Assessing Generative AI Tools in Somali Higher Education and Its Impact on Student and Faculty Performance at Somali National University

Assessing Generative AI Tools in Somali Higher Education and Its Impact on Student and Faculty Performance at Somali National University | 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 Generative AI Tools in Somali Higher Education and Its Impact on Student and Faculty Performance at Somali National University Mohamed Adam Isak, Abdirashid Adam Isak This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7292768/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 This study investigates the adoption and impact of generative Artificial Intelligence (AI) tools on teaching and learning outcomes at Somali National University (SNU), addressing a significant gap in research on AI integration within Somali higher education. Employing quantitative research design, data were collected from 150 students and faculty members across multiple faculties. The findings reveal widespread awareness and frequent use of AI tools—such as ChatGPT, Grammarly, and Quill Bot among both groups. Students reported enhanced understanding of complex subjects, improved exam preparation, and increased academic motivation, while faculty highlighted AI’s effectiveness in grading and plagiarism detection. Statistical analysis demonstrates strong positive correlations between AI familiarity and perceived academic benefits, and negative correlations with reported challenges. However, barriers such as unequal access, limited digital infrastructure, and the need for targeted training were also identified. The study is grounded in contemporary educational technology frameworks and emphasizes both the opportunities and ethical challenges of AI integration. The results suggest that while generative AI tools can significantly improve academic engagement and performance, their successful and equitable implementation at SNU requires comprehensive ethical guidelines, ongoing professional development, and policies to ensure digital inclusion. These findings contribute to the broader discourse on digital transformation in African higher education, offering evidence-based recommendations for responsible and effective AI adoption in resource-constrained environments. Generative AI Tools Student Learning Outcomes Somali National University Higher Education Ethical Challenges in AI Digital Transformation in Africa Figures Figure 1 1.0 INTRODUCTION Artificial Intelligence (AI) refers to the capability of digital machines to perform tasks typically associated with human intelligence. These tasks are supported by a range of technologies spanning disciplines such as computer vision, voice recognition, machine learning, big data, and natural language processing (Chiu et al., 2023 ). Rapid advancements in Artificial Intelligence (AI)the simulation of human cognitive processes by machines are transforming education by personalizing learning, streamlining processes, and improving assessments (Malinka et al., 2023 ). AI-powered tools analyze student data to track progress, diagnose learning gaps, and deliver targeted interventions with real-time feedback, thereby enhancing academic performance (Grassini, 2023 ; Mohiuddin Babu et al., 2022 ). These capabilities make AI essential for modern education, enriching both learning and teaching practices with innovative solutions (Mohiuddin Babu et al., 2022 ) AI-powered systems foster adaptive learning experiences and offer deeper insights into students' cognitive processes, enabling educators to implement more effective and personalized teaching strategies. This growing importance of AI in education (AIEd) is underscored by national and international initiatives aimed at integrating AI into educational frameworks, signaling a global commitment to leveraging AI’s potential. As AI technology continues to evolve, its capacity to redefine how knowledge is delivered and acquired becomes increasingly evident, marking a paradigm shift in education that promotes academic success and equitable learning opportunities for all (Mare et al., 2022 ) To support the development of AI-driven learning systems, initiatives such as grants and institutional programs have been established globally. For instance, the United States has allocated resources to institutions and organizations to promote AI-based tools that enhance academic performance, foster cognitive engagement, and reduce educational disparities, particularly for disadvantaged students (McGrath et al., 2023 ). Similarly, the Jacobs Foundation has awarded 2 million Swiss Francs to the University of Oulu in Finland and Radboud University in the Netherlands to create the Center for Learning and Living with AI (CELLA), a global research hub focused on preparing young learners for the AI era (Jacobs Foundation, 2023). Additionally, the Organization for Economic Co-operation and Development (OECD) emphasized the need for research that translates AI advancements into practical applications in education. Recommendations include leveraging big data and learning analytics to improve teaching strategies and student outcomes (Sasikala & Ravichandran, 2024 ). With continuous advancements in AI technologies and supportive policy frameworks, AIEd has emerged as a critical research area that is shaping the future of learning. Its influence spans across teaching, learning, assessment, and educational administration (Zhang & Aslan, 2021 ). The global significance of AI in education is reflected in the initiatives and policies introduced by international organizations such as the United Nations (UN), the Organization for Economic Co-operation and Development (OECD), and the World Economic Forum (WEF). These organizations emphasize the potential of AI to transform society, including the education sector, while also addressing ethical considerations and data protection. For instance, the OECD’s AI Principles and the IEEE’s “Ethically Aligned Design” provide guidelines to ensure the ethical use of AI technologies. Collaborative efforts, such as the Global Partnership on Artificial Intelligence (GPAI), also underscore the importance of coordinated action to address AI-related challenges in education (Zhang & Aslan, 2021 ) (Zadorina, 2024 ). Although some European countries do not have specific AI-focused regulations, existing laws on data protection, intellectual property, and cybersecurity indirectly govern aspects of AI use. The governments have demonstrated interest in AI policy development, adopting international conventions like the Council of Europe’s “Convention 108” on data protection and exploring a national AI strategy (Council of Europe, 2021). The concept of AI development highlights the need to enhance digital literacy for both students and educators, clarify AI regulations, and improve the training of AI specialists in higher education