Students across disciplines struggle with sensemaking when they are faced with the need to understand and analyze massive amounts of information. This is particularly salient in the disciplines of both history and data science. Our approach to helping students build expertise with complex information leverages activity theory to think about the…

The NAEP EDM Competition required participants to predict efficient test-taking behavior based on log data. This paper describes our top-down approach for engineering features by means of psychometric modeling, aiming at machine learning for the predictive classification task. For feature engineering, we employed, among others, the Log-Normal…

This study investigates how youth from two cities in the United States engage in critical data practices as they learn about and take action in their lives and communities in relation to COVID-19 and its intersections with justice-related concerns. Guided by theories of critical data literacies and data justice, a historicized and future-oriented…

The "Forum Guide to Metadata" presents and examines the ways in which metadata can be used by education agencies to improve data quality and promote a better understanding of education data. Supported by metadata-related case studies from state and local education agencies, the guide highlights the uses of metadata from a technical point…

This report focuses on data governance at post-secondary institutions and related organizations. Data governance is defined as the formal execution and enforcement of authority over the management of data and data-related assets (Seiner, 2014). An overview of data governance at higher education institutions provides detail on elements of data…

In Technology Enhanced Learning field, learning analytics cover multiple research challenges, among which tracking data analysis and data indicator design and visualization. Part of our research effort is dedicated to changing their design process, in order to capitalize them. This would allow us to meet a need in cost savings of design workflow…

Educational data mining focuses on exploring increasingly large-scale data from educational settings, such as Learning Management Systems (LMS), and developing computational methods to understand students' behaviors and learning settings better. There has been a multitude of research dedicated to studying the student learning process, leading to…

In the higher education context, an increasing concern on the technical or instrumental approach permeates attention to academics' data literacies and faculty development. The need for data literacy to deal specifically with the rise of learning analytics in higher education has been raised by some authors, though in spite of some focus on the…

Many articles have been published in gifted education in recent years. This study aims to provide a comprehensive review of the evolution of academic studies in gifted education. In this context, the structural topic modeling (STM) method was used to analyze the topics and trends in the field. STM is a machine learning technique that utilizes…

Many of the decisions made related to student progress and intervention selection rely on data. In their roles, paraeducators often implement academic interventions; therefore, they must be prepared to monitor students' progress accurately and reliably. This pilot randomized control trial tested the effects of a remote training package on…

Background: Data missingness can bias interpretation and outcomes resulting from data use. We describe data missingness in the longest-standing US-based youth fitness surveillance system (2006/07-2019/20). Methods: This observational study uses the New York City FITNESSGRAM (NYCFG) database from 1,983,629 unique 4th-12th grade students (9,147,873…

Background: In recent years, there has been generalized concern in all countries about increasing the younger population's level of financial literacy. However, there is still little evidence on the key factors explaining financial literacy, as the existing literature is inconclusive about this issue. This paper focuses on exploring whether…

This paper proposes a computer-aided teaching model using knowledge graph construction and learning path recommendation. It first creates a multimodal knowledge graph to illustrate complex relationships among knowledge. Learning elements and sequences are then used to form time sequences stored as directed graphs, supporting flexible path…

State and local education agencies continue to make an effort to systematically assess school climate through student surveys. These assessments typically collect data from individual students about their perceptions of different components of the school and their relationship to individuals in the school and aggregate those responses to the…

"Self-regulated learning" (SRL) significantly impacts the process and outcome of "programming problem-solving." Studies on SRL behavioural patterns of programming students based on trace data are limited in number and lack of coverage. In this study, hence, the Hidden Markov Model (HMM) was employed to probabilistically mine…