Using concordancers in English classes is demanding, time-consuming, and challenging to both teachers and learners. On the other hand, research points to the effectiveness of data-driven learning (DDL) in improving second/foreign language learning. The present study proposed a new task type, that is, DDL focus on form (FonF) tasks, as a…

Data-driven decision making (DDDM) is an important teaching practice that can positively influence student achievement by using assessment data to make instructional decisions. The problem is that teachers do not always use this practice. Teachers' perspectives of DDDM can influence their data use practices. This basic qualitative study was…

In this position paper, the authors lay out the imperative for equitable artificial intelligence (AI), highlighting the essential role of access-oriented institutions and calling on technology companies (both large and small), foundations, and local, state, and federal regulators to consult with the newly convened Complete College America Council…

Background: Maintaining cohesion is critical for teams to achieve shared goals and performance outcomes within a work-integrated learning (WIL) environment. Cohesion is an emergent state that develops over time, representing the synchrony of different behavioural interactions. Cohesive teams will exhibit such phenomena by their temporal…

Quality, timely, purpose-driven education in emergencies (EiE) data can enable more effective response to education needs in crisis settings and strengthen system resilience. However, a growing body of evidence points to a number of problems related to the production, sharing, and use of EiE data within education information management systems…

In recent years, a multitude of datasets of human-human conversations has been released for the main purpose of training conversational agents based on data-hungry artificial neural networks. In this paper, we argue that datasets of this sort represent a useful and underexplored source to validate, complement, and enhance cognitive studies on…

In inclusive education, students with different needs learn in the same context. With the advancement of artificial intelligence (AI) technologies, it is expected that they will contribute further to an inclusive learning environment that meets the individual needs of diverse learners. However, in Japan, we did not find any studies exploring…

We present a historical case study of "data-driven" general education policy reform at the City University of New York, where within-system transfer issues prompted the need for curricular reform that was debated and eventually implemented from 2011 to 2017. Through an empirical examination of artifacts such as meeting minutes, internal…

The benefits of government administrative data are well-established, but research has not examined processes by which these data can be identified, organised and governed in line with ethical considerations. This is an important undertaking given the potential benefits of robust administrative data, especially at a time when the collection of…

Despite the promotion of data-driven or data-informed instructional practices in teacher education and professional development, past research indicates that teachers use a limited number of sources for student data to make short-term adjustments to their teaching in order to address deficiencies in student learning. Science teachers, with a more…

At the end of 2021, the spread of the COVID-19 virus Delta variant and the start of the new school year combined to present many educators and administrators with the hardest year yet in the pandemic, in terms of both delivering instruction and assessing student learning. Students entered the school year with increased anxiety, and assessment was…

Understanding data structures is fundamental for mastering algorithms. In order to solve problems and tasks, students must be able to choose the most appropriate data structure in which the data is stored and that helps in the process of the solution. Of course, there is no single correct solution, but in many cases, it is an important step to…

Background: To improve the use of evidence in policy and practice, many organisations and individuals seek to promote research-policy engagement activities, but little is known about what works. Aims and objectives: We sought (a) to identify existing research-policy engagement activities, and (b) evidence on impacts of these activities on research…

This article reports a session from the virtual international 2021 IUBMB/ASBMB workshop, "Teaching Science on Big Data." The awareness of using publicly available research data sets for undergraduate training is low in certain parts of the world. Final year projects always revolve around wet-lab based projects. The challenges occur…

Parents and the public use accountability data to judge if schools are doing a good or a bad job educating their students. However, using the current data, schools perceived as "good" tend to be in better-resourced districts and enroll higher percentages of wealthy and white students. Schools perceived as "bad" tend to be in…