Managing and analysing large qualitative datasets pose a particular challenge for researchers seeking a consistent and rigorous approach to qualitative data analysis. This paper describes and demonstrates the development and adoption of a matrix tool to guide the qualitative data analysis of a large sample (N = 122) of interview data. The paper…

Secondary data analyses occur when new analyses are proposed for existing data. Although they are prevalent in special education research, there is little guidance on how to prepare secondary data analyses studies. Preregistration of secondary data analyses studies provides a nice opportunity and structure for fellow researchers to share…

Participatory modeling (PM) is an engaged research methodology for creating analog or computer-based models of complex systems, such as socio-environmental systems. Used across a range of fields, PM centers stakeholder knowledge and participation to create more internally valid models that can inform policy and increase engagement and trust…

There has been extensive research into the underrepresentation of minoritized students in STEM disciplines since the 1990s with limited success in improving the representation of Black women in math-intensive STEM fields. This dissertation aims to address how the guiding tenets of critical quantitative (QuantCrit) methods work when used with…

More aggregate data on school performance is available than ever before, opening up new possibilities for applied researchers interested in assessing the effectiveness of school-level interventions quickly and at a relatively low cost by implementing comparative interrupted times series (CITS) designs. We examine the extent to which effect…

The arc of quantitative educational research should not be etched in stone but should adapt and change over time. In this article, I argue that it is time for a reshaping by offering my personal view of the past, present and future of our field. Educational research--and research in the social and life sciences--is at a crossroads. There are many…

Respondent attrition is a common problem in national longitudinal panel surveys. To make full use of the data, weights are provided to account for attrition. Weight adjustments are based on sampling design information and data from the base year; information from subsequent waves is typically not utilized. Alternative methods to address bias from…

This longitudinal pedagogical research investigates students' perceptions and learning outcomes by integrating web and social analytics--based learning activities (i.e., Google Analytics courses and certification test) into Public Relations Research course design. Results from the pretest before introducing the analytics learning assignment…

This paper argues that learning analytics (LA) can make contributions to learning research, in addition to aiming for improvements in learning and teaching practices in a solely applied sense. Indeed, there is potential for transforming learning research if certain approaches developed in LA were used more extensively to study learning. The…

We examine the American landscape of higher education quantitative research concerning how gender and sex demographic information is collected. We use a directed content analysis to examine the prevalence and operationalization of gender and sex among widely used higher education survey instruments. Our findings illuminate a seemingly haphazard…

Intended to guide scholars who are new to qualitative research, this methods brief focuses mostly on what reviewers look for in manuscripts submitted for publication. The author acknowledges that reviewers' preferences likely reflect their theoretical perspectives, research-oriented coursework, mentors, and research and writing experiences. The…

The Academic Pathway Study (APS) research program within National Science Foundation (NSF) Center for Advancement of Engineering Education (CAEE) ran from 2003-2010. It amassed a collection of longitudinal as well as cross-sectional data sets, of varying research method types and formats, from four different primary cohorts that included over…

Studies based on longitudinal data focus on the change and development of the situation being investigated and allow for examining cases regarding education, individual development, cultural change, and socioeconomic improvement in time. However, as these studies require taking repeated measures in different time periods, they may include various…

Latent state-trait (LST) analysis is frequently applied in psychological research to determine the degree to which observed scores reflect stable person-specific effects, effects of situations and/or person-situation interactions, and random measurement error. Most LST applications use multiple repeatedly measured observed variables as indicators…

The growth in the availability of longitudinal data--data collected over time on the same individuals--as part of program evaluations has opened up exciting possibilities for evaluators to ask more nuanced questions about how individuals' outcomes change over time. However, in order to leverage longitudinal data to glean these important insights,…