The education sector has been quick to recognize the power of predictive analytics to enhance student success rates. However, there are challenges to widespread adoption, including the lack of accessibility and the potential perpetuation of inequalities. These challenges present in different stages of modeling, including data preparation, model…

Since 2010, the State Higher Education Executive Officers Association's (SHEEO) Strong Foundations survey has reported on the evolution and value of postsecondary student unit record systems (PSURSs) by illuminating the condition of state postsecondary data in the U.S. In the "Strong Foundations 2023" survey, which was administered from…

This project reviews data collection practices regarding race, ethnicity and ancestry (REA) in post-secondary institutions (PSIs) in Canada, as well as in other relevant sectors (e.g., health, K-12 education, government agencies). The goal of the project was to identify promising practices and to develop recommendations to guide REA data…

Objective: College students who receive an acute care visit (ACV) from an emergency or inpatient unit require mental health follow-up (MHF) to improve long-term outcomes. This study describes tracking ACVs and MHF, while identifying characteristics of multiple vs. single ACVs. Participants: 191 students who received an ACV (N = 231) at one public…

We cannot continue to ask students -- and their families -- to make one of the largest and most important investments of their lives without clearer information about what their time and money will yield. In partnership with RTI International (RTI), operating in an independent capacity, IHEP is gathering expert insights needed to support making…

We cannot continue to ask students -- and their families -- to make one of the largest and most important investments of their lives without clearer information about what their time and money will yield. Fortunately, support is broad across the country and across the political spectrum for a federal student-level data network (SLDN), which would…

Institutional staff such as enrollment managers, business officers, and institutional researchers are often asked to predict enrollments. Developing any predictive model can be intimidating, particularly when there is no textbook to follow. This paper provides a practical framework for generating enrollment projection options and for evaluating…

This paper discusses the application value of the writing teaching mode combined with the mixed teaching mode in college English writing teaching against the background of big data. Focusing on production-oriented approach (POA) theory, this paper proposes a mixed learning writing model for English teaching and applies the POA mixed learning…

This paper combines a theoretical-based model with a data-driven approach to develop an Early Warning System that detects students who are more likely to dropout. The model uses innovative multilevel statistical and machine learning methods. The paper demonstrates the validity of the approach by applying it to administrative data from a leading…

The project presented in this paper aims to formulate a recommendation framework that consolidates the higher education students' particulars such as their academic background, current study and student activity records, their attended higher education institution's expectations of graduate attributes and self-assessment of their own generic…

Knowing relevant information about students entering the higher education (HE) system is becoming increasingly important, thus enabling higher education institutions (HEIs) to design effective studentcentred support programmes. Therefore, HEIs should ascertain all relevant information about their students before the commencement of the academic…

One of the reported methods of cheating in online environments in the literature is CAMEO (Copying Answers using Multiple Existences Online), where harvesting accounts are used to obtain correct answers that are later submitted in the master account which gives the student credit to obtain a certificate. In previous research, we developed an…

Early warning systems have been progressively implemented in higher education institutions to predict student performance. However, they usually fail at effectively integrating the many information sources available at universities to make more accurate and timely predictions, they often lack decision-making reasoning to motivate the reasons…

To successfully reduce student attrition, it is imperative to understand what the underlying determinants of attrition are and which students are at risk of dropping out. We develop an early detection system (EDS) using administrative student data from a state and private university to predict student dropout as a basis for a targeted…

Liberal Arts programs are often characterized by their open curriculum. Yet, the abundance of courses available and the highly personalized curriculum are often overwhelming for students who must select courses relevant to their academic interests and suitable to their academic background. This paper presents the course recommender system that we…