Experimental designs in the social sciences have received increasing attention due to their power to produce causal inferences. Nevertheless, experimental research faces limitations, including limited external validity and unrealistic treatments. We propose combining qualitative fieldwork and experimental design iteratively--moving back-and-forth…

This volume provides alternatives for tackling existing empirical, methodological, and analytical challenges. It does so by providing a broad overview of less established, as well as emerging methods, which are of great relevance for current research on professional learning and development. As such, it offers a comprehensive collection of…

In this Methods Showcase Article, we outline a workflow for running behavioral experiments online, with a focus on experiments that rely on presentation of complex stimuli and measurement of reaction times, which includes many psycholinguistic experiments. The workflow that we describe here relies on three tools: OpenSesame/OSWeb (open source)…

This article draws on a new materialist paradigm to explore bricolaging data from an early childhood research project through an immanent ethical lens. This lens enables the researcher to stretch towards non-hierarchical relationships in between subjects and objects, thinking and doing. A bricoleur explores and builds different…

Past research indicates that individuals respond adaptively to contextual factors in multiattribute choice tasks. Yet it remains unclear how this adaptation is cognitively governed. In this article, empirically testable implementations of two prominent competing theoretical frameworks are developed and compared across two multiattribute choice…

Programs that improve teaching effectiveness represent a core strategy to improve student educational outcomes and close student achievement gaps. This article compiles empirical values of intraclass correlations for designing effective and efficient experimental studies evaluating the effects of these programs. The Early Childhood Longitudinal…

Multimodality in learning analytics and learning science is under the spotlight. The landscape of sensors and wearable trackers that can be used for learning support is evolving rapidly, as well as data collection and analysis methods. Multimodal data can now be collected and processed in real time at an unprecedented scale. With sensors, it is…

Data collection can be a frustrating experience for student researchers due to difficulty in scheduling appointments with participants. To increase the efficiency of research project data collection, we organized a Research Participation Night in which volunteers were incentivized to participate in as many experiments as time allowed. By offering…

Descriptive assessments involve recording naturally occurring instances of behavior and corresponding antecedent and consequent events. Authors have argued for the use of two forms of descriptive assessment, structured and narrative Antecedent-Behavior-Consequence recording, because these methods may require little training. However, the extent to…

Although the literature on institutional diversity suggests that quality assurance practices could affect institutional diversity, there has been little empirical research on this relationship. This article seeks to shed some light on the possible connection between quality assurance practices and institutional diversity by examining the…

Higher education accreditation frameworks typically consider academic staff quality a key element. This article embarks on an empirical study of what academic staff quality means, how it is measured, and how different aspects of staff quality relate to each other. It draws on the relatively nascent Portuguese experience with study programme…

To regulate health messages on food labels, the U.S. Food and Drug Administration (FDA) traditionally relied on mall intercepts to collect consumer data. In recent years, web surveys have presented a viable alternative for presenting visual stimuli with more control and efficiency in data collection. However, there is a paucity of empirical data…

Machine Learning methods for Performance Prediction in Intelligent Tutoring Systems (ITS) have proven their efficacy; specific methods, e.g. Matrix Factorization (MF), however suffer from the lack of available information about new tasks or new students. In this paper we show how this problem could be solved by applying Transfer Learning (TL),…

Business analytics courses, such as marketing research, data mining, forecasting, and advanced financial modeling, have substantial predictive modeling components. The predictive modeling in these courses requires students to estimate and test many linear regressions. As a result, false positive variable selection ("type I errors") is…

In e-learning systems, tutors have a significant impact on learners' life to increase their knowledge level and to make the learning process more effective. They are characterized by different features. Therefore, identifying tutoring styles is a critical step in understanding the preference of tutors on how to organize and help the learners. In…