Assessing Student Satisfaction Using Lectures Generated by Artificial Intelligence (AI)

Assessing Student Satisfaction Using Lectures Generated by Artificial Intelligence (AI) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Assessing Student Satisfaction Using Lectures Generated by Artificial Intelligence (AI) Althaf Hussain Kallamadugu, Nurudeen Segun Lawal, Joseph Michael Burgett, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7394155/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The integration of Artificial Intelligence (AI) in education has gained significant momentum, particularly in online learning environments. This study evaluates the effectiveness of AI-generated voice-over lectures as an alternative to traditional human-narrated presentations in preparing students for the Federal Aviation Administration (FAA) Part 107 certification exam for small Unmanned Aircraft Systems (sUASs). Utilizing a mixed-methods approach, the research examines student performance, engagement, and satisfaction through quantitative analysis of exam scores and survey data, supplemented by qualitative insights from student interviews. The study employs a comparative design, assessing two groups: one receiving AI-generated instructional content and the other engaging with human-narrated lectures. Results indicate no significant difference in exam performance between the two groups, demonstrating that AI-generated lectures are as effective as traditional methods in supporting student learning outcomes. Survey responses reveal that students appreciate the accessibility and consistency of AI-driven instruction but highlight a preference for human interaction in certain aspects of learning. AI tools such as chatbots and digital notes offer supplementary benefits, particularly in providing quick clarifications, though they are perceived as less effective for in-depth explanations. The findings underscore the viability of AI-generated lectures in education, particularly for technical certification training. Future research should focus on optimizing AI instructional design to enhance personalization, engagement, and interaction, ensuring that AI-driven education continues to align with pedagogical best practices. Artificial Intelligence (AI) online education FAA Part 107 sUAS student satisfaction instructional effectiveness Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 Introduction The evolution of education has been significantly influenced by advancements in technology, transitioning from traditional classroom instruction to digital learning platforms. The widespread availability of high-speed internet, mobile devices, and AI tools has transformed learning experiences, offering students greater accessibility and flexibility (Guo, 2025 ). Online education has emerged as a viable alternative to conventional in-person learning, with institutions adopting innovative methods such as flexible delivery, technology-enhanced engagement, and hybrid models to enhance student performance, satisfaction, and retention (Najjar, 2025 ). Among these developments, AI-generated instructional materials particularly voice-over lectures have gained attention for their potential to replicate traditional teaching methods while optimizing efficiency and accessibility (Kallamadugu & Burgett, 2025 ). AI applications in education—such as intelligent tutoring systems, adaptive learning platforms, and automated assessments—deliver personalized learning experiences catered to individual student needs (Gligorea & Mihăilă, 2023 ). While AI-driven instructional technologies have demonstrated effectiveness in enhancing teaching quality, their use in voice-over lectures remains underexplored (Pang et al., 2024 ). This study examines the effectiveness of AI-generated voice-over lectures in comparison to human-narrated presentations in preparing students for the FAA Part 107 exam for commercial small sUASs. By evaluating student satisfaction, engagement, and performance, the research seeks to determine whether AI-generated lectures offer a comparable learning experience to traditional methods. The integration of AI-generated instructional content raises important questions regarding the role of human interaction in online education. While AI offers consistency in content delivery, students may perceive the absence of human presence as a limitation in engagement and comprehension. Additionally, concerns regarding the clarity, intonation, and perceived effectiveness of AI-narrated lectures compared to human instructors necessitate further investigation. Given the increasing reliance on AI in educational settings, understanding its impact on student outcomes is crucial for informed decision-making in instructional design. The FAA Part 107 exam is a standardized certification process ensuring that remote pilots possess the necessary knowledge and skills for safe and compliant drone operation (FAA, 2024). Lawal et., al 2024 found that FAA Part 107–related topics ranked as the critical component of a UAS curriculum, emphasizing the exam’s central role in drone training programs. Because Part 107 preparation is already an established component of drone training programs, it provides a structured framework for evaluating instructional effectiveness. This study explores whether AI-generated voice-over lectures can effectively prepare students for the Part 107 exam, providing insights into the feasibility of AI-driven instructional methods in specialized technical training. Significance of the Study The findings of this research contribute to the broader discourse on AI adoption in education, particularly in specialized certification training. By analyzing student performance and feedback, the study provides empirical evidence regarding the feasibility of AI-generated lectures as an alternative to human instruction. Additionally, the research informs best practices for integrating AI-driven content into online education, ensuring that technological advancements align with pedagogical objectives. Given the increasing reliance on AI in digital learning environments, this study offers valuable insights for educators, instructional designers, and policymakers seeking to enhance the effectiveness of online education. As AI technologies continue to evolve, their application in technical training programs can streamline instructional processes, reduce costs, and improve accessibility. By assessing the potential of AI-generated voice-over lectures in preparing students for the FAA Part 107 exam, this research provides a foundation for further exploration into AI-driven educational methodologies in aviation and other technical disciplines. Research Questions This study aims to address the following research questions: Can artificial intelligence (AI) be used to recreate traditional voice-over PowerPoint lectures in a manner that provides a comparable learning experience and yields similar assessment outcomes? To what extent does the use of a human voice, compared to an AI-generated voice, influence the effectiveness of online instruction? Research Objectives To achieve the study’s aims, the following research objectives are established: To evaluate the impact of AI-generated voice-over PowerPoint lectures on student learning and performance on the FAA Part 107 knowledge exam for unmanned aircraft systems (UASs) To compare AI-voiced lectures with traditional human-delivered lectures in the context of Part 107 exam preparation, identifying any differences in the learning experience and assessment results. To investigate the role of human voice in online asynchronous courses and its relationship to student satisfaction and performance on the Part 107 exam. Literature Review Artificial Intelligence Definition and Functionality of AI AI systems—comprising both software and hardware components—are engineered to perform complex tasks in physical or digital environments. These systems collect, interpret, and reason over both structured and unstructured data to determine optimal actions that align with specified goals (Mikalef et al., 2021). AI systems can adapt their behavior by learning from past actions and environmental feedback (Mathis, 2024 ). GPT vs. LLM Generative Pre-trained Transformers (GPT), such as OpenAI’s ChatGPT, are large language models built on transformer architecture that generate coherent, human-like text using advanced attention mechanisms (Roumeliotis, 2023 ). Large Language Models (LLMs) include GPT and other models like BERT, representing various transformer-based approaches trained on extensive datasets for natural language understanding and generation (Zhou et al., 2023). ChatGPT ChatGPT leverages GPT architecture to deliver conversational, human-like text generation through advanced transformer-based language modeling (Ray 2023 ). ChatGPT was initially launched using GPT-3.5 and later upgraded to GPT-5. These models are trained not only with supervised fine-tuning but also with reinforcement learning from human feedback (RLHF), enabling them to generate high-quality responses for tasks such as content creation, answering queries, and language translation (OpenAI, 2022; Ouyang et.al., 2022). Despite concerns about the quality of text generated for academic purposes, ChatGPT has been praised for its efficiency in producing program code and responding to structured queries (Stokel-Walker, 2022 ). AI in Online Higher Education AI in education, or AIEd, integrates AI tools into teaching, learning, and administrative functions to enhance educational experiences (Hwang et al., 2020 ). Complementing these findings, Kallamadugu et.al 2024 detailed a practical workflow for creating narration for voice-over presentations using commercially available AI tools illustrating how educators can integrate AI seamlessly into content production processes. AI technologies are increasingly used to generate personalized learning resources, predict student performance, and automate the assessment process (Halkiopoulos & Gkintoni, 2024 ). Instructors can use AI as a tutor, automating repetitive tasks and offering customized learning paths based on students' needs (Hwang et al., 2020 ). AI can empower administrators to make evidence-based decisions regarding course content and pedagogical strategies, improving both curriculum quality and instructional effectiveness (Sposato, 2025 ). Artificial Intelligence in Education (AIEd) transforms the learning experience by enabling personalized instruction and delivering real-time feedback to learners (Tapalova & Zhiyenbayeva, 2022 ). Best Practices in Online Education Engaging Students in Online Learning Creating an interactive and student-centered environment is essential for effective online learning, fostering deeper engagement and improving learning outcomes (Rayens & Ross, 2018 ). Teachers should foster active participation and enrich learning by utilizing multimedia, delivering personalized feedback, and grounding instruction in real-world examples, thereby creating engaging and meaningful educational environments (Kerimbayev et al., 2023 ). Additionally, instructors should strategically leverage educational technologies and adopt a flexible teaching style to sustain high levels of student engagement and accommodate diverse learning needs (Rapanta et al., 2020 ). Voice tonality, including factors such as pitch, rhythm, and intonation, has been shown to significantly influence student engagement and comprehension in online learning environments. Studies indicate that learners are more likely to maintain attention and feel connected to the content when the narration includes natural variations in tone, as opposed to flat or synthetic delivery (Paulmann & Weinstein, 2023 ). Creating a Sense of Community Collaboration and community are essential in online education. Instructors can foster these outcomes through collaborative learning activities, addressing specific group needs, and facilitating peer-to-peer interactions, which promote deeper engagement and knowledge construction (Laal & Ghodsi, 2012 ). Smaller groups formed with attention to learners’ time zones and schedules support effective synchronous collaboration, while asynchronous tools (e.g., LMS discussion boards, writing tools) scale well for larger cohorts (Oyarzun & Martin, 2023 ). Technological Tools for Online Education Effective online education depends on selecting appropriate technologies, and instructors’ familiarity and competence with these tools are critical for effective course facilitation (Rapanta et al., 2022 ). Clear expectations, regular and substantive instructor interaction (including timely updates), and accessibility-oriented course design have all been linked to improved engagement, satisfaction, and learning outcomes in online education (Sweetman, 2020 ). Teachers should also create inclusive and engaging learning environments by leveraging technology to enhance participation, foster motivation, and support diverse learner needs (Bond et al., 2021 ). Implementation of Artificial Intelligence in Online Education Best Practices for AI Integration Incorporating AI into online learning environments requires thoughtful planning and a clear understanding of AI’s capabilities and limitations to ensure it enhances, rather than disrupts, the learning process (Zawacki-Richter et al., 2019 ). AI can support education by streamlining administrative tasks, delivering personalized learning experiences, and providing real-time feedback to students (Chen et al., 2020 ). However, AI should complement human interaction, as it cannot replace the nuanced guidance provided by educators. Ethical concerns regarding data usage and transparency are critical considerations in AI-powered classrooms (Holstein and Aleven 2022 ). Personalized Learning with AI AI tools can analyze student data to deliver personalized learning experiences, dynamically adjusting curricular content to match individual learners’ needs (Al Nabhani et.al., 2025 ). AI can deliver immediate, tailored feedback and recommend targeted resources to enhance learning (Ma et.al., 2014 ; da Silva et.al., 2023 ). These tools support diverse learning pathways by adapting to each student’s level of understanding, thereby enhancing educational outcomes through targeted instruction (Xie et al., 2019 ). Effective Use of AI in Education AI can enhance teaching by automating routine administrative tasks, delivering personalized instruction, and supporting students through intelligent tutoring systems (Zawacki-Richter et al., 2019 ). For AI tools to be used effectively, they must align with clearly defined educational objectives while maintaining a balance between technological support and meaningful human interaction (Holstein & Aleven, 2022 ). Educators must guide learning, foster critical thinking, and ensure the responsible use of AI to optimize educational outcomes (Zawacki-Richter et al., 2019 ). Unmanned Aircraft Systems Overview of Drone Technology Drones, or Unmanned Aircraft Systems (UASs), are aircraft that operate without a pilot on board. They are used for various applications, including surveillance, mapping, and monitoring, and are increasingly utilized in the construction industry for tasks like surveying, inspections, and safety management (Lawal et.al., 2024 ; Burgett, 2021 ). Drones Role in Construction UASs are transforming the construction industry by enabling enhanced data collection for site monitoring and inspection, which in turn improves operational efficiency and safety (Liang, 2023 ; Zhou, 2024). They are used for tasks such as monitoring construction progress, mapping sites, and performing inspections (Zaychenko et al., 2018 ). Drones offer unique aerial perspectives on construction sites, significantly enhancing safety, productivity, and project quality (Choi et al., 2023 ). Challenges and Opportunities with Drones While drones provide numerous benefits—such as improved safety and operational efficiency—their integration into construction operations also presents challenges including privacy concerns and regulatory compliance (Daoud et al., 2025 ; Krook, 2024 ). Companies must address these issues through proper training and compliance with FAA regulations (FAA, 2016). Effective planning is crucial for maximizing the benefits of drones in construction while minimizing risks (Hasa, 2024 ). FAA Part 107 Certification The FAA's Part 107 regulations govern the commercial use of drones in the U.S. This includes certifications for remote pilots, operational limits, and safety requirements (FAA, 2016). Passing the Part 107 knowledge test is a requirement for commercial drone pilots, ensuring they are equipped with the necessary knowledge for safe and legal drone operations (Burgett, J. M., & Dees, C. 2023). See table 1 for companies offering jobs to drone pilots (Dumpati, CT, 2023 ). Table 1 Firms offering jobs to drone pilots (Dumpati, CT, 2023) Research Gap While AI has been integrated into online education, particularly in personalized learning and automated assessments, there is a gap in research regarding the effectiveness of AI-generated voice-over lectures compared to human-narrated ones, especially for specialized certification exams like the FAA Part 107 exam. The literature often overlooks the importance of the human voice in asynchronous learning environments. The proposed study aims to fill this gap by comparing AI-generated and human-narrated lectures and assessing their impact on learning outcomes, using the Part 107 exam for the study’s experiment. This research will provide insights into the role of AI in education and inform best practices for integrating AI without compromising the human element essential for effective learning. Methodology Overview of Experiment The methodology begins with a comprehensive literature review to understand the existing research on the use of AI in online education. Next, a workflow was developed to generate AI voice-over lectures specifically for an existing drone course. Following this, the Part 107 section of [INSERT COURSE NUMBER AND NAME] was updated with AI-generated course materials. The effectiveness of the AI voice-over lectures were then assessed by comparing the Part 107 exam scores of students in the traditional drone course section with those in the course using AI voice-over lectures. A quantitative survey was administered to both control (students in the traditional voice-over course) and experimental (students in the AI voice-over course) groups to collect data on their experiences. The survey results was analyzed quantitatively to compare the student experiences. Additionally, qualitative data was gathered through interviews with students from the experimental group who were exposed to the AI-generated lectures. The interview data was coded and analyzed to provide a deeper understanding of their experiences. This paper presents the research findings based on the results from the quantitative surveys, qualitative interviews, and exam score comparisons. In summary, this mixed-methods approach combines both quantitative data (from surveys and exam scores) and qualitative data (from interviews) to evaluate the effectiveness of AI-generated voice-over lectures in online drone education. The results will offer valuable insights into the integration of AI technologies in online education and their impact on student learning and engagement. Figure 2 outlines the methodology flow chart. Overview of the “Workflow” The methodology involves a step-by-step process to generate AI voice-over lectures from existing human voice-over lectures. This research refers to this process as the “Workflow.” Initially, audio is extracted from the existing PowerPoint lecture files, converted into text using online tools, and then refined with ChatGPT. The generated transcripts undergo multiple rounds of cleaning using ChatGPT 4.0, along with human proofreading to enhance accuracy and relevance. The final transcript is reviewed and fine-tuned by a subject matter expert. In this case, the subject matter expert was the instructor of the drone course and author of the PowerPoint lectures. AI-generated voice narration for the lecture files was then created from the refined transcript using a text-to-speech application. Closed captions were generated from the audio files and manually proofread. The human voice-over lectures were then recreated using the AI-generated audio, enhanced with closed captions and synchronized animations. Furthermore, the transcripts were organized into a study guide, complete with a thumbnail image of the PowerPoint slide and a place for the students to take notes. An AI chatbot, trained on the study guide, transcripts and other publicly available Part 107 resources, was developed to assist students with any questions. This comprehensive Workflow converts traditional lectures into AI-generated voice-overs and creates additional resources such as study guides and chatbots to enhance the learning experience. Figure 3 illustrates the methodology of "The Workflow." The “Workflow” Adapted for this Experiment Step 1: Create Transcripts by Extracting Audio from the Existing Course The researchers began by extracting audio files from the human-narrated Power Point presentations and converting them into text using the online tool KwiCut. These initial transcripts were then refined with ChatGPT to improve clarity and coherence. Step 2: Clean and Fine-Tune the Transcript Using ChatGPT To enhance the quality of the transcripts, the researchers used ChatGPT with a structured prompt aimed at rephrasing the lecture content in a professional yet approachable tone. Transcripts were initially edited using ChatGPT 3.5 and further refined with ChatGPT 4.0. Subject matter experts then reviewed the transcripts for clarity and accuracy, followed by manual proofreading by the research team. Final revisions were streamlined using a simplified prompt with ChatGPT 4.0, resulting in polished transcripts ready for the next step. Step 3: Create Audio Lecture Files from the Fine-Tuned Transcript The finalized transcripts were reviewed for pronunciation using Word’s "Read Aloud" feature. They were then imported into the online text-to-speech application ElevenLabs. A deep American male accent voice profile (Antoni) was selected for its natural, human-like quality. It was found that when long transcripts were provided to the text-to-speech prompt, it increased the chance of mispronounced words. To ensure consistency in quality, longer transcripts were divided into smaller sections, producing high-quality audio files. While the AI-generated narration provided a consistent and efficient means of delivering lecture content, some challenges with pronunciation were noted. Certain technical terms and abbreviations were occasionally mispronounced, leading to minor comprehension issues. To mitigate this, transcripts were segmented into smaller text inputs before synthesis, and pronunciation verification was conducted using Word’s ‘Read Aloud’ feature. However, future improvements could involve using AI models with user-customizable pronunciation dictionaries or training AI voices specifically on subject-matter vocabulary to enhance accuracy. Step 4: Create Closed Caption Files from Audio Files & Recreate Human Lectures with AI-Generated Material The finalized audio files were used to create closed captions with the KwiCut, exporting the captions in SRT format. These captions were manually proofread for accuracy and then integrated into the presentation software Storyline, produced by Articulate. The original human-narrated audio was replaced with AI-generated narration, and animations were synchronized with the new audio and captions. This process successfully transformed the original human lecture presentations into AI-narrated versions, ensuring consistency and maintaining quality across all materials. Step 5: Develop a study guide and AI chatbot using fine-tuned transcripts and FAA study materials With the completion of the AI-generated lectures, the researchers created a study guide based on fine-tuned transcripts. This guide helps students understand class material and includes a notes section for key takeaways. Following this, we developed a chatbot trained on the study guide and publicly available Part 107 material, allowing students to get answers to their questions on their own. Example of Human narrated lecture: https://demo-drone-course.s3.amazonaws.com/course1/human-voice-presentation/story.html Example of AI narrated lecture: https://demo-drone-course.s3.amazonaws.com/course2/ai-voice-presentation/story.html Quantitative Analysis This research employs quantitative analysis to measure the impact of AI-generated voice-over lectures on student performance and satisfaction in preparing for the FAA Part 107 exam. Data was collected through surveys and exam scores, offering objective insights into whether AI-generated lectures can provide a learning experience comparable to human-narrated lectures. The study compares two groups: one receiving AI-generated lectures and the other traditional human-narrated lectures. Key metrics include exam scores and satisfaction survey responses, allowing for a statistical comparison of outcomes. This analysis aims to determine if AI lectures match or exceed the effectiveness of human narration in preparing students for the Part 107 exam. Beyond performance, student satisfaction surveys assess perceptions of AI-generated lectures regarding clarity, engagement, and overall learning experience. These measurable insights complement qualitative findings, offering a comprehensive evaluation of AI’s potential in education. Part 107 Test Scores In Fall 2023 and Spring 2024, 59 students completed the human voice-over course and took the Part 107 knowledge test. In Summer 2024 and Fall 2024, 44 students completed the AI voice-over course and also took the same knowledge test. Their test scores were collected to evaluate the impact of each lecture format on knowledge retention. Before conducting inferential statistical tests, the distribution of scores for each group was examined to assess the assumption of normality. Visual inspection using histograms and Q–Q plots (Figs. 8 and 9) indicated that the human voice-over group’s scores were approximately symmetric and aligned closely with the theoretical normal distribution. The AI voice-over group also displayed a generally symmetric distribution, although slight deviations were observed in the lower tail. Given the slight deviation from normality in one group, both parametric (Welch’s t-test) and non-parametric (Mann–Whitney U test) approaches were applied to compare group performance, ensuring robustness of results. Table 2 presents the T-test results, highlighting the comparative effectiveness of AI-generated versus human-narrated lectures in preparing students for the Part 107 exam. Table 2 T-test table for Part 107 Knowledge Test Scores t-Test: Two-Sample Assuming Unequal Variances Control Group Students Experimental Group Students Mean 85.22033898 85.76363636 Variance 38.23130333 60.474926 Observations 59 44 Hypothesized Mean Difference 0 df 80 t Stat -0.382034087 . P(T < = t) one-tail 0.351724519 t Critical one-tail 1.664124579 P(T < = t) two-tail 0.703449039 t Critical two-tail 1.990063421 Table 2 (above) shows the results of the two-sample t-test comparing Part 107 knowledge test scores between the human voice-over and AI voice-over groups. Figure 10 illustrates the two-tailed t-test decision chart, visually depicting the observed t statistic in relation to the rejection regions. The black curve represents the t-distribution under the null hypothesis. The red shaded regions indicate the rejection zones at α = 0.05, with critical values at ± 1.990. The blue vertical line marks the observed t statistic (t = − 0.382), which lies well within the acceptance region. The difference in mean scores between the two groups was 0.54 points on a 100-point scale, with the AI voice-over group scoring slightly higher. The null hypothesis proposed no significant difference in Part 107 knowledge test results, whereas the alternative hypothesis posited a difference. This finding indicates that the observed difference is not statistically significant, suggesting that both instructional formats yielded comparable exam performance. Mann-Whitney U test is conducted to complement the T-test, comparing Part 107 test scores between students of control group and experimental group. The U statistic is 1211.0, and the p-value is 0.563, which is greater than the 0.05 significance threshold. Figure 11 shows a boxplot showing that the median scores and score distributions are comparable, with similar variability and a few outliers in both groups. The Mann-Whitney U test indicates that there is no statistically significant difference in test scores between the two groups. This reinforces the T-test results and confirms that AI-generated lectures were as effective as human-narrated lectures in preparing students for the exam. These findings suggest that AI-generated lectures provide a learning experience equivalent to human narration, making them a viable alternative in educational settings. Survey A survey was conducted with the experimental group, which included the standard course evaluation questions provided by XXX University, as well as targeted questions on the AI voice-over lectures, chatbot usage, and tutorial notes. The survey employed a Likert scale (1 to 5) to assess overall student satisfaction. The collected data was statistically analyzed to measure satisfaction levels and evaluate the effectiveness of both course formats. This quantitative data directly addresses the second research objective. Course Evaluation Survey Questions There were nine Likert Scale questions from XXX University's standard end-of-year course evaluation survey included with the survey provided to the experimental group. A T-test was conducted to compare the responses of the control group and experimental group for each survey question. A summary of descriptive statistics is presented in Table 4. The Likert Scale questions from XXX University’s standard end-of-year questionnaire are outlined below. 1. The learning outcomes in the course were clearly communicated. 2. The course assignments were related to the course learning outcomes. 3. I understood what was expected of me in this course. 4. The instructor clearly explained concepts, methods, and subject matter. 5. The instructor encouraged questioning and discussion of course topics from the students. 6. The feedback on my performance on assignments and tests supported my learning. 7. The course challenged me to think critically and communicate clearly about the subject. 8. Approximately how many hours did you spend in a typical 7-day week on learning activities outside of class time for this course? 9. Please indicate your satisfaction with the availability of the instructor outside the classroom by choosing one response from the scale. In selecting your rating, consider the instructor's availability via established office hours, appointments, and other opportunities for face-to-face or virtual interactions. Table 3 Summary of Mean, Median & P-value of Course Evaluation Survey Question No. Mean Median P-Value Control Group Experimental Group Control Group Experimental Group 1 4.78 4.8 5 5 0.46 2 4.78 4.84 5 5 0.28 3 4.68 4.68 5 5 0.48 4 4.71 4.62 5 5 0.21 5 4.42 4.55 5 5 0.18 6 4.59 4.55 5 5 0.39 7 4.50 4.48 5 5 0.44 8 2.26 2.26 2 2 0.49 9 4.43 4.51 5 5 0.32 The comparison between the control group and the experimental group revealed no statistically significant differences, as all P-values exceeded 0.05. This indicates that students perceived both methods as equally effective in terms of quality. Notably, both groups reported a high median score of 5 on key aspects such as learning outcomes, assignment clarity, and instructor availability. Despite the shift in teaching methodology, student satisfaction with AI-generated courses closely mirrors traditional approaches, reinforcing the potential of AI-driven education to uphold the standards set by human instruction. The Mann-Whitney U Test was also conducted to evaluate differences between the Control Group and the Experimental Group across nine survey questions. Here again, all p-values were greater than 0.05, indicating there was no statistically significant difference between the two groups. When compared with the T-Test, the Mann-Whitney U Test provides a robust non-parametric alternative for cases where normality is uncertain. The alignment between both tests strengthens the statistical reliability of the findings. Boxplots and p-value charts further support this conclusion, showing consistent response distributions across both groups. Since no significant differences emerged, these results confirm that AI-based teaching methods can be effectively integrated into online education without compromising student experience. AI-Related Course Evaluation Survey Questions The experimental group received additional course evaluation questions specifically addressing AI-narrated lectures, listed as questions 10 and 11. As shown in Table 5, students expressed overall satisfaction with the quality of the Part 107 lecture materials, giving an average rating of 4.46 out of 5. However, when asked to compare AI narration to human narration, the rating was more moderate at 3.66, suggesting that while students found the AI voice adequate, they did not consider it superior to human narration. The questions related to AI-narrated lectures are provided below. 