{"title":"高等教育中的生成技术--现状评估、基本技能和教学方法建议","authors":"Andrzej Wodecki","doi":"10.15219/em100.1617","DOIUrl":null,"url":null,"abstract":"This article proposes the application of generative technologies, specifically large language models, in higher education. While such technologies present novel opportunities, at the same time, they raise concerns, including potential cognitive degradation, job displacement, and intellectual property issues. The first section of this paper introduces the essential concepts and methods of generative technologies, coupled with a discussion on the necessary competencies to fully harness their potential. The next section suggests an addition to usual teaching methods, using the ‘Artificial Intelligence in Business’ course as an example. This proposed enhancement incorporates a review of student work outcomes by systems powered by large language models. The underlying didactic principles of the course, sample system reports, and an illustrative diagram of the teaching process are presented. The paper concludes by contemplating the possible advantages and challenges posed by these technologies in pedagogy, along with recommendations for future research.","PeriodicalId":42136,"journal":{"name":"E-Mentor","volume":"253 23","pages":""},"PeriodicalIF":0.2000,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Generative technologies in higher education – assessment of the current state, essential skills, and a proposal for a didactic method\",\"authors\":\"Andrzej Wodecki\",\"doi\":\"10.15219/em100.1617\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article proposes the application of generative technologies, specifically large language models, in higher education. While such technologies present novel opportunities, at the same time, they raise concerns, including potential cognitive degradation, job displacement, and intellectual property issues. The first section of this paper introduces the essential concepts and methods of generative technologies, coupled with a discussion on the necessary competencies to fully harness their potential. The next section suggests an addition to usual teaching methods, using the ‘Artificial Intelligence in Business’ course as an example. This proposed enhancement incorporates a review of student work outcomes by systems powered by large language models. The underlying didactic principles of the course, sample system reports, and an illustrative diagram of the teaching process are presented. The paper concludes by contemplating the possible advantages and challenges posed by these technologies in pedagogy, along with recommendations for future research.\",\"PeriodicalId\":42136,\"journal\":{\"name\":\"E-Mentor\",\"volume\":\"253 23\",\"pages\":\"\"},\"PeriodicalIF\":0.2000,\"publicationDate\":\"2023-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"E-Mentor\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.15219/em100.1617\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"EDUCATION & EDUCATIONAL RESEARCH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"E-Mentor","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15219/em100.1617","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"EDUCATION & EDUCATIONAL RESEARCH","Score":null,"Total":0}
Generative technologies in higher education – assessment of the current state, essential skills, and a proposal for a didactic method
This article proposes the application of generative technologies, specifically large language models, in higher education. While such technologies present novel opportunities, at the same time, they raise concerns, including potential cognitive degradation, job displacement, and intellectual property issues. The first section of this paper introduces the essential concepts and methods of generative technologies, coupled with a discussion on the necessary competencies to fully harness their potential. The next section suggests an addition to usual teaching methods, using the ‘Artificial Intelligence in Business’ course as an example. This proposed enhancement incorporates a review of student work outcomes by systems powered by large language models. The underlying didactic principles of the course, sample system reports, and an illustrative diagram of the teaching process are presented. The paper concludes by contemplating the possible advantages and challenges posed by these technologies in pedagogy, along with recommendations for future research.