Jennie L. Farmer

Estimating individual treatment effects from multiple-baseline data: A Monte Carlo study of multilevel-modeling approaches

While conducting intervention research, researchers and practitioners are often interested in how the intervention functions not only at the group level, but also at the individual level. One way to examine individual treatment effects is through multiple-baseline studies analyzed with multilevel modeling. This analysis allows for the construction of confidence intervals, which are strongly recommended in the reporting guidelines of the American Psychological Association. The purpose of this study was to examine the accuracy of confidence intervals of individual treatment effects obtained from multilevel modeling of multiple-baseline data. Monte Carlo methods were used to examine performance across conditions varying in the number of participants, the number of observations per participant, and the dependency of errors. The accuracy of the confidence intervals depended on the method used, with the greatest accuracy being obtained when multilevel modeling was coupled with the Kenward—Roger method of estimating degrees of freedom.

Technology, Mathematics PS/RTI, and Students with LD: What Do We Know, What Have We Tried, and What Can We Do to Improve Outcomes Now and in the Future?

Effective integration of technology within mathematics problem solving/response to instruction (PS/RTI) for students with/at risk for identification of learning disabilities (LD) is the focus of this article. The discussion is situated within the current context of mathematics PS/RTI, the literature base relative to technology integration in mathematics for students with LD, and emerging 21st-century technologies. Limitations of the research base are identified, and suggestions for the future are provided. Next, a systematic framework for integration of technology in mathematics PS/RTI is introduced that incorporates consideration of (a) effective mathematics instructional practice within mathematics PS/RTI, and (b) the nature of the mathematics content and student learning barriers and strengths. Ways in which technology can enhance effective mathematics practices for students with LD are suggested, and implications for research, development, and practice are discussed.

What Does "Highly Qualified" Mean for Urban Special Educators?.

In this article, the authors discuss the context of urban special education and the complexities of meeting the demands of standards-based reform in urban settings. The study presented highlights the voices of urban special educators in two large urban school districts as they navigate meeting the demands of teaching students with disabilities, and share their perceptions of their roles and responsibilities as a result of No Child Left Behind Act. Findings reveal several implications for educational policy and areas of future research in teacher quality and workplace conditions for urban special educators.

Preservice Teacher Education and Response to Intervention Within Multi-Tiered Systems of Support: What Can We Learn from Research and Practice?

This chapter provides teacher educators and policy makers with suggestions for integrating RTI within preservice teacher preparation programs. A rationale for the need to do this and the corresponding empirical research base are described. Based on a review of relevant literature in the areas of teacher education, professional development, and RTI, five overall suggestions that teacher educators and policy makers can use to frame the improvement of preservice preparation in RTI are offered. These suggestions include systematically integrating RTI content across preservice programs, emphasizing data literacy, emphasizing essential content and pedagogical content knowledge, emphasizing knowledge of instructional practices that promote positive outcomes for students across instructional tiers, and emphasizing practices for engaging families in the RTI process. Each suggestion is discussed and key aspects to implementation are described with support from the literature. The chapter concludes with final thoughts and suggestions for future research.