Paul Denny, Brett A. Becker, Juho Leinonen, J. Prather
{"title":"聊天溢出:计算机教育的人工智能模型——复兴还是末日?","authors":"Paul Denny, Brett A. Becker, Juho Leinonen, J. Prather","doi":"10.1145/3587102.3588773","DOIUrl":null,"url":null,"abstract":"Recent breakthroughs in deep learning have led to the emergence of generative AI models that exhibit extraordinary performance at producing human-like outputs. Using only simple input prompts, it is possible to generate novel text, images, video, music, and source code, as well as tackle tasks such as answering questions and translating and summarising text. However, the potential for these models to impact computing education practice is only just beginning to be explored. For example, novices learning to code can now use free tools that automatically suggest solutions to programming exercises and assignments; yet these tools were not designed with novices in mind and little to nothing is known about how they will impact learning. Furthermore, much attention has focused on the immediate challenges these models present, such as academic integrity concerns. It seems that even in the AI-era a pending apocalypse sells better than a promising renaissance. Generative AI will likely play an increasing role in people's lives in the reasonably foreseeable future. Model performance seems set to continue accelerating while novel uses and new possibilities multiply. Given this, we should devote just as much effort to identifying and exploiting new opportunities as we do to identifying and mitigating challenges. In this talk, we begin by discussing several concrete and research-backed opportunities for computing educators. Many of these have already shown great promise in positively impacting current practice. We then discuss more short- to medium-term possibilities in areas such as student recruitment, and curricular changes. Finally - against our better judgement - we speculate over the longer-term, including rethinking the very fundamentals of the practice of teaching introductory and advanced computing courses. In these discussions we suggest potential research questions and directions. Although making remotely accurate predictions in such a fast-changing landscape is foolhardy, we believe that now is the time to explore and embrace opportunities to help make positive change in as many computing classrooms as possible.","PeriodicalId":410890,"journal":{"name":"Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 1","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Chat Overflow: Artificially Intelligent Models for Computing Education - renAIssance or apocAIypse?\",\"authors\":\"Paul Denny, Brett A. Becker, Juho Leinonen, J. Prather\",\"doi\":\"10.1145/3587102.3588773\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Recent breakthroughs in deep learning have led to the emergence of generative AI models that exhibit extraordinary performance at producing human-like outputs. Using only simple input prompts, it is possible to generate novel text, images, video, music, and source code, as well as tackle tasks such as answering questions and translating and summarising text. However, the potential for these models to impact computing education practice is only just beginning to be explored. For example, novices learning to code can now use free tools that automatically suggest solutions to programming exercises and assignments; yet these tools were not designed with novices in mind and little to nothing is known about how they will impact learning. Furthermore, much attention has focused on the immediate challenges these models present, such as academic integrity concerns. It seems that even in the AI-era a pending apocalypse sells better than a promising renaissance. Generative AI will likely play an increasing role in people's lives in the reasonably foreseeable future. Model performance seems set to continue accelerating while novel uses and new possibilities multiply. Given this, we should devote just as much effort to identifying and exploiting new opportunities as we do to identifying and mitigating challenges. In this talk, we begin by discussing several concrete and research-backed opportunities for computing educators. Many of these have already shown great promise in positively impacting current practice. We then discuss more short- to medium-term possibilities in areas such as student recruitment, and curricular changes. Finally - against our better judgement - we speculate over the longer-term, including rethinking the very fundamentals of the practice of teaching introductory and advanced computing courses. In these discussions we suggest potential research questions and directions. Although making remotely accurate predictions in such a fast-changing landscape is foolhardy, we believe that now is the time to explore and embrace opportunities to help make positive change in as many computing classrooms as possible.\",\"PeriodicalId\":410890,\"journal\":{\"name\":\"Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 1\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 1\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3587102.3588773\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 1","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3587102.3588773","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Chat Overflow: Artificially Intelligent Models for Computing Education - renAIssance or apocAIypse?
Recent breakthroughs in deep learning have led to the emergence of generative AI models that exhibit extraordinary performance at producing human-like outputs. Using only simple input prompts, it is possible to generate novel text, images, video, music, and source code, as well as tackle tasks such as answering questions and translating and summarising text. However, the potential for these models to impact computing education practice is only just beginning to be explored. For example, novices learning to code can now use free tools that automatically suggest solutions to programming exercises and assignments; yet these tools were not designed with novices in mind and little to nothing is known about how they will impact learning. Furthermore, much attention has focused on the immediate challenges these models present, such as academic integrity concerns. It seems that even in the AI-era a pending apocalypse sells better than a promising renaissance. Generative AI will likely play an increasing role in people's lives in the reasonably foreseeable future. Model performance seems set to continue accelerating while novel uses and new possibilities multiply. Given this, we should devote just as much effort to identifying and exploiting new opportunities as we do to identifying and mitigating challenges. In this talk, we begin by discussing several concrete and research-backed opportunities for computing educators. Many of these have already shown great promise in positively impacting current practice. We then discuss more short- to medium-term possibilities in areas such as student recruitment, and curricular changes. Finally - against our better judgement - we speculate over the longer-term, including rethinking the very fundamentals of the practice of teaching introductory and advanced computing courses. In these discussions we suggest potential research questions and directions. Although making remotely accurate predictions in such a fast-changing landscape is foolhardy, we believe that now is the time to explore and embrace opportunities to help make positive change in as many computing classrooms as possible.