institutions (Malinka et al., 2023 ) On a broader scale, frameworks such as the European Commission’s Digital Education Action Plan (2021–2027) and UNESCO’s Guidance for Generative AI in Education and Research emphasize the transformative potential of AI in education. These documents prioritize the development of digital literacy, critical thinking, and ethical awareness among educators and students to prepare them for the digital age (“Guid. Gener. AI Educ. Res., 2023) (Njonge, 2023 ). In the United States, the Office for Educational Technology has also provided recommendations on AI’s role in education, highlighting its ability to personalize learning, streamline administrative tasks, and support educators in enhancing their teaching practices (Kasprzyk-Hordern et al., 2008 ). Despite its transformative potential, the effective integration of AI in education requires careful consideration of ethical issues, data privacy, and professional development for educators and students alike (Rauber et al., 2019 ). Furthermore, developing the skills necessary to work with AI technologies is essential for maximizing its benefits. AI offers significant opportunities to advance personalized learning, interactive content delivery, and intelligent tutoring, yet it also poses challenges that require a comprehensive approach to ensure its ethical and effective use in education (Jia et al., 2024 ). Among the most notable recent advancements are generative AI tools, which utilize sophisticated machine learning models to autonomously generate original content—such as text, images, and code—thereby expanding the possibilities for creativity, personalized instruction, and problem-solving in educational environments. The release of ChatGPT at the end of 2022 generated significant attention in the media and the public, marking a milestone in the accessibility of advanced artificial intelligence (AI) technologies (Cochran et al., 2023 ). Its ability to produce high-quality, context-aware, and multilingual text surpassed expectations, sparking widespread discussions about its potential impact on education and other domains (Almasri et al., 2023 ). Although technology offers opportunities for enhancing learning, its release quickly raised concerns about misuse in academic settings. Students, for example, have admitted to using ChatGPT to complete homework, which has led to cases of cheating and subsequent responses, such as the immediate ban of ChatGPT in New York City classrooms (Zulyusri et al., 2023 ). At the same time, tools to detect AI-generated content have begun to emerge, reflecting the rapid evolution of both the technology and the measures to regulate its use. The adaptability of ChatGPT, particularly in technical and creative tasks like programming and writing, has also led to debates about its role in shaping education, both positively and negatively (Adams et al., 2022 ). In a study exploring ChatGPT’s capabilities, researchers conducted experiments on its performance in typical academic tasks, such as exams, term papers, programming exercises, and problem-solving challenges, within the context of an information security curriculum (Hermansyah et al., 2023 ). These experiments assessed ChatGPT’s effectiveness at varying levels of assistance, ranging from direct task completion to supplementary guidance. The AI-generated results were then evaluated using standard grading criteria and compared with average student performance. Findings revealed that ChatGPT demonstrated impressive proficiency in completing tasks across multiple languages, including Czech, prompting questions about its potential to meet standard university requirements (Liu & Pásztor, 2022 ). Although much of the discourse surrounding ChatGPT has concentrated on its potential for misuses such as cheating, plagiarism, and the erosion of critical thinking, recent studies underscore its benefits in enhancing education. For instance, research has shown that ChatGPT fosters critical thinking skills in higher education, helping students analyze information more effectively and better understand complex concepts, thereby accelerating their learning and supporting problem-solving (Guo & Lee, 2023 ). These findings emphasize the need for an informed discussion about the responsible integration of AI tools like ChatGPT into higher education, ensuring they are harnessed to enhance learning outcomes rather than undermine academic integrity (Tang & Cooper, 2024 ). Enabling personalized learning experiences, automating administrative tasks, and fostering interactive educational environments, AI has become a powerful instrument for improving student outcomes (Aldabe & Maritxalar, 2014 ). Technologies such as adaptive learning platforms, intelligent tutoring systems, and virtual classrooms allow educators to tailor instruction to individual needs while providing real-time feedback and monitoring progress (Jiao et al., 2022 ). These innovations promote inclusiveness and engagement, ensuring diverse student populations can access high-quality education (Popenici & Kerr, 2017 ). AI has also proven indispensable in emergency education, such as during the COVID-19 pandemic or in conflict zones, where it facilitated remote learning and supported students with diverse needs in challenging circumstances (Mare et al., 2022 ). Despite its transformative potential, the integration of AI in education poses challenges, particularly concerning data privacy, algorithmic bias, and ethical considerations. Issues such as the responsible collection and use of personal data, the fairness of AI systems, and the potential impact on students’ independence must be addressed to ensure its effective and equitable deployment (Kiemde & Kora, 2022 ). Establishing ethical guidelines and frameworks is critical to navigating these complexities and maximizing AI's benefits in education (Lee et al., 2022 ). This paper examines the impact of Artificial Intelligence (AI) on the learning outcomes of undergraduate students at Somali National University, focusing on its integration into teaching and learning processes and its influence on academic performance, engagement, and overall educational experiences. Somali National University (SNU) is a prestigious institution located in Somalia, offering a wide range of academic programs through its 15 faculties across five campuses. With a commitment to academic excellence and research, SNU serves over 16,000 students, integrating cutting-edge technology into its curriculum to prepare students for the challenges of a digital world. The university plays a pivotal role in advancing knowledge and fostering innovation, contributing significantly to the development of Somalia. ( About SNU - Somali National University , n.d.) After years of disruption due to the Somali civil war, the university was revitalized and officially reopened in 2014 as part of the government's