Teachers' Data Literacy for Learning Analytics: A Central Predictor for Digital Data Use in Upper Secondary Schools

Autor/inn/en	Michos, Konstantinos; Schmitz, Maria-Luisa; Petko, Dominik
Titel	Teachers' Data Literacy for Learning Analytics: A Central Predictor for Digital Data Use in Upper Secondary Schools
Quelle	In: Education and Information Technologies, 28 (2023) 11, S.14453-14471 (19 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Michos, Konstantinos) ORCID (Schmitz, Maria-Luisa) ORCID (Petko, Dominik)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1360-2357
DOI	10.1007/s10639-023-11772-y
Schlagwörter	Secondary School Teachers; Prediction; Data Use; Data Analysis; Foreign Countries; Learning Analytics; Pedagogical Content Knowledge; Teaching Methods; Teacher Attitudes; Self Evaluation (Individuals); Switzerland + Suchen Sie Ihr Suchwort? Vorhersage; Auswertung; Ausland; Pädagogische Kompetenz; Teaching method; Lehrmethode; Unterrichtsmethode; Lehrerverhalten; Schweiz
Abstract	Since schools increasingly use digital platforms that provide educational data in digital formats, teacher data use, and data literacy have become a focus of educational research. One main challenge is whether teachers use digital data for pedagogical purposes, such as informing their teaching. We conducted a survey study with N = 1059 teachers in upper secondary schools in Switzerland to investigate teacher digital data use and related factors such as the available technologies in schools. Descriptive analysis of the survey responses indicated that although more than half of Swiss upper-secondary teachers agreed with having data technologies at their disposal, only one-third showed a clear tendency to use these technologies, and only one-quarter felt positively confident in improving teaching in this way. An in-depth multilevel modeling showed that teachers' use of digital data could be predicted by differences between schools, teachers' positive beliefs towards digital technologies (will), self-assessed data literacy (skill), and access to data technologies (tool) as well as by general factors such as frequency of using digital devices in lessons by students. Teacher characteristics, such as age and teaching experience, were minor predictors. These results show that the provision of data technologies needs to be supplemented with efforts to strengthen teacher data literacy and use in schools. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01