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Using AI as a Learning Tool through Simulation Interviews to Enhance Adult Learning

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Title: Using AI as a Learning Tool through Simulation Interviews to Enhance Adult Learning
Language: English
Authors: Xi Lin (ORCID 0000-0003-2387-4117), Tianjiao Zhao (ORCID 0000-0002-1897-3797), Steve W. Schmidt (ORCID 0000-0002-1213-6904), Shulin Zhou
Source: Adult Learning. 2026 37(2):100-112.
Availability: SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
Peer Reviewed: Y
Page Count: 13
Publication Date: 2026
Document Type: Journal Articles
Reports - Research
Education Level: Adult Education
Descriptors: Artificial Intelligence, Technology Uses in Education, Electronic Learning, Simulation, Interviews, Adult Learning, Adult Students, Professional Development, Cooperative Learning, Interpersonal Communication, Questioning Techniques, Computer Mediated Communication, Efficiency, Man Machine Systems, Interaction
DOI: 10.1177/10451595251345274
ISSN: 1045-1595
2162-4070
Abstract: This study explores adult learners' perceptions of simulated interviews with artificial intelligence (AI) for understanding professional roles in the field of adult education as well as better understanding the capabilities and limitations of using AI as a learning tool. A total of forty-two adult learners across four sessions of the same asynchronous online graduate-level course engaged in the AI-driven simulation interview activity, followed by reflective discussions. Both sentiment analysis and thematic analysis of the data revealed predominantly positive attitudes toward using AI for learning through simulation interviews, emphasizing its efficiency, accessibility, and preparatory value in professional learning. While participants valued AI for its flexibility and immediate feedback, concerns were raised regarding the depth and authenticity of AI interactions, underlining its limitations as a sole learning tool. The findings highlight the potential of using AI to enhance learning, while indicating the critical need for integration with human interactions to maximize its educational benefits.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1502386
Database: ERIC
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  Value: <anid>AN0192697301;adl01may.26;2026Apr03.06:11;v2.2.500</anid> <title id="AN0192697301-1">Using AI as a Learning Tool Through Simulation Interviews to Enhance Adult Learning </title> <p>This study explores adult learners' perceptions of simulated interviews with artificial intelligence (AI) for understanding professional roles in the field of adult education as well as better understanding the capabilities and limitations of using AI as a learning tool. A total of forty-two adult learners across four sessions of the same asynchronous online graduate-level course engaged in the AI-driven simulation interview activity, followed by reflective discussions. Both sentiment analysis and thematic analysis of the data revealed predominantly positive attitudes toward using AI for learning through simulation interviews, emphasizing its efficiency, accessibility, and preparatory value in professional learning. While participants valued AI for its flexibility and immediate feedback, concerns were raised regarding the depth and authenticity of AI interactions, underlining its limitations as a sole learning tool. The findings highlight the potential of using AI to enhance learning, while indicating the critical need for integration with human interactions to maximize its educational benefits.</p> <p>Keywords: artificial intelligence (AI); ChatGPT; adult learners; simulation interview; virtual professional development</p> <p>"AI responses are sometimes surface-level or may lack the complexity needed to fully explore the professional roles of adult educators."</p> <p>Artificial intelligence (AI) is reshaping how knowledge is imparted and skills are developed, moving beyond traditional boundaries to offer learners immersive, interactive, and context-specific experiences previously unattainable through conventional methods. The role of AI in dialogue and interview scenarios has demonstrated substantial potential. By simulating human-like interactions, AI can facilitate efficient screening processes and enhance customer service experiences ([<reflink idref="bib1" id="ref1">1</reflink>]). These AI-driven interactions would not only improve operational efficiency but also help collect valuable insights and improve communication strategies, illustrating the technology's potential to transform how information is exchanged in professional settings. Yet, previous studies related to the use of AI for interviews have predominantly focused on improving users' interview skills (e.g., [<reflink idref="bib24" id="ref2">24</reflink>]; [<reflink idref="bib28" id="ref3">28</reflink>]). As the integration of AI continues to expand, it is important to investigate its application in simulation-based interviews to support educational development, particularly among adult learners.</p> <p>Adult learners are usually identified as self-directed, intrinsically motivated, and bring rich life and working experiences to their learning; they often engage in lifelong learning to enhance personal and professional growth ([<reflink idref="bib18" id="ref4">18</reflink>]). However, balancing work, family, and educational commitments often limits their ability to participate in traditional experiential activities such as in-person interviews with professionals, which are crucial for professional skill development, such as critical thinking and interpretive skills, communication and interpersonal skills, contextual and transdisciplinary understanding, and ethnographic and process-oriented observation ([<reflink idref="bib23" id="ref5">23</reflink>]). Therefore, using AI for simulation interviews may offer a flexible and accessible alternative, allowing adult learners to engage in virtual interviews with professionals, such as educators, program coordinators, or human resource managers, without the constraints of time and location.