Related papers: Peer Grading in a Course on Algorithms and Data St…
Commonly, introductory programming courses in higher education institutions have hundreds of participating students eager to learn to program. The manual effort for reviewing the submitted source code and for providing feedback can no…
The use of automatic grading tools has become nearly ubiquitous in large undergraduate programming courses, and recent work has focused on improving the quality of automatically generated feedback. However, there is a relative lack of data…
Teamwork assessments often result in a single final product, for which all team members receive a single mark regardless of their contribution to the team project. In order to respond to feedback from students in terms of fair marking of…
Graded labels are ubiquitous in real-world learning-to-rank applications, especially in human rated relevance data. Traditional learning-to-rank techniques aim to optimize the ranked order of documents. They typically, however, ignore…
In many economically relevant contexts where machine learning is deployed, multiple platforms obtain data from the same pool of users, each of whom selects the platform that best serves them. Prior work in this setting focuses exclusively…
Bottlenecks such as the latency in correcting assignments and providing a grade for Massive Open Online Courses (MOOCs) could impact the levels of interest among learners. In this proposal for an auto-grading system, we present a method to…
Machine Learning models have many potentially beneficial applications in education settings, but a key barrier to their development is securing enough data to train these models. Labelling educational data has traditionally relied on highly…
To increase efficacy in traditional classroom courses as well as in Massive Open Online Courses (MOOCs), automated systems supporting the instructor are needed. One important problem is to automatically detect students that are going to do…
Online teaching has become a new reality due to the COVID-19 pandemic raising a lot of questions about its learning outcomes. Recent studies have shown that peer communication positively affects learning outcomes of online teaching.…
While large language models (LLMs) have been used for automated grading, they have not yet achieved the same level of performance as humans, especially when it comes to grading complex questions. Existing research on this topic focuses on a…
Peer-customer is a mechanism to pair student teams with customers in hands-on curriculum courses. Each student pitches a problem they want someone else in the class to solve for them. The use of peer-customers provides practical and…
Online tools provide unique access to research students' study habits and problem-solving behavior. In MOOCs, this online data can be used to inform instructors and to provide automatic guidance to students. However, these techniques may…
Peer review is a multi-stage process involving reviews, rebuttals, meta-reviews, final decisions, and subsequent manuscript revisions. Recent advances in large language models (LLMs) have motivated methods that assist or automate different…
We propose the PeerRank method for peer assessment. This constructs a grade for an agent based on the grades proposed by the agents evaluating the agent. Since the grade of an agent is a measure of their ability to grade correctly, the…
Peer assessment is an efficient and effective learning assessment method that has been used widely in diverse fields in higher education. Despite its many benefits, a fundamental problem in peer assessment is that participants lack the…
Peer review is the main mechanism by which the software engineering community assesses the quality of scientific results. However, the rapid growth of paper submissions in software engineering venues has outpaced the availability of…
Assessing student performance becomes challenging when course enrollment becomes very large (~10^4 students). As part of a Massive Open Online Course (MOOC) in introductory physics offered by Georgia Tech in 2013, students submitted video…
Peer review remains the central quality-control mechanism of science, yet its ability to fulfill this role is increasingly strained. Empirical studies document serious shortcomings: long publication delays, escalating reviewer burden…
Peer learning is a novel high-level reinforcement learning framework for agents learning in groups. While standard reinforcement learning trains an individual agent in trial-and-error fashion, all on its own, peer learning addresses a…
Peer review is a key activity intended to preserve the quality and integrity of scientific publications. However, in practice it is far from perfect. We aim at understanding how reviewers, including those who have won awards for reviewing,…