Related papers: Quantifying the relationship between student enrol…
Federated Learning (FL) is a decentralized machine learning framework that enables learning from data distributed across multiple remote devices, enhancing communication efficiency and data privacy. Due to limited communication resources, a…
Federated learning has emerged as an umbrella term for centralized coordination strategies in multi-agent environments. While many federated learning architectures process data in an online manner, and are hence adaptive by nature, most…
We investigate the impact of content sequencing on student learning outcomes in a first-year university electromagnetism course. Using a custom-built online system, the McGill Learning Platform (McLEAP), we test student problem-solving…
A plethora of research has been done in the past focusing on predicting student's performance in order to support their development. Many institutions are focused on improving the performance and the education quality; and this can be…
When users can benefit from certain predictive outcomes, they may be prone to act to achieve those outcome, e.g., by strategically modifying their features. The goal in strategic classification is therefore to train predictive models that…
We ran a study on engagement and achievement for a first year undergraduate programming module which used an online learning environment containing tasks which generate automated feedback. Students could also access human feedback from…
Peer interaction and social roles have been important factors in students' academic performance. Recent work on what influences academic performance in Thailand has focused on the quality of a school, students' backgrounds, and students…
This paper is motivated by the analysis of a survey study of college student wellbeing before and after the outbreak of the COVID-19 pandemic. A statistical challenge in well-being survey studies lies in that outcome variables are often…
The flipped classroom model has been widely acknowledged as a practical pedagogical approach to enhancing student engagement and learning. However, it faces challenges such as improving student interaction with learning content and peers,…
Massive Open Online Courses (MOOCs) continue to see increasing enrolment, but only a small percent of enrolees completes the MOOCs. Whilst a lot of research has focused on predicting completion, there is little research analysing the…
While large language models (LLMs) fine-tuned with lightweight adapters achieve strong performance across diverse tasks, their performance on individual tasks depends on the fine-tuning strategy. Fusing independently trained models with…
Given progressive developments and demands on clinical trials, accurate enrollment timeline forecasting is increasingly crucial for both strategic decision-making and trial execution excellence. Naive approach assumes flat rates on…
We study the course allocation problem, where universities assign course schedules to students. The current state-of-the-art mechanism, Course Match, has one major shortcoming: students make significant mistakes when reporting their…
In this paper, we compare predictive models for students' final performance in a blended course using a set of generic features collected from the first six weeks of class. These features were extracted from students' online homework…
Training multimodal networks requires a vast amount of data due to their larger parameter space compared to unimodal networks. Active learning is a widely used technique for reducing data annotation costs by selecting only those samples…
Two-stage exams, which pair a traditional individual exam with a subsequent collaborative, group exam, have been shown to enhance learning, retention, and student attitudes in midterm settings. This study investigates whether these benefits…
For many students, placement into developmental education becomes a self-fulfilling prophecy. Placing college students into developmental education significantly negatively impacts student attainment, student probability of passing, and…
University students routinely use the tools provided by online course ranking forums to share and discuss their satisfaction with the quality of instruction and content in a wide variety of courses. Student perception of the efficacy of…
Federated Learning (FL) enables multiple clients to collaboratively train a shared model while preserving data privacy. However, the high memory demand during model training severely limits the deployment of FL on resource-constrained…
Mentoring is a key component of scientific achievements, contributing to overall measures of career success for mentees and mentors. A common success metric in the scientific enterprise is acquiring a large research group, which is believed…