</p> <p>This study uniquely investigates how AI-powered simulation interviews, beyond merely enhancing communication skills, can serve as a tool to enhance adult learners' understanding of professional roles. Particularly, learners choose a role related to adult education, such as program developer, instructor, advisor, counselor, or mentor, within a particular context (e.g., military education and training, GED programs, or human resource development). They then use an AI tool as a simulated interviewee to investigate key topics, including core responsibilities, approaches to relationship building, strategies for supporting learners, and methods for handling conflict. By replicating the experiential value of real-life interviews with human experts, this innovative approach aligns with the needs of adult learners, providing both flexibility and interactivity. The guiding research question is: <emph>What are adult learners' attitudes toward interviewing AI for learning the roles of adult educators?</emph> This study aims to contribute to the growing body of knowledge on AI in education and offer insights for educators and policymakers to effectively integrate AI simulation interviews to enhance professional understanding and skill development.</p> <hd id="AN0192697301-2">Literature Review</hd> <p>AI tools such as ChatGPT have potential to support learning through human-AI interaction. These tools offer real-time communication that could simulate social dialogue, provide feedback, and motivate reflection. The following section explores how AI tools align with the principles of social constructivism by reviewing previous studies that have applied AI in conversational contexts across different fields, thereby highlighting the opportunities and challenges of using AI as a conversational learning partner.</p> <hd id="AN0192697301-3">Social Constructivism</hd> <p>Social constructivism, rooted in the work of Lev Vygotsky, emphasizes the collaborative and social nature of learning, where knowledge is constructed through interactions rather than as an individual endeavor. [<reflink idref="bib31" id="ref6">31</reflink>] noted that cognitive development originates socially before becoming individual, highlighting the importance of interaction for learning. Learning is inherently a social process, facilitated through collaborative activities, discussions, and shared ideas ([<reflink idref="bib16" id="ref7">16</reflink>]). [<reflink idref="bib32" id="ref8">32</reflink>] argued that human actions are mediated by tools and signs, particularly language, which enables learners to negotiate meaning and co-construct knowledge within a shared cultural context ([<reflink idref="bib26" id="ref9">26</reflink>]). In short, social constructivism provides a robust framework for understanding how knowledge is constructed through social processes. By emphasizing the importance of dialogue and interaction, this theory offers valuable insights into effective educational practices that promote collaborative learning and deeper understanding.</p> <p>While social constructivism traditionally focuses on interaction with human peers or instructors, the emergence of AI tools has potential to perform as dialogic partners by motivating reflection, encouraging elaboration, and enhancing understanding through human-AI interaction. For instance, [<reflink idref="bib8" id="ref10">8</reflink>] noted that students could co-construct knowledge with AI tools, and [<reflink idref="bib21" id="ref11">21</reflink>]indicated that engaging with AI to complete online discussion activities could benefit students' critical thinking, promote knowledge exploration, and increase overall learning engagement.</p> <hd id="AN0192697301-4">The Use of AI in Conversations</hd> <p>AI has increasingly been used for learning, leveraging human-AI interactions to simulate real-world scenarios and enhance skill acquisition across various fields. Defined as systems capable of performing tasks requiring human intelligence, AI is particularly effective in training communication skills through simulated environments ([<reflink idref="bib9" id="ref12">9</reflink>]). For instance, AI has been integrated into interview systems to enhance interview skills ([<reflink idref="bib7" id="ref13">7</reflink>]) or assist recruiters in candidate evaluation, with studies showing notably high satisfaction rates for fairness and efficiency ([<reflink idref="bib20" id="ref14">20</reflink>]). Additionally, AI combined with virtual reality (VR) has been applied to create immersive training environments, such as simulating investigative interviews with maltreated children, thus improving knowledge and skills for child protection service and law enforcement personnel ([<reflink idref="bib15" id="ref15">15</reflink>]).</p> <p>AI also plays an important role in healthcare education, specifically the doctor–patient interview process, where virtual humans (VHs) are used to simulate patient–doctor relationships. Research shows that VHs could reduce barriers to self-disclosure and improve system usability, fostering more honest communication compared to human interactions ([<reflink idref="bib12" id="ref16">12</reflink>]). Similarly, ChatGPT—a commonly used AI tool—has shown feasibility in patient-doctor communication, although trust levels fluctuate depending on task complexity ([<reflink idref="bib25" id="ref17">25</reflink>]). However, limitations such as inconsistent performance and difficulty processing new knowledge ([<reflink idref="bib30" id="ref18">30</reflink>]) highlight the need for improvement.