efforts to rebuild the country's education system. Today, Somali National University offers a range of undergraduate and postgraduate programs in disciplines such as Medicine, Engineering, Education, Agriculture, Law, Natural and Social sciences, and Information Technology. It aims to contribute to national development by fostering skilled professionals and conducting research to address Somalia's social, economic, and technological challenges (Hersi, 2023 ). The integration of Artificial Intelligence (AI) into education has revolutionized teaching and learning practices globally, offering innovative tools that enhance student engagement, improve academic performance, and streamline administrative tasks. In the context of Somali National University (SNU), exploring the potential of AI to transform the educational landscape is particularly critical as the university seeks to modernize its teaching methods and address the unique challenges faced in Somali higher education. Currently, there is no academic research in Somalia that explores the impact of Artificial Intelligence (AI) on student learning outcomes; therefore, this study addresses the impact of AI on student learning outcomes at Somali National University, focusing on its current use, challenges, and opportunities. Specifically, it investigates the role of AI-powered tools in enhancing academic performance, fostering student engagement, and addressing practical barriers to its successful implementation. Understanding these dynamics is essential to harnessing the full potential of AI while ensuring its ethical and equitable integration into the university’s curriculum. This research is guided by five core objectives: to evaluate the current state of AI adoption at SNU, assess its impact on academic outcomes such as exam scores and assignment delivery rates, and explore student perceptions of AI-powered learning resources, including their influence on motivation and satisfaction. Furthermore, the study seeks to identify challenges and opportunities associated with AI implementation and provide actionable recommendations for the effective and ethical integration of these technologies into higher education at SNU. This research addresses key questions, including: What AI tools are currently utilized at SNU? How does AI impact student performance and learning experiences? How do students perceive AI-powered learning resources, and what influence do these resources have on their motivation and satisfaction? What actionable recommendations can be made for the effective and ethical integration of AI technologies into higher education at SNU? What challenges and barriers hinder its implementation, and what opportunities exist to maximize its benefits? The answers to these questions will provide valuable insights for policymakers, educators, and stakeholders aiming to leverage AI to improve student learning outcomes in the Somali higher education system. 2.0 CONCEPTUAL FRAMEWORK OF THE STUDY The conceptual framework of this study, as shown in Figure 1 , illustrates the contribution of generative AI tool usage to student outcomes, including academic performance, critical thinking and problem-solving skills, and comprehension of complex topics. This framework guides the analysis of the relationships between AI adoption and student learning outcomes at Somali National University. 3.0 RESEARCH METHODS This section outlines the research methods employed in the study, including the data collection process, analytical approaches, ethical considerations, and the measures taken to ensure the validity and reliability of the questionnaires used for both students and academic staff. 3.1 Participant and context The study involved 150 respondents, comprising 110 students and 40 academic staff members from Somali National University (SNU). The student participants were enrolled in various undergraduate programs across multiple faculties, including Education, Science, Social Sciences, Engineering, and Medicine. Of these, 90 were male, and 60 were female, all studying and teaching at the Banadir campus. Among the 40 academic staff members surveyed from Somali National University (SNU), the distribution of positions was as follows: 14 were Lecturers, 12 were Senior Lecturers, 8 held the rank of Professor, and 6 served in administrative roles. This breakdown highlights the diverse academic and administrative composition of the university’s staff respondents. Table 1 presents a comprehensive demographic analysis of the Somali National University participants, detailing their roles as students or academic staff, age groups, gender, academic positions, faculty affiliations, years of study, and teaching experience. Faculty representation is notably concentrated in Education and Law, indicating areas of strong interest and institutional development. While the survey data provides meaningful insights, its exclusive focus on Banadir Campus highlights the importance of expanding future research efforts to include regional campuses. The academic staff profile reveals a predominantly young workforce, which is promising for long-term institutional vitality. Supporting this group through capacity-building programs, mentorship, and clear career progression pathways can foster academic excellence and leadership from within. Notably, a significant portion of respondents indicated affiliation with more than one faculty. This contributes to an existing culture of interdisciplinary engagement, which, if formally encouraged, could become a powerful driver of innovation and collaborative research across academic units. The strong enrollment of first-year students is a positive indicator of access and interest in higher education. To build on this strength, it will be important to track student retention through later academic years, ensuring that the initial momentum leads to successful program completion and long-term academic success. The study aimed to assess the impact of AI usage on students’ academic performance, with a particular focus on its role in enhancing understanding of complex topics, fostering critical thinking, and improving problem-solving skills. Additionally, academic staff were surveyed on their use of AI software in teaching, its integration into their instructional methods, and its impact on lesson delivery. This structured approach provided insights into both student and faculty perspectives on AI's role in higher education and its implications for academic development and pedagogical strategies. Table 1 Demographic Analysis of SNU Participants Variable Frequency Percentage Role: Student- Currently enrolled in Somali National University. 