Exploring ChatGPT and Other Generative Tools in the Adult Classroom

By Lilian H. Hill

 

Generative AI (GenAI) tools like ChatGPT, DALL-E, or Co-Pilot are quickly becoming part of the everyday digital landscape. Generative AI refers to systems that can produce new content: text, images, audio, video—based on patterns learned from vast datasets. Tools like ChatGPT, Claude, Gemini, and DALL·E can generate human-like responses, summarize complex ideas, or create original examples in seconds. Using these tools, a teacher can quickly produce tailored practice materials, conversational prompts, or real-world scenarios aligned to learners’ needs. For adult educators, these technologies present both exciting opportunities and important questions about how they can—and should—be integrated into teaching and learning. Used thoughtfully, GenAI can become a powerful partner in creating richer, more personalized, and more engaging educational experiences.

 

Why GenAI is Applicable to Adult Education

Adult learners often bring a wealth of prior knowledge, diverse life experiences, and specific goals to the classroom. The table below links ways that incorporating GenAI tools in instruction relates to the principles of andragogy (Adarkwah, 2024):

 

Principle of Andragogy	GenAI Tools in Instruction
Personalized, self-directed learning	Adults typically bring diverse backgrounds, experiences, and learning goals. GenAI tools can tailor explanations, examples, and practice materials to individual needs, supporting self-paced and self-directed learning.
Immediate relevance and application	Adult learners often seek education that directly connects to their careers, personal growth, or problem-solving in daily life. GenAI can generate context-specific resources, simulations, or writing support aligned with real-world tasks.
Flexibility and accessibility	Many adults balance education with jobs, families, and other responsibilities. GenAI offers on-demand tutoring, feedback, and content generation, making learning more flexible and accessible.
Support for diverse skill levels	Adult classrooms can vary widely in terms of prior knowledge, literacy levels, or digital skills. GenAI adapts dynamically, providing scaffolded explanations for beginners and advanced insights for experienced learners.
Enhancement of critical thinking and creativity	Adults often bring rich experiences that allow them to critique and expand on generated outputs. GenAI serves as a partner in brainstorming, reflection, and creative problem-solving rather than just a source of answers.
Lifelong learning orientation	Adult education emphasizes continuous learning beyond formal degrees. GenAI supports this by offering lifelong, personalized, and low-cost opportunities for exploration and skill-building.

 

Practical Classroom Applications

The most effective use comes when instructors frame GenAI as a support tool, not a replacement—encouraging learners to use outputs as starting points for critical analysis, revision, and discussion. Here are six ways educators can integrate generative tools (Storey & Wagner, 2024):

 

1.    Personalized Learning Assistance: Because adult learners bring different skill levels and backgrounds to the classroom, GenAI can serve as an adaptive learning assistant. Learners can ask the tool to re-explain difficult concepts in simpler terms, provide step-by-step guidance, or create analogies that connect with their professional experiences. In addition, GenAI can generate study aids such as practice quizzes, flashcards, and summaries that align with class content, helping learners prepare more effectively.

 

2.    Writing and Communication Support: Adult learners can use GenAI as a tool for drafting and revising various forms of writing, from essays and reports to professional emails. For those learning English as an additional language, GenAI tools can provide grammar corrections, vocabulary suggestions, and conversational practice. Instructors can then guide learners in refining the AI-generated drafts, turning the process into a valuable exercise in editing and communication.

 

3.    Career and Professional Development: GenAI offers practical applications in career-focused education. Learners can use it to draft resumes, cover letters, or professional profiles, which they can then refine through peer review or instructor feedback. The technology can also simulate job interviews by posing realistic, industry-specific questions, giving learners the opportunity to rehearse their responses in a low-stakes environment before entering the real job market.

 

4.    Critical Thinking and Media Literacy: One powerful use of GenAI in adult education is cultivating critical thinking. Learners can be tasked with analyzing AI-generated content to identify potential bias, inaccuracies, or missing perspectives. They can also engage in fact-checking exercises, comparing the AI’s responses against credible sources. These activities not only strengthen critical evaluation skills but also build media and digital literacy, both of which are essential in today’s information-rich society.

 

5.    Creative Applications: Adult learners can use GenAI to brainstorm project ideas, develop proposals, or solve workplace-related problems in innovative ways. The tool can also support storytelling and reflective writing by generating prompts that help learners articulate personal narratives or professional case studies. In this way, AI fosters both creative expression and deeper engagement with course material.

