Automated, adaptive guidance for K-12 education

Publication date: Available online 28 April 2015 Source:Educational Research Review Author(s): Libby Gerard , Camillia Matuk , Kevin McElhaney , Marcia C. Linn 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 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 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.
Source: Educational Research Review - Category: Child Development Source Type: research