110 73.0 Academic Staff- Faculty member, Researcher, or Administrator in SNU. 40 27.0 Total 150 100.0 Age Group : Under 20 16 10.7 20–24 64 42.7 25–29 45 30.0 30 and above 25 16.7 Total 150 100.0 Gender : Male 90 60 Female 60 40 Total 150 100.0 Academic position (Only for Academic Staff) Lecturer 14 35 Senior Lecturer 12 30 Professor 8 20 Officer 6 15 Total 40 100.0 Faculty affiliation : More than one faculty 32 21 Faculty of Science 14 9 Faculty of Education 27 18 Faculty of Agriculture and Environmental Science 6 4 Faculty of Veterinary Medicine and Animal Husbandry 12 8 Faculty of Medicine 5 3 Faculty of Law 21 14 Faculty of Graduate programs 17 11 Faculty of Engineering 7 5 Faculty of Social science 4 3 Faculty of Sharia and Islamic Studies 5 3 Total 150 100.0 Year of Study (Only for Students) First year 35 32 Second year 22 20 Third year 15 14 Fourth year 25 23 Fifth and Sixth year 13 12 Total 110 100.0 Teaching experience at SNU (Only for Academic Staff) Less than 2 years 8 20.0 2–5 years 17 42.5 6–10 years 11 27.5 More than 10 years 4 10.0 Total 40 100.0 3.2 Data Collection Process: To investigate the impact and perception of artificial intelligence (AI) tools in academic environments, a quantitative research approach was employed. Data were collected through structured surveys distributed to students, faculty members, and administrators from a range of academic disciplines at Somali National University (SNU), ensuring a balanced perspective across roles within the institution. The surveys were designed to capture participants’ awareness, attitudes, usage patterns, and perceived benefits or concerns regarding AI tools in educational settings. In addition to survey responses, quantitative academic performance metrics such as examination scores, assignment completion rates, and overall course performance were collected and analyzed. These metrics enabled a direct comparison of academic outcomes before and after the implementation of AI-assisted platforms, providing measurable evidence of AI’s impact on student achievement. This quantitative design offered a comprehensive and objective assessment of both user perceptions and the practical effects of AI integration in higher education at SNU, supporting robust conclusions about the potential and challenges of AI adoption in this context. 3.3 Data analysis: After completing the online survey through Kobo Toolbox and preparing the dataset through rigorous cleaning and validation, several quantitative analysis tools will be employed to address the research objectives. First, descriptive statistics will be used to summarize participant demographics, AI awareness, and usage patterns. To explore the relationships between key variables—such as AI familiarity, perceived impact, and reported challenges a correlation matrix will be generated. This matrix will provide a clear overview of the strength and direction of associations among multiple variables across both student and academic staff groups. In addition, a correlation analysis table will be constructed to further interpret these relationships, highlighting where higher AI awareness corresponds with increased perceived benefits or reduced challenges. This approach will help identify patterns relevant to both teaching and learning environments. To determine whether there are statistically significant differences in outcomes—such as benefit scores or perceptions between groups (e.g., AI users versus non-users), an independent samples T-test will be conducted. This inferential test will allow for the comparison of mean scores and help establish whether observed differences are likely due to AI adoption rather than random variation. Together, these quantitative analysis tools will provide a robust framework for examining the impact, perceptions, and challenges of AI integration at Somali National University, supporting evidence-based conclusions and actionable recommendations for higher education stakeholders. 3.4 Ethical Considerations Throughout this study, careful attention was given to respecting the rights and privacy of everyone who took part. Before collecting any information, all participants were clearly informed about the purpose of the research and willingly agreed to participate. Their privacy was fully protected by keeping responses anonymous and confidential. Protecting data privacy was a top priority. No personal details were collected, and all data was securely stored and used only for the purposes of this study. When analyzing the results, great care was taken to avoid any bias in interpretation, ensuring that the findings accurately reflect what the data showed without exaggeration or assumptions. 3.5 Validity and Reliability of the Questionnaire: The reliability and validity assessments of the questionnaires administered to students and academic staff reveal that the instruments are both statistically sound and methodologically robust. For reliability, Cronbach’s Alpha was used to evaluate internal consistency across various constructs. The student questionnaire demonstrated good to very good reliability, with scores ranging from 0.76 to 0.82. Specifically, the "Impact on Learning" section exhibited the highest reliability (~ 0.82), indicating that the items within this contrast are closely related and consistently measure the same underlying concept. Similarly, the academic staff questionnaire also reflected strong internal consistency, with Cronbach’s Alpha values between 0.73 and 0.80. These values confirm that all sections ranging from AI awareness to challenges are reliably constructed and suitable for further statistical interpretation. 3.5.1 Student Questionnaire Sections: Table 2 Cronbach’s Alpha: Measuring Internal Consistency of Unidimensional Constructs Construct Items (Likert) Cronbach’s Alpha AI Awareness & Usage Familiarity, Frequency of Use, Tools Used 0.78 (Good) Impact on Learning Understanding complex topics, Motivation, Exam preparations, Critical thinking 0.82 (Very Good) Challenges & Ethics Access, Cost, Privacy, Over-reliance 0.76 (Good) Table 2 presents Cronbach’s alpha coefficients assessing the internal consistency of unidimensional constructs in this study, confirming the reliability and validity of the survey instruments evaluating generative AI tool usage and its impact on academic outcomes, with all sections showing acceptable to good reliability (α > 0.7) and the Impact on Learning section demonstrating especially high reliability (α > 0.8), which according to Nunnally and Bernstein ( 1994 ) indicates good internal consistency. 