To improve and facilitate the acquisition of learning outcomes, teachers often use innovative teaching methods such as gamification to keep students' attention and increase their motivation. In recent years, the use of educational data mining (EDM) methods to explore academic topics has increased. With the expansion of EDM, a gap in the literature…

Eye tracking has taken hold in second language acquisition (SLA) and bilingualism as a valuable technique for researching cognitive processes, yet a comprehensive picture of reporting practices is still lacking. Our systematic review addressed this gap. We synthesized 145 empirical eye-tracking studies, coding for 58 reporting features and…

Background: This study examines the engagement of knowledge users in knowledge mobilisation (KMb) research on Canadian K-12 teaching and education policy. Research on and around KMb has grown in the decade since this field was first assessed comprehensively. Thus, it is timely to re-evaluate if current knowledge producer-user relationships in KMb…

As data-informed decision-making continues to evolve across multiple disciplines in higher education institutions, and as the role of research administration continues to expand from proposal submissions, compliance, and managing research and development expenditures to a profession with an active partnership with investigators to support…

The purpose of this study is to determine the trend in studies related to Science instruction and ICT. The study has been studied with extensive data, and the data mining method has been used. Some articles entered the ERIC database within the research scope and published in January 2020, starting from 1965. In this context, 1,783,418 articles…

The current study presents a systematic review of teachers' data literacy, arising from a synthesis of 83 empirical studies published between 1990 to 2021. Our review identified 95 distinct indicators across five dimensions: (a) knowledge about data, (b) skills in using data, (c) dispositions towards data use, (d) data application for various…

Although big data applications in education have different usage areas, they can make important contributions to the evaluation of universities and education systems, decision-making and strategy development, and improvement of the education system. In this study, which is considered to contribute to the academicians who will work on big data in…

This study conducted a systematic literature review of articles on learning analytics published between 2004 and January 2024. A total of 1,064 articles, identified using the keyword "learning analytic*" in the Scopus database, were analyzed. The study integrated systematic literature review and bibliometric analysis approaches to…

Data-based decision-making (DBDM) using curriculum-based measurement (CBM) data has demonstrated effectiveness in improving academic achievement for students with or at risk for learning disability. Despite substantial evidence supporting DBDM, its use is not common practice for many educators, even those who regularly collect CBM data. One…

This meta-analysis study aimed to examine the effect of data literacy education, which affects databased decision processes, on data use knowledge and skills of school administrators and teachers. Therefore, theses on data literacy education for school administrators and teachers and relevant studies in peer-reviewed journals were examined through…

Formal achievement data such as test scores and school performance feedback from standardised assessments can be a powerful tool for data-based decision making and school improvement. However, teachers' and school leaders' usage of these data is not necessarily straightforward or predictable. In order to illuminate how educational professionals…

Educational data mining is an emerging interdisciplinary research area involving both education and informatics. It has become an imperative research area due to many advantages that educational institutions can achieve. Along these lines, various data mining techniques have been used to improve learning outcomes by exploring large-scale data that…

Large amounts of autism spectrum disorder (ASD) data is created through hospitals, therapy centers, and mobile applications; however, much of this rich data does not have pre-existing classes or labels. Large amounts of data--both genetic and behavioral--that are collected as part of scientific studies or a part of treatment can provide a deeper,…

Purpose: This article advocates that privacy literacy research and praxis mobilize people toward changing the technological and social conditions that discipline subjects toward advancing institutional, rather than community, goals. Design/methodology/approach: This article analyzes theory and prior work on datafication, privacy, data literacy,…

Across the international higher education sector, existing studies highlight that student evaluations of courses and teaching are biased and prejudiced towards academics and can cause mental distress. Yet student evaluation data is often used as part of faculty hiring, firing, promotion, award and grant decisions. That a data source known to be…