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…

Monitoring applications (MAs) use digital and online tools to collect and track data on student behavior, and they have become increasingly popular among schools. Empirical research on these complex surveillance platforms is scant, and little is known about the efficacy or impact that they have on students. This study used a multi-method…

Program evaluation is an essential practice for providers of behavior analytic services, as it helps providers understand the extent to which they are achieving their intended mission to the community they serve. A proposed method for conducting such evaluations, is through the use of a consecutive case series design, for which cases are…

Despite the rising popularity of big data, there is speculation that evaluators have been slow adopters of these new statistical approaches. Several possible reasons have been offered for why this is the case: ethical concerns, institutional capacity, and evaluator capacity and values. In this method note, we address one of these barriers and aim…

Conducting high-quality overviews of reviews (OoR) is time-consuming. Because the quality of systematic reviews (SRs) varies, it is necessary to critically appraise SRs when conducting an OoR. A well-established appraisal tool is A Measurement Tool to Assess Systematic Reviews (AMSTAR) 2, which takes about 15-32 min per application. To save time,…

With the growing attention on large-scale educational testing and assessment, the ability to process substantial volumes of response data becomes crucial. Current estimation methods within item response theory (IRT), despite their high precision, often pose considerable computational burdens with large-scale data, leading to reduced computational…

Education plays a major role in the development of the consciousness of the whole society. Education has been improved by analyzing educational data related to student academic performance. By using data mining techniques and algorithms on data from the educational environment, students' performances can be predicted. In this study, a novel Hybrid…

Learning performance data, such as correct or incorrect answers and problem-solving attempts in intelligent tutoring systems (ITSs), facilitate the assessment of knowledge mastery and the delivery of effective instructions. However, these data tend to be highly sparse (80%90% missing observations) in most real-world applications. This data…

In 2015, a multidisciplinary group of academic researchers and extension personnel was awarded a US Department of Agriculture Coordinated Agricultural Project grant. The team's goal was to understand human decision-making in the context of potential livestock disease outbreaks, investigating the impediments to increased adoption of biosecurity…

A technology-based problem-solving test can automatically capture all the actions of students when they complete tasks and save them as process data. Response sequences are the external manifestations of the latent intellectual activities of the students, and it contains rich information about students' abilities and different problem-solving…

Trial-based functional analysis (TBFA) is an accurate and ecologically valid assessment of challenging behavior. Further, there is evidence to suggest that individuals with minimal exposure to behavior analytic assessment methodology (e.g., parents, teachers) can quickly be trained to conduct TBFAs in naturalistic settings (e.g., schools, homes).…

Systematic reviews are a time-consuming yet effective approach to understanding research trends. While researchers have investigated how to speed up the process of screening studies for potential inclusion, few have focused on to what extent we can use algorithms to extract data instead of human coders. In this study, we explore to what extent…

By using modern data analysis techniques, this study aims to construct an innovative university English teaching effectiveness evaluation model based on particle swarm algorithm and support vector machine. The model is designed to improve assessment accuracy and personalization. The research process includes the methodology of data collection,…

The traditional system focuses excessively on physical skills and physical fitness assessment, with problems such as single indicator, static approach, subject limitation and inefficient data utilization, making it difficult to assess students in a comprehensive and fair manner. The rise of big data technology has brought about a turnaround, from…

Carefully designed evaluations of informal science events are key to gaining insights into their efficacy and impact on audiences. However, traditional approaches to evaluation, such as interviews and questionnaires, can be disruptive to the audience experience of science events. There is therefore a need to develop and implement new evaluation…