{"title":"教授不必只是一张漂亮的脸:教员名录如何通过直接提供语义信息来减少偏见的机会并更好地支持用户","authors":"Frank E Ritter, Aidan C Engleka","doi":"10.1093/iwc/iwad053","DOIUrl":null,"url":null,"abstract":"Websites for university units provide lists of faculty (teaching staff) to support a variety of users’ tasks including creating collaborations and student choice for projects and courses. However, these lists often only provide shallow features about the faculty such as pictures and names and not the semantic attributes of expertise, interest, or accomplishments. Prospective students, faculty, parents, donors, and those in the community often cannot directly access these semantic attributes and sometimes not without extensive search. Not having scholarship-focused individual entries leaves the selection process more open for implicit and explicit biases to be applied when searching for areas of expertise—if the website is face-focused (only pictures and names are provided), users can only choose (or choose who to explore further) based solely on name and physical appearance, thus including race, clothing and attractiveness. This paper argues for ease of access to the right information and self-authorship of the public-facing information. We document that this problem is pervasive at universities across the world (n = 275). We suggest good practices for decreasing the prominence of less relevant information to summarize faculty. This is accomplished by increasing the prominence and accessibility of more relevant information, including self-reported research interests and accomplishments. We provide example templates to support more semantic choices that would be applicable to similar organizational lists. This approach could be applied to other sets of professionals, such as doctors and lawyers.","PeriodicalId":50354,"journal":{"name":"Interacting with Computers","volume":"164 1","pages":""},"PeriodicalIF":1.0000,"publicationDate":"2024-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Professors Need Not Be Just a Pretty Face: How Faculty Directories Can Decrease the Opportunity for Bias and Better Support Users by Directly Providing Semantic Information\",\"authors\":\"Frank E Ritter, Aidan C Engleka\",\"doi\":\"10.1093/iwc/iwad053\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Websites for university units provide lists of faculty (teaching staff) to support a variety of users’ tasks including creating collaborations and student choice for projects and courses. However, these lists often only provide shallow features about the faculty such as pictures and names and not the semantic attributes of expertise, interest, or accomplishments. Prospective students, faculty, parents, donors, and those in the community often cannot directly access these semantic attributes and sometimes not without extensive search. Not having scholarship-focused individual entries leaves the selection process more open for implicit and explicit biases to be applied when searching for areas of expertise—if the website is face-focused (only pictures and names are provided), users can only choose (or choose who to explore further) based solely on name and physical appearance, thus including race, clothing and attractiveness. This paper argues for ease of access to the right information and self-authorship of the public-facing information. We document that this problem is pervasive at universities across the world (n = 275). We suggest good practices for decreasing the prominence of less relevant information to summarize faculty. This is accomplished by increasing the prominence and accessibility of more relevant information, including self-reported research interests and accomplishments. We provide example templates to support more semantic choices that would be applicable to similar organizational lists. This approach could be applied to other sets of professionals, such as doctors and lawyers.\",\"PeriodicalId\":50354,\"journal\":{\"name\":\"Interacting with Computers\",\"volume\":\"164 1\",\"pages\":\"\"},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2024-01-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Interacting with Computers\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1093/iwc/iwad053\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, CYBERNETICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Interacting with Computers","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1093/iwc/iwad053","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, CYBERNETICS","Score":null,"Total":0}
Professors Need Not Be Just a Pretty Face: How Faculty Directories Can Decrease the Opportunity for Bias and Better Support Users by Directly Providing Semantic Information
Websites for university units provide lists of faculty (teaching staff) to support a variety of users’ tasks including creating collaborations and student choice for projects and courses. However, these lists often only provide shallow features about the faculty such as pictures and names and not the semantic attributes of expertise, interest, or accomplishments. Prospective students, faculty, parents, donors, and those in the community often cannot directly access these semantic attributes and sometimes not without extensive search. Not having scholarship-focused individual entries leaves the selection process more open for implicit and explicit biases to be applied when searching for areas of expertise—if the website is face-focused (only pictures and names are provided), users can only choose (or choose who to explore further) based solely on name and physical appearance, thus including race, clothing and attractiveness. This paper argues for ease of access to the right information and self-authorship of the public-facing information. We document that this problem is pervasive at universities across the world (n = 275). We suggest good practices for decreasing the prominence of less relevant information to summarize faculty. This is accomplished by increasing the prominence and accessibility of more relevant information, including self-reported research interests and accomplishments. We provide example templates to support more semantic choices that would be applicable to similar organizational lists. This approach could be applied to other sets of professionals, such as doctors and lawyers.
期刊介绍:
Interacting with Computers: The Interdisciplinary Journal of Human-Computer Interaction, is an official publication of BCS, The Chartered Institute for IT and the Interaction Specialist Group .
Interacting with Computers (IwC) was launched in 1987 by interaction to provide access to the results of research in the field of Human-Computer Interaction (HCI) - an increasingly crucial discipline within the Computer, Information, and Design Sciences. Now one of the most highly rated journals in the field, IwC has a strong and growing Impact Factor, and a high ranking and excellent indices (h-index, SNIP, SJR).