</p> <p>In the realm of education, AI tools such as ChatGPT are particularly used in language learning. Studies demonstrated that learners who engage in dialogues with ChatGPT to revise essays usually anthropomorphize the tool and perceive it as an approachable peer ([<reflink idref="bib14" id="ref19">14</reflink>]). Furthermore, AI can support English learning by simulating dialogue and enhancing skills ([<reflink idref="bib11" id="ref20">11</reflink>]; [<reflink idref="bib22" id="ref21">22</reflink>]), aligning with social-constructivist principles that emphasize knowledge construction through interaction. By acting as conversational partners, AI can provide feedback, pose questions, and offer diverse perspectives, which may facilitate learners' critical thinking and reflection. These capabilities would make AI valuable in various training contexts, including adult education, where learners often seek knowledge and professional skills to enhance their competence in the workplace. For example, they can engage with AI to co-perform tasks such as programming ([<reflink idref="bib19" id="ref22">19</reflink>]), interact with AI to explore data-driven decision-making for organizations ([<reflink idref="bib2" id="ref23">2</reflink>]), consult AI tools to evaluate job-related outcomes such as teamwork and communication ([<reflink idref="bib17" id="ref24">17</reflink>]; [<reflink idref="bib27" id="ref25">27</reflink>]), collaborate with AI for leadership training ([<reflink idref="bib3" id="ref26">3</reflink>]), and interact with AI for skill development ([<reflink idref="bib6" id="ref27">6</reflink>]; [<reflink idref="bib10" id="ref28">10</reflink>]). In essence, engaging with AI has the potential to support these learners in developing both practical (e.g., performing tasks) and interpersonal skills (e.g., communication), making them a powerful resource for professional growth. However, as AI applications continue to expand, while it excels in providing structured and immediate responses, concerns have been raised about its limitations in handling complex tasks requiring ethical judgment, interpersonal interactions, and cultural sensitivity ([<reflink idref="bib5" id="ref29">5</reflink>]; [<reflink idref="bib13" id="ref30">13</reflink>]).</p> <hd id="AN0192697301-5">Methods</hd> <p></p> <hd id="AN0192697301-6">Activities Design</hd> <p>The activity <emph>Simulating an Interview with an Adult Educator</emph> was designed to enhance learners' understanding of the professional roles of adult educators (see Figure 1). Learners selected an adult education-related, such as program developer, instructor, advisor, counselor, or mentor in a specific field (e.g., military education and training, general educational development, human resource development), and used AI (i.e., ChatGPT) as an interviewee to explore key topics, including key duties and responsibilities, relationship building, learner support strategies, and conflict resolution. Sample prompts were provided by the instructor, and learners were encouraged to tailor the prompts and engage in meaningful dialogue with ChatGPT. Following the interview, learners reflected on their insights and analyzed challenges and strategies through discussion board questions such as "Does the simulation interviews help you better understand this specific role of the adult educator?" "What challenges did you encounter when interviewing this virtual human?" "Do you find the virtual human helpful? How do you feel about interviewing the virtual human?"</p> <p>Graph: Figure 1.Workflow of the simulating an interview with an adult educator activity.</p> <hd id="AN0192697301-7">Participants</hd> <p>A total of 42 students participated in this activity from four sessions of the same fully asynchronous online graduate-level course in the field of adult education offered across the spring and fall semesters of 2024. All participants identified themselves as adult learners with full-time employment and/or caregiving responsibilities. These learners came from diverse backgrounds including working and/or teaching as community college professionals, human resource trainers, healthcare providers, and dental practitioners.</p> <hd id="AN0192697301-8">Data Collection and Analysis</hd> <p>A total of 42 reflections as responses to the questions on the discussion board were collected. Sentiment analysis was chosen for its ability to quantify learners' emotional valence, thus offering structured insights into their attitudes ([<reflink idref="bib33" id="ref31">33</reflink>]). Using the <emph>Bing</emph> lexicon, the sentiment of each response were classified and evaluated. The <emph>Bing</emph> lexicon assigns words a positive or negative value, allowing for the calculation of an overall sentiment score by subtracting the total negative values from the positive ones for each review. Lexicon can effectively identify general sentiment patterns, and its limitations in contextual interpretation were mitigated by further examining word frequencies and their sentiment values to reveal dominant patterns and themes. This method allowed for the quantification of student sentiment, offering insights into their attitudes toward interviewing AI for learning the role of an adult educator.</p> <p>To complement the quantitative data results, thematic analysis, following [<reflink idref="bib4" id="ref32">4</reflink>]- guidelines, was conducted to analyze students' responses for further understanding of their perspectives toward interviewing AI for learning. This approach included initial coding, theme generation, and iterative refinement. A multiple-case study approach was used to qualitatively analyze those responses. The case study method was particularly valuable in addressing the "how" and "why" aspects of class engagement, focusing on contemporary events while allowing minimal control over the data by the researchers (Yin, 2014). Each participant was treated as an individual case in this study. This approach facilitated the presentation of learners' authentic voices. The initial coding phase relied on each participant's responses, leading to the creation of a codebook. In the second round of analysis, an inductive open-coding approach was used, with the authors comparing notes to identify major themes. Finally, the themes were refined in the final round, ensuring the production of robust and compelling results for the study ([<reflink idref="bib29" id="ref33">29</reflink>][<reflink idref="bib34" id="ref34">34</reflink>]).