10. How satisfied were you with the quality of the material presented in the Part 107 lectures? 11. How would you rate the AI-generated voice of the Part 107 lectures compared to a similar presentation with a human narrator? Table 4 Summary of Mean & Median of AI-related Course Evaluation Survey Question No. Mean Median 10 4.46 5 11 3.66 4 While the results showed that AI-generated lectures were just as effective in delivering content, student feedback suggested that AI narration lacked the engagement of human instructors. This could be attributed to the lack of emotional inflection, natural pauses, or dynamic tone variations typically found in human speech. Prior research on online learning suggests that voice tonality plays a key role in student engagement, potentially explaining why some students favored human narration despite similar learning outcomes (Paulmann et al., 2025). Future improvements in AI voice synthesis, including more natural prosody and emotion-driven speech models, may help address this limitation. Chatbot & Study Guide Related Course Evaluation Survey Questions The experimental group received additional questions regarding the Chatbot and Study Guide, listed as questions 12 - 18. As presented in Table 6, students provided feedback on the effectiveness of these tools in understanding the Part 107 content. The Chatbot's usefulness received an average rating of 3.48 out of 5, indicating that while it was considered helpful, it was not overwhelmingly beneficial. Additionally, the preference for asking questions to the Chatbot over a human instructor was rated at 3.06, suggesting that while students were moderately inclined to use the Chatbot, they still valued direct human interaction. The questions related to AI-narrated lectures are provided below. 12. How useful did you find the Chatbot (Tiger Bot) when learning about Part 107? (Likert) 13. Were you more inclined to ask the Chatbot (Tiger Bot) questions over your human instructor? (Likert) 14. How helpful was the Chatbot (Tiger Bot) with understanding difficult concepts related to Part 107? (Likert) 15. How strongly do you believe chatbots trained on course material should be integrated into future courses? (Likert) 16. How helpful was the tutorial notes for understanding Part 107 concepts? (Likert) 17. How frequently did you use the tutorial notes? (Likert) 18. Select all of the statements about the tutorial notes that are true for you. (Select multiple answers.) a. I printed hard copies of some or all of them b. I made handwritten notes on them c. I made electronic notes on them d. I used them to help study e. I read them before I watch the lectures f. I read them while I was watching the lectures g. I read them after I watched the lectures h. Other (write in):……………………….. Table 5 Summary of Mean & Median of Chatbot &Tutorial Notes Related Course Evaluation Survey Question No. Mean Median 12 3.48 4 13 3.06 3 14 3.37 3 15 3.84 4 16 4 4 17 3.82 4 18 2.64 3 The Chatbot's effectiveness in explaining difficult concepts received a moderate rating of 3.37, indicating that students found it somewhat helpful. However, the idea of integrating Chatbots into future courses was rated higher, with an average score of 3.84, suggesting that students recognize its potential for future applications. Regarding tutorial notes, students rated them highly useful for understanding Part 107 concepts, with an average score of 4.0. The frequency of usage was rated at 3.82, indicating regular but not constant reliance on these materials. Overall, these results reflect a positive yet cautious reception of AI-driven tools in the course. Open-Ended Course Evaluation Questions The experimental group received additional open-ended questions in the course evaluation survey regarding the AI Part 107 Presentations and Chatbot, listed as questions 19 - 21. Student responses were collected, compiled into a Word document, and analyzed using QDA Miner Lite software. This qualitative analysis categorized responses into two main themes: "Feedback" and "Improvements." The Feedback category included themes such as "Positive Feedback, Negative Feedback, and AI Voice Uncertainties," reflecting student satisfaction and concerns. The Improvements category covered aspects like "Visual Aids, Course Content Coverage, Technical Issues, Voice Quality Concerns, Customization, and Human Inclusion," identifying areas for course enhancement. Figure 3 illustrates the QDA Miner Lite analysis, summarizing key insights from student responses. The open-ended questions from the course evaluation survey are provided below. What improvements could be made to the Part 107 lectures? (Write in) What features or improvements would enhance the usefulness of the Chatbot (Tiger Bot) to you? (write in) In what type of course do you think a chatbot would provide the most assistance? (Write in) The qualitative analysis of survey responses revealed a mix of positive feedback and areas for improvement. While many students appreciated the clarity of the course, some highlighted issues with the AI-generated voice, mentioning pronunciation errors and inconsistent accents. One student remarked, "The AI-generated voice terribly mispronounced a lot of simple words," which affected comprehension. Additionally, students suggested incorporating more visual aids to enhance the understanding of complex topics. The preference for human interaction was evident, with some recommending traditional classroom settings over AI-driven content to improve the overall learning experience. Qualitative Analysis The purpose of qualitative analysis in this study is to gain a deeper understanding of students’ perceptions and experiences with AI-generated voice-over lectures compared to human-narrated lectures. While quantitative data from exam scores and surveys provide measurable outcomes of student performance and satisfaction, qualitative analysis helps uncover nuanced factors influencing these results. Specifically, this analysis explores how students perceive the effectiveness, engagement, and overall learning experience of AI-generated lectures. The Research team interviewed randomly selected students from the experimental group who completed the AI voice-over lectures to assess their perceptions, engagement, and satisfaction with AI-generated lectures in preparing for the Part 107 exam. The interview questionnaire featured open-ended questions focusing on comprehension, engagement, clarity, effectiveness, and overall satisfaction, encouraging students to compare AI-generated lectures with traditional human-narrated courses. Interviews were conducted via Zoom, recorded with participant consent, transcribed, and analyzed. Each session lasted approximately 20 minutes. Institutional Review Board (IRB) approval was obtained under protocol number IRB2024-0284-01, ensuring ethical compliance in the research process. Interview Process A total of nine voluntary participants took part in the interviews—two students from the Summer 2024 cohort and seven from the Fall 2024 cohort. The research team facilitated structured discussions, asking probing follow-up questions based on students’ responses to uncover deeper insights. Post-Interview Processing Following the interviews, the responses and transcripts underwent systematic refinement. First, raw transcripts were compiled into a structured Word document. Next, transcripts were cross-referenced with original recordings to correct inconsistencies such as missing words or misinterpretations. To ensure anonymity, all transcripts were de-identified. Irrelevant dialogue and filler words were removed, and responses were formatted into a question-and-answer structure. This process ensured accuracy, enhanced data organization for future reference, and maintained the integrity of collected information, providing a strong foundation for qualitative analysis. Data Analysis Each student interview was analyzed individually, anonymized as S1–S9, and uploaded into QDA Miner Lite for thematic coding. Transcripts were systematically reviewed, with key responses assigned specific codes. Recurring topics were grouped into sub-themes and broader themes, linking insights to the study’s research objectives. The software’s interface (Figure 13) organized individual interviews, stored relevant metadata, and structured coded themes, ensuring a clear and consistent analysis of student experiences with AI-generated lectures. This approach provided a structured method for identifying patterns in engagement, comprehension, and overall satisfaction. Several students emphasized that while the AI narration provided clarity and consistency, it lacked the emotional resonance of human speech. This perception aligns with existing research in human-computer interaction, which underscores the importance of vocal emotion and prosody in maintaining learner engagement. As students reflected on their experiences, many attributed their preference for human narration to its ability to convey enthusiasm, urgency, or emphasis—elements that are often flattened in synthetic voices. Integrating more expressive and dynamic AI-generated speech may enhance engagement in future iterations of AI-based instruction. The final stage of qualitative analysis involved categorizing the data into themes derived from coded interview responses. This process established connections between the research objectives and identified themes. By following this structured approach, the study ensured that student feedback was accurately captured and effectively analyzed. The findings contribute to a comprehensive understanding of how AI-generated voice-over lectures impact student engagement, comprehension, and overall learning experience, informing best practices for AI-driven educational content delivery. A representation of the framework, from the objectives to the generation of themes, can be observed in Figure 14. For instance, categories such as “AI Voice Clarity” and “Human Voice Engagement” are grouped under the sub-theme “Instructional Quality.” Similarly, “Learning Retention” and “Study Guide Usage” contribute to the sub-theme “Learning Effectiveness.” Sub-themes like “Technical Challenges” and “Visual Learning Aids” fall under “Technical Considerations.” These sub-themes collectively form broader themes, including “Comparative Effectiveness of AI vs. Human Instruction,” “Student Learning Preferences and Retention,” and “Challenges with AI Implementation.” This structured framework ensures a systematic approach to analysis, providing a clear progression from data collection to meaningful thematic insights. Note: This study used ChatGPT solely for grammatical proofreading and text refinement all research findings and references are based on original work and verified sources. Summary of Results Comparison of Exam Performance The study compared the exam performance of the control group (59 students with human narration) and the experimental group (44 students with AI-generated narration) to evaluate the effectiveness of AI voice-over lectures for the FAA Part 107 exam preparation. A two-sample T-test revealed no statistically significant difference between the groups (p-value = 0.35), with mean scores of 85.22 (control) and 85.76 (experimental). These results confirm that AI-generated narration is as effective as human narration in delivering course content and preparing students for the exam. Student Satisfaction Survey Survey results indicated no statistically significant difference in overall satisfaction between the groups (p-values > 0.05). However, students in the experimental group rated “Accessibility” (mean = 4.46/5, median = 5) and “Consistent Pacing” higher due to AI’s uniform tone and clarity. Some students preferred human narration for its personal touch and engagement. AI-powered tools, such as the chatbot and tutorial notes, received mixed feedback—while helpful for quick clarifications, they lacked the depth of human interaction. These findings highlight AI’s advantages in consistency and accessibility while underscoring the continued preference for human engagement in certain learning scenarios. Engagement and Learning Experience Students in the experimental group found AI-generated lectures engaging and effective, with a mean satisfaction score of 4.35/5. The P-value of 0.48 for engagement-related questions indicates no significant difference between AI and human-narrated lectures. AI’s consistency and clarity were well-received, but some students noted that human narration enhanced motivation and connection. The findings suggest that AI can effectively deliver course content but may not fully replicate the interactive and personal aspects of human instruction. Despite the comparable effectiveness of AI-generated and human-narrated lectures, student feedback highlighted the perceived lack of engagement in AI voices. This suggests that while AI-generated instruction is consistent and accessible, it does not yet fully replicate the natural cadence and emotional nuance of human speech. Qualitative Interview Insights Student interviews provided deeper insights into AI-generated lectures. A minority preferred human narration for its emotional tone and engagement, while most found AI effective for delivering technical content. Some students highlighted mispronunciations of technical terms, which occasionally led to confusion. One limitation of AI-generated narration identified in this study was the occasional mispronunciation of technical terms. This was noted in both student feedback and the transcript refinement process. While adjustments such as segmenting transcripts and manually verifying pronunciation helped, future research could explore more sophisticated AI models that allow for phonetic customization. Additionally, enabling AI voices to learn from human corrections could significantly enhance the accuracy and effectiveness of AI-driven instruction. Key Themes from Interviews : Comparative Effectiveness of AI vs. Human Instruction: AI was effective for structured content delivery, but human lectures fostered better engagement and motivation. Student Learning Preferences and Retention: AI was preferred for clarity and consistency, while human narration was favored for complex or abstract topics. Challenges with AI Implementation: Issues like mispronunciations and a lack of emotional engagement were common concerns. Students suggested improvements in AI voice technology to enhance clarity and interaction. Overall, AI-generated lectures proved to be a viable alternative to human narration, offering efficiency and consistency. However, human instruction remains valuable for fostering engagement and deeper learning, especially in subjects requiring interaction and motivation. Conclusion AI Lectures as a Viable Alternative This study confirms that AI-generated voice-over lectures are a viable alternative to human-narrated lectures for certain technical exam preparations. The quantitative analysis showed no significant difference in exam scores between students