The Affordances and Contradictions of AI-Generated Text for Second Language Writers

Warschauer, Mark; Tseng, Waverly; Soobin, Yim; Webster, Thomas J.; Jacob, Sharin; Du, Qian; Tate, Tamara

doi:10.2139/ssrn.4404380

Cited by 29 publications

(11 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Kumar's (2023) analysis of AI-generated responses to academic writing prompts shows that the text output, although mostly original and relevant to the topics, contained inappropriate references and lacked personal perspectives that AI is generally incapable of producing. For second language learners, constructing appropriate prompts poses a challenge in itself as it requires a certain level of linguistic skills; and overreliance on GenAI tools may compromise students' genuine efforts to develop writing competence (Warschauer et al, 2023). In addition, the content produced by GenAI may be biased, inaccurate, or harmful if the dataset on which a model was trained contains such elements (Harrer, 2023).…”

Section: Benefits and Challenges Of Using Generative Ai In Higher Edu...mentioning

confidence: 99%

Students’ voices on generative AI: perceptions, benefits, and challenges in higher education

Chan

2023

Int J Educ Technol High Educ

186

View full text Add to dashboard Cite

This study explores university students’ perceptions of generative AI (GenAI) technologies, such as ChatGPT, in higher education, focusing on familiarity, their willingness to engage, potential benefits and challenges, and effective integration. A survey of 399 undergraduate and postgraduate students from various disciplines in Hong Kong revealed a generally positive attitude towards GenAI in teaching and learning. Students recognized the potential for personalized learning support, writing and brainstorming assistance, and research and analysis capabilities. However, concerns about accuracy, privacy, ethical issues, and the impact on personal development, career prospects, and societal values were also expressed. According to John Biggs’ 3P model, student perceptions significantly influence learning approaches and outcomes. By understanding students’ perceptions, educators and policymakers can tailor GenAI technologies to address needs and concerns while promoting effective learning outcomes. Insights from this study can inform policy development around the integration of GenAI technologies into higher education. By understanding students’ perceptions and addressing their concerns, policymakers can create well-informed guidelines and strategies for the responsible and effective implementation of GenAI tools, ultimately enhancing teaching and learning experiences in higher education.

show abstract

Section: Benefits and Challenges Of Using Generative Ai In Higher Edu...mentioning

confidence: 99%

Students’ voices on generative AI: perceptions, benefits, and challenges in higher education

Chan

2023

Int J Educ Technol High Educ

186

View full text Add to dashboard Cite

show abstract

“…Another concern is that the use of generative AI may lead to a decline in students' writing and critical thinking skills (Civil, 2023;Warschauer et al, 2023), as they become more reliant on automated tools to complete their work. Some academics argue that this could have a negative impact on the quality of education and ultimately harm the students' learning outcomes (Chan & Lee, 2023;Korn & Kelly, 2023;Oliver, 2023;Zhai, 2022).…”

Section: Introductionmentioning

confidence: 99%

A comprehensive AI policy education framework for university teaching and learning

Chan

2023

Int J Educ Technol High Educ

190

View full text Add to dashboard Cite

This study aims to develop an AI education policy for higher education by examining the perceptions and implications of text generative AI technologies. Data was collected from 457 students and 180 teachers and staff across various disciplines in Hong Kong universities, using both quantitative and qualitative research methods. Based on the findings, the study proposes an AI Ecological Education Policy Framework to address the multifaceted implications of AI integration in university teaching and learning. This framework is organized into three dimensions: Pedagogical, Governance, and Operational. The Pedagogical dimension concentrates on using AI to improve teaching and learning outcomes, while the Governance dimension tackles issues related to privacy, security, and accountability. The Operational dimension addresses matters concerning infrastructure and training. The framework fosters a nuanced understanding of the implications of AI integration in academic settings, ensuring that stakeholders are aware of their responsibilities and can take appropriate actions accordingly.

show abstract

“…Another issue is that, as students become increasingly dependent on automated tools to complete their work, the usage of generative AI may result in deterioration in their writing and critical thinking abilities (Warschauer et al, 2023). According to some researchers, this might have a detrimental effect on educational quality and eventually affect students' learning outcomes (Chan, 2023;Chan & Lee, 2023;Zhai, 2022).…”

Section: Technological Implementation and Challengesmentioning

confidence: 99%

E-learning & Artificial Intelligence

2023

E-Learning

View full text Add to dashboard Cite

Great Britain reflect on E-learning & Artificial Intelligence, e-learning in the time of COVID-19 pandemic and after this time, presented research results, contemporary trends and scientific and educational project devoted to MOOCs, artificial intelligence (AI), augmented reality (AR), virtual reality (VR), selected Web 2.0 and Web 3.0 technologies, LMS, CMS, STEAM, mobile learning and other topics.

show abstract

The Affordances and Contradictions of AI-Generated Text for Second Language Writers

Cited by 29 publications

References 27 publications

Students’ voices on generative AI: perceptions, benefits, and challenges in higher education

Students’ voices on generative AI: perceptions, benefits, and challenges in higher education

A comprehensive AI policy education framework for university teaching and learning

E-learning & Artificial Intelligence

Contact Info

Product

Resources

About