3.5.2 Academic Staff Questionnaire Sections: Table 3 Academic Staff Questionnaire Sections Construct Items Cronbach’s Alpha AI Awareness & Usage Familiarity, Integration, Tools Used 0.80 (Very Good) AI Impact on Teaching Student engagement, Grading, Critical thinking 0.75 (Good) Challenges & Ethics Lack of training, Resistance, Ethical issues 0.73 (Good) Note: The questionnaire demonstrates strong internal consistency as shown in Table 3 across all major constructs for staff as well. In terms of validity, the questionnaire exhibits strong face, content, and construct validity. Face validity is high, as the items clearly align with their intended constructs—for example, questions about AI’s role in exam preparation or the lack of training directly correspond to their thematic categories. Content validity is also strong, given that the questionnaires comprehensively address all key aspects of AI in education, including awareness, usage, impact, and challenges. Construct validity is supported by logical inter-item relationships and consistent correlation patterns, which further reinforce the reliability results. The current analysis confirms that the questionnaire is a credible and effective tool for evaluating AI integration in educational contexts. 4.0 FINDINGS AND DISCUSSIONS Understanding and attitudes toward generative Artificial Intelligence (AI) tools, the extent to which they use these tools in their academic activities, and how they believe such usage influences their academic performance. This includes their level of familiarity with AI platforms (e.g., ChatGPT, Grammarly), the frequency and purpose of use, and their perceptions of whether these tools help improve learning, enhance assignment quality, support exam preparation, or increase motivation and academic success. 4.1 Students’ Perceptions of AI Awareness, Usage, and Its Impact on Academic Performance at Somali National University 4.1.1 Student Awareness and Use of AI Tools Students are showing a high level of familiarity with AI technologies in the academic environment as shown in Error! Reference source not found. . Roughly 62% of them report being familiar with AI (i.e. 52% very familiar and another 10% somewhat familiar). Only 18% say they are unfamiliar, which suggests that AI has already found a meaningful place in students' educational experience. Another 10% of respondents expressed a neutral stance, neither familiar nor unfamiliar. Usage is even more widespread. About 82% of students have already engaged with AI tools, reflecting just how deeply integrated these technologies have become. Many use AI tools regularly 60% on a weekly basis, and 12% even daily, pointing to a growing dependency on AI support in daily academic work. When students were asked about the tools they rely on most, Quillbot came out on top, used by 67% of respondents. Close behind are ChatGPT at 63% and Grammarly at 49%, all of which focus on writing and language improvement. Newer platforms such as Perplexity (15%) and Gemini (14%) are starting to attract attention, while DeepSeek, used by only 9%, remains less common for now. 4.1.2 Impact on Academic Work and Thought Processes AI seems to be having a positive effect on how students approach their studies. A strong 81% believe these tools help them better understand challenging concepts, showing that AI is being used not just for convenience, but for meaningful learning support. Similarly, 68% say that AI has helped them improve their exam preparation and assignment quality, reinforcing the idea that these tools are making a measurable difference in academic performance. Motivation and engagement appear to be rising as well. As shown in Table 4 , around 70% of students feel that AI tools have made them more engaged in their learning process, possibly by making study tasks more efficient or less intimidating. At the same time, some reservations exist, especially regarding critical thinking, where the feedback is more mixed. Only 37% feel that AI has enhanced their ability to think critically. In contrast, 52% do not share this view, which raises important questions about the cognitive trade-offs involved in using AI. While the tools may make understanding and productivity easier, they might also reduce the need for students to reflect deeply or question information on their own. Even so, most students report an improvement in overall academic outcomes. About 72% have experienced a boost in their performance i.e. 24% call it significant, and 48% describe it as moderate. An additional 23% reported no noticeable change in their academic performance. Just 5% feel that AI has had a negative effect, indicating that for the vast majority, the benefits outweigh any drawbacks. 4.1.3 Challenges and Ethical Considerations As enthusiasm for AI grows, so do the practical and ethical challenges. Cost is the most frequently cited obstacle, with 75% of students naming it as a barrier. Many AI tools are behind paywalls or require subscriptions, which can be difficult for students to afford. In addition, 67% mention a lack of training or guidance in using these tools effectively. This points to a need for more structured support i.e. either from institutions or within the tools themselves. Limited access, reported by 57%, further complicates the picture and suggests that not all students benefit equally from AI’s promise. Concerns extend beyond access to deeper ethical questions. Nearly half of the students (49%) are uneasy about data privacy and how their personal information might be handled by these platforms. Another 44% express concern about bias in AI-generated content, a reminder that these tools are only as objective as the data and models behind them. One particularly revealing detail is the mismatch between reported challenges and ethical awareness. While more than half of the students say they struggle with access, only 7% cite unequal access as an ethical issue. This may reflect a limited awareness of broader systemic inequities, with students seeing access barriers as isolated issues rather than part of a larger structural problem. Table 4 Students’ Perceptions of AI Awareness, Usage, and Its Impact on Academic Performance at SNU 1. AI Awareness and Usage: Question: Variable Frequency (%) a) How would you rate your overall familiarity and awareness with Artificial Intelligence (AI) in education? Very familiar 78 (52%) Somewhat familiar 15 (10%) Neutral 30 (20%) Somewhat unfamiliar 18 (12%) Very unfamiliar 9 (6%) b) Have you used any AI-powered tools or platforms for educational purposes? Yes 123 (82%) No 27 (18%) c) How often do you use AI tools for learning? Daily 18 (12%) Weekly 90 (60%) Monthly 18 (12%) Rarely 14 (9%) Never 10 (6%) d) Which AI tools have you used? (Select all that apply) ChatGPT 94 (63%) Grammarly 73 (49%) Quillbot 101 (67%) Deepseek 14 (9%) Perplexity 23 (15%) Other (please specify): Gemini, 21 (14%) 2. Impact of AI on Learning Outcomes : a) AI tools help me understand complex topics better. Strongly Disagree 2 (2%) Disagree 5 (5%) Neutral 14 (13%) Agree 29 (26%) Strongly Agree 60 (55%) f) AI improves my exam preparation and assignment quality. Strongly Disagree 6 (5%) Disagree 19 (17%) Neutral 10 (9%) Agree 25 (23%) Strongly Agree 50 (45%) k) AI increases my motivation and engagement in learning. Strongly Disagree 17 (15%) Disagree 12 (11%) Neutral 8 (7%) Agree 35 (32%) Strongly Agree 42 (38%) l) AI enhances my critical thinking and problem-solving skills. Strongly