Tutoring in the United States

• In Event: 75.061 - Roundtable Session 34
  In Roundtable Session: 75.061-11 - Education Markets and Social Inequalities: A Global Perspective

Abstract

Objectives or Purposes. In the United States, under the No Child Left Behind Act of 2002 (NCLB), vendors contract with districts and receive public, Title I money to provide out of school time (OST) tutoring to low income students. This paper reports findings from a mixed method longitudinal study of OST tutoring. A “digital” tutoring vendor is one that uses a digital platform (software or live tutor via a technological platform, such as a compute, netbook, or handheld device) as an intentional, integral, part of its instructional delivery strategy. Digital tutoring has become an important component of the tutoring industry, driven in large part by technology that offer the promise of scale and low cost.

Method and Data Sources. Our longitudinal, mixed-method design integrates rigorous, quasi-experimental analysis of OST tutoring program impacts on student achievement with an in-depth, comprehensive examination of the intervention—provider instructional practice in different program models and settings, the nature and quality of tutoring provided and district-level program administration—in and across six large, urban school districts. The qualitative data are drawn from observations of tutoring sessions using a standardized instrument developed to capture OST tutoring in practice, including those elements of instruction specific to the digital context. Qualitative data sources also include personal interviews with district staff, provider administrators and tutoring staff, focus groups with parents of eligible students, and curriculum analysis. Quantitative analysis relies on three econometric strategies in estimating digital and non-digital OST tutoring effects (to address research question #2) include: 1) value-added modeling (following Zimmer et al., 2007 and Heinrich & Nisar, forthcoming), 2) fixed effects models (student and school fixed effects), and 3) generalized propensity score matching methods. Our two comparison groups consist of students eligible for OST tutoring in each district who: (1) do not receive tutoring, or (2) receive non-digital tutoring services.

Results and Significance. Digital providers are gaining market share at a faster rate than providers of face-to-face private tutoring. Further, online providers tend to charge significantly more per hour ($20 more per hour) and provide students with fewer hours of service than face-to-face tutoring providers (18 hours versus 35 hours). These higher rates could be justified if students and families were getting higher quality services for their money. However, estimates of the comparative effectiveness of digital vs. non-digital providers in our study do not appear to justify their differential rates. By our estimates, digital tutoring is, on average, negatively correlated with student performance in mathematics and reading. Coupled with on our in depth qualitative research into the nature of the instructional setting in digital OST, the factors impacting the design of the instructional setting, and its impact on student learning, we identify several conditions that are likely to determine digital tutoring effectiveness: access (including hardware and software), the role of the tutor, and the nature of curriculum and assessment. We are capturing how decisions made about hardware, software, the role of the tutor, curriculum and assessment influence instructional quality and the impact on student learning.

Authors

• Patricia Burch, University of Southern California

• Jahni Madrica Ann Smith, University of Southern California