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Can educational technology effectively differentiate instruction for reader profiles?
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DOI：10.1007/s11145-019-09949-4.png)
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Abstract
En 中文
Teachers are responsible for identifying and instructing an increasingly diverse population of student readers. Advances in educational technology may facilitate differentiated instruction. Using data from a large, population-based sample of third-grade students, we investigated what works for whom in technology-based literacy instruction. We classified 594 students into four reader subgroups or profiles based on two scores from a readily-available, commonly-used progress monitoring tool (aimsweb (c)). Using this simple and accessible method, we identified profiles of readers that resemble the poor decoder, poor comprehender, mixed deficit, and typical reader subgroups found in past studies that used extensive test batteries or advanced statistics. We then employed nonparametric analyses to examine both proximal and distal outcomes across one academic year. First, we compared the relative progress of reader profiles on a technology-based reading program (Lexia (R) Core5 (R) Reading). Second, we determined whether each reader profile made gains on aimsweb at the end of the year. We found that Core5 effectively differentiated online instruction and contributed to improved aimsweb performance for most reader profiles. The findings from this study help inform educational best practices for efficient identification of and effective intervention for all students.
Keywords:
Simple view of reading
Reading profiles
Educational technology
Poor comprehenders
Poor decoders
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