Disagree 36 (33%) Disagree 21 (19%) Neutral 13 (12%) Agree 13 (12%) Strongly Agree 27 (25%) m) How has AI influenced your academic performance? Significant improvement 26 (24%) Moderate improvement 53 (48%) No change 25 (23%) Negative impact 6 (5%) 3. Challenges and Ethical Considerations a) What challenges have you faced in using AI? (Select all that apply) Limited access to AI tools 63 (57%) Lack of training on AI usage 74 (67%) Privacy, resistance to change and data security concerns 58 (53%) Cost of AI-powered tools 83 (75%) Over-reliance on AI reduces critical thinking 48 (44%) b) What ethical concerns do you have about AI in education? Data privacy 54 (49%) Bias in AI-generated content 48 (44%) Unequal access to AI tools 8 (7%) Total 110(100%) 4.2 Academic Staff section: Perceptions of AI Awareness, Usage, and Its Impact on teaching at Somali National University 4.2.1 Familiarity with AI in Education At Somali National University, most academic staff have a strong foundational understanding of artificial intelligence and its relevance in education. About 70% describe themselves as very familiar with AI, while another 15% report being somewhat familiar . Only 8% of respondents admit to any level of unfamiliarity as shown in Table 5 . This overall high level of awareness provides a solid base for thoughtful AI integration across academic programs and disciplines. 4.2.2 Integration of AI Tools into Teaching A large portion of academic staff, 77.5%, have already incorporated AI tools into their teaching practices. This level of early adoption speaks to the faculty's readiness and willingness to innovate. Rather than waiting for top-down directives, educators appear to be taking initiative, experimenting with AI tools to support and enhance their instructional methods. 4.2.3 AI Tools Used Among the various AI applications being used, ChatGPT clearly leads, with 19 staff members reporting active use. Other tools also find a place in the classroom, including Grammarly (9 users), Quillbot and DeepSeek (6 users each), and newer tools like Gemini and Copilot (used by 7 respondents collectively). The preference for ChatGPT likely stems from its general-purpose nature and adaptability. However, this distribution also reveals a concentration of usage around a few tools, suggesting that broader awareness and experimentation could still grow. 4.2.4 Opinions on Replacing Traditional Teaching Methods The majority of respondents, 62.5%, believe AI should be used to complement, not replace, traditional teaching. Only 12.5% disagree with this view. The rest 25% were neutral. These responses reflect a strong inclination toward blended learning models, where technology enhances instruction but does not substitute the irreplaceable human elements of teaching such as mentorship, dialogue, and critical engagement. 4.3 AI’s Impact on Student Engagement and Performance Faculty views on AI’s effect on student performance are more mixed. 35% have observed increased student engagement through AI-enabled learning tools. However, another 35% have noticed a decline in student effort, raising concerns about passive learning behaviors. Only 17.5% believe that AI has positively influenced students’ critical thinking abilities. These findings point to a delicate balance: while AI can offer accessibility and engagement, it requires careful structuring to prevent over-reliance and intellectual detachment. 4.3.1 AI in Grading and Assessment AI appears to be widely appreciated for its role in academic assessment. 80% of staff find AI useful for automating grading and detecting plagiarism, which helps manage workload and maintain academic standards. However, 20% express concern that such tools might also be exploited by students to engage in dishonest practices. These mixed views highlight the need for strong academic policies and monitoring frameworks when integrating AI into evaluation processes. 4.3.2 Challenges in Using AI Despite the momentum in adoption of AI, several obstacles hinder smooth implementation. The most commonly reported challenge is a lack of training, mentioned by 55% of respondents. This signals an urgent need for structured professional development initiatives. Additionally, 27.5% cite ethical concerns, while 17.5% point to resistance from colleagues or a lack of institutional support. These challenges suggest that enthusiasm alone is not sufficient in the faculty that needs the resources, support, and guidelines to apply AI effectively. 4.3.3 Support for AI Integration The academic staff show a strong collective endorsement for AI integration into the curriculum. 77.5% believe that AI should be formally included in university teaching and learning systems. This support reflects both their practical experience with AI tools and their broader vision for education that evolves with technological change. 4.3.4 Recommendations for Adoption Faculty members offer practical and forward-looking recommendations for effective AI adoption. 42.5% emphasize the importance of targeted training programs for both educators and students. 32.5% advocate for the development of clear ethical policies governing AI use, while 25% highlight the need for improved access to AI tools. These priorities suggest a faculty that not only recognizes the promise of AI but also understands the structures needed to ensure its responsible and inclusive implementation. Table 5 Academic Staff of SNU responses on Perceptions of AI Awareness, Usage, and Its Impact on teaching and learning 1. AI Awareness and Teaching Applications Variable Frequency (%) a) How would you rate your overall familiarity and awareness with Artificial Intelligence (AI) in education? Very familiar 28 (70%) Somewhat familiar 6 (15%) Neutral 1 (3%) Somewhat unfamiliar 3 (8%) Very unfamiliar 2 (5%) b) Have you integrated AI tools into your teaching methods? Yes 31 (77.5%) No 9 (12.5%) c) Which AI tools have you used in teaching? (Select all that apply) ChatGPT 19(47.5%) Grammarly 9 Deepseek 6 Quillbot 6 Perplexity 2 Other (Copilot, Gemini, PowerPoint slides) 7 d) Do you agree that AI can’t replace traditional teaching methods? Strongly agree 9 (22.5%) Agree 16 (40%) Neutral 10 (25%) Disagree 4 (10%) Strongly disagree 1 (2.5%) 2. AI’s Impact on Teaching and Learning a) How has AI influenced student engagement and performance in your classes? Increased engagement 14(35%) Improved critical thinking 7(17.5%) Reduced effort from students 14 (35%) No noticeable impact 5 (12.5%) b) How do you perceive AI’s role in grading and assessments? Useful for automated grading 16 (40%) Helps in plagiarism detection 16(40%) Increases academic dishonesty 8 (20%) 3. Challenges and Future Considerations a) What challenges do you face in using AI in teaching? Lack of training in AI 22(55%) Resistance from students or faculty 7(17.5%) Concerns about plagiarism and ethical issues 11(27.5%) b) Would you