{"title":"学生能从错误代码中学到更多吗?在无错误与全错误的SAS®编程环境中探索学生的表现和满意度","authors":"H. Hoffman, Angelo F. Elmi","doi":"10.1080/26939169.2021.1967229","DOIUrl":null,"url":null,"abstract":"Abstract Teaching students statistical programming languages while simultaneously teaching them how to debug erroneous code is challenging. The traditional programming course focuses on error-free learning in class while students’ experiences outside of class typically involve error-full learning. While error-free teaching consists of focused lectures emphasizing correct coding, error-full teaching would follow such lectures with debugging sessions. We aimed to explore these two approaches by conducting a pilot study of 18 graduate students who voluntarily attended a SAS programming seminar held weekly from September 2018 through November 2018. Each seminar had a 10-min error-free lecture, 15-min programming assignment, 5-min break, 10-min error-full lecture, and 15-min programming assignment. We examined student performance and preference. While four students successfully completed both assignments and ten students did not successfully complete either assignment, one student successfully completed only the first assignment that directly followed the error-free lecture and three students successfully completed only the second assignment that directly followed the error-full lecture. Of the 15 students who responded, twelve (80%) preferred error-full to error-free learning. We will evaluate error-full learning on a larger scale in an introductory SAS course. Supplemental files are available online for this article.","PeriodicalId":34851,"journal":{"name":"Journal of Statistics and Data Science Education","volume":"29 1","pages":"228 - 240"},"PeriodicalIF":1.5000,"publicationDate":"2021-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Do Students Learn More from Erroneous Code? Exploring Student Performance and Satisfaction in an Error-Free Versus an Error-full SAS® Programming Environment\",\"authors\":\"H. Hoffman, Angelo F. Elmi\",\"doi\":\"10.1080/26939169.2021.1967229\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract Teaching students statistical programming languages while simultaneously teaching them how to debug erroneous code is challenging. The traditional programming course focuses on error-free learning in class while students’ experiences outside of class typically involve error-full learning. While error-free teaching consists of focused lectures emphasizing correct coding, error-full teaching would follow such lectures with debugging sessions. We aimed to explore these two approaches by conducting a pilot study of 18 graduate students who voluntarily attended a SAS programming seminar held weekly from September 2018 through November 2018. Each seminar had a 10-min error-free lecture, 15-min programming assignment, 5-min break, 10-min error-full lecture, and 15-min programming assignment. We examined student performance and preference. While four students successfully completed both assignments and ten students did not successfully complete either assignment, one student successfully completed only the first assignment that directly followed the error-free lecture and three students successfully completed only the second assignment that directly followed the error-full lecture. Of the 15 students who responded, twelve (80%) preferred error-full to error-free learning. We will evaluate error-full learning on a larger scale in an introductory SAS course. Supplemental files are available online for this article.\",\"PeriodicalId\":34851,\"journal\":{\"name\":\"Journal of Statistics and Data Science Education\",\"volume\":\"29 1\",\"pages\":\"228 - 240\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2021-09-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Statistics and Data Science Education\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/26939169.2021.1967229\",\"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/10.1080/26939169.2021.1967229","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"EDUCATION, SCIENTIFIC DISCIPLINES","Score":null,"Total":0}
Do Students Learn More from Erroneous Code? Exploring Student Performance and Satisfaction in an Error-Free Versus an Error-full SAS® Programming Environment
Abstract Teaching students statistical programming languages while simultaneously teaching them how to debug erroneous code is challenging. The traditional programming course focuses on error-free learning in class while students’ experiences outside of class typically involve error-full learning. While error-free teaching consists of focused lectures emphasizing correct coding, error-full teaching would follow such lectures with debugging sessions. We aimed to explore these two approaches by conducting a pilot study of 18 graduate students who voluntarily attended a SAS programming seminar held weekly from September 2018 through November 2018. Each seminar had a 10-min error-free lecture, 15-min programming assignment, 5-min break, 10-min error-full lecture, and 15-min programming assignment. We examined student performance and preference. While four students successfully completed both assignments and ten students did not successfully complete either assignment, one student successfully completed only the first assignment that directly followed the error-free lecture and three students successfully completed only the second assignment that directly followed the error-full lecture. Of the 15 students who responded, twelve (80%) preferred error-full to error-free learning. We will evaluate error-full learning on a larger scale in an introductory SAS course. Supplemental files are available online for this article.