who received AI lectures and those who had human narration (p-value = 0.703), indicating that AI can deliver effective instruction without compromising learning outcomes. AI lectures offer key advantages, including consistent pacing, accessibility, and reduced instructor workload. Students appreciated the clarity of AI narration. AI also ensures uniform instruction, eliminating variability in tone and pacing seen in human lectures. Additionally, AI reduces the burden on instructors by automating lecture delivery, allowing them to focus on interaction and feedback. However, human narration remains valuable for fostering engagement and motivation. Some students preferred the emotional tone and interactivity of human lectures, particularly for complex or abstract topics. While AI excels in technical and procedural content delivery, human elements enhance personal connection and engagement. Future educational strategies should blend AI and human instruction to maximize learning benefits. Potential for Broader Application The scalability of AI-generated lectures makes them suitable for various online learning environments, particularly for structured, factual, or procedural subjects. AI ensures consistent content delivery, reducing variability in instruction. The success of AI in FAA exam preparation suggests its applicability in other standardized and technical courses. Despite AI's benefits, the feedback received suggests that human interaction remains crucial for courses that require critical thinking, discussion, and emotional engagement. While AI improves accessibility and flexibility, an optimal approach may be to integrate AI for foundational knowledge while retaining human-led discussions and mentoring. Balancing AI with Human Interaction This study underscores the potential importance of a hybrid approach that combines AI efficiency with human engagement. AI excels in delivering structured content, reducing instructor workload, and providing self-paced learning opportunities. However, students value human interaction for motivation, personalization, and deeper comprehension, especially in skill-based courses. AI-generated lectures can supplement traditional teaching, not replace it. Educators should strategically integrate AI where efficiency is key while maintaining human instruction for interactive and discussion-based learning. This balance ensures an engaging and effective learning experience. Ethical Considerations Universities must address intellectual property concerns when using AI-generated content, ensuring fair recognition and compensation for educators. The described workflow allows institutions to repurpose an instructor’s work for content delivery without the instructor’s direct involvement or compensation. Clear policies should be established to protect educators’ contributions and define ownership rights over AI-generated adaptations of their materials. Future Studies Future research should explore enhanced AI voice technology to improve pronunciation and engagement, AI-generated human-like video lectures, and interactive AI features for real-time student queries. In addition, future studies could examine whether giving students the ability to select from different AI voice models varying in tone, gender, or style impacts their engagement or comprehension. This customization may offer a pathway to bridge the current gap between technical effectiveness and emotional resonance in AI-delivered content. Studies should also investigate long-term impacts on learning retention and the ethical implications of AI in education, particularly regarding intellectual property rights. Declarations Funding The authors declare that no funds, grants, or other financial support were received during the preparation of this manuscript. Competing Interests The authors declare that they have no relevant financial or non-financial interests to disclose. Author Contributions All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Althaf Hussain Kallamadugu, Nurudeen Segun Lawal, Joseph Micheal Burgett, Dhaval Gajjar Kirk Bingenheimer. The first draft of the manuscript was written by Althaf Hussain Kallamadugu and all authors commented on previous versions of the manuscript. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7394155","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":501906041,"identity":"58ddc55b-529d-4862-ae89-d46bb407cecc","order_by":0,"name":"Althaf Hussain Kallamadugu","email":"","orcid":"","institution":"Clemson University","correspondingAuthor":false,"prefix":"","firstName":"Althaf","middleName":"Hussain","lastName":"Kallamadugu","suffix":""},{"id":501906042,"identity":"dacd419d-9991-4e30-adbf-3c128c23c5a6","order_by":1,"name":"Nurudeen Segun Lawal","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAx0lEQVRIiWNgGAWjYDACdhBRYMPABxc5QEgLM4gwSGNgI1XLYRK0mDMzP5P4YXBeno29O/nDxx0Mcnw3EvBrsWxmM5PsMbht2MZzdpvkzDMMxpKEtACdZHaDx+B2AptE7jZm3jaGxA2EtbB/u/nH4FwCm/zbzZ+BWuqJ0MJjdpvH4ADQFt4N0kAtCQZEaCn/LWOQDPRLLtAvbRKGM888IKDlePtmwzcVdvL87Gc3f/jYZiPPd5yALehAgjTlo2AUjIJRMAqwAwA4e0CUmnlMdgAAAABJRU5ErkJggg==","orcid":"","institution":"Clemson University","correspondingAuthor":true,"prefix":"","firstName":"Nurudeen","middleName":"Segun","lastName":"Lawal","suffix":""},{"id":501906043,"identity":"fd831b57-3e4a-41dd-92d0-09fd10994542","order_by":2,"name":"Joseph Michael Burgett","email":"","orcid":"","institution":"Clemson University","correspondingAuthor":false,"prefix":"","firstName":"Joseph","middleName":"Michael","lastName":"Burgett","suffix":""},{"id":501906044,"identity":"98dd98ea-ea86-41e8-ab14-5cae0f327f97","order_by":3,"name":"Dhaval Gajjar","email":"","orcid":"","institution":"Clemson University","correspondingAuthor":false,"prefix":"","firstName":"Dhaval","middleName":"","lastName":"Gajjar","suffix":""},{"id":501906045,"identity":"48b20c9d-d850-4e40-8daf-409fa05532cb","order_by":4,"name":"Kirk Bingenheimer","email":"","orcid":"","institution":"Clemson University","correspondingAuthor":false,"prefix":"","firstName":"Kirk","middleName":"","lastName":"Bingenheimer","suffix":""}],"badges":[],"createdAt":"2025-08-17 19:38:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7394155/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7394155/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":89887175,"identity":"9d4851de-fad4-4f0f-b976-6edb1675ac47","added_by":"auto","created_at":"2025-08-26 06:51:48","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":139985,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 2. Stages of the methodology.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-7394155/v1/bdbde91d17e2f634201bc98e.png"},{"id":89885932,"identity":"6e4fb102-269e-4dc6-bba4-d72d80d33eec","added_by":"auto","created_at":"2025-08-26 06:35:48","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":110801,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 3 Steps of Workflow for creating AI-narrated presentations.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-7394155/v1/72de5c8cd7dedca1c48c5c47.png"},{"id":89885933,"identity":"d9bba3a6-0cd6-49cf-a556-ddf74a7f8523","added_by":"auto","created_at":"2025-08-26 06:35:48","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":249464,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 4. PPT with human voice-over and the extracted transcripts.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-7394155/v1/58756efe0f1ee431dab9156c.png"},{"id":89885941,"identity":"2cdcb62a-e387-4afe-b6d7-623da4cb0f1e","added_by":"auto","created_at":"2025-08-26 06:35:48","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":672171,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 5. Comparison of AI transcripts along with human corrected transcript.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-7394155/v1/14ced0b3ff651e9c92f03eba.png"},{"id":89885943,"identity":"f42dc042-f8c9-46e0-a7b6-0deb25cb74ca","added_by":"auto","created_at":"2025-08-26 06:35:48","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":182997,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 6. Verified pronunciation using Word's 'Read Aloud' feature and generated audio with ElevenLabs.\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-7394155/v1/f5b63d7d2bd06a7c92a82738.png"},{"id":89886922,"identity":"e5950b06-e685-4d3d-9a0a-d172a9283444","added_by":"auto","created_at":"2025-08-26 06:43:48","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":204584,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 7. Created closed captions with KwiCut and replaced the audio with adjusted animations in Storyline.\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-7394155/v1/c6d9e927bd9652433a7bdcc6.png"},{"id":89886924,"identity":"86ed6ae1-fa8a-48c7-a538-4292f90e77b0","added_by":"auto","created_at":"2025-08-26 06:43:48","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":139999,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 8. Distributional Analysis of Part 107 Test Scores for the Human Voice-Over Group: Histogram and Q–Q Plot\u003c/p\u003e","description":"","filename":"image8.png","url":"https://assets-eu.researchsquare.com/files/rs-7394155/v1/4f3def0f66d9199a7229f704.png"},{"id":89885964,"identity":"e5e344c5-57cf-4f86-aee4-90ccca8c309f","added_by":"auto","created_at":"2025-08-26 06:35:49","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":132375,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 9. Distributional Analysis of Part 107 Test Scores for the AI Voice-Over Group: Histogram and Q–Q Plot\u003c/p\u003e","description":"","filename":"image9.png","url":"https://assets-eu.researchsquare.com/files/rs-7394155/v1/227970568441ceeba55a42f3.png"},{"id":89885959,"identity":"f6f73c54-dfca-4d58-9372-28e642081ce0","added_by":"auto","created_at":"2025-08-26 06:35:48","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":58404,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 10. Two-tailed t-test decision chart for Part 107 knowledge test scores (df = 80).\u003c/p\u003e","description":"","filename":"image10.png","url":"https://assets-eu.researchsquare.com/files/rs-7394155/v1/b7ebea41003b56763ede7344.png"},{"id":89885942,"identity":"de6b3567-dc46-4806-933f-74b8bd0eae28","added_by":"auto","created_at":"2025-08-26 06:35:48","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":165283,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 11. Comparison of Part 107 Test Scores (Mann-Whitney U Test)\u003c/p\u003e","description":"","filename":"image11.png","url":"https://assets-eu.researchsquare.com/files/rs-7394155/v1/69882a28c24d95e3f69ad2c9.png"},{"id":89885966,"identity":"bb2a104e-1a26-4c89-be97-86f61218055b","added_by":"auto","created_at":"2025-08-26 06:35:49","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":377767,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 12. Image of the interface of QDA Miner Lite software used for analysis.\u003c/p\u003e","description":"","filename":"image12.png","url":"https://assets-eu.researchsquare.com/files/rs-7394155/v1/3cf6aeab9da217db2c2747c0.png"},{"id":89885957,"identity":"4bfdf394-2ac6-479b-ab94-c1747c97624e","added_by":"auto","created_at":"2025-08-26 06:35:48","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":494137,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 13. Image of the interface of QDA Miner Lite software used for analysis\u003c/p\u003e","description":"","filename":"image13.png","url":"https://assets-eu.researchsquare.com/files/rs-7394155/v1/589c669fbf4cf72939ab9d76.png"},{"id":89885967,"identity":"f5a459af-79b5-467e-bfef-b051e7485db8","added_by":"auto","created_at":"2025-08-26 06:35:49","extension":"png","order_by":13,"title":"Figure 13","display":"","copyAsset":false,"role":"figure","size":261076,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 14. Content analysis for the research and its phase-wise procedure\u003c/p\u003e","description":"","filename":"image14.png","url":"https://assets-eu.researchsquare.com/files/rs-7394155/v1/dfd254e822a7cf199f168c6a.png"},{"id":104962772,"identity":"b0061140-1a18-4722-ba78-404b291e69d7","added_by":"auto","created_at":"2026-03-19 09:14:11","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4577614,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7394155/v1/0e680d35-8f36-4a80-b684-eba0e2d4f5ec.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Assessing Student Satisfaction Using Lectures Generated by Artificial Intelligence (AI)","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe evolution of education has been significantly influenced by advancements in technology, transitioning from traditional classroom instruction to digital learning platforms. The widespread availability of high-speed internet, mobile devices, and AI tools has transformed learning experiences, offering students greater accessibility and flexibility (Guo, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Online education has emerged as a viable alternative to conventional in-person learning, with institutions adopting innovative methods such as flexible delivery, technology-enhanced engagement, and hybrid models to enhance student performance, satisfaction, and retention (Najjar, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Among these developments, AI-generated instructional materials particularly voice-over lectures have gained attention for their potential to replicate traditional teaching methods while optimizing efficiency and accessibility (Kallamadugu \u0026amp; Burgett, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAI applications in education\u0026mdash;such as intelligent tutoring systems, adaptive learning platforms, and automated assessments\u0026mdash;deliver personalized learning experiences catered to individual student needs (Gligorea \u0026amp; Mihăilă, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). While AI-driven instructional technologies have demonstrated effectiveness in enhancing teaching quality, their use in voice-over lectures remains underexplored (Pang et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). This study examines the effectiveness of AI-generated voice-over lectures in comparison to human-narrated presentations in preparing students for the FAA Part 107 exam for commercial small sUASs. By evaluating student satisfaction, engagement, and performance, the research seeks to determine whether AI-generated lectures offer a comparable learning experience to traditional methods.\u003c/p\u003e\u003cp\u003eThe integration of AI-generated instructional content raises important questions regarding the role of human interaction in online education. While AI offers consistency in content delivery, students may perceive the absence of human presence as a limitation in engagement and comprehension. Additionally, concerns regarding the clarity, intonation, and perceived effectiveness of AI-narrated lectures compared to human instructors necessitate further investigation. Given the increasing reliance on AI in educational settings, understanding its impact on student outcomes is crucial for informed decision-making in instructional design.\u003c/p\u003e\u003cp\u003eThe FAA Part 107 exam is a standardized certification process ensuring that remote pilots possess the necessary knowledge and skills for safe and compliant drone operation (FAA, 2024). Lawal et., al 2024 found that FAA Part 107\u0026ndash;related topics ranked as the critical component of a UAS curriculum, emphasizing the exam\u0026rsquo;s central role in drone training programs. Because Part 107 preparation is already an established component of drone training programs, it provides a structured framework for evaluating instructional effectiveness. This study explores whether AI-generated voice-over lectures can effectively prepare students for the Part 107 exam, providing insights into the feasibility of AI-driven instructional methods in specialized technical training.