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Automated, adaptive guidance for K-12 education
ARTICLE

, Graduate School of Education, United States ; , School of Culture, Education, and Human Development, Media and Games Network, United States ; , Center for Technology in Learning, United States ; , Graduate School of Education, United States

Educational Research Review Volume 15, Number 1, ISSN 1747-938X Publisher: Elsevier Ltd

Abstract

This paper distinguishes features of automated adaptive guidance used in K-12 instructional settings and recommends directions for design. We use meta-analysis to synthesize 24 independent comparisons between automated adaptive guidance and guidance provided during typical teacher-led instruction, and 29 comparisons that isolate the effects of specific adaptive guidance design features in computer-based instruction. We find automated adaptive guidance to be significantly more effective than guidance provided in typical instruction, particularly for students with low prior knowledge. Automated adaptive guidance is most effective when students are generating and integrating ideas (e.g. writing essays, making concept diagrams) as opposed to selecting from the given options. Guidance that promoted self-monitoring was more likely to improve learning outcomes than guidance that addressed only content knowledge. Our findings have implications for researchers who investigate K-12 teaching and learning, designers who create and refine instructional materials using automated guidance, and practitioners who deliver or customize instruction featuring automated guidance.

Citation

Gerard, L., Matuk, C., McElhaney, K. & Linn, M.C. (2015). Automated, adaptive guidance for K-12 education. Educational Research Review, 15(1), 41-58. Elsevier Ltd. Retrieved August 18, 2019 from .

This record was imported from Educational Research Review on January 29, 2019. Educational Research Review is a publication of Elsevier.

Full text is availabe on Science Direct: http://dx.doi.org/10.1016/j.edurev.2015.04.001

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