</p> <hd id="AN0192697301-9">Results</hd> <p></p> <hd id="AN0192697301-10">Sentiment Analysis</hd> <p>Figure 2 shows the sentiment scores derived from learners' responses. The absence of negative sentiment scores indicates no dominant negative attitudes toward interviewing AI for learning the roles of adult educators among the participated students. The majority of responses fall within the sentiment score range from 3 to 10, demonstrating a generally positive or favorable attitudes. This pattern reflects an overall sense of optimism or neutral-to-positive stance regarding the integration of AI in their learning experiences.</p> <p>Graph: Figure 2.Sentiment scores and distribution.</p> <p>Further analysis was conducted to examine the frequency of words associated with positive and negative attitudes (see Figure 3). Positive words, such as "helpful" account for 11% among all the words with more than 2 frequencies and "better[understand]" represents 5.7%, dominating the dataset. In contrast, negative words appear much less frequently. The results demonstrate the predominance of positive sentiment in the students' perspectives toward interviewing AI for learning the professional roles of adult educators.</p> <p>Graph: Figure 3.Positive and negative word usage.</p> <p>The word cloud in Figure 4 additionally shows a representation of the top 50 words used across the responses. Words with higher frequency appear larger, highlighting their significance in students' responses reflecting on the simulation interviews with AI for learning the roles of adult educators This visualization complements the frequency analysis by providing a clear and immediate reference to the most impactful terms that shape the sentiment landscape.</p> <p>Graph: Figure 4.Word cloud of key terms.</p> <p>While the overall sentiment was predominantly positive, negative words such as "repetitive" (0.9%), "problem" (0.9%) "lacks" (0.9%) "conflict" (0.9%), "lengthy" (1.5%) and "issues" (2.4%) reveal subtle underlying concerns that students may have when interviewing AI to understand the role of an adult educator. For instance, words such as "repetitive" and "lengthy" may imply apprehensions about the interviews' depth and efficiency, suggesting concerns that AI may not capture the complexity and dynamic nature of an adult educator's role. The term "lacks" may reveal students' awareness of potential gaps in AI's ability to provide a comprehensive understanding of a specific professional adult educator's role. Terms such as "problem" and "conflict" may indicate a skepticism about AI's capacity to correctly interpret the intricate dimensions of the professional roles of adult educators.</p> <p>It is possible that students may realize that the role of an adult educator extends beyond surface-level descriptions, involving complex interpersonal skills, adaptive teaching strategies, and contextual understanding that may be challenging for AI to fully articulate or comprehend. Further, the use of negative words may reflect students' critical thinking and analytical engagement rather than a deterrent to interviewing AI for learning. Regardless, the overwhelmingly positive sentiment indicates that students view these potential limitations as minor compared to the perceived benefits of interviewing AI for learning the professional roles of adult educators. Meanwhile, this activity may additionally provide an opportunity for students to develop a deeper understanding of AI, including its limitations, which helped them critically evaluate its capabilities and constraints.</p> <hd id="AN0192697301-11">Thematic Analysis</hd> <p>The analysis of students' discussion board reflections toward their experiences with AI interviewing showed five key themes: (<reflink idref="bib1" id="ref35">1</reflink>) Efficiency and accessibility of AI tools, (<reflink idref="bib2" id="ref36">2</reflink>) Repetition and lack of personalization in AI responses, (<reflink idref="bib3" id="ref37">3</reflink>) The use of AI as a learning and preparatory tool, (<reflink idref="bib4" id="ref38">4</reflink>) Comparison of AI feedback to human feedback, and (<reflink idref="bib5" id="ref39">5</reflink>) Challenges in trusting AI.</p> <hd id="AN0192697301-12">Theme One: Efficiency and Accessibility of AI Tools</hd> <p>Participants highlighted the speed, accessibility, and convenience of AI tools (i.e., ChatGPT) in providing detailed and structured responses. They emphasized the benefits of AI in saving time and offering immediate insights compared to human interactions. Specifically, participants consistently noted that the time-saving aspect of ChatGPT made it highly accessible for educational tasks, as one learner said, "The AI interview was very quick. An actual interview with a human would have taken much longer." Similarly, participants believed that AI's streamlined format adds value to interview processes, as one noted, "The responses flowed like they would with a human, but it was faster and more structured." Yet, While AI provided efficiency, some participants expressed a desire for additional depth from human professionals. One participant argued,</p> <p>This simulation allowed me to gain more insight into this role in the field of adult education. It provided detailed roles with specific information and examples. I believe with my knowledge and partial use of AI, this interview provided enough information that led me wanting to know more from a human professional.</p> <hd id="AN0192697301-13">Theme Two: Repetition and Lack of Personalization in AI Responses</hd> <p>AI's tendency to provide repetitive and generalized answers was identified as a limitation, reducing its ability to offer personalized or emotionally resonant feedback. For example, one learner complained that "I found that some of the responses were repeated." This recurring observation indicates redundancy in AI outputs across multiple interview questions. Additionally, AI responses included some disclaimers that acknowledged the limited nature of AI responses. For example, students who assigned AI the role of program planner, and then asked AI questions about program planning received responses that all began with "Although I am not a program planner, here is some information for you...."