\u003c/p\u003e\n\u003ch3\u003eSignificance of the Study\u003c/h3\u003e\n\u003cp\u003eThe findings of this research contribute to the broader discourse on AI adoption in education, particularly in specialized certification training. By analyzing student performance and feedback, the study provides empirical evidence regarding the feasibility of AI-generated lectures as an alternative to human instruction. Additionally, the research informs best practices for integrating AI-driven content into online education, ensuring that technological advancements align with pedagogical objectives. Given the increasing reliance on AI in digital learning environments, this study offers valuable insights for educators, instructional designers, and policymakers seeking to enhance the effectiveness of online education.\u003c/p\u003e\u003cp\u003eAs AI technologies continue to evolve, their application in technical training programs can streamline instructional processes, reduce costs, and improve accessibility. By assessing the potential of AI-generated voice-over lectures in preparing students for the FAA Part 107 exam, this research provides a foundation for further exploration into AI-driven educational methodologies in aviation and other technical disciplines.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eResearch Questions\u003c/h2\u003e\u003cp\u003eThis study aims to address the following research questions:\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eCan artificial intelligence (AI) be used to recreate traditional voice-over PowerPoint lectures in a manner that provides a comparable learning experience and yields similar assessment outcomes?\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eTo what extent does the use of a human voice, compared to an AI-generated voice, influence the effectiveness of online instruction?\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eResearch Objectives\u003c/h3\u003e\n\u003cp\u003eTo achieve the study\u0026rsquo;s aims, the following research objectives are established:\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eTo evaluate the impact of AI-generated voice-over PowerPoint lectures on student learning and performance on the FAA Part 107 knowledge exam for unmanned aircraft systems (UASs)\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eTo compare AI-voiced lectures with traditional human-delivered lectures in the context of Part 107 exam preparation, identifying any differences in the learning experience and assessment results.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eTo investigate the role of human voice in online asynchronous courses and its relationship to student satisfaction and performance on the Part 107 exam.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e"},{"header":"Literature Review","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003eArtificial Intelligence\u003c/h2\u003e\u003cdiv id=\"Sec7\" class=\"Section3\"\u003e\u003ch2\u003eDefinition and Functionality of AI\u003c/h2\u003e\u003cp\u003eAI systems\u0026mdash;comprising both software and hardware components\u0026mdash;are engineered to perform complex tasks in physical or digital environments. These systems collect, interpret, and reason over both structured and unstructured data to determine optimal actions that align with specified goals (Mikalef et al., 2021). AI systems can adapt their behavior by learning from past actions and environmental feedback (Mathis, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eGPT vs. LLM\u003c/h2\u003e\u003cp\u003eGenerative Pre-trained Transformers (GPT), such as OpenAI\u0026rsquo;s ChatGPT, are large language models built on transformer architecture that generate coherent, human-like text using advanced attention mechanisms (Roumeliotis, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Large Language Models (LLMs) include GPT and other models like BERT, representing various transformer-based approaches trained on extensive datasets for natural language understanding and generation (Zhou et al., 2023).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eChatGPT\u003c/h3\u003e\n\u003cp\u003eChatGPT leverages GPT architecture to deliver conversational, human-like text generation through advanced transformer-based language modeling (Ray \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eChatGPT was initially launched using GPT-3.5 and later upgraded to GPT-5. These models are trained not only with supervised fine-tuning but also with reinforcement learning from human feedback (RLHF), enabling them to generate high-quality responses for tasks such as content creation, answering queries, and language translation (OpenAI, 2022; Ouyang et.al., 2022). Despite concerns about the quality of text generated for academic purposes, ChatGPT has been praised for its efficiency in producing program code and responding to structured queries (Stokel-Walker, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eAI in Online Higher Education\u003c/h3\u003e\n\u003cp\u003eAI in education, or AIEd, integrates AI tools into teaching, learning, and administrative functions to enhance educational experiences (Hwang et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Complementing these findings, Kallamadugu et.al \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2024\u003c/span\u003e detailed a practical workflow for creating narration for voice-over presentations using commercially available AI tools illustrating how educators can integrate AI seamlessly into content production processes. AI technologies are increasingly used to generate personalized learning resources, predict student performance, and automate the assessment process (Halkiopoulos \u0026amp; Gkintoni, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Instructors can use AI as a tutor, automating repetitive tasks and offering customized learning paths based on students' needs (Hwang et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). AI can empower administrators to make evidence-based decisions regarding course content and pedagogical strategies, improving both curriculum quality and instructional effectiveness (Sposato, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Artificial Intelligence in Education (AIEd) transforms the learning experience by enabling personalized instruction and delivering real-time feedback to learners (Tapalova \u0026amp; Zhiyenbayeva, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eBest Practices in Online Education\u003c/h2\u003e\u003cdiv id=\"Sec12\" class=\"Section3\"\u003e\u003ch2\u003eEngaging Students in Online Learning\u003c/h2\u003e\u003cp\u003eCreating an interactive and student-centered environment is essential for effective online learning, fostering deeper engagement and improving learning outcomes (Rayens \u0026amp; Ross, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Teachers should foster active participation and enrich learning by utilizing multimedia, delivering personalized feedback, and grounding instruction in real-world examples, thereby creating engaging and meaningful educational environments (Kerimbayev et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Additionally, instructors should strategically leverage educational technologies and adopt a flexible teaching style to sustain high levels of student engagement and accommodate diverse learning needs (Rapanta et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eVoice tonality, including factors such as pitch, rhythm, and intonation, has been shown to significantly influence student engagement and comprehension in online learning environments. Studies indicate that learners are more likely to maintain attention and feel connected to the content when the narration includes natural variations in tone, as opposed to flat or synthetic delivery (Paulmann \u0026amp; Weinstein, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eCreating a Sense of Community\u003c/h2\u003e\u003cp\u003eCollaboration and community are essential in online education. Instructors can foster these outcomes through collaborative learning activities, addressing specific group needs, and facilitating peer-to-peer interactions, which promote deeper engagement and knowledge construction (Laal \u0026amp; Ghodsi, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Smaller groups formed with attention to learners\u0026rsquo; time zones and schedules support effective synchronous collaboration, while asynchronous tools (e.g., LMS discussion boards, writing tools) scale well for larger cohorts (Oyarzun \u0026amp; Martin, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eTechnological Tools for Online Education\u003c/h2\u003e\u003cp\u003eEffective online education depends on selecting appropriate technologies, and instructors\u0026rsquo; familiarity and competence with these tools are critical for effective course facilitation (Rapanta et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Clear expectations, regular and substantive instructor interaction (including timely updates), and accessibility-oriented course design have all been linked to improved engagement, satisfaction, and learning outcomes in online education (Sweetman, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Teachers should also create inclusive and engaging learning environments by leveraging technology to enhance participation, foster motivation, and support diverse learner needs (Bond et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eImplementation of Artificial Intelligence in Online Education\u003c/h2\u003e\u003cdiv id=\"Sec16\" class=\"Section3\"\u003e\u003ch2\u003eBest Practices for AI Integration\u003c/h2\u003e\u003cp\u003eIncorporating AI into online learning environments requires thoughtful planning and a clear understanding of AI\u0026rsquo;s capabilities and limitations to ensure it enhances, rather than disrupts, the learning process (Zawacki-Richter et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). AI can support education by streamlining administrative tasks, delivering personalized learning experiences, and providing real-time feedback to students (Chen et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, AI should complement human interaction, as it cannot replace the nuanced guidance provided by educators. Ethical concerns regarding data usage and transparency are critical considerations in AI-powered classrooms (Holstein and Aleven \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003ePersonalized Learning with AI\u003c/h2\u003e\u003cp\u003eAI tools can analyze student data to deliver personalized learning experiences, dynamically adjusting curricular content to match individual learners\u0026rsquo; needs (Al Nabhani et.al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). AI can deliver immediate, tailored feedback and recommend targeted resources to enhance learning (Ma et.al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; da Silva et.al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). These tools support diverse learning pathways by adapting to each student\u0026rsquo;s level of understanding, thereby enhancing educational outcomes through targeted instruction (Xie et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eEffective Use of AI in Education\u003c/h2\u003e\u003cp\u003eAI can enhance teaching by automating routine administrative tasks, delivering personalized instruction, and supporting students through intelligent tutoring systems (Zawacki-Richter et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). For AI tools to be used effectively, they must align with clearly defined educational objectives while maintaining a balance between technological support and meaningful human interaction (Holstein \u0026amp; Aleven, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Educators must guide learning, foster critical thinking, and ensure the responsible use of AI to optimize educational outcomes (Zawacki-Richter et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003eUnmanned Aircraft Systems\u003c/h2\u003e\u003cdiv id=\"Sec20\" class=\"Section3\"\u003e\u003ch2\u003eOverview of Drone Technology\u003c/h2\u003e\u003cp\u003eDrones, or Unmanned Aircraft Systems (UASs), are aircraft that operate without a pilot on board. They are used for various applications, including surveillance, mapping, and monitoring, and are increasingly utilized in the construction industry for tasks like surveying, inspections, and safety management (Lawal et.al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Burgett, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003eDrones Role in Construction\u003c/h2\u003e\u003cp\u003eUASs are transforming the construction industry by enabling enhanced data collection for site monitoring and inspection, which in turn improves operational efficiency and safety (Liang, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Zhou, 2024). They are used for tasks such as monitoring construction progress, mapping sites, and performing inspections (Zaychenko et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Drones offer unique aerial perspectives on construction sites, significantly enhancing safety, productivity, and project quality (Choi et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\u003ch2\u003eChallenges and Opportunities with Drones\u003c/h2\u003e\u003cp\u003eWhile drones provide numerous benefits\u0026mdash;such as improved safety and operational efficiency\u0026mdash;their integration into construction operations also presents challenges including privacy concerns and regulatory compliance (Daoud et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Krook, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Companies must address these issues through proper training and compliance with FAA regulations (FAA, 2016). Effective planning is crucial for maximizing the benefits of drones in construction while minimizing risks (Hasa, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cdiv id=\"Sec23\" class=\"Section3\"\u003e\u003ch2\u003eFAA Part 107 Certification\u003c/h2\u003e\u003cp\u003eThe FAA's Part 107 regulations govern the commercial use of drones in the U.S. This includes certifications for remote pilots, operational limits, and safety requirements (FAA, 2016). Passing the Part 107 knowledge test is a requirement for commercial drone pilots, ensuring they are equipped with the necessary knowledge for safe and legal drone operations (Burgett, J. M., \u0026amp; Dees, C. 2023). See table 1 for companies offering jobs to drone pilots (Dumpati, CT, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTable 1 Firms offering jobs to drone pilots (Dumpati, CT, 2023)\u003c/p\u003e\u003cp\u003e\u003cimg 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\" width=\"584\" height=\"251\"\u003e\u003c/p\u003e\u003cdiv id=\"Sec24\" class=\"Section2\"\u003e\u003ch2\u003eResearch Gap\u003c/h2\u003e\u003cp\u003eWhile AI has been integrated into online education, particularly in personalized learning and automated assessments, there is a gap in research regarding the effectiveness of AI-generated voice-over lectures compared to human-narrated ones, especially for specialized certification exams like the FAA Part 107 exam. The literature often overlooks the importance of the human voice in asynchronous learning environments. The proposed study aims to fill this gap by comparing AI-generated and human-narrated lectures and assessing their impact on learning outcomes, using the Part 107 exam for the study\u0026rsquo;s experiment. This research will provide insights into the role of AI in education and inform best practices for integrating AI without compromising the human element essential for effective learning.\u003c/p\u003e"},{"header":"Methodology","content":"\u003cdiv id=\"Sec25\" class=\"Section3\"\u003e\u003cdiv id=\"Sec26\" class=\"Section4\"\u003e\u003ch2\u003eOverview of Experiment\u003c/h2\u003e\u003cp\u003eThe methodology begins with a comprehensive literature review to understand the existing research on the use of AI in online education. Next, a workflow was developed to generate AI voice-over lectures specifically for an existing drone course. Following this, the Part 107 section of [INSERT COURSE NUMBER AND NAME] was updated with AI-generated course materials.