Methods and Meta-science

Evidence in Learning and Didactics (ELD) is a larger collaboration aimed at producing evidence for learning and didactics through systematic reviews, meta-analyses, and meta-reviews, and presenting them on an interactive platform.

A main part of this project is a large-scale review of the “Hattie's list”, which is conducted within the framework of the project Rethinking Hattie's list of student achievement, funded by the Swedish Research Council (Vetenskapsrådet).

ELD also includes the development of a resource specifically for educators. By writing pop-science summaries of carefully reviewed systematic reviews and analyses, we aim to make educational research more accessible, understandable, and relevant for teachers, principals, and other educators.

Community-Augmented Meta-Analyses (CAMA) is a method to make meta-analyses accessible by presenting them as interactive datasets on a web platform according to FAIR principles of open data (findable, accessible, interoperable, reusable). These datasets can then be expanded and augmented by all researchers conducting meta-analyses. While the long-term aim is to develop this for various fields, we are currently using the method for Evidence in Learning and Didactics (see above), as well as for school interventions for students with intellectual disabilities (in collaboration with Linköping University).

We have recently conducted an interdisciplinary scoping review of systematic reviews on the use of artificial intelligence as decision support tools. Based on this review, we aim to focus on, among other things, the application within education (known as Learning Analytics).

In close collaboration with the journal Meta-Psychology, we develop methods to ensure that the results in scientific articles can be reproduced. Lucija Batinović conducts reproducibility checks for all articles published in Meta-Psychology. We also work on developing methods to detect errors in research literature and are in the startup phase of a project to develop tools for error checks and “risk of error” checks.

We also conduct systematic reviews and meta-analyses on discrimination in the labor market (Rickard Carlsson, Samantha Sinclair, Lucija Batinović) and replication studies in various fields focusing on social psychology (Samantha Sinclair) and forensic psychology (Rebecca Willén).

In psychometrics, Anna Bratt and Viktor Kaldo primarily work on developing self-assessment scales. Anna Bratt works on developing self-assessment scales within self-compassion. Viktor Kaldo develops, among other things, short self-assessment scales that can be used for specific diagnoses. His work also involves methods for monitoring treatments and developing models based on machine learning or traditional statistics to predict patients' treatment outcomes.