Jash Shah

h-index6
2papers
176citations

2 Papers

CYJun 13
Students' Perceptions of Peer Grading

Uchswas Paul, Jash Shah, Keira McArthur et al.

Peer grading is widely used in education, yet it elicits mixed reactions from educators and students. Although many studies have examined students' views of peer grading, their findings are scattered, and no clear overall picture has emerged. To address this gap, we conducted a mixed-source thematic analysis of literature and student discussions on Reddit. To scale the Reddit data analysis, we fine-tuned a Gemini 2.5 text-classification model and used it as an initial relevance filter for our initially retrieved dataset of 659 posts and 6,607 comments, after which the items predicted as relevant were manually reviewed. The study synthesized evidence from 107 papers, 114 Reddit posts, and 300 comments. The findings show that students view peer grading as both beneficial and problematic. Positive perceptions included learning and understanding benefits, skill development, engagement, and collaboration, while negative perceptions centered on unreliable grading, unfairness, weak feedback quality, emotional stress, and workload. Reddit discussions also suggested an emerging concern that remains underexplored in the literature: AI use in peer grading may weaken students' trust in the accuracy and authenticity of the process. We further identified eight mitigation strategies and mapped them to the negative perceptions they help address. Among these, instructor oversight and training played the most central role.

1.4CVFeb 23, 2022
A Method for Waste Segregation using Convolutional Neural Networks

Jash Shah, Sagar Kamat

Segregation of garbage is a primary concern in many nations across the world. Even though we are in the modern era, many people still do not know how to distinguish between organic and recyclable waste. It is because of this that the world is facing a major crisis of waste disposal. In this paper, we try to use deep learning algorithms to help solve this problem of waste classification. The waste is classified into two categories like organic and recyclable. Our proposed model achieves an accuracy of 94.9%. Although the other two models also show promising results, the Proposed Model stands out with the greatest accuracy. With the help of deep learning, one of the greatest obstacles to efficient waste management can finally be removed.