Asset and deficit discourses in refugee education: A systematic review and meta-synthesis of historical and disciplinary patterns

• In Event: Refugee education: Balancing challenges and assets

Proposal

The published literature on refugee education has grown substantially during the past two decades since the creation of the education humanitarian cluster and the commitment of international actors to refugee inclusion in the public education systems of host countries. However, there remains a concern that the literature overly medicalizes and objectifies those who are classified as refugees. Despite these concerns, there is no systematic evidence of the extent of the use of positive and negative framing to discuss refugees within the literature concerned with education in emergencies. This extensive systematic review and meta-synthesis seeks to provide such an overview, while also identifying patterns associated with more or less positive, asset-based framing. From this, we encourage researchers in the field to move toward a more asset-based approach to their research. By doing so, we believe refugee education research will be better equipped to support the everyday protests and actions undertaken by those who’s learning has been affected by large-scale displacement. The systematic review and meta-synthesis addresses the following research questions:

1) To what degree does the peer-reviewed academic literature on refugee education use positive and/or negative discourse(s)? 2) To what degree does this differ by the first authors’ discipline and location? 3) To what degree has this changed over time?

In order to address these research questions we conducted a structured search on September 29, 2022 using the following education and sociology databases via the ProQuest platform: (1) ProQuest Education Database, (2) ERIC, (3) International Bibliography of the Social Sciences, (4) PAIS Index, (5) ProQuest Social Science Database, (6) Sociological Abstracts, (7) Sociology Database. This search returned over 10,295 potential papers which were then each screened using Covidence for inclusion based on whether they were about the correct population (refugees) and the correct sector (education). Screening of titles and abstracts was done by two reviewers, with disagreements resolved by a third reviewer. Full texts were reviewed by a single reviewer with uncertain articles reviewed by a second. Finally, 1,221 articles were included for analysis.

Articles were converted into a corpus for large-scale textual analysis using R. Using the R package sentimentr, each article was assigned an average sentiment score (on a negative to positive valanced scale). Patterns in this score were then analyzed using descriptive statistics and regression analysis. For qualitative analysis, 60 articles were sampled purposely for maximum variation to cover high/low sentiment scores, high-/middle-/low-income countries, the journal’s disciplinary focus (education/other), and whether there was more than one author. These were then thematically coded to provide a more in-depth and nuanced understanding of when, why, and how authors use asset-based approaches (or not) in refugee education research.

Authors

• Daniel D Shephard, Indiana University Bloomington and NORRAG

• Jihae Cha, The George Washington University

• InJung Cho, The George Washington University

• Isabella McCallum, Leading Through Learning Global Platform and EDC