Automated decision-making is becoming increasingly common in the public sector. As a result, political institutions recommend the presence of humans in these decision-making processes as a safeguard against potentially erroneous or biased algorithmic decisions. However, the scientific literature on human-in-the-loop performance is not conclusive…

Contextual multi-armed bandits have previously been used to personalize student support messages given to learners by supplying a model with relevant context about the user, problem, and available student supports. In this work, we propose using careful feature selection with relevant domain knowledge to improve the quality of student support…

Recommender systems in education aim to help students make good decisions about the direction of their learning. The design of such systems in conventional research has treated the decision making process of students as a black box and assumes the best recommendations to be those that accurately predict student choices. Such an approach overlooks…

Ethical decision-making is challenging for most students. Values clarification exercises (VCEs) can help reduce decisional conflicts and feelings of regret. Scholars have suggested Ethical decision-making is challenging for most students. Values clarification exercises (VCEs) can help reduce decisional conflicts and feelings of regret. Scholars…

Massive open online courses (MOOCs; online courses delivered over the Internet) enable distance learning without time and place constraints. MOOCs are popular; however, active participation level among students who take MOOCs is generally lower than that among students who take in-person courses. Students who take MOOCs often lack guidance, and…

Defenses against adversarial attacks are essential to ensure the reliability of machine learning models as their applications are expanding in different domains. Existing ML defense techniques have several limitations in practical use. I proposed a trustworthy framework that employs an adaptive strategy to inspect both inputs and decisions. In…

This study aims to produce a more personalized recommendation system for online learning using multicriteria in collaborative filtering and data from the Binus Online Learning repository as a knowledge base. The study uses forecasting (regression) and consists of three stages: (1) collecting data on the results of the learning process; (2) adding…

No records of systematic reviews focused on deep learning in open learning have been found, although there has been some focus on other areas of machine learning. Through a systematic review, this study aimed to determine the trends, applied computational techniques, and areas of educational use of deep learning in open learning. The PRISMA…

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 and which is based on the explainable k-nearest neighbor algorithm,…

Schools across the United States suffer from low on-time graduation rates. Targeted interventions help at-risk students meet graduation requirements in a timely manner, but identifying these students takes time and practice, as warning signs are often context-specific and reflected in a combination of attendance, social, and academic signals…

The concept of precision medicine aims to provide additional context to patient data for healthcare providers. Precision medicine overlays three additional layers of patient data on top of standard patient information: environmental exposure, personal lifestyle and behavior patterns, and information gleaned from their genome. While precision…

Clinical Decision Support is one of the only aspects of health information technology that has demonstrated decreased costs and increased quality in healthcare delivery, yet it is extremely expensive and time-consuming to create, maintain, and localize. Consequently, a majority of health care systems do not utilize it, and even when it is…

The research presented in this dissertation focuses on the organizational and consumer need for knowledge based support in unstructured domains, by developing a measurement scale for dynamic interaction. Addressing this need is approached and evaluated from two different perspectives. The first approach is the development of Knowledge Based…

Recommender systems aim to support users in their decision-making process while interacting with large information spaces and recommend items of interest to users based on preferences they have expressed, either explicitly or implicitly. Recommender systems are increasingly used with product and service selection over the Internet. Although…

The National Airspace System (NAS) is a resource managed in the public good. Equity in NAS access, and use for private, commercial and government purposes is coordinated by regulations and made possible by procedures, and technology. Researchers have documented scenarios in which the introduction of new concepts-of-operations and technologies has…