Predicting students' success is crucial in educational settings to improve academic performance and prevent dropouts. This study aimed to improve student performance prediction by combining advanced machine learning (ML) approaches. Convolutional Neural Networks (CNNs) and attention mechanisms were used for extracting relevant features from…

Predicting and improving the academic achievement of university students is a multifactorial problem. Considering the low success rates and high dropout rates, particularly in open education programs characterized by mass enrollment, academic success is an important research area with its causes and consequences. This study aimed to solve a…

The early detection of students' academic performance or final grades helps instructors prepare their online courses. In the Open University Learning Analytics Dataset, I found many online students clicked the course materials before the first day of class. This study aims to investigate how data mining models can use this student interaction data…

We propose a novel model, Wide & Deep Item Response Theory (Wide & Deep IRT), to predict the correctness of students' responses to questions using historical clickstream data. This model combines the strengths of conventional Item Response Theory (IRT) models and Wide & Deep Learning for Recommender Systems. By leveraging clickstream…

A capability maturity model provides a thorough understanding of where the organization is and, perhaps more importantly, where the organization needs to grow. The purpose of this report is to describe the development of the ADL Initiative Distributed Learning Capability Maturity Model (DL-CMM), illustrate its major components, and explain how it…

Over the past decades, Vincent Tinto, Edmund Thile, Francis Ianni, and others all link mentoring to better academic performance, improved social adjustment, enhanced academic experiences, and greater rates of degree completion. Even more specifically, Jean E. Rhodes, Renée Spencer, Thomas E. Keller, Belle Liang, and Gil Noam describe three…

In this qualitative study, a proposed organizing framework of college and career readiness for secondary students with disabilities was developed based on a synthesis of extant research articulating student success. The original proposed framework included six domains representing academic and nonacademic skills associated with college and career…

This study takes a novel approach toward understanding success in a math course by examining the linguistic features and affect of students' language production within a blended (with both on-line and traditional face to face instruction) undergraduate course (n=158) on discrete mathematics. Three linear effects models were compared: (a) a…

Due to poor student success rates in developmental mathematics, many institutions have implemented various forms of redesign into their developmental math curricula. Since the goal of redesign is to increase student success, it is salient to explore all aspects of the redesign process. Many studies have focused on the positive outcomes of redesign…

Acting as the lead agency for the "National STEM Consortium" (NSC), Anne Arundel Community College (AACC) engaged Hezel Associates to provide an independent program and impact evaluation of the U.S. Department of Labor (USDOL)-funded STEM certificate initiative. This report is comprehensive and covers the findings from all 4 years of the…

In this chapter, the author proposes a model for assessing institutional effectiveness. The Volkwein model for assessing institutional effectiveness consists of five parts that summarize the steps for assessing institutions, programs, faculty, and students. The first step in the model distinguishes the dual purposes of institutional effectiveness:…

The 13th iteration of the International Conference on Educational Data Mining (EDM 2020) was originally arranged to take place in Ifrane, Morocco. Due to the SARS-CoV-2 (coronavirus) epidemic, EDM 2020, as well as most other academic conferences in 2020, had to be changed to a purely online format. To facilitate efficient transmission of…

This technical report, produced in partnership by the Council for Advancement and Support of Education (CASE) and SPSS Inc., explores the promise of data mining alumni records at educational institutions. Working with individual alumni records from The Johns Hopkins Zanvyl Krieger School of Arts and Sciences, a predictive regression model is…

The 10th International Conference on Educational Data Mining (EDM 2017) is held under the auspices of the International Educational Data Mining Society at the Optics Velley Kingdom Plaza Hotel, Wuhan, Hubei Province, in China. This years conference features two invited talks by: Dr. Jie Tang, Associate Professor with the Department of Computer…

The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…