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Machine learning models achieve state-of-the-art performance on many supervised learning tasks. However, prior evidence suggests that these models may learn to rely on shortcut biases or spurious correlations (intuitively, correlations that…
This study examines the impact of lifelong learning on the professional lives of employed and unemployed individuals. Lifelong learning is a crucial factor in securing employment or enhancing one's existing career prospects. To achieve this…
Increasing the batch size during training -- a ''batch ramp'' -- is a promising strategy to accelerate large language model pretraining. While for SGD, doubling the batch size can be equivalent to halving the learning rate, the optimal…
Amidst the outbreak of the coronavirus (COVID 19) pandemic, distance education, where the learning process is conducted online, has become the norm. Campus-based programs and courses have been redesigned in a timely manner which was a…
Present-day federated learning (FL) systems deployed over edge networks consists of a large number of workers with high degrees of heterogeneity in data and/or computing capabilities, which call for flexible worker participation in terms of…
Timely and high-quality feedback is essential for effective learning in programming courses; yet, providing such support at scale remains a challenge. While AI-based systems offer scalable and immediate help, their responses can…
With the recent rapid increase in digitization across all major industries, acquiring programming skills has increased the demand for introductory programming courses. This has further resulted in universities integrating programming…
Workers without formal credentials experience substantially lower employment rates than their credentialed counterparts, but the extent to which information frictions contribute to these disparities remains unclear. We conducted a…
Code completion is widely used by software developers to provide coding suggestions given a partially written code snippet. Apart from the traditional code completion methods, which only support single token completion at minimal positions,…
The growing prominence of LLMs has led to an increase in the development of AI tutoring systems. These systems are crucial in providing underrepresented populations with improved access to valuable education. One important area of education…
Confounding bias and selection bias bring two significant challenges to the validity of conclusions drawn from applied causal inference. The latter can stem from informative missingness, such as in cases of attrition. We introduce the…
Multi-armed bandit (MAB) algorithms are efficient approaches to reduce the opportunity cost of online experimentation and are used by companies to find the best product from periodically refreshed product catalogs. However, these algorithms…
Why do biased predictions arise? What interventions can prevent them? We evaluate 8.2 million algorithmic predictions of math performance from $\approx$400 AI engineers, each of whom developed an algorithm under a randomly assigned…
A matching platform is a system that matches different types of participants, such as companies and job-seekers. In such a platform, merely maximizing the number of matches can result in matches being concentrated on highly popular…
Prior research suggests that using evidence-based pedagogies can not only improve learning for all students, it can also reduce the gender gap. We describe the impact of physics education research based pedagogical techniques in flipped and…
Computer science's increased recognition as a prominent field of study has attracted students with diverse academic backgrounds. This has significantly increased the already high failure rates in introductory courses. To address this…
Worldwide, computer science departments have experienced a dramatic increase in the number of student enrolments. Moreover, the ongoing COVID-19 pandemic requires institutions to radically replace the traditional way of on-site teaching,…
This study investigates the causal relationship between the COVID-19 pandemic and wage levels, aiming to provide a quantified assessment of the impact. While no significant evidence is found for long-term effects, the analysis reveals a…
We present a perspective on platforms for code submission and automated evaluation in the context of university teaching. Due to the COVID-19 pandemic, such platforms have become an essential asset for remote courses and a reasonable…
This study investigates the reaction of workers to employer-sponsored general training that provides skills useful not only in the incumbent employer but also in other firms in the industry. While previous research has focused primarily on…