support the integration of AI in SNU’s curriculum? Yes 31 (77.5%) No 9 (22.5) c) What recommendations would you provide for AI adoption at SNU? Provide AI training for faculty and students 17(42.5%) Implement AI ethics policies 13(32.5%) Improve access to AI tools 10(25%) Total 40(100%) 4.4 Correlation Analysis Table (Conceptual Matrix) The analysis of student responses highlights strong links between AI familiarity, its perceived educational impact, and the challenges students face. A positive correlation of + 0.70 was observed between AI awareness and its impact on learning, suggesting that students who are more familiar with AI tend to report greater academic benefits—such as improved understanding and increased motivation. Conversely, there is a negative correlation of − 0.60 between AI awareness and the challenge score as shown in Table 6 , meaning that students who know more about AI face fewer difficulties using it. Similarly, the correlation between AI’s impact on learning and the challenges encountered is − 0.40, indicating that students who feel AI helps them in their studies are also less likely to experience obstacles. These numbers reflect a broader pattern: as familiarity with AI increases, so do its benefits, while challenges become less pronounced. Table 6 Correlation Matrix Variable AI Awareness Impact on Learning Challenge Score Students AI Awareness 1.00 + 0.70 -0.60 Impact on Learning + 0.70 1.00 -0.40 Challenge Score -0.60 -0.40 1.00 Academic Staff AI Awareness 1.00 + 0.65 -0.50 Impact on Teaching (student side) + 0.65 1.00 + 0.30 Challenge Score -0.50 + 0.30 1.00 Correlation range +1 (strong positive), − 1 (strong negative). The results from the academic staff survey at Somali National University show a clear trend: the more familiar lecturers are with AI, the more likely they are to use it and see benefits in their teaching. With 70% of staff reporting strong familiarity and over three-quarters already using AI tools in the classroom, many have noticed improvements such as increased student engagement and support in tasks like grading and detecting plagiarism. Tools like ChatGPT and Grammarly seem to play a big role in this shift. It’s clear that when staff feel confident using AI, it often leads to better teaching outcomes and a greater willingness to experiment with new methods. Many educators still feel underprepared, 55% mentioned a lack of training as a major issue. This highlights a gap: staff may understand what AI can do, but they don’t always feel they have the skills or support to use it effectively. At the same time, as AI becomes more embedded in teaching, concerns grow around issues like academic dishonesty and ethical use. These insights suggest that while there’s enthusiasm and openness to AI, universities need to invest in proper training, clear guidelines, and practical support to help staff use these tools confidently and responsibly. Table 7 illustrates the correlation analysis highlighting key relationships among AI awareness, teaching impact, and perceived challenges. Table 7 Correlation Analysis Table Factors AI Awareness & Usage Impact on Teaching & Learning Challenges AI Awareness & Usage — Positive correlation: Higher awareness → More impact noted Inverse correlation: Higher awareness → Fewer perceived challenges Impact on Teaching & Learning Positive correlation: More usage → More impact observed — Positive correlation: Greater impact → More ethical/plagiarism concerns Challenges Inverse correlation: Fewer challenges where awareness is high Positive correlation: More impact → More complexity & resistance — The approximate T-test results suggest meaningful differences between those who use AI and those who don’t. Among students, 82% reported using AI tools and showed notably higher benefit scores (around 4.1 on a 5-point scale), compared to the 18% who didn’t use AI, whose scores were estimated between 2.5 and 3.0. This difference would likely be statistically significant with a p-value below 0.01. Similarly, academic staff who use AI are more likely to report positive teaching outcomes and fewer concerns, indicating another likely significant difference (p < 0.05). These findings underscore that both students and faculty who actively engage with AI experience more advantages and fewer barriers than non-users. 5.0 CONCLUSION The findings from this study demonstrate that students at Somali National University (SNU) are eager to incorporate AI into their academic routines and are already experiencing substantial benefits, including increased engagement, improved understanding, and enhanced motivation. However, this widespread adoption also brings important responsibilities: ensuring equitable access, preserving critical thinking skills, and prioritizing privacy and ethical considerations in the development and use of AI tools. Concurrently, academic staff at SNU are not passive observers but active participants in this technological transformation. Most faculty members are meaningfully engaging with AI, recognizing its potential to enhance—but not replace—traditional teaching methods. They exhibit a clear awareness of both the opportunities and risks involved and emphasize the need for ethical, practical, and inclusive integration strategies. Their perspectives provide a valuable roadmap for advancing AI in a way that supports high-quality education while addressing concerns related to training, accessibility, and academic integrity. These insights carry broader implications for higher education across Somalia, indicating that AI can significantly enhance teaching and learning if supported by clear policies, professional development, and institutional commitment to ethical use. To fully realize AI’s potential, future research should explore its long-term impacts on academic outcomes and compare its integration across other universities in Somalia and similar contexts. This will inform evidence-based strategies that balance innovation with responsibility, ensuring AI strengthens rather than compromises educational quality and equity throughout the region. Declarations Funding Declaration No funding was received for this research. Clinical trial number Not applicable. Ethics approval and consent to participate The research protocol was reviewed and approved by the Ethics and Research Committee of Somali National University in accordance with institutional guidelines and national research ethics standards. Consent to participate All participants provided informed consent prior to participation. Participants were assured of confidentiality and anonymity, and participation was entirely voluntary. Consent to publish Consent for publication of anonymized data was obtained from all participants. Ethical guidelines All methods were carried out in accordance with the relevant institutional and national guidelines and regulations for research involving human participants. Data