Conference Agenda

In 2024, EERA celebrates its 30^th anniversary. This makes ECER 2024 in Nicosia the ideal moment to look back at the previous conferences in order to get a grasp of the central topics that were addressed throughout the years. This is precisely the focus of this EERA session. The session starts with a presentation of the preliminary results of an empirical analysis of the ECER abstracts database identifying the most important topics that were addressed in the previous three decades. This is followed by a panel discussion in which is explored what this means for the field: Which topics have been dominating European educational research, what has been under-addressed so far, and where do we see promising and necessary pathways for the future?

This EERA session is part of an ongoing research project aimed at identifying the most important themes or research topics (both substantive and methodological) that have been addressed in the previous decennia of European Conferences on Educational Research. The aim is to create an overview of the very diverse work that has already been done in the field, in doing so offering an insight into which research topics dominate the field. The focus of the research project purposefully supersedes the level of the individual networks, using abstracts across the networks as a window into what European educational research these past years has been about.

The session pivots around the results of an empirical analysis of the ECER abstracts database. This is done through topic modelling, which is an automated content analysis technique for the analysis of large corpora (Arora et al., 2018). It is a powerful text mining technique that derives latent meaning from a body of text by investigating large patterns over multiple documents. This general approach is also called distant reading (Wiedemann, 2013). Topic modelling reduces the complexity of a corpus by finding topics, “collections of words that have a high probability of co-occurrence” within documents throughout the corpus (Jaworska & Nanda, 2018, p. 11). A topic model is then a model consisting of several “topics” that together represent the content of the corpus. Every topic has a weight that reflects its importance in the corpus. Taken together, this means that the topics this study identifies are collections of words that are repeatedly used together throughout the analyzed ECER abstracts, in this way representing the most important themes or topics that have been addressed at the conferences.