The AI generation gap: Are Gen Z students more interested in adopting
generative AI such as ChatGPT in teaching and learning than their Gen X and
Millennial Generation teachers?
- URL: http://arxiv.org/abs/2305.02878v1
- Date: Thu, 4 May 2023 14:42:06 GMT
- Title: The AI generation gap: Are Gen Z students more interested in adopting
generative AI such as ChatGPT in teaching and learning than their Gen X and
Millennial Generation teachers?
- Authors: Cecilia Ka Yuk Chan, Katherine K. W. Lee
- Abstract summary: Gen Z students were generally optimistic about the potential benefits of generative AI (GenAI)
Gen X and Gen Y teachers expressed heightened concerns about overreliance, ethical and pedagogical implications.
- Score: 0.0
- License: http://creativecommons.org/licenses/by-nc-sa/4.0/
- Abstract: This study aimed to explore the experiences, perceptions, knowledge,
concerns, and intentions of Gen Z students with Gen X and Gen Y teachers
regarding the use of generative AI (GenAI) in higher education. A sample of
students and teachers were recruited to investigate the above using a survey
consisting of both open and closed questions. The findings showed that Gen Z
participants were generally optimistic about the potential benefits of GenAI,
including enhanced productivity, efficiency, and personalized learning, and
expressed intentions to use GenAI for various educational purposes. Gen X and
Gen Y teachers acknowledged the potential benefits of GenAI but expressed
heightened concerns about overreliance, ethical and pedagogical implications,
emphasizing the need for proper guidelines and policies to ensure responsible
use of the technology. The study highlighted the importance of combining
technology with traditional teaching methods to provide a more effective
learning experience. Implications of the findings include the need to develop
evidence-based guidelines and policies for GenAI integration, foster critical
thinking and digital literacy skills among students, and promote responsible
use of GenAI technologies in higher education.
Related papers
- Model-based Maintenance and Evolution with GenAI: A Look into the Future [47.93555901495955]
We argue that Generative Artificial Intelligence (GenAI) can be used as a means to address the limitations of Model-Based Engineering (MBM&E)
We propose that GenAI can be used in MBM&E for: reducing engineers' learning curve, maximizing efficiency with recommendations, or serving as a reasoning tool to understand domain problems.
arXiv Detail & Related papers (2024-07-09T23:13:26Z) - Teacher agency in the age of generative AI: towards a framework of hybrid intelligence for learning design [0.0]
Generative AI (genAI) is being used in education for different purposes.
From the teachers' perspective, genAI can support activities such as learning design.
However, GenAI has the potential to negatively affect professional agency due to teachers' limited power.
arXiv Detail & Related papers (2024-07-09T08:28:05Z) - Understanding Student and Academic Staff Perceptions of AI Use in Assessment and Feedback [0.0]
The rise of Artificial Intelligence (AI) and Generative Artificial Intelligence (GenAI) in higher education necessitates assessment reform.
This study addresses a critical gap by exploring student and academic staff experiences with AI and GenAI tools.
An online survey collected data from 35 academic staff and 282 students across two universities in Vietnam and one in Singapore.
arXiv Detail & Related papers (2024-06-22T10:25:01Z) - Generative AI as a Learning Buddy and Teaching Assistant: Pre-service Teachers' Uses and Attitudes [0.8566597970144211]
We surveyed 167 Ghana PSTs' specific uses of generative artificial intelligence (GenAI) applications.
We identified three key factors shaping PSTs' attitudes towards GenAI: teaching, learning, and ethical and advocacy factors.
PSTs expressed concerns about the accuracy and trustworthiness of the information provided by GenAI applications.
arXiv Detail & Related papers (2024-06-03T20:38:29Z) - Securing the Future of GenAI: Policy and Technology [50.586585729683776]
Governments globally are grappling with the challenge of regulating GenAI, balancing innovation against safety.
A workshop co-organized by Google, University of Wisconsin, Madison, and Stanford University aimed to bridge this gap between GenAI policy and technology.
This paper summarizes the discussions during the workshop which addressed questions, such as: How regulation can be designed without hindering technological progress?
arXiv Detail & Related papers (2024-05-21T20:30:01Z) - Genetic Auto-prompt Learning for Pre-trained Code Intelligence Language Models [54.58108387797138]
We investigate the effectiveness of prompt learning in code intelligence tasks.
Existing automatic prompt design methods are very limited to code intelligence tasks.
We propose Genetic Auto Prompt (GenAP) which utilizes an elaborate genetic algorithm to automatically design prompts.
arXiv Detail & Related papers (2024-03-20T13:37:00Z) - Bringing Generative AI to Adaptive Learning in Education [58.690250000579496]
We shed light on the intersectional studies of generative AI and adaptive learning.
We argue that this union will contribute significantly to the development of the next-stage learning format in education.
arXiv Detail & Related papers (2024-02-02T23:54:51Z) - Exploring Parent's Needs for Children-Centered AI to Support
Preschoolers' Storytelling and Reading Activities [54.8155184348616]
New advances in artificial intelligence have sparked a surge of AI-based storytelling technologies.
This paper investigates how they function in practical storytelling scenarios and how parents, the most critical stakeholders, experience and perceive them.
Our findings suggest that even though AI-based storytelling technologies provide more immersive and engaging interaction, they still cannot meet parents' expectations.
arXiv Detail & Related papers (2024-01-24T20:55:40Z) - Identifying and Mitigating the Security Risks of Generative AI [179.2384121957896]
This paper reports the findings of a workshop held at Google on the dual-use dilemma posed by GenAI.
GenAI can be used just as well by attackers to generate new attacks and increase the velocity and efficacy of existing attacks.
We discuss short-term and long-term goals for the community on this topic.
arXiv Detail & Related papers (2023-08-28T18:51:09Z) - Innovating Computer Programming Pedagogy: The AI-Lab Framework for
Generative AI Adoption [0.0]
We introduce "AI-Lab," a framework for guiding students in effectively leveraging GenAI within core programming courses.
By identifying and rectifying GenAI's errors, students enrich their learning process.
For educators, AI-Lab provides mechanisms to explore students' perceptions of GenAI's role in their learning experience.
arXiv Detail & Related papers (2023-08-23T17:20:37Z) - Students' Voices on Generative AI: Perceptions, Benefits, and Challenges
in Higher Education [2.0711789781518752]
This study explores university students' perceptions of generative AI (GenAI) technologies, such as ChatGPT, in higher education.
Students recognized the potential for personalized learning support, writing and brainstorming assistance, and research and analysis capabilities.
Concerns about accuracy, privacy, ethical issues, and the impact on personal development, career prospects, and societal values were also expressed.
arXiv Detail & Related papers (2023-04-29T15:53:38Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.