In recent years, machine learning (ML) techniques have received more attention in detecting aberrant test-taking behaviors due to advantages when compared to traditional data forensics methods. However, defining "True Test Cheaters" is challenging--different than other fraud detection tasks such as flagging forged bank checks or credit…

The massive amount of text related to education provides rich information to support education in many aspects. In the meantime, the vast yet increasing volume of text makes it impossible to analyze manually. Text mining is a powerful tool to automatically analyze large-scaled texts and generate insights from the texts. However, many educational…

Practical work involving laboratory experiments is agreed upon to be an essential component of secondary science education. Practical work encompasses a broad range of activity types. The different forms of practical work are not equal in terms of cognitive demand and learning benefit. Inquiry-based investigations provide experience of cognitive…

Due to the precautionary measures during the COVID-19 pandemic many universities offered unproctored take-home exams. We propose methods to detect potential collusion between students and apply our approach on event log data from take-home exams during the pandemic. We find groups of students with suspiciously similar exams. In addition, we…

Programming skills (PS) are indispensable abilities in the information age, but the current research on PS cultivation mainly focuses on the teaching methods and lacks the analysis of program features to explore the differences in learners' PS and guide programming learning. Therefore, the purpose of this study aims to explore horizontal…

Educational data mining is widely deployed to extract valuable information and patterns from academic data. This research explores new features that can help predict the future performance of undergraduate students and identify at-risk students early on. It answers some crucial and intuitive questions that are not addressed by previous studies.…

The large rates of students' failure is a very frequent problem in undergraduate courses, being even more evident in exact sciences. Pointing out the reasons of such problem is a paramount research topic, though not an easy task. An alternative is to use Educational Data Mining techniques (EDM), which enables one to convert data from educational…

Demographic features are commonly used in Educational Data Mining (EDM) research to predict at-risk students. Yet, the practice of using demographic features has to be considered extremely problematic due to the data's sensitive nature, but also because (historic and representation) biases likely exist in the training data, which leads to strong…

This article introduces researchers in the science concerned with developing and studying research methods, measurement, and evaluation (RMME) to the educational data mining (EDM) community. It assumes that the audience is familiar with traditional priorities of statistical analyses, such as accurately estimating model parameters and inferences…

MOOCs can be considered as a powerful alternative in extraordinary situations where people cannot reach formal education. In recent years, the widespread use of the internet worldwide and especially the COVID-19 has increased the need of people for MOOCs. However, in order to increase the effectiveness of MOOCs, and to provide a better learning…

This study attempts to predict secondary school students' performance in English and Mathematics subjects using data mining (DM) techniques. It aims to provide insights into predictors of students' performance in English and Mathematics, characteristics of students with different levels of performance, the most effective DM technique for students'…

There is an increasing interest and growing practice in Citizen Science (CS) that goes along with the usage of websites for communication as well as for capturing and processing data and materials. From an educational perspective, it is expected that by integrating information about CS in a formal educational setting, it will inspire teachers to…

Educators in higher education institutes often use statistical results obtained from their online Learning Management System (LMS) dataset, which has limitations, to evaluate student academic performance. This study differs from the current body of literature by including an additional dataset that advances the knowledge about factors affecting…

This paper focuses on the opportunities and challenges associated with the use of artificial intelligence (AI) in academic library operations. In the quest to render fast, effective and efficient services, academic libraries have adopted different technologies in the past. Artificial intelligence technologies is the latest among the technologies…

The large flood of data flowing from observatories presents significant challenges to astronomy and cosmology--challenges that will only be magnified by projects currently under development. Growth in both volume and velocity of astrophysics data is accelerating: whereas the Sloan Digital Sky Survey (SDSS) has produced 60 terabytes of data in the…