Toward a Typology of Technology-Using Teachers in the “New Digital Divide”: A Latent Class Analysis (LCA) of the NCES Fast Response Survey System Teachers’ Use of Educational Technology in U.S. Public Schools, 2009 (FRSS 95)
by Kenneth E. Graves & Alex J. Bowers - 2018
Background: Recently, policy makers and school leaders have heavily invested in the promise that educational technology could catalyze systemic school change. Yet some critics note that the conversation surrounding technology in schools is a red herring that has not produced clear, definitive, and equitable results across different school settings. In order to address this concern, prior research has mainly focused on understanding how and why teachers use technology. Still, we argue that an understudied third perspective—examining what types of technology-using teachers exist—could provide innovative and impactful insights to shape research, policy, and practice in instructional technology.
Purpose of the Study: We investigate the extent to which there is a typology of teachers who use technology, as well as to what extent school- and teacher-level variables predict membership in the different subgroups in the typology, by analyzing a nationally generalizable sample (2,764 teachers) from the Teachers' Use of Educational Technology in U.S. Public Schools, 2009 Fast Response Survey System dataset, collected by the National Center for Education Statistics.
Research Design: We used a three-step, one-level latent class analysis (LCA) with nationally generalizable data that identify significantly different types of technology-using teachers, as well as what covariates predict membership in the identified subgroups.
Findings: We find that there are four statistically significant subgroups of technology-using teachers: Dexterous (24.4%), Evaders (22.2%), Assessors (28.4%), and Presenters (24.8%). We also find that several covariates, such as student socioeconomic status, school type, enrollment, years of teacher experience, and total number of school computers, predicted teachers' membership in these four subgroups of technology-using teachers.
Conclusions: Our findings reiterate the notion that technology-using teachers are not a monolithic group or are randomly distributed across school settings, finding that low-income schools are more likely to have teachers who use technology in less meaningful ways. As a quantitative phenomenology, this study provides one of the first empirically based, nationally generalizable depictions of technology use in schools, which could inform school leaders and policy makers as they evaluate new digital tools, design professional learning for teachers, and tackle inequalities in technology access, teacher knowledge, and technology-mediated learning experiences and outcomes for students.
Keywords: Educational Technology, Teachers, Social Justice, Digital Divide, Technology Leadership, Latent Class Analysis, Mixture Modeling, Survey Research, NCES
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