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- Creators: School of Politics and Global Studies
- Creators: Panchanathan, Sethuraman
This thesis/creative project is a guide for other universities to follow in making their campuses more inclusive and accessible via maps. This guide will be offered in different formats (ex – PDF, a website, audio, etc.) to accommodate the disabled community. Hopefully, this guide will serve as inspiration and starting point for universities around the country to better the college experience for all.
Studies have previously found a significant relationship between student writing center usage and demographic factors including gender, GPA, and English-language proficiency (Salem, 2015). Additional research has been conducted on writing center outcomes and student conceptions and misconceptions of writing centers as academic resources. However, previous scholarship has attested to the need for continuous research into writing center usage patterns and the factors that affect them. This will allow centers to make the necessary changes and improvements to become more accessible and inclusive for the benefit of all students. The present research contributes to the ongoing discussion about why students choose to use or not use the writing center and how their identities and pre-existing ideas about the center inform this decision. Further, it addresses research gaps by surveying students in an honors college setting at a large public university and considering new decision-making factors such as race, mental health, and social stigma. By comparing students demographics and impressions of the Barrett Writing Center (BWC) on the ASU campus, the study draws conclusions about the significant gap between positive perception and usage, the influence of social anxiety and stigma amongst honors students, the successes and failures of tutoring for second language English speakers, and the benefit derived by students who attend multiple writing center sessions. Suggestions to improve the BWC and guide future research are offered based on these observations and significant trends in the data.
This dissertation outlines various applications to improve accessibility and independence for visually impaired people during shopping by helping them identify products in retail stores. The dissertation includes the following contributions; (i) A dataset containing images of breakfast-cereal products and a classifier using a deep neural (ResNet) network; (ii) A dataset for training a text detection and scene-text recognition model; (iii) A model for text detection and scene-text recognition to identify product images using a user-controlled camera; (iv) A dataset of twenty thousand products with product information and related images that can be used to train and test a system designed to identify products.
"Access the project here: https://libguides.asu.edu/BeyondBooks"