\u003c/p\u003e\u003cp\u003eThe effectiveness of the AI voice-over lectures were then assessed by comparing the Part 107 exam scores of students in the traditional drone course section with those in the course using AI voice-over lectures. A quantitative survey was administered to both control (students in the traditional voice-over course) and experimental (students in the AI voice-over course) groups to collect data on their experiences. The survey results was analyzed quantitatively to compare the student experiences.\u003c/p\u003e\u003cp\u003eAdditionally, qualitative data was gathered through interviews with students from the experimental group who were exposed to the AI-generated lectures. The interview data was coded and analyzed to provide a deeper understanding of their experiences.\u003c/p\u003e\u003cp\u003eThis paper presents the research findings based on the results from the quantitative surveys, qualitative interviews, and exam score comparisons. In summary, this mixed-methods approach combines both quantitative data (from surveys and exam scores) and qualitative data (from interviews) to evaluate the effectiveness of AI-generated voice-over lectures in online drone education. The results will offer valuable insights into the integration of AI technologies in online education and their impact on student learning and engagement. Figure\u0026nbsp;2 outlines the methodology flow chart.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec27\" class=\"Section3\"\u003e\u003ch2\u003eOverview of the \u0026ldquo;Workflow\u0026rdquo;\u003c/h2\u003e\u003cp\u003eThe methodology involves a step-by-step process to generate AI voice-over lectures from existing human voice-over lectures. This research refers to this process as the \u0026ldquo;Workflow.\u0026rdquo; Initially, audio is extracted from the existing PowerPoint lecture files, converted into text using online tools, and then refined with ChatGPT. The generated transcripts undergo multiple rounds of cleaning using ChatGPT 4.0, along with human proofreading to enhance accuracy and relevance.\u003c/p\u003e\u003cp\u003eThe final transcript is reviewed and fine-tuned by a subject matter expert. In this case, the subject matter expert was the instructor of the drone course and author of the PowerPoint lectures. AI-generated voice narration for the lecture files was then created from the refined transcript using a text-to-speech application. Closed captions were generated from the audio files and manually proofread. The human voice-over lectures were then recreated using the AI-generated audio, enhanced with closed captions and synchronized animations.\u003c/p\u003e\u003cp\u003eFurthermore, the transcripts were organized into a study guide, complete with a thumbnail image of the PowerPoint slide and a place for the students to take notes. An AI chatbot, trained on the study guide, transcripts and other publicly available Part 107 resources, was developed to assist students with any questions. This comprehensive Workflow converts traditional lectures into AI-generated voice-overs and creates additional resources such as study guides and chatbots to enhance the learning experience. Figure\u0026nbsp;3 illustrates the methodology of \"The Workflow.\"\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec28\" class=\"Section2\"\u003e\u003ch2\u003eThe \u0026ldquo;Workflow\u0026rdquo; Adapted for this Experiment\u003c/h2\u003e\u003cdiv id=\"Sec29\" class=\"Section3\"\u003e\u003ch2\u003eStep 1: Create Transcripts by Extracting Audio from the Existing Course\u003c/h2\u003e\u003cp\u003eThe researchers began by extracting audio files from the human-narrated Power Point presentations and converting them into text using the online tool KwiCut. These initial transcripts were then refined with ChatGPT to improve clarity and coherence.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\n\u003ch3\u003eStep 2: Clean and Fine-Tune the Transcript Using ChatGPT\u003c/h3\u003e\n\u003cp\u003eTo enhance the quality of the transcripts, the researchers used ChatGPT with a structured prompt aimed at rephrasing the lecture content in a professional yet approachable tone. Transcripts were initially edited using ChatGPT 3.5 and further refined with ChatGPT 4.0. Subject matter experts then reviewed the transcripts for clarity and accuracy, followed by manual proofreading by the research team. Final revisions were streamlined using a simplified prompt with ChatGPT 4.0, resulting in polished transcripts ready for the next step.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv id=\"Sec31\" class=\"Section2\"\u003e\u003ch2\u003eStep 3: Create Audio Lecture Files from the Fine-Tuned Transcript\u003c/h2\u003e\u003cp\u003e The finalized transcripts were reviewed for pronunciation using Word\u0026rsquo;s \"Read Aloud\" feature. They were then imported into the online text-to-speech application ElevenLabs. A deep American male accent voice profile (Antoni) was selected for its natural, human-like quality. It was found that when long transcripts were provided to the text-to-speech prompt, it increased the chance of mispronounced words. To ensure consistency in quality, longer transcripts were divided into smaller sections, producing high-quality audio files.\u003c/p\u003e\u003cp\u003e While the AI-generated narration provided a consistent and efficient means of delivering lecture content, some challenges with pronunciation were noted. Certain technical terms and abbreviations were occasionally mispronounced, leading to minor comprehension issues. To mitigate this, transcripts were segmented into smaller text inputs before synthesis, and pronunciation verification was conducted using Word\u0026rsquo;s \u0026lsquo;Read Aloud\u0026rsquo; feature. However, future improvements could involve using AI models with user-customizable pronunciation dictionaries or training AI voices specifically on subject-matter vocabulary to enhance accuracy.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eStep 4: Create Closed Caption Files from Audio Files \u0026amp; Recreate Human Lectures with AI-Generated Material\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThe finalized audio files were used to create closed captions with the KwiCut, exporting the captions in SRT format. These captions were manually proofread for accuracy and then integrated into the presentation software Storyline, produced by Articulate. The original human-narrated audio was replaced with AI-generated narration, and animations were synchronized with the new audio and captions. This process successfully transformed the original human lecture presentations into AI-narrated versions, ensuring consistency and maintaining quality across all materials.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eStep 5: Develop a study guide and AI chatbot using fine-tuned transcripts and FAA study materials\u003c/em\u003e\u003c/p\u003e\u003cp\u003eWith the completion of the AI-generated lectures, the researchers created a study guide based on fine-tuned transcripts. This guide helps students understand class material and includes a notes section for key takeaways. Following this, we developed a chatbot trained on the study guide and publicly available Part 107 material, allowing students to get answers to their questions on their own.\u003c/p\u003e\u003cp\u003eExample of Human narrated lecture: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://demo-drone-course.s3.amazonaws.com/course1/human-voice-presentation/story.html\u003c/span\u003e\u003cspan address=\"https://demo-drone-course.s3.amazonaws.com/course1/human-voice-presentation/story.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003cp\u003eExample of AI narrated lecture: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://demo-drone-course.s3.amazonaws.com/course2/ai-voice-presentation/story.html\u003c/span\u003e\u003cspan address=\"https://demo-drone-course.s3.amazonaws.com/course2/ai-voice-presentation/story.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec32\" class=\"Section2\"\u003e\u003ch2\u003eQuantitative Analysis\u003c/h2\u003e\u003cp\u003eThis research employs quantitative analysis to measure the impact of AI-generated voice-over lectures on student performance and satisfaction in preparing for the FAA Part 107 exam. Data was collected through surveys and exam scores, offering objective insights into whether AI-generated lectures can provide a learning experience comparable to human-narrated lectures.\u003c/p\u003e\u003cp\u003eThe study compares two groups: one receiving AI-generated lectures and the other traditional human-narrated lectures. Key metrics include exam scores and satisfaction survey responses, allowing for a statistical comparison of outcomes. This analysis aims to determine if AI lectures match or exceed the effectiveness of human narration in preparing students for the Part 107 exam.\u003c/p\u003e\u003cp\u003eBeyond performance, student satisfaction surveys assess perceptions of AI-generated lectures regarding clarity, engagement, and overall learning experience. These measurable insights complement qualitative findings, offering a comprehensive evaluation of AI\u0026rsquo;s potential in education.\u003c/p\u003e\u003cdiv id=\"Sec33\" class=\"Section3\"\u003e\u003ch2\u003ePart 107 Test Scores\u003c/h2\u003e\u003cp\u003eIn Fall 2023 and Spring 2024, 59 students completed the human voice-over course and took the Part 107 knowledge test. In Summer 2024 and Fall 2024, 44 students completed the AI voice-over course and also took the same knowledge test. Their test scores were collected to evaluate the impact of each lecture format on knowledge retention. Before conducting inferential statistical tests, the distribution of scores for each group was examined to assess the assumption of normality. Visual inspection using histograms and Q\u0026ndash;Q plots (Figs.\u0026nbsp;8 and 9) indicated that the human voice-over group\u0026rsquo;s scores were approximately symmetric and aligned closely with the theoretical normal distribution. The AI voice-over group also displayed a generally symmetric distribution, although slight deviations were observed in the lower tail.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eGiven the slight deviation from normality in one group, both parametric (Welch\u0026rsquo;s t-test) and non-parametric (Mann\u0026ndash;Whitney U test) approaches were applied to compare group performance, ensuring robustness of results. Table\u0026nbsp;2 presents the T-test results, highlighting the comparative effectiveness of AI-generated versus human-narrated lectures in preparing students for the Part 107 exam.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eT-test table for Part 107 Knowledge Test Scores\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003et-Test: Two-Sample Assuming Unequal Variances\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eControl Group Students\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eExperimental Group Students\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e85.22033898\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e85.76363636\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e38.23130333\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e60.474926\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eObservations\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e44\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypothesized Mean Difference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003edf\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003et Stat\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.382034087\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eP(T\u0026thinsp;\u0026lt;\u0026thinsp;=\u0026thinsp;t) one-tail\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.351724519\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003et Critical one-tail\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.664124579\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eP(T\u0026thinsp;\u0026lt;\u0026thinsp;=\u0026thinsp;t) two-tail\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.703449039\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003et Critical two-tail\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.990063421\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;2 (above) shows the results of the two-sample t-test comparing Part 107 knowledge test scores between the human voice-over and AI voice-over groups. Figure\u0026nbsp;10 illustrates the two-tailed t-test decision chart, visually depicting the observed t statistic in relation to the rejection regions.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe black curve represents the t-distribution under the null hypothesis. The red shaded regions indicate the rejection zones at α\u0026thinsp;=\u0026thinsp;0.05, with critical values at \u0026plusmn;\u0026thinsp;1.990. The blue vertical line marks the observed t statistic (t = \u0026minus;\u0026thinsp;0.382), which lies well within the acceptance region.\u003c/p\u003e\u003cp\u003eThe difference in mean scores between the two groups was 0.54 points on a 100-point scale, with the AI voice-over group scoring slightly higher. The null hypothesis proposed no significant difference in Part 107 knowledge test results, whereas the alternative hypothesis posited a difference. This finding indicates that the observed difference is not statistically significant, suggesting that both instructional formats yielded comparable exam performance.\u003c/p\u003e\u003cp\u003eMann-Whitney U test is conducted to complement the T-test, comparing Part 107 test scores between students of control group and experimental group. The U statistic is 1211.0, and the p-value is 0.563, which is greater than the 0.05 significance threshold. Figure\u0026nbsp;11 shows a boxplot showing that the median scores and score distributions are comparable, with similar variability and a few outliers in both groups. The Mann-Whitney U test indicates that there is no statistically significant difference in test scores between the two groups. This reinforces the T-test results and confirms that AI-generated lectures were as effective as human-narrated lectures in preparing students for the exam. These findings suggest that AI-generated lectures provide a learning experience equivalent to human narration, making them a viable alternative in educational settings.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSurvey\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA survey was conducted with the experimental group, which included the standard course evaluation questions provided by XXX University, as well as targeted questions on the AI voice-over lectures, chatbot usage, and tutorial notes. The survey employed a Likert scale (1 to 5) to assess overall student satisfaction. The collected data was statistically analyzed to measure satisfaction levels and evaluate the effectiveness of both course formats. This quantitative data directly addresses the second research objective.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCourse Evaluation Survey Questions\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere were nine Likert Scale questions from XXX University\u0026apos;s standard end-of-year course evaluation survey included with the survey provided to the experimental group. A T-test was conducted to compare the responses of the control group and experimental group for each survey question. A summary of descriptive statistics is presented in Table 4. The Likert Scale questions from XXX University\u0026rsquo;s standard end-of-year questionnaire are outlined below.\u003c/p\u003e\n\u003cp\u003e1. The learning outcomes in the course were clearly communicated.\u003c/p\u003e\n\u003cp\u003e2. The course assignments were related to the course learning outcomes.\u003c/p\u003e\n\u003cp\u003e3. I understood what was expected of me in this course.\u003c/p\u003e\n\u003cp\u003e4. The instructor clearly explained concepts, methods, and subject matter.\u003c/p\u003e\n\u003cp\u003e5. The instructor encouraged questioning and discussion of course topics from the students.\u003c/p\u003e\n\u003cp\u003e6. The feedback on my performance on assignments and tests supported my learning.\u003c/p\u003e\n\u003cp\u003e7. The course challenged me to think critically and communicate clearly about the subject.