**2. Benefits of Big Data in Education**

Research has suggested that the appropriate engagement with big data can be a force for educational equity, evidenced by countless studies where educational stakeholders have engaged with complex data sets to identify equity gaps and improve teaching and learning and student outcomes [3–7,9–14]. The benefits of big data utility are multifarious, and the following sections will outline several crucial benefits for developing nations seeking the ability to make large-scale data-informed decisions.

#### *2.1. Individualization through Data-Informed Teaching and Learning*

As many researchers argue, the primary function of education is teaching and learning, and many scholars have pointed to the utility of big data as a driver of the improvement of teaching and learning at all levels of education. Schildkamp et al. reasoned that as schools

are increasingly held more accountable for student learning, countless school districts in developed nations have used local or regional data sets to improve the manner in which students are oriented with curricular materials and how teachers are prepared for the classroom by post-secondary institutions [13]. Nazarenko and Khronusova explained that there are "incredible opportunities for individualization and personalization of the student's path to content mastery based on adaptive learning or competency-based education" [15] (p. 676), as schools in developed nations often have access to increasingly technologically advanced modes of content delivery, and thus access to even more data to make even more decisions.

Moreover, Nazarenko and Khronusova have explained that teachers and administrators would likely have ample data to target educational inequities, such as the challenges faced by students with disabilities. Here, the authors reasoned that schools could provide "targeted interventions to improve student's success and to reduce overall costs to students and institutions" [15] (p. 676). In the Australian context, the national government has engaged with big data analytics to provide teachers and administrators with information to personalize learning to align with national policies related to teacher and school effectiveness, including the stemming of educational inequities [16].

Wang went into further detail, explaining that schools can move far beyond "student demographics, test scores, and psychological questionnaires" toward more fine-grained data collection methods, such as "computer mouse clicks, number of attempts, learning browsing patterns, online chats, discussion forum participations, and visual and facial reactions" [3] (p. 382). Although these approaches require technologically mediated education, the technology exists to equip classrooms with cameras and tracking devices to allow teachers to understand when students are on task and how efficient and effective their teaching style is for diverse learners [3]. Furthermore, the expansion of mobile devices and "bring your own device" initiatives has greatly expanded the walls of the classroom, allowing schools to understand not only which technologies are best for student learning and teaching by faculty, but administrators can also understand which type of hardware is most conducive to effective teaching and learning [3,6]. This insight can be facilitated by capturing and analyzing big data to inform a wide variety of teaching and learning subjects such as student attention, teacher effectiveness, relationship development, assessment types and strategies, and a plethora of others.