</p> <p>While participants valued structure, they also noted the lack of human-like adaptability and personalization, as one mentioned,</p> <p>ChatGPT did an amazing job at thoroughly answering all my questions and laying the answers out in a neat and concise manner. However, I think the biggest difference is obvious. AI is not a human adult educator so it really felt more like formal research but in a simplified manner.</p> <p>Some participants hold complex emotions as they believed "It [interviewing AI] was like interviewing a human...but I felt strange to be able to get a response to those questions." These reflections suggest that while AI could simulate human interactions to a degree, it falls short in replicating the nuanced and relational aspects of communication that learners value in human experts.</p> <hd id="AN0192697301-14">Theme Three: AI as a Learning and Preparatory Tool</hd> <p>Participants viewed AI as an effective tool for learning, preparation, and gaining preliminary insights into professional roles, though they stressed its complementary role alongside human expertise. Particularly, many participants used AI to build a foundational understanding of educational roles, as one learner expressed, "The simulation helped me expand my horizon on the different aspects of the role." Thus, AI was seen as beneficial for exploring and understanding role-specific tasks and strategies, as noted by one participant,</p> <p>...the simulation provided a clear and structured overview of the mentor role in adult education. By posing questions about responsibilities, relationship-building, and handling challenges, the simulation highlighted the multifaceted nature of mentoring.</p> <p>Furthermore, some participants appreciated the ability of AI to streamline learning processes and mentioned that "It's a great way to get a lot of information in a short period of time. What used to take hours of research can now be found in a matter of minutes." These reflections indicate AI's utility in offering quick, structured, and accessible insights, while acknowledging its role as a complement to human expertise.</p> <hd id="AN0192697301-15">Theme Four: Comparison of AI Feedback to Human Feedback</hd> <p>Students' feedback towards the comparison revealed distinct advantages and limitations of AI and human educators, highlighting the unique emotional and experiential aspects humans bring. For example, some participants considered AI's neutrality as a strength of AI feedback compared to potentially subjective human inputs. As one mentioned, "AI is not biased and it gives a good outline of potential strategies and explanations."</p> <p>However, others missed the emotional and relational dynamics present in human interactions, as some participants expressed, "While I did find the AI human interview helpful, I do feel that it was somewhat of a robot experience. I enjoy interacting with humans and watching their facial expressions and body language." Additionally, some hold neutral opinion by stating that "both the simulated interview and a human interview would be detailed, however, the type of detail would be different."</p> <hd id="AN0192697301-16">Theme Five: Challenges in Trusting AI</hd> <p>Participants expressed several concerns about the reliability, depth, and authenticity of AI-generated information, particularly for nuanced or emotional topics. While some students noted that "It [AI] is like an interactive Wikipedia article, which is obviously an incredibly powerful tool," others questioned about the accuracy and sourcing of AI responses. For instance, one student critiqued, "Honestly, I am not sure what to think about this experience. How would we know if the information is correct?" Likewise, while AI was appreciated for its breadth, its inability to guarantee accuracy was noted, which further indicates the significance of receiving knowledge from human professionals, as one noted,</p> <p>I think the difference with using AI and an actual human is AI is getting the information from all over the internet. Some information might not be reliable. From a human, you might get more specific detailed information from a more specific career.</p> <hd id="AN0192697301-17">Discussions</hd> <p>The findings of this study showed that the majority of responses from participating adult learners reflect optimism about the potential of interacting with AI to enhance learning experiences. Through simulation interviews, learners engage in a process of active inquiry, allowing them to explore, reflect on, and contextualize the professional roles of adult educators in a flexible and accessible manner.</p> <p>Particularly, the frequently noted positive terms demonstrated that these learners' appreciation for the AI's ability to facilitate learning, indicating that the AI tool—ChatGPT in this study—may act as helpful conversational partners. For example, terms like "helpful" suggest that learners perceive AI as a supportive tool that makes knowledge accessible and actionable. This mirrors findings from previous conclusions ([<reflink idref="bib14" id="ref40">14</reflink>]) that students view AI as an approachable peer capable of offering valuable insights and guidance. The term "better [understand]" meanwhile implies that AI deconstructs complex concepts into manageable and comprehensible elements, thereby fostering learners' comprehension. These results were echoed in the findings from thematic analysis, where participants highlighted AI's efficiency and accessibility in providing detailed and structured responses. These findings also suggest that AI tools, such as ChatGPT, can act as effective conversational partners, enabling learners to break down complex concepts into manageable components. This aligns with the principles of social constructivism, where knowledge is co-constructed through interaction and feedback, indicating AI's potential of acting as a conversational partner that facilitates learning within a collaborative framework. Such interactions may additionally enable adult learners to co-construct knowledge in a manner similar to human peer interactions, thus reflecting AI's potential to scaffold learning within a collaborative framework. Moreover, these findings indicate that AI tools like ChatGPT could serve as a bridge for learners who may feel intimidated by traditional human-led interactions, fostering a safe and non-judgmental space for experimentation and self-paced exploration. This aspect could be particularly valuable for adult learners with diverse cultural or linguistic backgrounds, thus offering an inclusive avenue for skill-building.