{"title":"探索学生和人工智能生成的文本:对反思文本的思考","authors":"Marcia Håkansson Lindqvist, Catarina Arvidsson","doi":"10.34190/ejel.22.6.3473","DOIUrl":null,"url":null,"abstract":"As pointed out by many scholars, Artificial Intelligence (AI) provides both opportunities and challenges in regard to assignments and examination in higher education. The accessibility and use of AI in regard to student assignments, examinations and assessments places demands on teachers’ work in course design and formats of assignments and examination. For teachers, this work is a constant and continuous process, in line with the Scholarship of Teaching and Learning (SoTL) according to Boyer (1991). In order to meet these new demands, teachers need to reflect upon design, as reflective practitioners (Schön, 1987). Reflective design may alleviate the challenges with AI as well as make use of the opportunities with the use of AI. In this paper there are two sets of data. This study aspires to contribute to the current state of AI (ChatGPT) as it is applied in higher education through an empirical study of authentic reflection texts by students in comparison to AI (ChatGPT) generated texts. The first set of data is authentic reflection texts (N=20) written by students. The second set of data is texts generated by AI (ChatGPT). The texts are analysed using reflective thematic analysis (Braun & Clarke, 2019). The themes in the two sets of texts are described, analysed and compared. The two sets of data are then explored, analysed and compared to highlight similarities and differences between the authentic texts and the texts generated by AI. These insights may provide support for teachers in regard to the design of assignments and examinations as well as the practical use of AI (ChatGPT) in higher education.","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":"23 2","pages":""},"PeriodicalIF":4.6000,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Exploring Student and AI Generated Texts: Reflections on Reflection Texts\",\"authors\":\"Marcia Håkansson Lindqvist, Catarina Arvidsson\",\"doi\":\"10.34190/ejel.22.6.3473\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As pointed out by many scholars, Artificial Intelligence (AI) provides both opportunities and challenges in regard to assignments and examination in higher education. The accessibility and use of AI in regard to student assignments, examinations and assessments places demands on teachers’ work in course design and formats of assignments and examination. For teachers, this work is a constant and continuous process, in line with the Scholarship of Teaching and Learning (SoTL) according to Boyer (1991). In order to meet these new demands, teachers need to reflect upon design, as reflective practitioners (Schön, 1987). Reflective design may alleviate the challenges with AI as well as make use of the opportunities with the use of AI. In this paper there are two sets of data. This study aspires to contribute to the current state of AI (ChatGPT) as it is applied in higher education through an empirical study of authentic reflection texts by students in comparison to AI (ChatGPT) generated texts. The first set of data is authentic reflection texts (N=20) written by students. The second set of data is texts generated by AI (ChatGPT). The texts are analysed using reflective thematic analysis (Braun & Clarke, 2019). The themes in the two sets of texts are described, analysed and compared. The two sets of data are then explored, analysed and compared to highlight similarities and differences between the authentic texts and the texts generated by AI. These insights may provide support for teachers in regard to the design of assignments and examinations as well as the practical use of AI (ChatGPT) in higher education.\",\"PeriodicalId\":2,\"journal\":{\"name\":\"ACS Applied Bio Materials\",\"volume\":\"23 2\",\"pages\":\"\"},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2024-08-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Bio Materials\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.34190/ejel.22.6.3473\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MATERIALS SCIENCE, BIOMATERIALS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.34190/ejel.22.6.3473","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
Exploring Student and AI Generated Texts: Reflections on Reflection Texts
As pointed out by many scholars, Artificial Intelligence (AI) provides both opportunities and challenges in regard to assignments and examination in higher education. The accessibility and use of AI in regard to student assignments, examinations and assessments places demands on teachers’ work in course design and formats of assignments and examination. For teachers, this work is a constant and continuous process, in line with the Scholarship of Teaching and Learning (SoTL) according to Boyer (1991). In order to meet these new demands, teachers need to reflect upon design, as reflective practitioners (Schön, 1987). Reflective design may alleviate the challenges with AI as well as make use of the opportunities with the use of AI. In this paper there are two sets of data. This study aspires to contribute to the current state of AI (ChatGPT) as it is applied in higher education through an empirical study of authentic reflection texts by students in comparison to AI (ChatGPT) generated texts. The first set of data is authentic reflection texts (N=20) written by students. The second set of data is texts generated by AI (ChatGPT). The texts are analysed using reflective thematic analysis (Braun & Clarke, 2019). The themes in the two sets of texts are described, analysed and compared. The two sets of data are then explored, analysed and compared to highlight similarities and differences between the authentic texts and the texts generated by AI. These insights may provide support for teachers in regard to the design of assignments and examinations as well as the practical use of AI (ChatGPT) in higher education.
期刊介绍:
ACS Applied Bio Materials is an interdisciplinary journal publishing original research covering all aspects of biomaterials and biointerfaces including and beyond the traditional biosensing, biomedical and therapeutic applications.
The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrates knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important bio applications. The journal is specifically interested in work that addresses the relationship between structure and function and assesses the stability and degradation of materials under relevant environmental and biological conditions.