Data are everywhere. Data collected from samples are often reported in the form of polls, medical studies, and advertisement information and an understanding of sampling distributions and statistical inference is important for evaluating data-based claims (Bargagliotti et al., 2020). Despite the importance of understanding statistical inference…

This paper describes a short module for introducing data science to senior school students or other data-science beginners. The design focuses on "data moves." Students use CODAP to do their work.

Objectives: Java is a popular programming language for use in computing education, but it is difficult to get a wide picture of the issues that it presents for novices; most studies look only at the types or frequency of errors. In this observational study, we aim to learn how novices use different features of the Java language. Participants:…

Generative AI (GenAI) has the potential to revolutionize the analysis of educational data, significantly impacting learning analytics (LA). This study explores the capability of non-experts, including administrators, instructors, and students, to effectively use GenAI for descriptive LA tasks without requiring specialized knowledge in data…

Interest in applied educational research methodology is growing as educators and researchers strive to seek empirical evidence about what is effective teaching within distinctive contexts. However, for beginner researchers who are interested in conducting case studies within educational settings and are looking for an appropriate starting point,…

Educational data mining involves the application of data mining techniques to student activity. However, in the context of computer programming, many data mining techniques can not be applied because they require vector-shaped input, whereas computer programs have the form of syntax trees. In this paper, we present ast2vec, a neural network that…

Prior studies indicate that faculty often struggle with Scholarship of Teaching and Learning (SoTL) research due to limited knowledge of relevant research methodologies and data analysis techniques (Boshier, 2009; Kim et al., 2021; McKinney, 2006). Faculty developers at a teaching-intensive institution created an innovative, scaffolded model to…

This paper reports on the challenges faced by two researchers during data collection and translation of data and analysis in two public sector universities in Pakistan. Data collection from each institute involved different procedures and a different set of issues, including negotiating access with gatekeepers and participants, dealing with…

This case study discusses how theory and deductive analysis can be used to better understand work-based learning (WBL). Based in a U.K. teacher education setting, it discusses a project which examined how novice teachers in English Further Education develop their professional knowledge and how their experiences might help understand WBL more…

A significant number of U.S. students are unable to read proficiently by fourth grade, and over two billion dollars are spent each year on students who repeat a grade due to reading problems. The purpose of this basic qualitative study was to examine novice elementary teachers' perspectives of their self-efficacy in using adaptive instructional…

In an increasingly data-driven world, large volumes of fine-grained data are infiltrating all aspects of our lives. The world of education is no exception to this phenomenon: in classrooms, we are witnessing an increasing amount of information being collected on learners and teachers. Because educational practitioners have so much contextual and…

Data analysis is a significant methodological component when conducting quantitative education studies. Guidelines for conducting data analyses in quantitative education studies are common but often underemphasize four important methodological components impacting the validity of inferences: quality of constructed measures, proper handling of…

Data literacy is a growing area of focus across multiple disciplines in higher education. The dominant forms of introduction focus on computational toolchains and statistical ways of knowing. As data driven decision-making becomes more central to democratic processes, a larger group of learners must be engaged in order to ensure they have a seat…

Informed by critical data literacy efforts to promote social justice, this paper uses qualitative methods and data collected during two years of workplace ethnography to characterize the notion of critical novice data work. Specifically, we analyze everyday language used by novice data workers at DataWorks, an organization that trains and employs…

Curriculum-Based Measurement of Reading (CBM-R) is frequently used to monitor instructional effects and evaluate response to instruction. Educators often view the data graphically on a time-series graph that might include a variety of statistical and visual aids, which are intended to facilitate the interpretation. This study evaluated the effects…