Big Data Comes to School

Abstract

The prospect of “big data” at once evokes optimistic views of an information-rich future and concerns about surveillance that adversely impacts our personal and private lives. This overview article explores the implications of big data in education, focusing by way of example on data generated by student writing. We have chosen writing because it presents particular complexities, highlighting the range of processes for collecting and interpreting evidence of learning in the era of computer-mediated instruction and assessment as well as the challenges. Writing is significant not only because it is central to the core subject area of literacy; it is also an ideal medium for the representation of deep disciplinary knowledge across a number of subject areas. After defining what big data entails in education, we map emerging sources of evidence of learning that separately and together have the potential to generate unprecedented amounts of data: machine assessments, structured data embedded in learning, and unstructured data collected incidental to learning activity. Our case is that these emerging sources of evidence of learning have significant implications for the traditional relationships between assessment and instruction. Moreover, for educational researchers, these data are in some senses quite different from traditional evidentiary sources, and this raises a number of methodological questions. The final part of the article discusses implications for practice in an emerging field of education data science, including publication of data, data standards, and research ethics.

Exploring Adaptive Teaching Competencies in Big Data Era

“…For instance, an online learning from the materials provided by the instructor can be supplied with relevant and reliable links to resources, within three main headings: directed, automated, and volunteered [30]. With big data adoption, generating records of the users' lives can be made by frequently posting details of activities to develop the course structure or make decisions based on this context [39]. By various students' blogs to understand their learning quality for instance, the instructor can provide such content appropriate with personal learning needs.…”

Using big data to promote precision oral health in the context of a learning healthcare system

“…98,99 This approach was shown to have implications for optimizing personalized learning and improving student assessments based on individualized feedback provided in a timely fashion. 100 Additionally, use of real life examples drawn from dental EHR in the process of dental education demonstrated promising results in predoctoral 39 and postdoctoral training. 101,102 As evidence-based dentist training is being considered as an essential means for improvements in the quality of patients care, 103 data analytics workflows for ongoing reporting of dental care quality metrics and providing instructive feedback to dental professionals will be increasingly used in the context of LHS.…”

Educational Assessment: What to Watch in a Rapidly Changing World

“…New types of data from online learning and online assessment are emerging. A salient example is process data (Cope & Kalantzis, 2016). With technology-based assessment, we can capture the type of action an examinee takes, when that action occurred, how long it lasted, and what preceded and followed it, all of which may hold useful information.…”