</p> <p>On the other hand, negative terms revealed concerns about the depth, authenticity, and reliability of AI-generated responses. AI responses are sometimes surface-level or may lack the complexity needed to fully explore the professional roles of adult educators. For instance, terms like "lengthy" and "repetitive" indicate concerns that AI may not capture the complexity and dynamic nature of an adult educator's role. Additionally, the term "lacks" shows the gap in AI's ability to provide contextually nuanced and rich insights. Participants' discussion board reflections also mentioned AI's tendency to provide repetitive or generalized responses, thereby reducing its ability to offer nuanced or emotionally resonant feedback. These findings aligns with [<reflink idref="bib25" id="ref41">25</reflink>] conclusions that ChatGPT's ability to generate credible information may decreased as the complexity of tasks increased, indicating that human interaction is crucial for addressing intricate or high-stakes scenarios.</p> <p>Moreover, its inability to adapt to interpersonal nuances limits its effectiveness in fully supporting learners. For example, the skepticism reflected in terms like "problem" and "conflict" reveals that learners may be concerned about AI's ability to correctly interpret the complexity of a professional adult educator's role. Qualitative results also show that adult learners perceived ChatGPT's limitations including its struggles to move beyond surface-level engagement, which is critical for addressing the intricate challenges of adult education, including cultural, emotional, and situational complexities. These concerns in some way highlight the development of critical thinking skills. The learners' ability to analyze these responses indicate that they were learning about the topics discussed during the AI interview process, which in return helps them to develop their critical thinking skills. Furthermore, this finding highlights the need for human involvement in learning processes as human educators would bring depth, flexibility, and an understanding of nuanced scenarios that AI cannot replicate.</p> <p>Despite these limitations, the findings show that interviewing AI tools (i.e., ChatGPT) demonstrates the potential to replicate real-world interactions and enhance understanding of professional roles and responsibilities by explaining job duties, responding to role-specific scenarios, and engaging in reflective communication. The AI tool provides a personalized, flexible, and engaging context for dialogue-based learning, making it particularly beneficial for adult learners navigating the constraints of work, family, and academic commitments. By offering 24/7 accessibility, AI-driven simulation interviews can help address the unique time and location challenges faced by adult learners. However, adult learners should not solely reply on this method to acquire professional skills. Instead, AI could serve as a complementary tool—a foundational scaffold that provides preliminary knowledge and understanding. Human experts remain essential for offering details and in-depth insights, real-world experiences, and opportunities for learners to refine their professional competencies. As a result, a hybrid learning model would offer a promising solution to these challenges by combining the scalability and efficiency of AI with the relational and contextual depth of human experts. While AI can provide accessible, repetitive practice, human professionals can foster critical thinking, ethical reasoning, and personalized support.</p> <hd id="AN0192697301-18">Implications</hd> <p>To maximize the potential of AI in education, instructors should design integrated and adaptive learning experiences that balance the strengths of AI with meaningful human interactions. Drawing on social-constructivist principles, the integration of AI and human facilitation would enable learners to co-construct knowledge through interaction and reflection. AI tools could offer efficient, structured, and consistent feedback, enabling adult learners to address immediate queries and access vast repositories of knowledge.</p> <p>However, their limitations in adapting to nuanced, contextual, and interpersonal aspects emphasize the need for a balanced approach. Collaborative learning strategies, such as guest lectures, peer discussions, and instructor-guided reflections, can help establish effective and interactive learning environments that bridge these gaps. In particular, incorporating structured opportunities for human facilitation can address areas where AI lacks depth, such as fostering critical thinking, contextual analysis, and understanding of ethical or emotional dimensions within professional practices. For example, guest lectures by industry professionals can provide real-world insights that complement AI's factual outputs. Similarly, instructor-guided reflections can help learners critically evaluate AI-provided feedback, encouraging them to identify gaps, explore alternative perspectives, and refine their understanding. Peer discussions can further allow learners to contextualize and challenge AI-generated suggestions, cultivating a richer learning experience through collaboration and diverse viewpoints.