A New Era in Multimodal Learning Analytics: Twelve Core Commitments to Ground and Grow MMLA

Autor/inn/en	Worsley, Marcelo; Martinez-Maldonado, Roberto; D'Angelo, Cynthia
Titel	A New Era in Multimodal Learning Analytics: Twelve Core Commitments to Ground and Grow MMLA
Quelle	In: Journal of Learning Analytics, 8 (2021) 3, S.10-27 (18 Seiten)Infoseite zur Zeitschrift PDF als Volltext kostenfreie Datei Verfügbarkeit
Zusatzinformation	ORCID (Worsley, Marcelo) ORCID (Martinez-Maldonado, Roberto) ORCID (D'Angelo, Cynthia)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1929-7750
Schlagwörter	Learning Analytics; Artificial Intelligence; Data Collection; Statistical Inference; Feedback (Response); Information Dissemination; Research Methodology; Learning Experience; Prediction; Data Interpretation + Suchen Sie Ihr Suchwort? Künstliche Intelligenz; Data capture; Datensammlung; Inferential statistics; Schließende Statistik; Informationsverbreitung; Research method; Forschungsmethode; Lernerfahrung; Vorhersage; Data evaluation; Datenauswertung
Abstract	Multimodal learning analytics (MMLA) has increasingly been a topic of discussion within the learning analytics community. The Society of Learning Analytics Research is home to the CrossMMLA Special Interest Group and regularly hosts workshops on MMLA during the Learning Analytics Summer Institute (LASI). In this paper, we articulate a set of 12 commitments that we believe are critical for creating effective MMLA innovations. Moreover, as MMLA grows in use, it is important to articulate a set of core commitments that can help guide both MMLA researchers and the broader learning analytics community. The commitments that we describe are deeply rooted in the origins of MMLA and also reflect the ways that MMLA has evolved over the past 10 years. We organize the 12 commitments in terms of (i) data collection, (ii) analysis and inference, and (iii) feedback and data dissemination and argue why these commitments are important for conducting ethical, high-quality MMLA research. Furthermore, in using the language of commitments, we emphasize opportunities for MMLA research to align with established qualitative research methodologies and important concerns from critical studies. (As Provided).
Anmerkungen	Society for Learning Analytics Research. 121 Pointe Marsan, Beaumont, AB T4X 0A2, Canada. Tel: +61-429-920-838; e-mail: info@solaresearch.org; Web site: https://learning-analytics.info/index.php/JLA/index
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01