The emergence of big data in educational contexts has led to new data-driven approaches to support informed decision making and efforts to improve educational effectiveness. Digital traces of student behavior promise more scalable and finer-grained understanding and support of learning processes, which were previously too costly to obtain with traditional data sources and methodologies. This synthetic review describes the affordances and applications of microlevel (e.g., clickstream data), mesolevel (e.g., text data), and macrolevel (e.g., institutional data) big data. For instance, clickstream data are often used to operationalize and understand knowledge, cognitive strategies, and behavioral processes in order to personalize and enhance instruction and learning. Corpora of student writing are often analyzed with natural language processing techniques to relate linguistic features to cognitive, social, behavioral, and affective processes. Institutional data are often used to improve student and administrational decision making through course guidance systems and early-warning systems. Furthermore, this chapter outlines current challenges of accessing, analyzing, and using big data. Such challenges include balancing data privacy and protection with data sharing and research, training researchers in educational data science methodologies, and navigating the tensions between explanation and prediction. We argue that addressing these challenges is worthwhile given the potential benefits of mining big data in education.

No abstract

No abstract

No abstract

This quantitative study examines the impact of a three-week online organic preparatory course for chemistry undergraduates that is designed to improve student performance in the subsequent organic chemistry course series (N = 1,289). Organic chemistry often serves as a gatekeeper for students pursuing careers in science, technology, engineering, or mathematics (STEM). Because many students are underprepared for the rigorous organic chemistry series, and consequently are at greater risk of failing it, an online preparatory course was offered that emphasized topics that students frequently struggle with when they enter organic chemistry. The average treatment effects of participation in the online preparatory course on students' subsequent organic chemistry course grades were analyzed utilizing inverse-probability weights with regression adjustment. The analyses indicate that participation in the online preparatory course led to an improvement in subsequent organic chemistry course performance of approximately one-third of a letter grade (e.g., C+ to B−). Notably, students typically at-risk in college environments (i.e., low-income students, first-generation college students, underrepresented minorities) showed commensurate gains when compared to their non-at-risk counterparts. Consequently, this study provides an example of a low-cost intervention that can increase student learning and achievement in organic chemistry. In addition, this study contributes to the nascent research base that examines more distal effects of online course participation.