Machine learning (ML) techniques have been successfully applied to a wide array of applications. This dissertation aims to take application data handling into account when developing ML-based solutions for real-world problems through a holistic framework. To demonstrate the generality of our framework, we consider two real-world applications: spam…

Modern Information Technology (IT) infrastructure and open-source software (OSS) have revolutionized our ability to access and process data, enabling us to tackle increasingly complex problems and challenges. While these technologies provide substantial benefits, they often expose users to vulnerabilities that can severely damage individuals and…

Generative Artificial Intelligence (GAI) holds promise for enhancing the educational experience by providing personalized feedback and interactive simulations. While its integration into classrooms would improve education, concerns about how students may use AI in the class has prompted research on the perceptions related to the intention to…

After the pandemic, research on Artificial Intelligence (AI) in the field of education has seen a significant increase globally. However, a few studies conducted before the pandemic addressed the problem of supporting intrinsic motivation in students, crucial for the quality of learning and knowledge retention. This study explores how this topic…

The last decade witnessed a spectacular rise in the volume of available textual data. With this new abundance came the question of how to analyze it. In the social sciences, scholars mostly resorted to two well-established approaches, human annotation on sampled data on the one hand (either performed by the researcher, or outsourced to…

The greater the proliferation of AI in educational contexts, the more important it becomes to ensure that AI adheres to the equity and inclusion values of an educational system or institution. Given that modern AI is based on historic datasets, mitigating historic biases with respect to protected classes (ie, fairness) is an important component of…

In recent years, there has been an increasing trend of utilizing artificial intelligence (AI) methodologies over traditional statistical methods for predicting student performance in e-learning contexts. Notably, many researchers have adopted AI techniques without conducting a comprehensive investigation into the most appropriate and accurate…

This study investigates how 11- to 12-year-old students construct data-based decision trees using data cards for classification purposes. We examine the students' heuristics and reasoning during this process. The research is based on an eight-week teaching unit during which students labeled data, built decision trees, and assessed them using test…

In a number of settings risk prediction models are being used to predict distal future outcomes for individuals, including high school risk prediction. We propose a new method, non-overlapping-leave-future-out (NOLFO) validation, to be used in settings with long delays between feature and outcome observation and where there are overlapping…

This study examines the potential to use keystroke logs to examine differences between authentic writing and transcribed essay writing. Transcribed writing produced within writing platforms where copy and paste functions are disabled indicates that students are likely copying texts from the internet or from generative artificial intelligence (AI)…

We presented two empirical studies to assess the efficacy of two Deep Reinforcement Learning (DRL) frameworks on two distinct Intelligent Tutoring Systems (ITSs) to exploring the impact of Worked Example (WE) and Problem Solving (PS) on student learning. The first study was conducted on a probability tutor where we applied a classic DRL to induce…

This study explores Arab university faculty's views on fully AI-generated assignments and research papers submitted by students, what reasons they give for their stance and how they react in this case. Surveys with a sample of 45 Arab instructors revealed that 98% do not accept AI-generated assignments and research papers from students at all.…

This study examines log data from proctored examinations from two classes offered as part of a large online graduate program in computer science. In these two classes, students are permitted to access any internet content during their exams, which themselves have remained largely unchanged over the last several semesters. As a result, when ChatGPT…

Automatically assessing classroom discussion quality is becoming increasingly feasible with the help of new NLP advancements such as large language models (LLMs). In this work, we examine how the assessment performance of 2 LLMs interacts with 3 factors that may affect performance: task formulation, context length, and few-shot examples. We also…

Artificial intelligence was an emergent and powerful new force in education. The public release of ChatGPT 3.0 in 2022 transformed learning for many students. This phenomenological qualitative study sought to record and analyze student's perspectives on the influence of artificial intelligence on their learning routines. This study collected data…