The purpose of this qualitative descriptive study was to explore how experienced elementary educators in Central Montana described their use of new knowledge from research evidence to inform their teaching practice. Data sources included 15 semi-structured interviews and two focus groups. The Cognitive Affective Model of Conceptual Change was…

The availability of large-scale learning data presents unprecedented opportunities for investigating student learning processes. However, it is challenging for instructors to fully make sense of this data and effectively support their teaching practices. This study introduces LearningViz, an interactive learning analytics dashboard to help…

Previous studies on the effectiveness of virtual laboratories for learning have shown inconsistent results over the past decade. The purpose of this research was to explore the effects of a virtual laboratory and meta-cognitive scaffolding on students' data modeling competences. A quasi-experimental design was used. Three classes of eighth graders…

This paper examines to what extent paper-based data-driven learning (DDL) activities can improve Thai EFL students' vocabulary learning concerning three English synonymous adjectives, which are naughty, disobedient and rebellious, and explores the attitudes of the participants towards learning through the DDL activities. This study was a one-group…

This article reports a workshop from the 2021 IUBMB/ASBMB Teaching Science with Big Data conference held virtually in June 2021 where participants learned to explore and visualize large quantities of protein PBD data using Jupyter notebooks and the Python programming language. This activity instructs participants using Jupyter notebooks, Python…

Many data science applications involve generating questions, acquiring data and preparing it for analysis--be it exploratory, inferential, or modeling focused--and communicating findings. Most data science curricula address each of these steps as separate units in a course or as separate courses. Open-ended term projects, however, allow students…

In this contribution to the Platform Studies in Education symposium, Luci Pangrazio, Amy Stornaiuolo, T. Philip Nichols, Antero Garcia, and Thomas M. Philip explore how digital platforms can be used to build knowledge and understanding of datafication processes among teachers and students. The essay responds to the turn toward data-driven teaching…

Understanding professional development is a key component in ensuring school improvement. This study examines the professional development experiences of 16 school leaders and staff members in the Northeast Region of the United States. This qualitative grounded theory study investigates the type of professional development experiences that result…

Data-driven instruction centers around measuring student learning and determining the actions needed to improve student learning (Bambrick-Santoyo, 2019). This qualitative case study explored teachers' experiences at a single research site surrounding data-driven instruction. Classroom instruction responsive to student performance data is a focus…

Teacher-level factors are theoretically linked to student outcomes in data-based instruction (DBI; Lembke et al., 2018). Professional development and ongoing support can increase teachers' knowledge, skills, and beliefs related to DBI, as well as their instructional fidelity (McMaster et al., 2020). However, less is known about how each of these…

Reading and understanding scientific literature is an essential skill for any scientist to learn. While students' scientific literacy can be improved by reading research articles, an article's technical language and structure can hinder students' understanding of the scientific material. Furthermore, many students struggle with interpreting graphs…

In Singapore, where primary and secondary students routinely top standardized worldwide mathematics examinations, a paradox emerges: when reaching university, many struggle to apply their skills critically in real-world contexts. This commentary examines the challenges and strategies involved in teaching quantitative reasoning (QR) to…

Many aspects of noticing in the classroom are tacitly understood by experienced educators. In this case study, we pair ecological and cognitive psychology with computer-augmented analysis of video data to try to better understand some of the tacit elements of educator noticing and decision-making. The ecological model of noticing views noticing as…

In regression analysis courses, there are many settings in which the response variable under study is continuous, strictly positive, and right skew. This type of response variable does not adhere to the normality assumptions underlying the traditional linear regression model, and accordingly may be analyzed using a generalized linear model…

Learning analytics involve the measurement, collection, analysis, and reporting of data about learners and their contexts, in order to understand and optimize learning and the environments in which it occurs. Since emerging as a distinct field in 2011, learning analytics has grown rapidly, and early adopters around the world are developing and…