The European Journal of Development Research

, Volume 31, Issue 2, pp 139–162 | Cite as

Bridging to Action Requires Mixed Methods, Not Only Randomised Control Trials

  • Wendy OlsenEmail author


Development evaluation refers to evaluating projects and programmes in development contexts. Some evaluations are too narrow. Narrow within-discipline impact evaluations are weaker than multidisciplinary, mixed-methods evaluations. A two-step process leads toward profoundly better arguments in assessing the impact of a development intervention. The first step is setting out the arena for discussion, including what the various entities are in the social, political, cultural and natural environment surrounding the chosen problem. The second step is that, once this arena has been declared, the project and triangulation of data can be brought to bear upon logical arguments with clear, transparent reasoning leading to a set of conclusions. In this second step, we do need scientific methods such as peer review, data and so on, but, crucially, the impact evaluation process must not rest upon a single data type, such as survey data. It is dangerous and undesirable to have the entire validity of the conclusions resting upon randomised control trials, or even a mixture of data types. Different contributions to knowledge exist within the evaluation process, including the interaction of people during action research, ethnography, case-study methods, process tracing and qualitative methods. The cement holding my argument together is that multiple logics are used (retroductive, deductive, and inductive, in particular). Deductive mathematics should not dominate the evaluation of an intervention, as randomised controlled trials on their own lend themselves to worrying fallacies about causality. I show this using Boolean fuzzy set logic. An indicator of high-quality development evaluation is the use of multiple logics in a transparent way.


Evaluation Randomised control trials Comparative case-study research Methodology Retroduction Mixed-methods Impact evaluation 


L’évaluation du développement se réfère à l’évaluation de projets et programmes dans le contexte du développement. Certaines évaluations sont trop restreintes. Les évaluations étroites, au sein de la même discipline, sont plus faibles que les évaluations multidisciplinaires utilisant des approches mixtes. Pour évaluer l’impact des interventions en matière de développement, un procédé a deux étapes nous aide à bâtir des argumentations beaucoup plus fortes. La première étape est d’établir l’espace de la discussion, y compris les organismes sociales, politiques, culturales et naturels qui encerclent le problème choisi. La deuxième étape, une fois cet espace est défini, est d’utiliser le projet et la triangulation des données de forme logique, produisant un raisonnement transparent et clair qui nous amène à des conclusions. Cette deuxième étape nécessite de méthodologies scientifiques tels que la révision par des pairs, l’utilisation des données, etc. C’est crucial que le processus d’évaluation des impacts ne s’appuie pas que sur un seul type de données, comme par exemple les données d’enquête. Que l’ensemble de la validité des conclusions soit basé que sur des essais de contrôle randomisées (en anglais: randomised control trials, ou RCT), ou même sur une combinaison de différents types de données, est c’est au même temps dangereux et non désirable. Le processus d’évaluation contribue de différentes façons à la connaissance, y inclus à travers les interactions des gens pendant la recherche, l’ethnographie, les méthodologies d’études de cas, le traçage des processus, et les méthodologies qualitatives. C’est clé que multiples logiques soient utilisées (en particulier, retroductive, déductive, et inductive). Les mathématiques deductives ne doivent pas dominer les évaluations des interventions, puisque les RCTs mêmes se prêtent à des préoccupantes erreurs de casualité: on le démontre utilisant les ensembles Boolean de logiques floues. Un indicateur d’une haute qualité des évaluations des interventions est l’utilisation de multiples logiques d’une façon transparente.



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Copyright information

© European Association of Development Research and Training Institutes (EADI) 2019

Authors and Affiliations

  1. 1.Department of Social StatisticsUniversity of ManchesterManchesterUK

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