\u003c/p\u003e\n\u003cp\u003e8. Approximately how many hours did you spend in a typical 7-day week on learning activities outside of class time for this course?\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e9. Please indicate your satisfaction with the availability of the instructor outside the classroom by choosing one response from the scale. In selecting your rating, consider the instructor\u0026apos;s availability via established office hours, appointments, and other opportunities for face-to-face or virtual interactions.\u003c/p\u003e\n\u003cp\u003eTable 3 Summary of Mean, Median \u0026amp; P-value of Course Evaluation Survey\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"576\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eQuestion No.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 198px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedian\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-Value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eControl Group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003eExperimental Group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eControl Group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003eExperimental Group\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e4.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e4.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e4.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e4.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e4.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e4.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e4.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e4.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e4.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e4.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e4.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e4.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e7\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e4.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e4.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e2.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e2.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e9\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e4.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e4.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe comparison between the control group and the experimental group revealed no statistically significant differences, as all P-values exceeded 0.05. This indicates that students perceived both methods as equally effective in terms of quality. Notably, both groups reported a high median score of 5 on key aspects such as learning outcomes, assignment clarity, and instructor availability. Despite the shift in teaching methodology, student satisfaction with AI-generated courses closely mirrors traditional approaches, reinforcing the potential of AI-driven education to uphold the standards set by human instruction.\u003c/p\u003e\n\u003cp\u003eThe Mann-Whitney U Test was also conducted to evaluate differences between the Control Group and the Experimental Group across nine survey questions. Here again, all p-values were greater than 0.05, indicating there was no statistically significant difference between the two groups.\u003c/p\u003e\n\u003cp\u003eWhen compared with the T-Test, the Mann-Whitney U Test provides a robust non-parametric alternative for cases where normality is uncertain. The alignment between both tests strengthens the statistical reliability of the findings. Boxplots and p-value charts further support this conclusion, showing consistent response distributions across both groups. Since no significant differences emerged, these results confirm that AI-based teaching methods can be effectively integrated into online education without compromising student experience.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAI-Related Course Evaluation Survey Questions\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe experimental group received additional course evaluation questions specifically addressing AI-narrated lectures, listed as questions 10 and 11. As shown in Table 5, students expressed overall satisfaction with the quality of the Part 107 lecture materials, giving an average rating of 4.46 out of 5. However, when asked to compare AI narration to human narration, the rating was more moderate at 3.66, suggesting that while students found the AI voice adequate, they did not consider it superior to human narration. The questions related to AI-narrated lectures are provided below.\u003c/p\u003e\n\u003cp\u003e10. How satisfied were you with the quality of the material presented in the Part 107 lectures?\u003c/p\u003e\n\u003cp\u003e11. How would you rate the AI-generated voice of the Part 107 lectures compared to a similar presentation with a human narrator?\u003c/p\u003e\n\u003cp\u003eTable 4 Summary of Mean \u0026amp; Median of AI-related Course Evaluation Survey\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eQuestion No.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedian\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003e4.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e11\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003e3.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eWhile the results showed that AI-generated lectures were just as effective in delivering content, student feedback suggested that AI narration lacked the engagement of human instructors. This could be attributed to the lack of emotional inflection, natural pauses, or dynamic tone variations typically found in human speech. Prior research on online learning suggests that voice tonality plays a key role in student engagement, potentially explaining why some students favored human narration despite similar learning outcomes (Paulmann et al., 2025). Future improvements in AI voice synthesis, including more natural prosody and emotion-driven speech models, may help address this limitation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eChatbot \u0026amp; Study Guide Related Course Evaluation Survey Questions\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe experimental group received additional questions regarding the Chatbot and Study Guide, listed as questions 12 - 18. As presented in Table 6, students provided feedback on the effectiveness of these tools in understanding the Part 107 content. The Chatbot\u0026apos;s usefulness received an average rating of 3.48 out of 5, indicating that while it was considered helpful, it was not overwhelmingly beneficial. Additionally, the preference for asking questions to the Chatbot over a human instructor was rated at 3.06, suggesting that while students were moderately inclined to use the Chatbot, they still valued direct human interaction. The questions related to AI-narrated lectures are provided below.\u003c/p\u003e\n\u003cp\u003e12. \u0026nbsp; \u0026nbsp; \u0026nbsp; How useful did you find the Chatbot (Tiger Bot) when learning about Part 107? (Likert)\u003c/p\u003e\n\u003cp\u003e13. \u0026nbsp; \u0026nbsp; \u0026nbsp; Were you more inclined to ask the Chatbot (Tiger Bot) questions over your human instructor? (Likert)\u003c/p\u003e\n\u003cp\u003e14. \u0026nbsp; \u0026nbsp; \u0026nbsp; How helpful was the Chatbot (Tiger Bot) with understanding difficult concepts related to Part 107? (Likert)\u003c/p\u003e\n\u003cp\u003e15. \u0026nbsp; \u0026nbsp; \u0026nbsp; How strongly do you believe chatbots trained on course material should be integrated into future courses? (Likert)\u003c/p\u003e\n\u003cp\u003e16. \u0026nbsp; \u0026nbsp; \u0026nbsp; How helpful was the tutorial notes for understanding Part 107 concepts? (Likert)\u003c/p\u003e\n\u003cp\u003e17. \u0026nbsp; \u0026nbsp; \u0026nbsp; How frequently did you use the tutorial notes? (Likert)\u003c/p\u003e\n\u003cp\u003e18. \u0026nbsp; \u0026nbsp; \u0026nbsp; Select all of the statements about the tutorial notes that are true for you. \u0026nbsp; (Select multiple answers.)\u003c/p\u003e\n\u003cp\u003ea. I printed hard copies of some or all of them\u003c/p\u003e\n\u003cp\u003eb. I made handwritten notes on them\u003c/p\u003e\n\u003cp\u003ec. I made electronic notes on them\u003c/p\u003e\n\u003cp\u003ed. I used them to help study\u003c/p\u003e\n\u003cp\u003ee. I read them before I watch the lectures\u003c/p\u003e\n\u003cp\u003ef. I read them while I was watching the lectures\u003c/p\u003e\n\u003cp\u003eg. I read them after I watched the lectures\u003c/p\u003e\n\u003cp\u003eh. Other (write in):\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;..\u003c/p\u003e\n\u003cp\u003eTable 5 Summary of Mean \u0026amp; Median of Chatbot \u0026amp;Tutorial Notes Related Course Evaluation Survey\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eQuestion No.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedian\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e12\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003e3.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e13\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003e3.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e14\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003e3.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e15\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003e3.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e16\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e17\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003e3.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e18\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003e2.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe Chatbot\u0026apos;s effectiveness in explaining difficult concepts received a moderate rating of 3.37, indicating that students found it somewhat helpful. However, the idea of integrating Chatbots into future courses was rated higher, with an average score of 3.84, suggesting that students recognize its potential for future applications.\u003c/p\u003e\n\u003cp\u003eRegarding tutorial notes, students rated them highly useful for understanding Part 107 concepts, with an average score of 4.0. The frequency of usage was rated at 3.82, indicating regular but not constant reliance on these materials. Overall, these results reflect a positive yet cautious reception of AI-driven tools in the course.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eOpen-Ended Course Evaluation Questions\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe experimental group received additional open-ended questions in the course evaluation survey regarding the AI Part 107 Presentations and Chatbot, listed as questions 19 - 21. Student responses were collected, compiled into a Word document, and analyzed using QDA Miner Lite software.\u003c/p\u003e\n\u003cp\u003eThis qualitative analysis categorized responses into two main themes: \u0026quot;Feedback\u0026quot; and \u0026quot;Improvements.\u0026quot; The Feedback category included themes such as \u0026quot;Positive Feedback, Negative Feedback, and AI Voice Uncertainties,\u0026quot; reflecting student satisfaction and concerns. The Improvements category covered aspects like \u0026quot;Visual Aids, Course Content Coverage, Technical Issues, Voice Quality Concerns, Customization, and Human Inclusion,\u0026quot; identifying areas for course enhancement. Figure 3 illustrates the QDA Miner Lite analysis, summarizing key insights from student responses. The open-ended questions from the course evaluation survey are provided below.\u003c/p\u003e\n\u003col start=\"19\"\u003e\n \u003cli\u003eWhat improvements could be made to the Part 107 lectures? \u0026nbsp; (Write in)\u003c/li\u003e\n \u003cli\u003eWhat features or improvements would enhance the usefulness of the Chatbot (Tiger Bot) to you? \u0026nbsp;(write in)\u003c/li\u003e\n \u003cli\u003eIn what type of course do you think a chatbot would provide the most assistance? (Write in)\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eThe qualitative analysis of survey responses revealed a mix of positive feedback and areas for improvement. While many students appreciated the clarity of the course, some highlighted issues with the AI-generated voice, mentioning pronunciation errors and inconsistent accents. One student remarked, \u0026quot;The AI-generated voice terribly mispronounced a lot of simple words,\u0026quot; which affected comprehension.\u003c/p\u003e\n\u003cp\u003eAdditionally, students suggested incorporating more visual aids to enhance the understanding of complex topics. The preference for human interaction was evident, with some recommending traditional classroom settings over AI-driven content to improve the overall learning experience.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eQualitative Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe purpose of qualitative analysis in this study is to gain a deeper understanding of students\u0026rsquo; perceptions and experiences with AI-generated voice-over lectures compared to human-narrated lectures. While quantitative data from exam scores and surveys provide measurable outcomes of student performance and satisfaction, qualitative analysis helps uncover nuanced factors influencing these results. Specifically, this analysis explores how students perceive the effectiveness, engagement, and overall learning experience of AI-generated lectures.\u003c/p\u003e\n\u003cp\u003eThe Research team interviewed randomly selected students from the experimental group who completed the AI voice-over lectures to assess their perceptions, engagement, and satisfaction with AI-generated lectures in preparing for the Part 107 exam. The interview questionnaire featured open-ended questions focusing on comprehension, engagement, clarity, effectiveness, and overall satisfaction, encouraging students to compare AI-generated lectures with traditional human-narrated courses. Interviews were conducted via Zoom, recorded with participant consent, transcribed, and analyzed. Each session lasted approximately 20 minutes. Institutional Review Board (IRB) approval was obtained under protocol number IRB2024-0284-01, ensuring ethical compliance in the research process.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eInterview Process\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of nine voluntary participants took part in the interviews\u0026mdash;two students from the Summer 2024 cohort and seven from the Fall 2024 cohort. The research team facilitated structured discussions, asking probing follow-up questions based on students\u0026rsquo; responses to uncover deeper insights.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003ePost-Interview Processing\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFollowing the interviews, the responses and transcripts underwent systematic refinement. First, raw transcripts were compiled into a structured Word document. Next, transcripts were cross-referenced with original recordings to correct inconsistencies such as missing words or misinterpretations. To ensure anonymity, all transcripts were de-identified. Irrelevant dialogue and filler words were removed, and responses were formatted into a question-and-answer structure. This process ensured accuracy, enhanced data organization for future reference, and maintained the integrity of collected information, providing a strong foundation for qualitative analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eData Analysis\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEach student interview was analyzed individually, anonymized as S1\u0026ndash;S9, and uploaded into QDA Miner Lite for thematic coding. Transcripts were systematically reviewed, with key responses assigned specific codes. Recurring topics were grouped into sub-themes and broader themes, linking insights to the study\u0026rsquo;s research objectives. The software\u0026rsquo;s interface (Figure 13) organized individual interviews, stored relevant metadata, and structured coded themes, ensuring a clear and consistent analysis of student experiences with AI-generated lectures. This approach provided a structured method for identifying patterns in engagement, comprehension, and overall satisfaction.