 

6.    Accessibility and Inclusivity: GenAI can play a crucial role in making learning more accessible for adults with diverse needs. It can simplify complex texts into plain language for learners with lower literacy levels or reframe content in different formats, such as visual diagrams or role-play scenarios, to suit various learning styles. This flexibility helps ensure that all learners, regardless of background, can engage meaningfully with course materials.

 

Ethical and Pedagogical Considerations

While GenAI tools offer benefits for adult education, their use also raises important ethical and pedagogical concerns that educators must address thoughtfully (Reihanian et al., 2025).

 

A key issue is accuracy, as these tools are prone to generating responses that may sound authoritative but contain factual errors or incomplete information. These are sometimes referred to as AI hallucinations that can be misleading for students and educators. This makes it essential for both educators and learners to adopt verification practices, such as cross-checking AI outputs with credible sources.

 

Another concern is bias, since AI systems are trained on vast datasets that may carry historical or cultural stereotypes. If left unexamined, these biases can influence the output and potentially even reinforce inequities.

 

Equally important is transparency. Learners need to understand not only the capabilities of generative tools but also their limitations, including how they arrive at certain outputs and why their responses should be treated critically rather than accepted at face value.

 

Finally, assessment integrity presents a pedagogical challenge. Instructors must consider how to design assignments and evaluation strategies that encourage authentic learning while discouraging overreliance on AI-generated content. This may involve clarifying expectations around responsible use, integrating AI literacy into the curriculum, and developing assessments that prioritize process, reflection, and critical thinking alongside final products.

 

Collectively, these considerations highlight the importance of using GenAI in ways that enhance learning without compromising ethical standards or academic integrity.

 

Keeping Humans in the Loop

GenAI should not replace the educator. Instead, it should enhance their role. Teachers remain essential for providing context, fostering critical thinking, and building the human connections that are at the heart of learning. By positioning AI as a co-pilot rather than an autopilot, educators can ensure that technology supports, rather than dictates, the learning process. As tools like ChatGPT continue to evolve, adult educators have an opportunity to shape how they are used in ways that promote equity, creativity, and lifelong learning. The key is to remain curious, informed, and willing to experiment—while keeping learners’ needs and goals at the center of the process.

 

References

Adarkwah, M. A. (2024). GenAI-infused adult learning in the digital era: a conceptual framework for higher education. Adult Learning, 36(3), 149-161. https://doi.org/10.1177/10451595241271161 

Reihanian, I., Hou, Y., Chen, Y., Zheng, Y.  (2025). A Review of Generative AI in Computer Science Education: Challenges and Opportunities in Accuracy, Authenticity, and Assessment. arXiv. https://arxiv.org/html/2507.11543v1?utm_source=chatgpt.com

Storey, V., & Wagner, A. (2024). Integrating artificial intelligence (AI) Into adult education.  International Journal of Adult Education and Technology, 15(1), https://doi.org/10.4018/IJAET.345921

 

Understanding Generative AI: Benefits, Risks, and Ethical Use

 

By Lilian H. Hill

 

Generative Artificial Intelligence (GenAI) refers to systems that can create new content such as text, images, music, or even video based on patterns learned from large datasets. Unlike traditional AI systems that classify or predict, generative models generate original content. These sophisticated tools are popular and widely available at a low cost. Tools like OpenAI’s ChatGPT, DALL-E, and Google’s Gemini are notable examples (Bommasani et al., 2021).

 

GenAI is rapidly transforming the way we work, create, and communicate. From producing human-like text and generating realistic images to assisting in software development and content creation, GenAI is no longer a futuristic concept; it’s a tool many of us are already using, knowingly or not. But as with any powerful technology, its potential comes with critical questions about benefits, risks, ethics, and responsible use.

 

Benefits of GenAI
GenAI offers a wide range of benefits across sectors by enhancing creativity, efficiency, and accessibility. Some key advantages include:

 

1.    Creativity and Content Generation. GenAI can produce text, images, music, code, and video, supporting creative professionals and everyday users. It enables rapid prototyping of ideas, assists in drafting content, and offers inspiration for writers, designers, educators, and artists.

 

2.    Efficiency and Automation. By automating repetitive or time-consuming tasks—such as summarizing documents, composing emails, or generating reports—GenAI saves time and increases productivity. In industries like marketing or journalism, it can streamline content creation workflows.

 

3.    Personalization. GenAI can tailor content to individual preferences or needs. For example, in education, it can create adaptive learning materials suited to different skill levels. In business, it can generate personalized marketing messages or customer support responses.

