{"title":"Integrating Computational Data Science in University Curriculum for the New Generation of Scientists","authors":"N. Renu, K. Sunil","doi":"10.1177/23476311231183204","DOIUrl":null,"url":null,"abstract":"Integration of computational data science (CDS) into the university curriculum offers several advantages for students, faculty and the institution. This article discusses the benefits to students of introducing CDS into the university curriculum with a focus on developing skills in cheminformatics, data analysis, structure–activity relationships, modelling and simulation. Moreover, CDS can enable students to engage with complex chemical and toxicological data in new and dynamic ways, helping them to develop a more nuanced understanding of the potential hazards and risks associated with different chemicals and substances. On the other hand, it can foster greater collaboration between students and faculty and with external partners in industry and government. This can lead to the development of more effective and efficient toxicological testing methods and tools to screen chemicals for potential hazards and aid the development of environmentally friendly chemicals. Overall, the integration of CDS into the university curriculum will help prepare the next generation of scientists giving them a competitive edge to make considerable contributions to green chemistry, designing safer chemicals and non-animal testing methods. It will enable them to tackle modern challenges facing society including identifying safer and more sustainable chemicals and predicting the health and environmental impacts of novel chemical substances.","PeriodicalId":36834,"journal":{"name":"Higher Education for the Future","volume":"10 1","pages":"183 - 195"},"PeriodicalIF":0.0000,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Higher Education for the Future","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/23476311231183204","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Social Sciences","Score":null,"Total":0}
引用次数: 0
Abstract
Integration of computational data science (CDS) into the university curriculum offers several advantages for students, faculty and the institution. This article discusses the benefits to students of introducing CDS into the university curriculum with a focus on developing skills in cheminformatics, data analysis, structure–activity relationships, modelling and simulation. Moreover, CDS can enable students to engage with complex chemical and toxicological data in new and dynamic ways, helping them to develop a more nuanced understanding of the potential hazards and risks associated with different chemicals and substances. On the other hand, it can foster greater collaboration between students and faculty and with external partners in industry and government. This can lead to the development of more effective and efficient toxicological testing methods and tools to screen chemicals for potential hazards and aid the development of environmentally friendly chemicals. Overall, the integration of CDS into the university curriculum will help prepare the next generation of scientists giving them a competitive edge to make considerable contributions to green chemistry, designing safer chemicals and non-animal testing methods. It will enable them to tackle modern challenges facing society including identifying safer and more sustainable chemicals and predicting the health and environmental impacts of novel chemical substances.