</p> <p>By leveraging the complementary strengths of AI and human facilitation, educators can therefore create a robust ecosystem that not only enhances adult learners' professional understanding but also equips them with essential soft skills, such as adaptability, teamwork, and reflective practice. This hybrid approach would also empower these learners to develop critical digital literacy skills, enabling them to engage with AI tools thoughtfully and strategically in their professional contexts. Additionally, this integration can lead to broader implications for educational equity. For instance, AI tools may offer scalable support for large or diverse adult learner groups, while human facilitators could ensure that cultural, emotional, and situational complexities are acknowledged and addressed. This balanced design would promote inclusivity, ensuring that no learner is left behind due to the limitations of either AI or human intervention alone. Lastly, the successful implementation of AI in education requires intentional design and continuous refinement. By blending AI's strengths in efficiency and scale with the adaptability and empathy of human interactions, educators can maximize the potential of AI tools to transform learning and foster meaningful skill development across a range of professional fields.</p> <hd id="AN0192697301-19">Conclusions</hd> <p>This study contributes to the growing literature by offering new perspectives into how human-AI interactions may be examined through a social-constructivist lens. It opens several promising avenues for future research. One important next step is to include a larger and more diverse participant group to better understand how various adult learners perceive and interact with AI. Additionally, future studies could directly compare AI-based and human-led interactions in a controlled setting. While AI simulation interviews offer flexibility and accessibility, it remains unclear how they compare to interviews with human professionals in fostering authentic learning experiences. Future studies should examine these differences to better explore AI's unique benefits and limitations. Furthermore, future study should investigate the use of AI for simulation interviews across various disciplines beyond adult education to provide a more comprehensive understanding of the potential of using AI for simulation interviews in education. Expanding the scope would help identify domain-specific challenges and opportunities in applying AI to professional learning contexts.</p> <p>In conclusion, this study explores the use of AI as a learning tool through simulation interviews, highlighting its potential to enhance learners' understanding of professional roles of adult educators. While learners expressed predominantly positive attitudes toward this approach, their concerns indicate that AI should complement, rather than replace, human interactions. By integrating AI with human facilitation, educators can better apply the strengths of both to create enriched learning environments that support professional development and foster meaningful educational outcomes. Furthermore, a hybrid learning model leveraging AI for initial exposure and repetitive practice, coupled with human-led activities for discussions and critical thinking, could create a more comprehensive framework for professional skill development in adult education. This approach would also allow learners to benefit from AI's efficiency and scalability while addressing its limitations through the depth, adaptability, and relational dynamics provided by human educators.</p> <hd id="AN0192697301-20">ORCID iDs</hd> <p>Xi Lin https://orcid.org/0000-0003-2387-4117</p> <p>Tianjiao Zhao https://orcid.org/0000-0002-1897-3797</p> <p>Steve W. Schmidt https://orcid.org/0000-0002-1213-6904</p> <hd id="AN0192697301-21">Data Availability Statement</hd> <p>Data will be provided upon request.</p> <ref id="AN0192697301-22"> <title> References </title> <blist> <bibl id="bib1" idref="ref1" type="bt">1</bibl> <bibtext> Adam M., Wessel M., Benlian A. (2021). AI-based chatbots in customer service and their effects on user compliance. Electronic Markets, 31(2), 427–445. https://doi.org/10.1007/s12525-020-00414-7</bibtext> </blist> <blist> <bibl id="bib2" idref="ref23" type="bt">2</bibl> <bibtext> Anagnoste S., Biclesanu I., D'Ascenzo F., Savastano M. (2021). The role of chatbots in end-to-end intelligent automation and future employment dynamics. In Business revolution in a digital era: 14th international conference on business excellence, ICBE 2020 (pp. 287–302): Springer International Publishing.</bibtext> </blist> <blist> <bibl id="bib3" idref="ref26" type="bt">3</bibl> <bibtext> Babashahi L., Barbosa C. 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Sage.</bibtext> </blist> </ref> <ref id="AN0192697301-23"> <title> Footnotes </title> <blist> <bibtext> The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.</bibtext> </blist> <blist> <bibtext> The author(s) received no financial support for the research, authorship, and/or publication of this article.</bibtext> </blist> </ref> <aug> <p>By Xi Lin; Tianjiao Zhao; Steve W. Schmidt and Shulin Zhou</p> <p>Reported by Author; Author; Author; Author</p> <p></p> <p>Xi Lin is an Associate Professor in the Department of Interdisciplinary Professions at East Carolina University. Her research focuses on student engagement and interaction in online and distance learning and international students and faculty in the US higher education. More information about her can be found at https://whoisxilin.weebly.com/</p> <p>Tianjiao Zhao is an Assistant Professor in the Department of Construction Management at East Carolina University. With a diverse background in sustainability, Building Information Modeling (BIM), green building, Lean Six Sigma, semantic web technologies, intelligent transportation, the Internet of Things (IoT), and water engineering, she is dedicated to advancing the efficiency, safety, and environmental sustainability of the construction industry. Her research emphasizes the integration of cutting-edge technologies, including artificial intelligence (AI) and human-computer interaction, to drive innovation in construction management. Passionate about education, Dr. Zhao also incorporates these advanced technologies into her teaching, fostering a dynamic, future-focused learning environment for the next generation of industry leaders.