The goal of the proposed working group is to create a space for those interested in researching issues around the teaching and learning of statistics to meet, discuss, synthesize past research, and begin to strategize ways of leveraging multiple perspectives and expertise to identify and address current challenges in statistics education. The…

Data-Driven Learning (DDL) is a method for learning languages that involves analyzing language usage trends and finding patterns in language data, utilizing technology and statistics. One of the key benefits of DDL is that it allows students to focus on the most relevant and useful language data for their needs. Data-driven learning is an…

The inaugural Working Lives of Teachers and Leaders (WLTL) survey was carried out in Spring 2022 with teachers and leaders in state schools in England. Conducted by IFF Research and the Institute of Education (IoE) on behalf of the Department for Education (DfE), the survey is longitudinal by design and will run annually for at least five years,…

Learner modeling, a challenging and complex endeavor, is an important and oft-studied research theme in computer-supported education. From this perspective, Educational Data Mining (EDM) research has focused on modeling and comprehending various dimensions of learning in computer-based learning environments (CBLE). Researchers and designers are…

This chapter describes the background and process for collecting postgraduation outcomes data at a 4-year not-for-profit private college. The strategies, analyses, and reporting of this data-collection effort are highlighted with the use of a case study.

Researchers point out the importance of teachers' knowledge of student thinking and the role of examining student work in various contexts to develop a knowledge base regarding students' ways of thinking. This study investigated prospective secondary mathematics teachers' interpretations of students' thinking as manifested in students' work that…

This paper provides a tutorial on epistemic network analysis (ENA), a novel method for identifying and quantifying connections among elements in coded data and representing them in dynamic network models. Such models illustrate the structure of connections and measure the strength of association among elements in a network, and they quantify…

Introduction: This paper presents the findings from a project that investigated the lived experiences of library and information professionals in relation to evidence-based practice within an Australian public library. Method: The project employed ethnography, which allows holistic description of people's experiences within a particular community…

In most qualitative research studies involving the creation of interview transcriptions, researchers seldom demonstrate much reflexivity about the transcription process, rarely making mention of transcription processes as part of their reporting of data collection and analysis procedures beyond a simple statement that audio- or videotaped data…

The amount of computerized information that organizations collect and process is growing so large that the term Big Data is commonly being used to describe the situation. Accordingly, Big Data is defined by a combination of the Volume, Variety, Velocity, and Veracity of the data being processed. Big Data tools are already having an impact in…

The emergence of social networks and social media has resulted in exponential increase in the amount of data that link diverse types of richly structured digital objects e.g., individuals, articles, images, videos, music, etc. Such data are naturally represented as heterogeneous networks with multiple types of objects e.g., actors, video,…

Describing the variation in test scores between and within school districts is critical for: (1) for policy-related and descriptive work that investigates the sorting of students among districts and the differential effectiveness of those districts; and (2) for methodological work planning future experiments or interventions. Intraclass…

Learning analytics provide a set of powerful tools to inform and support learners. They enable institutions and individuals to better understand and predict personal learning needs and performance. Universities already collect vast amounts of data about their student populations, but often this is underutilised. The current "state of the…

In this paper, we present a dataset consisting of data generated from 22 previously and currently running randomized controlled experiments inside the ASSISTments online learning platform. This dataset provides data mining opportunities for researchers to analyze ASSISTments data in a convenient format across multiple experiments at the same time.…

This study aims to investigate the effect of methods to deal with missing data on item difficulty estimations under different test length conditions and sampling sizes. In this line, a data set including 10, 20 and 40 items with 100 and 5000 sampling size was prepared. Deletion process was applied at the rates of 5%, 10% and 20% under conditions…