The prestigious award was given this week and recognizes his publication:
Campos, D. G., Fütterer, T., Gfrörer, T., Lavelle-Hill, R. E., Murayama, K., König, L., Hecht, M., Zitzmann, S., & Scherer, R. (2024). Screening Smarter, Not Harder: A Comparative Analysis of Machine Learning Screening Algorithms and Heuristic Stopping Criteria for Systematic Reviews in Educational Research. Educational Psychology Review, 36(1).DOI: 10.1007/s10648-024-09862-5.
In this study, Diego and his colleagues provide an empirical evaluation of machine learning (ML) screening algorithms and heuristic stopping criteria in systematic reviews and meta-analyses within educational research.
Innovative research
Systematic reviews play a crucial role in advancing knowledge and informing evidence-based practices, yet efficiently identifying relevant studies remained a challenge. This innovative research assesses the sensitivity, specificity, and time-saving potential of ML-driven screening technologies, offering much-needed performance estimates. The findings help educational researchers integrate these methods to streamline study selection and enhance research efficiency
Congratulations to Diego and his co-authors on this well-deserved achievement!
Here you can read more about the Society for Empirical Educational Research (external link)