</p> <p>Steven W. Schmidt is a Professor of Adult Education and the Adult Education Program Coordinator in the Higher, Adult, and Counselor Education Department at East Carolina University. He holds Ph.D. and MS degrees in adult education from the University of Wisconsin—Milwaukee and a Bachelor of Business Administration Degree from the University of Wisconsin—Whitewater. Dr. Schmidt's major areas of research and writing activity include workplace training and development, cultural competence, and online teaching and learning.</p> <p>Shulin Zhou is a Statistician in Institutional Planning, Assessment & Research (IPAR) at East Carolina University. He is proficient in statistics, data analysis, data visualization, and predictive modeling using various tools such as SAS, R, JMP, Power BI, and SPSS. He is also skilled in programming with PHP and Python. Moreover, Mr. Zhou has over seven years of experience teaching statistics and predictive modeling.</p> </aug> <nolink nlid="nl1" bibid="bib24" firstref="ref2"></nolink> <nolink nlid="nl2" bibid="bib28" firstref="ref3"></nolink> <nolink nlid="nl3" bibid="bib18" firstref="ref4"></nolink> <nolink nlid="nl4" bibid="bib23" firstref="ref5"></nolink> <nolink nlid="nl5" bibid="bib31" firstref="ref6"></nolink> <nolink nlid="nl6" bibid="bib16" firstref="ref7"></nolink> <nolink nlid="nl7" bibid="bib32" firstref="ref8"></nolink> <nolink nlid="nl8" bibid="bib26" firstref="ref9"></nolink> <nolink nlid="nl9" bibid="bib21" firstref="ref11"></nolink> <nolink nlid="nl10" bibid="bib20" firstref="ref14"></nolink> <nolink nlid="nl11" bibid="bib15" firstref="ref15"></nolink> <nolink nlid="nl12" bibid="bib12" firstref="ref16"></nolink> <nolink nlid="nl13" bibid="bib25" firstref="ref17"></nolink> <nolink nlid="nl14" bibid="bib30" firstref="ref18"></nolink> <nolink nlid="nl15" bibid="bib14" firstref="ref19"></nolink> <nolink nlid="nl16" bibid="bib11" firstref="ref20"></nolink> <nolink nlid="nl17" bibid="bib22" firstref="ref21"></nolink> <nolink nlid="nl18" bibid="bib19" firstref="ref22"></nolink> <nolink nlid="nl19" bibid="bib17" firstref="ref24"></nolink> <nolink nlid="nl20" bibid="bib27" firstref="ref25"></nolink> <nolink nlid="nl21" bibid="bib10" firstref="ref28"></nolink> <nolink nlid="nl22" bibid="bib13" firstref="ref30"></nolink> <nolink nlid="nl23" bibid="bib33" firstref="ref31"></nolink> <nolink nlid="nl24" bibid="bib29" firstref="ref33"></nolink> <nolink nlid="nl25" bibid="bib34" firstref="ref34"></nolink>
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  Data: Using AI as a Learning Tool through Simulation Interviews to Enhance Adult Learning
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  Data: <searchLink fieldCode="AR" term="%22Xi+Lin%22">Xi Lin</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-2387-4117">0000-0003-2387-4117</externalLink>)<br /><searchLink fieldCode="AR" term="%22Tianjiao+Zhao%22">Tianjiao Zhao</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-1897-3797">0000-0002-1897-3797</externalLink>)<br /><searchLink fieldCode="AR" term="%22Steve+W%2E+Schmidt%22">Steve W. Schmidt</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-1213-6904">0000-0002-1213-6904</externalLink>)<br /><searchLink fieldCode="AR" term="%22Shulin+Zhou%22">Shulin Zhou</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22Adult+Learning%22"><i>Adult Learning</i></searchLink>. 2026 37(2):100-112.
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  Data: SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
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  Data: <searchLink fieldCode="DE" term="%22Artificial+Intelligence%22">Artificial Intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Technology+Uses+in+Education%22">Technology Uses in Education</searchLink><br /><searchLink fieldCode="DE" term="%22Electronic+Learning%22">Electronic Learning</searchLink><br /><searchLink fieldCode="DE" term="%22Simulation%22">Simulation</searchLink><br /><searchLink fieldCode="DE" term="%22Interviews%22">Interviews</searchLink><br /><searchLink fieldCode="DE" term="%22Adult+Learning%22">Adult Learning</searchLink><br /><searchLink fieldCode="DE" term="%22Adult+Students%22">Adult Students</searchLink><br /><searchLink fieldCode="DE" term="%22Professional+Development%22">Professional Development</searchLink><br /><searchLink fieldCode="DE" term="%22Cooperative+Learning%22">Cooperative Learning</searchLink><br /><searchLink fieldCode="DE" term="%22Interpersonal+Communication%22">Interpersonal Communication</searchLink><br /><searchLink fieldCode="DE" term="%22Questioning+Techniques%22">Questioning Techniques</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+Mediated+Communication%22">Computer Mediated Communication</searchLink><br /><searchLink fieldCode="DE" term="%22Efficiency%22">Efficiency</searchLink><br /><searchLink fieldCode="DE" term="%22Man+Machine+Systems%22">Man Machine Systems</searchLink><br /><searchLink fieldCode="DE" term="%22Interaction%22">Interaction</searchLink>
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  Data: This study explores adult learners' perceptions of simulated interviews with artificial intelligence (AI) for understanding professional roles in the field of adult education as well as better understanding the capabilities and limitations of using AI as a learning tool. A total of forty-two adult learners across four sessions of the same asynchronous online graduate-level course engaged in the AI-driven simulation interview activity, followed by reflective discussions. Both sentiment analysis and thematic analysis of the data revealed predominantly positive attitudes toward using AI for learning through simulation interviews, emphasizing its efficiency, accessibility, and preparatory value in professional learning. While participants valued AI for its flexibility and immediate feedback, concerns were raised regarding the depth and authenticity of AI interactions, underlining its limitations as a sole learning tool. The findings highlight the potential of using AI to enhance learning, while indicating the critical need for integration with human interactions to maximize its educational benefits.
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