J 2026

Open Datasets in Learning Analytics: Trends, Challenges, and Best PRACTICE

ŠVÁBENSKÝ, Valdemar; Brendan FLANAGAN; Erwin Daniel LÓPEZ ZAPATA a Atsushi SHIMADA

Základní údaje

Originální název

Open Datasets in Learning Analytics: Trends, Challenges, and Best PRACTICE

Autoři

ŠVÁBENSKÝ, Valdemar; Brendan FLANAGAN; Erwin Daniel LÓPEZ ZAPATA a Atsushi SHIMADA

Vydání

ACM Transactions on Knowledge Discovery from Data, ACM, 2026, 1556-4681

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Stát vydavatele

Spojené státy

Utajení

není předmětem státního či obchodního tajemství

Odkazy

URL, URL

Označené pro přenos do RIV

Ne

Organizace

Fakulta informatiky – Masarykova univerzita – Repozitář

DOI

https://doi.org/10.1145/3798096

Klíčová slova anglicky

open data; public data; data sharing; data management; open science; learning analytics; educational data mining; artificial intelligence in education; AI in education; systematic literature review; systematic mapping study; survey

Návaznosti

GN25-15839I, projekt VaV.
Změněno: 27. 2. 2026 00:51, RNDr. Daniel Jakubík

Anotace

V originále

br /\>Results and contributions: Our study presents the most comprehensive collection and analysis of open educational datasets to date, along with the most detailed categorization. Of the 172 datasets identified, 143 were not captured in any prior survey of open data in learning analytics. We provide insights into the datasets’ context, analytical methods, use, and other properties. Based on this survey, we summarize the current gaps in the field. Furthermore, we list practical recommendations, advice, and 8-item guidelines under the acronym PRACTICE with a checklist to help researchers publish their data. Lastly, we share our original dataset: an annotated inventory detailing the discovered datasets and the corresponding publications. We hope these findings will support further adoption of open data practices in learning analytics communities and beyond.
Zobrazeno: 22. 6. 2026 07:02