The fullness of Black students' experiences in college has yet to be archived. The same can be said of Black people broadly, whose existence has long been reduced by and to what is observable, by systems of power and those at the helm. This is perhaps due to the structural and structural limitations of data collection efforts, or not of interest…

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…

Purpose: It has been demonstrated that AI-powered, data-driven tools' usage is not universal, but deeply linked to socio-cultural contexts. The purpose of this paper is to display the need of adopting situated lenses, relating to specific personal and professional learning about data protection and privacy. Design/methodology/approach: The authors…

There can be many reasons why students fail to answer correctly to summative tests in advanced computer science courses: often the cause is a lack of prerequisites or misconceptions about topics presented in previous courses. One of the ITiCSE 2020 working groups investigated the possibility of designing assessments suitable for differentiating…

With the vigorous development of intelligent campus construction, great changes have taken place in the development of information technology in colleges and universities from the previous digital to intelligent development. In the teaching process, the analysis of students' classroom learning has also changed from the previous manual observation…

Institutional researchers use skills from their diverse backgrounds to collect, analyze and report data about their institutions to stakeholders representing various interests and levels of data literacy. However, there is little research into how these professionals process data and none into what aspects are important to institutional…

Educational data mining has allowed for large improvements in educational outcomes and understanding of educational processes. However, there remains a constant tension between educational data mining advances and protecting student privacy while using educational datasets. Publicly available datasets have facilitated numerous research projects…

This paper describes the study of enforcement of prerequisites in the Computer Science program at a regional university in the Southwest. Prerequisites are a significant factor in programs of study in higher education. Allowing students to register in courses may assume that they have existing knowledge and skills. Some programs treat…

Higher education data mining and analytics, like learning analytics, may improve learning experiences and outcomes. However, such practices are rife with student privacy concerns and other ethics issues. It is crucial that student privacy expectations and preferences are considered in the design of educational data analytics. This study forefronts…

Assessing group work formatively in higher education poses a significant challenge. The complexity of evaluating individual contributions is compounded by the lack of efficient and effective methods for tracking, analysing and assessing individual engagement and contributions, which can impede timely feedback and the development of group work…

In many collegiate level statistics courses, the focus of the learning outcomes is often on the analysis of data after it has been collected. Students are provided with clean data sets from previous studies to practice statistical analysis, but receive little to no application as to the amount of time and effort that goes in to collecting good…

Traditional student information systems were designed primarily to collect and manage records of course enrollment and credit hours earned, as well as other data elements needed to monitor each student's progress to graduation. Now, institutions want to monitor and improve the quality and equity of students' learning experiences in courses and the…

While it is easy to assume that university students who wait until the last minute to complete surveys for their class research requirements provide low-quality data, this issue has not been empirically examined. The goal of the present study was to examine the relation between student research procrastination and two important data quality…

Contributions: This article explores the impact of environmental education interventions about e-waste recycling and management practices as well as about the energy usage of data centers (DCs) into the Information and Communication Technologies (ICTs) university curricula. Intended Outcomes: An education program was implemented aiming to raise…

Many postsecondary datasets collect gender data in ways that are not inclusive of all students. Many trans* students, those who identify as trans women, trans men, genderqueer, among other gender identities, are excluded when surveys collect gender data using only two categories. The American Bar Association recently became the first sector of…