\u003c/p\u003e\n\u003cp\u003eSeveral students emphasized that while the AI narration provided clarity and consistency, it lacked the emotional resonance of human speech. This perception aligns with existing research in human-computer interaction, which underscores the importance of vocal emotion and prosody in maintaining learner engagement. As students reflected on their experiences, many attributed their preference for human narration to its ability to convey enthusiasm, urgency, or emphasis\u0026mdash;elements that are often flattened in synthetic voices. Integrating more expressive and dynamic AI-generated speech may enhance engagement in future iterations of AI-based instruction.\u003c/p\u003e\n\u003cp\u003eThe final stage of qualitative analysis involved categorizing the data into themes derived from coded interview responses. This process established connections between the research objectives and identified themes. By following this structured approach, the study ensured that student feedback was accurately captured and effectively analyzed. The findings contribute to a comprehensive understanding of how AI-generated voice-over lectures impact student engagement, comprehension, and overall learning experience, informing best practices for AI-driven educational content delivery. A representation of the framework, from the objectives to the generation of themes, can be observed in Figure 14.\u003c/p\u003e\n\u003cp\u003eFor instance, categories such as \u0026ldquo;AI Voice Clarity\u0026rdquo; and \u0026ldquo;Human Voice Engagement\u0026rdquo; are grouped under the sub-theme \u0026ldquo;Instructional Quality.\u0026rdquo; Similarly, \u0026ldquo;Learning Retention\u0026rdquo; and \u0026ldquo;Study Guide Usage\u0026rdquo; contribute to the sub-theme \u0026ldquo;Learning Effectiveness.\u0026rdquo; Sub-themes like \u0026ldquo;Technical Challenges\u0026rdquo; and \u0026ldquo;Visual Learning Aids\u0026rdquo; fall under \u0026ldquo;Technical Considerations.\u0026rdquo; These sub-themes collectively form broader themes, including \u0026ldquo;Comparative Effectiveness of AI vs. Human Instruction,\u0026rdquo; \u0026ldquo;Student Learning Preferences and Retention,\u0026rdquo; and \u0026ldquo;Challenges with AI Implementation.\u0026rdquo; This structured framework ensures a systematic approach to analysis, providing a clear progression from data collection to meaningful thematic insights.\u003c/p\u003e\n\u003cp\u003eNote: This study used ChatGPT solely for grammatical proofreading and text refinement all research findings and references are based on original work and verified sources.\u003c/p\u003e"},{"header":"Summary of Results","content":"\u003cp\u003e\u003cb\u003eComparison of Exam Performance\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe study compared the exam performance of the control group (59 students with human narration) and the experimental group (44 students with AI-generated narration) to evaluate the effectiveness of AI voice-over lectures for the FAA Part 107 exam preparation. A two-sample T-test revealed no statistically significant difference between the groups (p-value\u0026thinsp;=\u0026thinsp;0.35), with mean scores of 85.22 (control) and 85.76 (experimental). These results confirm that AI-generated narration is as effective as human narration in delivering course content and preparing students for the exam.\u003c/p\u003e\u003cp\u003e\u003cb\u003eStudent Satisfaction Survey\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSurvey results indicated no statistically significant difference in overall satisfaction between the groups (p-values\u0026thinsp;\u0026gt;\u0026thinsp;0.05). However, students in the experimental group rated \u0026ldquo;Accessibility\u0026rdquo; (mean\u0026thinsp;=\u0026thinsp;4.46/5, median\u0026thinsp;=\u0026thinsp;5) and \u0026ldquo;Consistent Pacing\u0026rdquo; higher due to AI\u0026rsquo;s uniform tone and clarity. Some students preferred human narration for its personal touch and engagement. AI-powered tools, such as the chatbot and tutorial notes, received mixed feedback\u0026mdash;while helpful for quick clarifications, they lacked the depth of human interaction. These findings highlight AI\u0026rsquo;s advantages in consistency and accessibility while underscoring the continued preference for human engagement in certain learning scenarios.\u003c/p\u003e\u003cp\u003e\u003cb\u003eEngagement and Learning Experience\u003c/b\u003e\u003c/p\u003e\u003cp\u003eStudents in the experimental group found AI-generated lectures engaging and effective, with a mean satisfaction score of 4.35/5. The P-value of 0.48 for engagement-related questions indicates no significant difference between AI and human-narrated lectures. AI\u0026rsquo;s consistency and clarity were well-received, but some students noted that human narration enhanced motivation and connection. The findings suggest that AI can effectively deliver course content but may not fully replicate the interactive and personal aspects of human instruction. Despite the comparable effectiveness of AI-generated and human-narrated lectures, student feedback highlighted the perceived lack of engagement in AI voices. This suggests that while AI-generated instruction is consistent and accessible, it does not yet fully replicate the natural cadence and emotional nuance of human speech.\u003c/p\u003e\u003cp\u003e\u003cb\u003eQualitative Interview Insights\u003c/b\u003e\u003c/p\u003e\u003cp\u003eStudent interviews provided deeper insights into AI-generated lectures. A minority preferred human narration for its emotional tone and engagement, while most found AI effective for delivering technical content. Some students highlighted mispronunciations of technical terms, which occasionally led to confusion.\u003c/p\u003e\u003cp\u003eOne limitation of AI-generated narration identified in this study was the occasional mispronunciation of technical terms. This was noted in both student feedback and the transcript refinement process. While adjustments such as segmenting transcripts and manually verifying pronunciation helped, future research could explore more sophisticated AI models that allow for phonetic customization. Additionally, enabling AI voices to learn from human corrections could significantly enhance the accuracy and effectiveness of AI-driven instruction.\u003c/p\u003e\u003cp\u003e\u003cb\u003eKey Themes from Interviews\u003c/b\u003e:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eComparative Effectiveness of AI vs. Human Instruction: AI was effective for structured content delivery, but human lectures fostered better engagement and motivation.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eStudent Learning Preferences and Retention: AI was preferred for clarity and consistency, while human narration was favored for complex or abstract topics.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eChallenges with AI Implementation: Issues like mispronunciations and a lack of emotional engagement were common concerns. Students suggested improvements in AI voice technology to enhance clarity and interaction.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eOverall, AI-generated lectures proved to be a viable alternative to human narration, offering efficiency and consistency. However, human instruction remains valuable for fostering engagement and deeper learning, especially in subjects requiring interaction and motivation.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003e\u003cb\u003eAI Lectures as a Viable Alternative\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis study confirms that AI-generated voice-over lectures are a viable alternative to human-narrated lectures for certain technical exam preparations. The quantitative analysis showed no significant difference in exam scores between students who received AI lectures and those who had human narration (p-value\u0026thinsp;=\u0026thinsp;0.703), indicating that AI can deliver effective instruction without compromising learning outcomes.\u003c/p\u003e\u003cp\u003eAI lectures offer key advantages, including consistent pacing, accessibility, and reduced instructor workload. Students appreciated the clarity of AI narration. AI also ensures uniform instruction, eliminating variability in tone and pacing seen in human lectures. Additionally, AI reduces the burden on instructors by automating lecture delivery, allowing them to focus on interaction and feedback.\u003c/p\u003e\u003cp\u003eHowever, human narration remains valuable for fostering engagement and motivation. Some students preferred the emotional tone and interactivity of human lectures, particularly for complex or abstract topics. While AI excels in technical and procedural content delivery, human elements enhance personal connection and engagement. Future educational strategies should blend AI and human instruction to maximize learning benefits.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePotential for Broader Application\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe scalability of AI-generated lectures makes them suitable for various online learning environments, particularly for structured, factual, or procedural subjects. AI ensures consistent content delivery, reducing variability in instruction. The success of AI in FAA exam preparation suggests its applicability in other standardized and technical courses.\u003c/p\u003e\u003cp\u003eDespite AI's benefits, the feedback received suggests that human interaction remains crucial for courses that require critical thinking, discussion, and emotional engagement. While AI improves accessibility and flexibility, an optimal approach may be to integrate AI for foundational knowledge while retaining human-led discussions and mentoring.\u003c/p\u003e\u003cp\u003e\u003cb\u003eBalancing AI with Human Interaction\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis study underscores the potential importance of a hybrid approach that combines AI efficiency with human engagement. AI excels in delivering structured content, reducing instructor workload, and providing self-paced learning opportunities. However, students value human interaction for motivation, personalization, and deeper comprehension, especially in skill-based courses.\u003c/p\u003e\u003cp\u003eAI-generated lectures can supplement traditional teaching, not replace it. Educators should strategically integrate AI where efficiency is key while maintaining human instruction for interactive and discussion-based learning. This balance ensures an engaging and effective learning experience.\u003c/p\u003e\u003cp\u003e\u003cb\u003eEthical Considerations\u003c/b\u003e\u003c/p\u003e\u003cp\u003eUniversities must address intellectual property concerns when using AI-generated content, ensuring fair recognition and compensation for educators. The described workflow allows institutions to repurpose an instructor\u0026rsquo;s work for content delivery without the instructor\u0026rsquo;s direct involvement or compensation. Clear policies should be established to protect educators\u0026rsquo; contributions and define ownership rights over AI-generated adaptations of their materials.\u003c/p\u003e\u003cp\u003e\u003cb\u003eFuture Studies\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFuture research should explore enhanced AI voice technology to improve pronunciation and engagement, AI-generated human-like video lectures, and interactive AI features for real-time student queries. In addition, future studies could examine whether giving students the ability to select from different AI voice models varying in tone, gender, or style impacts their engagement or comprehension. This customization may offer a pathway to bridge the current gap between technical effectiveness and emotional resonance in AI-delivered content. Studies should also investigate long-term impacts on learning retention and the ethical implications of AI in education, particularly regarding intellectual property rights.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that no funds, grants, or other financial support were received during the preparation of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Althaf Hussain Kallamadugu, Nurudeen Segun Lawal, Joseph Micheal Burgett, Dhaval Gajjar Kirk Bingenheimer. The first draft of the manuscript was written by Althaf Hussain Kallamadugu and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCRediT Taxonomy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization, Methodology, Data Curation, Formal analysis, Writing \u0026ndash; Original draft: Althaf Hussain Kallamadugu,\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMethodology, investigation, validation, Writing \u0026ndash; review \u0026amp; editing: Nurudeen Segun Lawal\u003c/p\u003e\n\u003cp\u003eSupervision, Resources, Writing \u0026ndash; review \u0026amp; editing: Joseph Micheal Burgett\u003c/p\u003e\n\u003cp\u003eValidation, visualization, review \u0026amp; editing: Dhaval Gajjar\u003c/p\u003e\n\u003cp\u003eValidation, visualization, review \u0026amp; editing: Kirk Bingenheimer \u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAgarwal, S., Slama, K., Ray, A., Schulman, J., Hilton, J., Miller, L., Simens, M., Askell, A., Welinder, P., Christiano, P., Leike, J., \u0026amp; Lowe, R. 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Advance online publication. https://doi.org/10.1007/s13042-024-02443-6\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Artificial Intelligence (AI), online education, FAA Part 107, sUAS, student satisfaction, instructional effectiveness","lastPublishedDoi":"10.21203/rs.3.rs-7394155/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7394155/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe integration of Artificial Intelligence (AI) in education has gained significant momentum, particularly in online learning environments. This study evaluates the effectiveness of AI-generated voice-over lectures as an alternative to traditional human-narrated presentations in preparing students for the Federal Aviation Administration (FAA) Part 107 certification exam for small Unmanned Aircraft Systems (sUASs). Utilizing a mixed-methods approach, the research examines student performance, engagement, and satisfaction through quantitative analysis of exam scores and survey data, supplemented by qualitative insights from student interviews.\u003c/p\u003e\u003cp\u003eThe study employs a comparative design, assessing two groups: one receiving AI-generated instructional content and the other engaging with human-narrated lectures. Results indicate no significant difference in exam performance between the two groups, demonstrating that AI-generated lectures are as effective as traditional methods in supporting student learning outcomes. Survey responses reveal that students appreciate the accessibility and consistency of AI-driven instruction but highlight a preference for human interaction in certain aspects of learning. AI tools such as chatbots and digital notes offer supplementary benefits, particularly in providing quick clarifications, though they are perceived as less effective for in-depth explanations.\u003c/p\u003e\u003cp\u003eThe findings underscore the viability of AI-generated lectures in education, particularly for technical certification training. Future research should focus on optimizing AI instructional design to enhance personalization, engagement, and interaction, ensuring that AI-driven education continues to align with pedagogical best practices.\u003c/p\u003e","manuscriptTitle":"Assessing Student Satisfaction Using Lectures Generated by Artificial Intelligence (AI)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-26 06:35:43","doi":"10.21203/rs.3.rs-7394155/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fadef5f9-2bd1-499b-9150-216c6e70ffd1","owner":[],"postedDate":"August 26th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-19T09:13:37+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-26 06:35:43","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7394155","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7394155","identity":"rs-7394155","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}