Contribution: A competency assessment framework that enables learning analytics for course monitoring and continuous improvement. Our work fills the gap in systematic methods for competency assessment in higher education. Background: Many institutions are shifting toward competency-based education (CBE), thus encouraging their educators to start…

Monitoring students' academic progress is vital for ensuring timely completion of their studies and supporting at-risk students. Educational Data Mining (EDM) utilizes machine learning and feature selection to gain insights into student performance. However, many feature selection algorithms lack performance forecasting systems, limiting their…

Student success, both during and after college, is central to the mission of higher education. Within the higher-education and, more specifically, the student-success context, the core raison d'être of machine learning (ML) is to help institutions achieve their social mission in an efficient and effective manner. While there should be synergy…

The National Assessment of Educational Progress (NAEP), often referred to as The Nation's Report Card, offers a window into the state of U.S. K-12 education system. Since 2017, NAEP has transitioned to digital assessments, opening new research opportunities that were previously impossible. Process data tracks students' interactions with the…

In a higher education context, students are expected to take charge of their learning by deciding "what" to learn and "how" to learn. While the learning analytics (LA) community has seen increasing research on the "how" to learn part (i.e., researching methods for supporting students in their learning journey), the…

Learning data analytics improves the learning field in higher education using educational data for extracting useful patterns and making better decisions. Identifying potential at-risk students may help instructors and academic guidance to improve the students' performance and the achievement of learning outcomes. The aim of this research study is…

This action research project aimed to introduce and examine the impact of Professional Learning Communities (PLCs), the Meeting Wise Process, and the Data Wise Process on teaching practices at a Chinese middle school. PLCs, a collaborative model for continuous professional development, have been widely adopted in various educational contexts but…

First-Year Engineering (FYE) programs are a critical part of engineering education, yet they are quite complex settings. Given the importance and complexity of FYE programs, research to better understand student learning and inform design and assessment in FYE programs is imperative. Therefore, this dissertation showcases various uses of data…

Academic advising plays an important role in students' decision-making in higher education. Data-driven methods provide useful recommendations to students to help them with degree completion. Several course recommendation models have been proposed in the literature to recommend courses for the next semester. One aspect of the data that has yet to…

This chapter addresses how IR/IE both responds to and leads in our institutions and across higher education in measuring and improving student success. We introduce a new student success measurement framework in the context of internal and external facing needs, we define the importance of actionable information to inform decision-making, and we…

This case study reviews the implementation of a learning analytics (LA) system at a large southeastern university. The LA system uses cloud computing to automate data collection and distribution, providing faculty with insights into student performance and engagement. The system includes weekly alert emails and dashboards offering detailed…

Information is everywhere in a hidden and scattered way. It becomes useful when we apply Data mining to extracts the hidden, meaningful, and potentially useful patterns from these vast data resources. Educational data mining ensures a quality education by analyzing educational data based on various aspects. In this paper, we have analyzed the…

Higher education institutions are facing growing pressure to improve retention and graduation rates. Academic analytics has emerged as a strategy to address the completion issue. Because academic advisors are integral in providing successful student success initiatives and they often maintain relationships with students throughout their entire…

This explanatory case study investigated why educators (teachers, administrators and support teachers) in a northeast charter school found it difficult to implement a data-driven decision-making (D3M) process. To comprehend where the breakdown in the process occurred, the researcher examined the cultural, technological and political barriers that…

Data-informed decision-making has always been -- and always will be -- a smart approach to policy, including at institutions of higher education. Just over one year since the COVID-19 pandemic radically and abruptly shifted every aspect of higher education, states and institutions are tackling the same student success goals as before, but with…