Orchestration Load Indicators and Patterns: In-the-Wild Studies Using Mobile Eye-Tracking

Autor/inn/en	Prieto, Luis P.; Sharma, Kshitij; Kidzinski, Lukasz; Dillenbourg, Pierre
Titel	Orchestration Load Indicators and Patterns: In-the-Wild Studies Using Mobile Eye-Tracking
Quelle	In: IEEE Transactions on Learning Technologies, 11 (2018) 2, S.216-229 (14 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Prieto, Luis P.)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1939-1382
DOI	10.1109/TLT.2017.2690687
Schlagwörter	Eye Movements; Cognitive Ability; Usability; Classroom Techniques; Physiology; Case Studies; Educational Technology; Teaching Methods; Technology Integration; Elementary School Students; Secondary School Students; College Students; Models; Behavior Patterns; Student Behavior; Laptop Computers; Validity; Measurement; Familiarity; Foreign Countries; Technological Literacy; College Faculty; Elementary School Teachers; Secondary School Teachers; Prediction; Regression (Statistics); Switzerland + Suchen Sie Ihr Suchwort? Augenbewegung; Denkfähigkeit; Klassenführung; Physiologie; Case study; Fallstudie; Case Study; Unterrichtsmedien; Teaching method; Lehrmethode; Unterrichtsmethode; Sekundarschüler; Collegestudent; Analogiemodell; Student behaviour; Schülerverhalten; Laptop computer; Laptop; Computer; Digitalrechner; Gültigkeit; Messverfahren; Ausland; Technisches Wissen; Fakultät; Elementary school; Teacher; Teachers; Grundschule; Volksschule; Lehrer; Lehrerin; Lehrende; Vorhersage; Regression; Regressionsanalyse; Schweiz
Abstract	Orchestration load is the effort a teacher spends in coordinating multiple activities and learning processes. It has been proposed as a construct to evaluate the usability of learning technologies at the classroom level, in the same way that cognitive load is used as a measure of usability at the individual level. However, so far this notion has remained abstract. In order to ground orchestration load in empirical evidence and study it in a more systematic and detailed manner, we propose a method to quantify it, based on physiological data (concretely, mobile eye-tracking measures), along with human-coded behavioral data. This paper presents the results of applying this method to four exploratory case studies, where four teachers orchestrated technology-enhanced face-to-face lessons with primary, secondary school, and university students. The data from these studies provide a first validation of this method in different conditions, and illustrate how it can be used to understand the effect of different classroom factors on orchestration load. From these studies, we also extract empirical insights about classroom orchestration using technology. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01