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Conventional methods of obtaining student feedback on course experience face a fundamental tradeoff between feedback frequency and quality: as feedback requests become more frequent, participation often declines, and responses become less…
Reward learning algorithms utilize human feedback to infer a reward function, which is then used to train an AI system. This human feedback is often a preference comparison, in which the human teacher compares several samples of AI behavior…
To help faculty use research-based materials in a more significant way, we learn about their perceived needs and desires and use this information to suggest ways for the Physics Education Research community to address these needs. When…
A fundamental component in the theoretical school choice literature is the problem a student faces in deciding which schools to apply to. Recent models have considered a set of schools of different selectiveness and a student who is unsure…
Online courses have significantly lowered the barrier to accessing education, yet the varying content quality of these videos poses challenges. In this work, we focus on the task of automatically evaluating the quality of video course…
Algorithmic decision-making systems are increasingly used throughout the public and private sectors to make important decisions or assist humans in making these decisions with real social consequences. While there has been substantial…
The rapid proliferation of Generative Artificial Intelligence (GenAI) is reshaping pedagogical practices and assessment models in higher education. While institutional and educator perspectives on GenAI integration are increasingly…
Course evaluation plays a critical role in ensuring instructional quality and guiding curriculum development in higher education. However, traditional evaluation methods, such as student surveys, classroom observations, and expert reviews,…
The Georgia Tech blended introductory calculus-based mechanics course emphasizes scientific communication as one of its learning goals, and to that end, we gave our students a series of four peer-evaluation assignments intended to develop…
We study relationship between peer assessment of quality of U.S. Computer Science (CS) doctoral programs and objective measures of research strength of those programs. In Fall 2016 we collected Google Scholar citation data for 4,352…
Evaluating the performance of students in higher education is essential for gauging the effectiveness of teaching methods and achieving greater equality of opportunities for all. In this study, we investigate the correlation between two…
Educational technologies often misalign with instructors' pedagogical goals, forcing adaptations that compromise teaching efficacy. In this paper, we present a case study on the co-development of curriculum and technology in the context of…
The current work aims to better understand student course experiences for those who reported negative perceptions in introductory physics. We conducted semi-structured interviews with 24 students who reported negative perceptions of their…
The evaluation of recommendation systems is a complex task. The offline and online evaluation metrics for recommender systems are ambiguous in their true objectives. The majority of recently published papers benchmark their methods using…
Predictive models of student success in Massive Open Online Courses (MOOCs) are a critical component of effective content personalization and adaptive interventions. In this article we review the state of the art in predictive models of…
In humans and animals, curriculum learning -- presenting data in a curated order - is critical to rapid learning and effective pedagogy. Yet in machine learning, curricula are not widely used and empirically often yield only moderate…
There are various teaching methods developed in order to attain successful delivery of a subject without prior knowledge of the interaction among the students in a class. Social network analysis can be used to identify individual,…
Recommendation systems have been integrated into the majority of large online systems to filter and rank information according to user profiles. It thus influences the way users interact with the system and, as a consequence, bias the…
AI-powered coding assistants can support students in programming courses by providing on-demand explanations and debugging help. However, existing research often focuses on individual tools, leaving a gap in evidence-based design…
While much of the literature on student peer-review focusses on the success (or otherwise) of individual activities in specific classes (often implemented as part of scholarly research projects) there is little by way of published data…