Physics education researchers are interested in using the tools of machine learning and natural language processing to make quantitative claims from natural language and text data, such as open-ended responses to survey questions. The aspiration is that this form of machine coding may be more efficient and consistent than human coding, allowing…

In consultation, school psychologists may offer educators direct training to support the implementation of classroom interventions aimed to improve student outcomes. The purpose of this study was to conduct a systematic literature review of single-case design research studies during which educators received direct training to implement a classroom…

Background: Despite studies of how parent-child interactions relate to early child language development, few have examined the continued contribution of parenting to more complex language skills through the preschool years. The current study explored how positive and negative parenting behaviours relate to growth in complex syntax learning from…

This study seeks to explain macrolevel drivers of adolescent fertility rate using a panel data set derived from 17 Latin American countries over a period of 16 years (1997-2012). While many studies of adolescent fertility have focused on individual-level explanations, this study explores whether adolescent fertility rate is correlated to…

This study investigates the role of perspective-taking skills in how children explain spatially complex astronomical phenomena. Explaining many astronomical phenomena, especially those studied in elementary and middle school, requires shifting between an Earth-based description of the phenomena and a space-based reference frame. We studied 7- to…

This study tested two cognitive models, learning styles and dual coding, which make contradictory predictions about how learners process and retain visual and auditory information. Learning styles-based instructional practices are common in educational environments despite a questionable research base, while the use of dual coding is less…

Predicting item difficulty is highly important in education for both teachers and item writers. Despite identifying a large number of explanatory variables, predicting item difficulty remains a challenge in educational assessment with empirical attempts rarely exceeding 25% of variance explained. This paper analyses 216 science items of key stage…

Online classroom discussion is ubiquitous in higher education today, with both online and hybrid courses. As a result, tools need to be created that enable an in-depth assessment of this medium, thereby facilitating the establishment and support of best practices in education. Such an assessment requires tools for consistent, efficient analysis of…

Experts are more proficient in manipulating and translating between multiple representations (MRs) of a given concept than novices. Studies have shown that instruction using MR can increase student understanding of MR, and one model for MR instruction in chemistry is the chemistry triplet proposed by Johnstone. Concreteness fading theory suggests…

Previous work has shown that students have persistent difficulties in understanding how central dogma processes can be affected by a stop codon mutation. To explore these difficulties, we modified two multiple-choice questions from the Genetics Concept Assessment into three open-ended questions that asked students to write about how a stop codon…

Social network research on teachers and schools has risen exponentially in recent years as an innovative method to reveal the role of social networks in education. However, scholars are still exploring ways to incorporate traditional quantitative methods of Social Network Analysis (SNA) with qualitative approaches to social network research. This…

Purpose: The purpose of this paper is to do methodological review of the literature on educational leaders and emotions that includes 49 empirical studies published in peer-reviewed journals between 1992 and 2012. Design/methodology/approach: The work systematically analyzes descriptive information, methods, and designs in these studies, and their…

Piecewise growth models (PGMs) were used to estimate and model changes in the preliteracy skill development of kindergartners in a moderately sized school district in the Pacific Northwest. PGMs were applied to interrupted time-series (ITS) data that arose within the context of a response-to-intervention (RtI) instructional framework. During the…

Computational models that automatically detect learners' affective states are powerful tools for investigating the interplay of affect and learning. Over the past decade, affect detectors--which recognize learners' affective states at run-time using behavior logs and sensor data--have advanced substantially across a range of K-12 and postsecondary…

National calls for improving science education (e.g., "Vision and Change") emphasize the need to learn disciplinary core ideas through scientific practices. To address this need, we engaged small groups of students in developing diagrammatic models within two (one large-enrollment and one medium-enrollment) undergraduate introductory…