AI-Written Essays: The Future of Grading?

AI-Written Essays: The Future of Grading?

Table of Contents:

1. Introduction
   1. Background of the Presentation
   2. Purpose of the Presentation
   3. Structure of the Presentation
2. The Landscape of AI in Education
   1. Introduction to Chat GPT
   2. Recent Developments in AI Language Models
   3. Integration of AI in Language Learning Applications
   4. Specialized AI Applications in Academia
3. Vulnerability to AI in Higher Education
   1. The Massification of Higher Education
   2. Time Constraints and Increased Workloads
   3. Vulnerability in EAP Assessment Tasks
4. Rethinking Plagiarism and Cheating
   1. Redefining Plagiarism in a Post-AI World
   2. Distinguishing Assistance from Cheating
   3. The Importance of Writing as a Thinking Process
5. Maintaining the Integrity of Writing and Assessment
   1. Focus on Process Over Product
   2. Fostering Meaningful Feedback and Revision
   3. Communication within the Academic Community
6. A Potential Approach: The Case of XJTLU
   1. Context of XJTLU
   2. Changes in EAP Assessment Practices
   3. Project-Based Learning and Integrated Assessments
7. Conclusion

Article: The Impact of AI and Generative Language Models on Writing and Assessment in Higher Education

Introduction

In today's rapidly evolving technological landscape, the role of artificial intelligence (AI) and generative language models in education has become a subject of intense debate and concern. The emergence of advanced language models like Chat GPT has raised questions about the future of writing and assessment practices in higher education. In this article, we will explore the landscape of AI in education, discuss the vulnerability of higher education institutions to AI, rethink the concepts of plagiarism and cheating in a post-AI world, and propose a potential approach to maintaining the integrity of writing and assessment.

The Landscape of AI in Education

To understand the impact of AI on writing and assessment, it is crucial to examine the Current landscape of AI in education. Chat GPT, a popular generative language model, has garnered Attention for its ability to produce coherent responses to Prompts. Recent developments have seen the release of faster and more reliable language models like GPT4 and BART. Integration of AI in language learning applications, such as Quizlet and Duolingo, has become a trend. Moreover, specialized AI applications targeting researchers and students have emerged, offering tools for literature review, research summary, and academic essay writing.

Vulnerability to AI in Higher Education

Higher education institutions, including EAP (English for Academic Purposes) programs, are vulnerable to the impact of AI on writing and assessment. The massification of higher education has resulted in larger class sizes and increased workloads for academic staff, leaving little time for meaningful engagement with assessment practices. The reliance on traditional written coursework, often focused on basic writing skills, makes EAP modules susceptible to the use of Generative AI tools. The lack of time and resources to provide personalized feedback further exacerbates this vulnerability.

Rethinking Plagiarism and Cheating

The emergence of AI and generative language models necessitates a reevaluation of plagiarism and cheating in academia. The boundaries between AI assistance and AI cheating need to be defined. While AI can assist students in generating content, it also poses a risk of them outsourcing thinking and reflection, which are essential components of the learning process. Writing is more than the end product; it is a means of engaging in critical thinking and problem-solving. As educators, it is crucial to emphasize the importance of the writing process and encourage students to develop their own ideas.

Maintaining the Integrity of Writing and Assessment

To maintain the integrity of writing and assessment, a shift in focus from product to process is necessary. Reducing the weight of written coursework and placing more emphasis on speaking assessments can encourage critical thinking and problem-solving skills. Providing meaningful feedback and revision opportunities can enhance the value of the writing process. Communication within the academic community is vital to ensure a consistent approach towards the adoption of AI Tools and the preservation of academic integrity.

A Potential Approach: The Case of XJTLU

In response to the challenges posed by AI in writing and assessment, XJTLU (Xi'an Jiaotong-Liverpool University) has proposed a potential approach. In their EAP program, they plan to include more analog tests while promoting critical thinking and problem-solving skills. They aim to reduce the weight of written coursework and integrate speaking assessments. Project-based learning will be incorporated to foster language and content integration. The aim is to Align the assessment practices with the expectations of future disciplinary work.

Conclusion

The impact of AI and generative language models on writing and assessment in higher education cannot be ignored. Institutions need to redefine their approach to writing and assessment, considering the changing technological landscape. By maintaining a focus on process, fostering meaningful feedback, and encouraging critical thinking, the integrity of writing and assessment can be preserved. The case of XJTLU provides insights into how EAP programs can adapt their assessment practices to meet the challenges and opportunities posed by AI.

Highlights:

1. The landscape of AI in education has seen the emergence of advanced language models, integration in language learning applications, and specialized AI tools for researchers and students.
2. Higher education institutions are vulnerable to the impact of AI due to the massification of education and time constraints on academic staff.
3. Plagiarism and cheating need to be reexamined in a post-AI world to distinguish between AI assistance and AI cheating.
4. Writing should be seen as a thinking process, and the integrity of writing and assessment can be maintained by focusing on the process, providing meaningful feedback, and engaging in communication within the academic community.
5. XJTLU proposes a potential approach to adapt their EAP program, incorporating more analog tests, project-based learning, and integrated assessments.

FAQ:

Q: How can AI language models assist students in their writing tasks? A: AI language models can assist students by generating coherent responses to prompts, providing a starting point for their writing tasks. However, it is essential for students to develop their own ideas and engage in critical thinking.

Q: What challenges do higher education institutions face in adopting AI in writing and assessment? A: Higher education institutions face challenges such as increased workloads, limited time for personalized feedback, and the need to redefine plagiarism and cheating boundaries in a post-AI world.

Q: How can the integrity of writing and assessment be preserved in the face of AI? A: The integrity of writing and assessment can be preserved by focusing on the process rather than the end product, providing meaningful feedback and revision opportunities, and promoting critical thinking skills. Communication within the academic community is also crucial in determining a consistent approach towards the adoption of AI tools.