In this paper, we present an extended evaluation of a course recommender system designed to support students who struggle in the first semesters of their studies and are at risk of dropping out. The system, which was developed in earlier work using a student-centered design, is based on the explainable k-nearest neighbor algorithm and recommends a…

This research investigates how artificial intelligence (AI) influences higher education, specifically exploring the perspectives of academicians regarding associated risks and opportunities. The study is aimed at the implementation of AI within university settings and its impact on both educators and students. Given the swift integration of AI,…

To improve students' learning performance through review learning activities, we developed a personalized intervention tutoring approach that leverages learning analysis based on artificial intelligence. The proposed intervention first uses text-processing artificial intelligence technologies, namely bidirectional encoder representations from…

Early predictors of student success are becoming a key tool in flipped and online courses to ensure that no student is left behind along course activities. However, with an increased interest in this area, it has become hard to keep track of what the state of the art in early success prediction is. Moreover, prior work on early success prediction…

Educational data mining has gained a lot of attention among scientists in recent years and constitutes an efficient tool for unraveling the concealed knowledge in educational data. Recently, semisupervised learning methods have been gradually implemented in the educational process demonstrating their usability and effectiveness. Cotraining is a…

As students' achievement is correlated with self-regulation, finding interventions promoting self-regulated learning (SRL) in online courses is a current focus of research. However, few studies have explored the potential of contract learning in scaffolding and developing SRL in non-traditional learners who have work and family and are at risk of…

As higher education institutions develop fully online course programs to provide better access for the non-traditional learner, there is increasing interest in identifying students who may be at risk of attrition and poor performance in these online course programs. In our study, we investigate the effectiveness of an online orientation course in…

This case study investigates the implementation of a unique community-driven mentoring pilot program (PASOS[superscript 2]) forging stronger community and K-12 partnerships. Focused on surfacing what matters most in engaging community mentors, this case study explores a civic organization's quest to impact, expand, and bring value via mentoring to…

No significant body of research examines writing achievement and the specific skills and knowledge in the writing domain for postsecondary (college) students in the U.S., even though many at-risk students lack the prerequisite writing skills required to persist in their education. This paper addresses this gap through a novel…

This paper investigates the users and uses of a centralised customer relationship management (CRM) system at a regional Australian university to improve the understanding of the staff experience of interacting with this customised technology. How and why the software is used by a cross section of university departments is explored through…

This study investigated the use of automated essay scoring (AES) to identify at-risk students enrolled in a first-year university writing course. An application of AES, the "Criterion"[R] Online Writing Evaluation Service was evaluated through a methodology focusing on construct modelling, response processes, disaggregation, extrapolation,…

This paper presents the findings of a study on software development students from economically disadvantaged backgrounds that have dropped out of universities which have a strong research emphasis. In the UK, these universities are generally part of the Russell Group of Universities. The participants were all male, mainly black, working class and…

Earlier studies have suggested that higher education institutions could harness the predictive power of Learning Management System (LMS) data to develop reporting tools that identify at-risk students and allow for more timely pedagogical interventions. This paper confirms and extends this proposition by providing data from an international…

Technology usage is increasing important for community college students, but whether nontraditional students differ from traditional students in technology usage and support was unclear. Further, it was not known whether Nontraditional and Traditional community college students feel equally connected to the college when using social networking…

Community colleges continue to experience growth in online courses. This growth reflects the need to increase the numbers of students who complete certificates or degrees. Retaining online students, not to mention assuring their success, is a challenge that must be addressed through practical institutional responses. By leveraging existing student…