level categories that are too specific because this could lead to anonymity being compromised. 

It is important to think carefully about the phrasing of questions relating to demographics. The term BAME is not accepted by all and should be avoided, and the term ‘another’ is generally more inclusive when providing a list of categories for respondents to choose from, as opposed to ‘other’. Alternatively, participants can be given the opportunity to self-define if they do not identify with any of the proposed groups. Guidance on the use of terms relating to ethnicity, national identity, religion, gender and sex can be found in the ‘Further reading’ section.

Fundamentally, researchers must minimise the risk that participants taking part in their study will come to harm. Whilst central to research with any groups, this may be more pertinent when engaging with participants from underrepresented groups. For example, it is important to weigh up the wider benefits of the research with the possibility of unwittingly causing distress or creating self-doubt among your participants.

When choosing methods to recruit participants and collect data, it is important that accessibility is taken into consideration. Online methods may remove some barriers of face-to-face approaches (such as geographical and travel barriers) but exclude those who do not have access to digital devices or the necessary digital skills. This could lead to sampling biases in your study. Using a mixed methods approach to recruitment and data collection is therefore recommended. Careful consideration should be given to the location chosen for face-to-face methods, in terms of both accessibility requirements and whether participants will feel comfortable in the space. 

Conducting analysis

Broad categories have the potential to mask critical within-group differences and disparities. Disaggregation of data into the lowest possible level of characteristics is therefore important when analysing results. For example, conducting an analysis of educational attainment only at the Asian/Asian British level would fail to reveal significant variation among the five ONS-recommended Asian/Asian British sub-groups. 

Reflexivity and positionalityPositionality refers to what we know and believe. It relates to our understanding of ourselves, of who we are and what we bring to our research. For example, when a researcher describes their ‘position’ in relation to their study they may discuss their (possibly conflicting) roles as colleague, researcher, teacher and parent. It is linked to reflexivity. are important in qualitative research. It is important to acknowledge how the researcher’s beliefs, values and judgements may have influenced the conclusions reached. When conducting the analysis, it is also necessary to remain open to the issues and experiences that are important to the research participant(s). 

The most common approach to analysing quantitative data is to consider parametric/non-parametric tests, but there are many approaches beyond this. It is important to check that your data meets the assumptions for your identified statistical analysis. For example, when undertaking subgroup analysis to explore the data from underrepresented groups, there may be a risk that the sample size is too small and you may have to choose a different approach.

Reporting

Generally, it is important to cover four main areas in a report: 1) an overview of the problem or the topic; 2) data collection and analysis; 3) results, and 4) conclusions and recommendations. 

Just as with data collection, it is important to ensure you address a wide range of accessibility issues to make your data and evidence as accessible as possible. It is important to not unintentionally marginalise and/or stigmatise groups through the language that is used, and to avoid inaccessible technical language. Providing feedback to participants at the end of research, through presentations or brief summaries, can help to build trust and transparency around the research process. 

An example of conducting inclusive research in schools

Atkinson (2017) describes a mixed methods approach to research in one school that was driven by a desire to better understand the priorities of their community. Two contrasting strategies were adopted to better understand parents’ views. A parent research group was established, which consisted of around 20 parents representing a cross section of families from the school community. The group met every half-term, under the leadership of the deputy head. The school also used an online questionnaire to gather responses from a large number of parents about complex issues around school policies. You can read the full article on MyCollege. 

Further reading

For a discussion of sampling techniques and sample sizes in qualitative research, see Marshall (1996).

Sampling in quantitative research

Guidance on making written information easier to understand for people with learning disabilities.

Guidelines for producing materials for six diverse groups, including those with dyslexia and those who use screen readers.

Ethnicity data: how similar or different are aggregated ethnic groups?

Measuring equality: A guide for the collection and classification of ethnic group, national identity and religion data in the UK.

Sex and gender within the context of data collected for the Sustainable Development Goals (SDGs)

Inclusive Language Guidelines: American Psychological Association