The Data Dilemma: Authors' Intentions and Recognition of Research Data in Educational Technology Research

TL;DR

This paper investigates how educational technology researchers recognize and categorize their research data, revealing gaps in awareness and highlighting the need for better guidelines and recognition of diverse data types.

Contribution

It provides an analysis of researcher perspectives on research data in EdTec, identifying recognition gaps and suggesting the need for improved data publication guidelines.

Findings

Not all research data was recognized as such by authors.

Software and qualitative data are often overlooked as research data.

Analysis of DELFI proceedings shows the types of data published.

Abstract

Educational Technology (EdTec) research is conducted by multiple disciplines, some of which annually meet at the DELFI conference. Due to the heterogeneity of involved researchers and communities, it is our goal to identify categories of research data overseen in the context of EdTec research. Therefore, we analyze the author's perspective provided via EasyChair where authors specified whether they had research data to share. We compared this information with an analysis of the submitted articles and the contained research data. We found that not all research data was recognized as such by the authors, especially software and qualitative data, indicating a prevailing lack of awareness, and other potential barriers. In addition, we analyze the 2024 DELFI proceedings to learn what kind of data was subject to research, and where it is published. This work has implications for training future generations of EdTec researchers. It further stresses the need for guidelines and recognition of research data publications (particularly software, and qualitative data).