%0 Generic %1 kasneci2023chatgpt %A Kasneci, Enkelejda %A Seßler, Kathrin %A Küchemann, Stefan %A Bannert, Maria %A Dementieva, Daryna %A Fischer, Frank %A Gasser, Urs %A Groh, Georg %A Günnemann, Stephan %A Hüllermeier, Eyke %A Krusche, Stephan %A Kutyniok, Gitta %A Michaeli, Tilman %A Nerdel, Claudia %A Pfeffer, Jürgen %A Poquet, Oleksandra %A Sailer, Michael %A Schmidt, Albrecht %A Seidel, Tina %A Stadler, Matthias %A Weller, Jochen %A Kuhn, Jochen %A Kasneci, Gjergji %D 2023 %I Center for Open Science %K ChatGPT artificial_intelligence education educational_technologies large_language_models %R 10.35542/osf.io/5er8f %T ChatGPT for Good? On Opportunities and Challenges of Large Language Models for Education %U https://doi.org/10.35542%2Fosf.io%2F5er8f %X Large language models represent a significant advancement in the field of AI. The underlying technology is key to further innovations and, despite critical views and even bans within communities and regions, large language models are here to stay. This position paper presents the potential benefits and challenges of educational applications of large language models, from student and teacher perspectives. We briefly discuss the current state of large language models and their applications. We then highlight how these models can be used to create educational content, improve student engagement and interaction, and personalize learning experiences. With regard to challenges, we argue that large language models in education require teachers and learners to develop sets of competencies and literacies necessary to both understand the technology as well as their limitations and unexpected brittleness of such systems. In addition, a clear strategy within educational systems and a clear pedagogical approach with a strong focus on critical thinking and strategies for fact checking are required to integrate and take full advantage of large language models in learning settings and teaching curricula. Other challenges such as the potential bias in the output, the need for continuous human oversight, and the potential for misuse are not unique to the application of AI in education. But we believe that, if handled sensibly, these challenges can offer insights and opportunities in education scenarios to acquaint students early on with potential societal biases, criticalities, and risks of AI applications. We conclude with recommendations for how to address these challenges and ensure that such models are used in a responsible and ethical manner in education.

@misc{kasneci2023chatgpt, abstract = {Large language models represent a significant advancement in the field of AI. The underlying technology is key to further innovations and, despite critical views and even bans within communities and regions, large language models are here to stay. This position paper presents the potential benefits and challenges of educational applications of large language models, from student and teacher perspectives. We briefly discuss the current state of large language models and their applications. We then highlight how these models can be used to create educational content, improve student engagement and interaction, and personalize learning experiences. With regard to challenges, we argue that large language models in education require teachers and learners to develop sets of competencies and literacies necessary to both understand the technology as well as their limitations and unexpected brittleness of such systems. In addition, a clear strategy within educational systems and a clear pedagogical approach with a strong focus on critical thinking and strategies for fact checking are required to integrate and take full advantage of large language models in learning settings and teaching curricula. Other challenges such as the potential bias in the output, the need for continuous human oversight, and the potential for misuse are not unique to the application of AI in education. But we believe that, if handled sensibly, these challenges can offer insights and opportunities in education scenarios to acquaint students early on with potential societal biases, criticalities, and risks of AI applications. We conclude with recommendations for how to address these challenges and ensure that such models are used in a responsible and ethical manner in education.}, added-at = {2023-02-08T17:26:17.000+0100}, author = {Kasneci, Enkelejda and Se{\ss}ler, Kathrin and Küchemann, Stefan and Bannert, Maria and Dementieva, Daryna and Fischer, Frank and Gasser, Urs and Groh, Georg and Günnemann, Stephan and Hüllermeier, Eyke and Krusche, Stephan and Kutyniok, Gitta and Michaeli, Tilman and Nerdel, Claudia and Pfeffer, Jürgen and Poquet, Oleksandra and Sailer, Michael and Schmidt, Albrecht and Seidel, Tina and Stadler, Matthias and Weller, Jochen and Kuhn, Jochen and Kasneci, Gjergji}, biburl = {https://www.bibsonomy.org/bibtex/2f8ed57738c288b3b540a23a6d167f1fc/meneteqel}, doi = {10.35542/osf.io/5er8f}, howpublished = {EdArXiv}, interhash = {dfd07aa8fefafc40b65d0939387b52fa}, intrahash = {f8ed57738c288b3b540a23a6d167f1fc}, keywords = {ChatGPT artificial_intelligence education educational_technologies large_language_models}, language = {en}, month = jan, publisher = {Center for Open Science}, timestamp = {2023-02-08T17:26:17.000+0100}, title = {{ChatGPT} for Good? On Opportunities and Challenges of Large Language Models for Education}, url = {https://doi.org/10.35542%2Fosf.io%2F5er8f}, year = 2023 }