Employing Augmented-Reality-Embedded Instruction to Disperse the Imparities of Individual Differences in Earth Science Learning

Autor/inn/en	Chen, Cheng-ping; Wang, Chang-Hwa
Titel	Employing Augmented-Reality-Embedded Instruction to Disperse the Imparities of Individual Differences in Earth Science Learning
Quelle	In: Journal of Science Education and Technology, 24 (2015) 6, S.835-847 (13 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1059-0145
DOI	10.1007/s10956-015-9567-3
Schlagwörter	Science Instruction; Earth Science; Technology Uses in Education; Educational Technology; Simulated Environment; Teaching Methods; Instructional Effectiveness; Junior High Schools; Mixed Methods Research; Cognitive Style; Technological Literacy; Science Achievement; Statistical Inference; Interviews; Student Attitudes; Individual Differences + Suchen Sie Ihr Suchwort? Teaching of science; Science education; Natural sciences Lessons; Naturwissenschaftlicher Unterricht; Earth sciences; Geowissenschaften; Technology enhanced learning; Technology aided learning; Technologieunterstütztes Lernen; Unterrichtsmedien; Künstliche Umwelt; Teaching method; Lehrmethode; Unterrichtsmethode; Unterrichtserfolg; Sekundarstufe I; Cognitive styles; Kognitiver Stil; Technisches Wissen; Inferential statistics; Schließende Statistik; Interviewing; Interviewtechnik; Schülerverhalten; Individueller Unterschied
Abstract	Studies have proven that merging hands-on and online learning can result in an enhanced experience in learning science. In contrast to traditional online learning, multiple in-classroom activities may be involved in an augmented-reality (AR)-embedded e-learning process and thus could reduce the effects of individual differences. Using a three-stage AR-embedded instructional process, we conducted an experiment to investigate the influences of individual differences on learning earth science phenomena of "day, night, and seasons" for junior highs. The mixed-methods sequential explanatory design was employed. In the quantitative phase, factors of learning styles and ICT competences were examined alongside with the overall learning achievement. Independent "t" tests and ANCOVAs were employed to achieve inferential statistics. The results showed that overall learning achievement was significant for the AR-embedded instruction. Nevertheless, neither of the two learner factors exhibited significant effect on learning achievement. In the qualitative phase, we analyzed student interview records, and a wide variation on student's preferred instructional stages were revealed. These findings could provide an alternative rationale for developing ICT-supported instruction, as our three-stage AR-embedded comprehensive e-learning scheme could enhance instruction adaptiveness to disperse the imparities of individual differences between learners. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01