
The Quality of Evidence Synthesis Tool (QuEST) was developed by Dr Melissa Bond to help with appraising the quality of a variety of evidence syntheses across disciplines. So far, it has been used to appraise the quality of evidence synthesis in the fields of: Artificial intelligence in Education - e.g., Bond et al. (2024) Educational Technology - e.g., Buntins et al. (2023) Programming & Robotics - e.g., Forsström et al. (2024) Widening participation in Higher Education - e.g., Negrea & Gartland (2025) Climate & Health - forthcoming Teacher continuing professional development & initial teacher education - forthcoming The tool is being adopted by the Review of Education and the Journal of Open, Distance, and Digital Education (JODDE) to assist with editorial and peer reviewing processes. Researchers are encouraged to use this checklist when planning, undertaking and reporting their reviews, alongside other rigorous guidelines (e.g. PRISMA). An editorial is planned for the Review of Education, alongside a full methodological article about QuEST.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 1 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
