This paper discusses some of the recurrent issues which the authors have noticed in educational research. These might be concerned with the nature of social science research, such as its representation of the reality of student learning, the role for replication studies, and the tolerance for disagreements. There are also issues related to the…

Big qualitative data (Big Qual), or research involving large qualitative data sets, has introduced many newly evolving conventions that have begun to change the fundamental nature of some qualitative research. In this methodological essay, we first distinguish big data from big qual. We define big qual as data sets containing either primary or…

For school districts, the increasing importance of using data for continuous improvement has become part of the educational landscape under accountability. In many ways, educators have become inundated with data but not always in ways that provide them with a full picture to adequately weigh decisions for their specific context. One way to use…

This convergent parallel design mixed methods case study of four community colleges explores the relationship between organizational capacity and implementation of data-driven decision making (DDDM). The article also illustrates purposive sampling using replication logic for cross-case analysis and the strengths and weaknesses of quantitizing…

In recent years, more and more researchers in science education have been turning to the practice of combining qualitative and quantitative methods in the same study. This approach of using mixed methods creates possibilities to study the various issues that science educators encounter in more depth. In this content analysis, I evaluated 18…

This paper reports on a case study of a project-focused introduction to big data science course. The pedagogy of the course leveraged boundary theory, where students were positioned to be at the boundary between a client's desire to understand their data and the academic class. The results of the case study demonstrate that using live clients…

Data integration is a crucial element in mixed methods analysis and conceptualization. It has three principal purposes: illustration, convergent validation (triangulation), and the development of analytic density or "richness." This article discusses such applications in relation to new technologies for social research, looking at three…

This mixed methods study explores the pilot implementation of a Response to Intervention framework in the first grade classrooms in three urban schools. Two schools in a fully implemented condition (FI) with a facilitator and a partially implemented condition (PI) without a facilitator were investigated using student achievement data, field notes,…

Teachers and students increasingly enjoy unprecedented access to abundant web resources and digital libraries to enhance and enrich their classroom experiences. However, due to the distributed nature of such systems, conventional educational research methods, such as surveys and observations, provide only limited snapshots. In addition,…

Since the passage of the No Child Left Behind Act (2001), districts, schools, and educators are pressured to collect, analyze and report data annually regarding student performance. If high-stakes assessments are to be useful tools for educators in their classrooms, the data need to be applicable in conveying meaningful instructional information…