 

4.    Accessibility. Gen AI helps break down barriers to access by generating content in different formats and languages. For instance, it can convert text to audio, simplify complex language, or create visual aids, making information more inclusive for people with diverse needs.

 

5.    Support for Learning and Skill Development. Tools powered by GenAI can act as tutors or writing assistants, offering feedback, explanations, or examples. This empowers learners to practice and improve their skills in real-time, whether they’re learning a new language, writing an essay, or studying a complex concept.

 

6.    Innovation in Research and Development. GenAI accelerates discovery by simulating ideas, generating hypotheses, or assisting with data interpretation. In fields like drug discovery or materials science, it can suggest novel compounds or design prototypes more quickly than traditional methods.

 

Risks and Challenges

Despite its promise, GenAI presents several risks:

 

1.    Spreading Misinformation. AI-generated content can be used to create convincing fake news, propaganda, deepfakes, or misleading scientific papers, which can undermine trust and amplify social harm (Zellers et al., 2019). Fleming (2023) noted that AI tools can generate distorted historical accounts, enabling malicious actors to flood the public sphere with misinformation and hateful content. The global reach of social media enables falsehoods and conspiracy theories to spread instantly across borders.

 

2.    Bias and Fairness. Generative models can replicate and amplify the biases found in the data they were trained on, including stereotypes based on race, gender, or disability (Bender et al., 2021). This can lead to discriminatory output or harmful content, even when unintended. With the rise of GenAI, concerns around data justice have grown, as these technologies rely on large datasets that may carry embedded biases. For example, a GenAI-driven predictive policing system that draws from historically biased crime data could disproportionately target communities of color, leading to over-policing and further marginalization.

 

3.    Intellectual Property and Plagiarism. GenAI tools can produce text, images, music, and other forms of content that closely resemble or even replicate existing works that are often shared without clear attribution. This raises complex questions about authorship, originality, and ownership in both academic and creative domains (Crawford, 2021). Users may unknowingly commit plagiarism or violate intellectual property laws. The rapid proliferation of AI-generated content is prompting urgent discussions about how to define and protect original work in the age of GenAI.

 

4.    Environmental Impacts. Artificial intelligence is an extractive industry due to its significant environmental footprint. Training large AI models requires substantial computing power, resulting in high energy consumption. Data centers rely on extracting finite natural resources, such as lithium. This parallels traditional extractive industries by drawing heavily on both human and natural resources, often without equitable returns or sustainability safeguards (Crawford, 2021).

 

Ethical Use and Best Practices

Ethical use of GenAI begins with transparency. Users should disclose when AI-generated content is used, especially in educational, professional, or public communication contexts. For researchers and educators, citing tools appropriately and understanding their limitations is crucial.

 

Human oversight is essential. While AI can support decisions, it should not replace human judgment in contexts like grading, hiring, or healthcare. Ensuring accountability for AI-assisted decisions is crucial for maintaining trust and upholding ethical integrity (Floridi & Cowls, 2019). Inclusive and responsible design of AI systems requires incorporating diverse data, testing for bias, minimizing environmental impacts, and involving stakeholders, which is key to building technology that serves all members of society fairly.

 

Conclusion

GenAI is a powerful tool with immense potential to enhance human creativity and productivity. But to realize its benefits responsibly, we must remain vigilant about its risks and committed to ethical practices. As users, educators, researchers, and citizens, our role is to use GenAI wisely.

 

References

Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021). On the dangers of stochastic parrots: Can language models be too big? Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, 610–623. https://doi.org/10.1145/3442188.3445922

Bommasani, R., Hudson, D. A., Adeli, E., Altman, R., Arora, S., von Arx, S., ... & Liang, P. (2021). On the opportunities and risks of foundation models. Stanford University. https://arxiv.org/abs/2108.07258

Crawford, K. (2021). Atlas of AI: Power, politics, and the planetary costs of artificial intelligence. Yale University Press.

Fleming, M. (2023, June 13). Healing our troubled information ecosystem. Medium. https://melissa-fleming.medium.com/healing-our-troubled-information-ecosystem-cf2e9e8a4bed

Floridi, L., & Cowls, J. (2019). A unified framework of five principles for AI in society. Harvard Data Science Review, 1(1). https://doi.org/10.1162/99608f92.8cd550d1

Zellers, R., Holtzman, A., Rashkin, H., Bisk, Y., Farhadi, A., Roesner, F., & Choi, Y. (2019). Defending against neural fake news. Advances in Neural Information Processing Systems, 32, 9051–9062.