Margo Glantz, Jennifer Johnson, Marilyn Macy, Juan Nunez, Rachel Saidi, Camilo Velez Ramirez
{"title":"两年制大学数据科学课程的学生经验和观点","authors":"Margo Glantz, Jennifer Johnson, Marilyn Macy, Juan Nunez, Rachel Saidi, Camilo Velez Ramirez","doi":"10.1080/26939169.2023.2208185","DOIUrl":null,"url":null,"abstract":"Abstract Two-year colleges provide the opportunity for students of all ages to try new subjects, change careers, upskill, or begin exploring higher education, at affordable rates. Many might begin their exploration by taking a course at a local two-year college. Currently, not many of these institutions in the U.S. offer data science courses. This article introduces the perspective lens of students who have gone through the Montgomery College Data Science Certificate Program. We found that, contrary to many other educational fields at the College, data science students tend to come from diverse backgrounds and career paths. A common theme emerged that all students learned valuable skills and applications such as coding in various programming languages and approaches to machine learning. Other meaningful themes included an appreciation of course accessibility, especially catered toward busy professionals who might only be able to take evening courses. Students appreciated learning that data science and ethics are intertwined. Finally, it was evident that going through the data science program positively impacted the lives and careers of these students. The implications of the themes of these student experiences are discussed as they relate to data science education. Supplementary materials for this article are available online.","PeriodicalId":34851,"journal":{"name":"Journal of Statistics and Data Science Education","volume":null,"pages":null},"PeriodicalIF":1.5000,"publicationDate":"2023-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Students' Experience and Perspective of a Data Science Program in a Two-Year College\",\"authors\":\"Margo Glantz, Jennifer Johnson, Marilyn Macy, Juan Nunez, Rachel Saidi, Camilo Velez Ramirez\",\"doi\":\"10.1080/26939169.2023.2208185\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract Two-year colleges provide the opportunity for students of all ages to try new subjects, change careers, upskill, or begin exploring higher education, at affordable rates. Many might begin their exploration by taking a course at a local two-year college. Currently, not many of these institutions in the U.S. offer data science courses. This article introduces the perspective lens of students who have gone through the Montgomery College Data Science Certificate Program. We found that, contrary to many other educational fields at the College, data science students tend to come from diverse backgrounds and career paths. A common theme emerged that all students learned valuable skills and applications such as coding in various programming languages and approaches to machine learning. Other meaningful themes included an appreciation of course accessibility, especially catered toward busy professionals who might only be able to take evening courses. Students appreciated learning that data science and ethics are intertwined. Finally, it was evident that going through the data science program positively impacted the lives and careers of these students. The implications of the themes of these student experiences are discussed as they relate to data science education. Supplementary materials for this article are available online.\",\"PeriodicalId\":34851,\"journal\":{\"name\":\"Journal of Statistics and Data Science Education\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2023-04-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Statistics and Data Science Education\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/26939169.2023.2208185\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"EDUCATION, SCIENTIFIC DISCIPLINES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Statistics and Data Science Education","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/26939169.2023.2208185","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"EDUCATION, SCIENTIFIC DISCIPLINES","Score":null,"Total":0}
Students' Experience and Perspective of a Data Science Program in a Two-Year College
Abstract Two-year colleges provide the opportunity for students of all ages to try new subjects, change careers, upskill, or begin exploring higher education, at affordable rates. Many might begin their exploration by taking a course at a local two-year college. Currently, not many of these institutions in the U.S. offer data science courses. This article introduces the perspective lens of students who have gone through the Montgomery College Data Science Certificate Program. We found that, contrary to many other educational fields at the College, data science students tend to come from diverse backgrounds and career paths. A common theme emerged that all students learned valuable skills and applications such as coding in various programming languages and approaches to machine learning. Other meaningful themes included an appreciation of course accessibility, especially catered toward busy professionals who might only be able to take evening courses. Students appreciated learning that data science and ethics are intertwined. Finally, it was evident that going through the data science program positively impacted the lives and careers of these students. The implications of the themes of these student experiences are discussed as they relate to data science education. Supplementary materials for this article are available online.