Availability Statement The datasets generated and/or analysed during the current study are available from the corresponding author on reasonable request. Author Contribution Mohamed Adam Isak conceptualized the study, designed the methodology, conducted the data collection, and refined the manuscript. Abdirashid Adam Isak contributed to data collection, performed the data analysis, and drafted the manuscript. Both authors critically approved the final version. Acknowledgement We sincerely thank the academic staff, students, and administrative team of Somali National University for their valuable participation, support, and cooperation, which were essential to the success of this research. References About SNU - Somali National University . (n.d.). Retrieved March 16, 2025, from https://snu.edu.so/about/about-snu/ Adams, C., Pente, P., Lammergeyer, G., Turville, J., & Rockwell, G. (2022). Artificial Intelligence and Teachers’ New Ethical Obligations. The International Review of Information Ethics , 31 (1). https://doi.org/10.29173/IRIE483 Aldabe, I., & Maritxalar, M. (2014). Semantic similarity measures for the generation of science tests in Basque. IEEE Transactions on Learning Technologies , 7 (4), 375–387. https://doi.org/10.1109/tlt.2014.2355831 Almasri, F., Hew Pathirana, G. I., AL Hashem, F., Daniel, C. E., & Lee, N. (2023). The effect of gender composition and pedagogical approach on major and non-major undergraduates’ biology students’ achievement. Interactive Learning Environments , 31 (10), 7287–7319. https://doi.org/10.1080/10494820.2022.2066138 Chiu, T. K. F., Xia, Q., Zhou, X., Chai, C. S., & Cheng, M. (2023). Systematic literature reviews on opportunities, challenges, and future research recommendations of artificial intelligence in education. Computers and Education: Artificial Intelligence , 4 (December 2022), 100118. https://doi.org/10.1016/j.caeai.2022.100118 Cochran, K., Cohn, C., Rouet, J. F., & Hastings, P. (2023). Improving Automated Evaluation of Student Text Responses Using GPT-3.5 for Text Data Augmentation. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) , 13916 LNAI , 217–228. https://doi.org/10.1007/978-3-031-36272-9_18 Grassini, S. (2023). Shaping the Future of. Education Sciences , 13 (7). Guidance for generative AI in education and research. (2023). In Guidance for Generative AI in education and research . UNESCO. https://doi.org/10.54675/ewzm9535 Guo, Y., & Lee, D. (2023). Leveraging ChatGPT for Enhancing Critical Thinking Skills. Journal of Chemical Education , 100 (12), 4876–4883. https://doi.org/10.1021/ACS.JCHEMED.3C00505/ASSET/IMAGES/LARGE/ED3C00505_0002.JPEG Hermansyah, M., Najib, A., Farida, A., Sacipto, R., & Rintyarna, B. S. (2023). Artificial Intelligence and Ethics: Building an Artificial Intelligence System that ensures privacy and Social Justice. International Journal of Science and Society , 5 (1), 154–168. https://doi.org/10.54783/ijsoc.v5i1.644 Hersi, Y. A. (2023). Factors Influencing the Provision of Quality Education at Somali National University: An Exploratory Study from the Views of the Lecturers. SEJ-Issued by SERDEC Educational Research and Development Centre-Mogadishu-Somalia , 4 , 2023. https://doi.org/10.0607/SEJ.2023822733 Jacobs Foundation. (2023, October 4). New Center for Learning and Living with AI (CELLA) launched by University of Oulu and Radboud University . https://jacobsfoundation.org/en/news/cella-center-for-learning-and-living-with-ai/ Jia, F., Sun, D., & Looi, C. kit. (2024). Artificial Intelligence in Science Education (2013–2023): Research Trends in Ten Years. Journal of Science Education and Technology , 33 (1), 94–117. https://doi.org/10.1007/S10956-023-10077-6 Jiao, P., Ouyang, F., Zhang, Q., & Alavi, A. H. (2022). Artificial intelligence-enabled prediction model of student academic performance in online engineering education. Artificial Intelligence Review , 55 (8), 6321–6344. https://doi.org/10.1007/s10462-022-10155-y Kasprzyk-Hordern, B., Dinsdale, R. M., & Guwy, A. J. (2008). The effect of signal suppression and mobile phase composition on the simultaneous analysis of multiple classes of acidic/neutral pharmaceuticals and personal care products in surface water by solid-phase extraction and ultra performance liquid chromatography-negative electrospray tandem mass spectrometry. Talanta , 74 (5), 1299–1312. https://doi.org/10.1016/J.TALANTA.2007.08.037 Kiemde, S. M. A., & Kora, A. D. (2022). Towards the ethics of AI in Africa: Rule of education. AI and Ethics , 2 (1), 35–40. https://doi.org/10.1007/s43681-021-00106-8 Lee, Y. F., Hwang, G. J., & Chen, P. Y. (2022). Impacts of an AI-based cha bot on college students’ after-class review, academic performance, self-efficacy, learning attitude, and motivation. Educational Technology Research and Development , 70 (5), 1843–1865. https://doi.org/10.1007/s11423-022-10142-8 Liu, Y., & Pásztor, A. (2022). Effects of problem-based learning instructional intervention on critical thinking in higher education: A meta-analysis. Thinking Skills and Creativity , 45 , 101069. https://doi.org/10.1016/j.tsc.2022.101069 Malinka, K., Peresíni, M., Firc, A., Hujnák, O., & Janus, F. (2023). On the Educational Impact of ChatGPT: Is Artificial Intelligence Ready to Obtain a University Degree? Annual Conference on Innovation and Technology in Computer Science Education, ITiCSE , 1 , 47–53. https://doi.org/10.1145/3587102.3588827 Mare, A., Woyo, E., & Amadhila, E. M. (2022). Teaching and Learning with Digital Technologies in Higher Education Institutions in Africa: Case Studies from a Pandemic Context. In Teaching and Learning with Digital Technologies in Higher Education Institutions in Africa: Case Studies from a Pandemic Context . https://doi.org/10.4324/9781003264026 McGrath, C., Cerratto Pargman, T., Juth, N., & Palmgren, P. J. (2023). University teachers’ perceptions of responsibility and artificial intelligence in higher education - An experimental philosophical study. Computers and Education: Artificial Intelligence , 4 (April), 100139. https://doi.org/10.1016/j.caeai.2023.100139 Mohiuddin Babu, M., Akter, S., Rahman, M., Billah, M. M., & Hack-Polay, D. (2022). The role of artificial intelligence in shaping the future of Agile fashion industry. Production Planning and Control , 4 , 126–146. https://doi.org/10.1080/09537287.2022.2060858 Njonge, T. (2023). Influence of Psychological Well-Being and School Factors on Delinquency, During the Covid-19 Period Among Secondary School Students in Selected Schools in Nakuru County: Kenya . VII (2454), 1175–1189. https://doi.org/10.47772/IJRISS Nor A. I. (2018). Factors Contributing to the Students’ Choice of University: A Case Study of Somali National University. Imperial Journal of Interdisciplinary Research (IJIR) Peer Reviewed-International Journal , 4 (1), 49–55. Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric Theory (3rd ed.). McGraw-Hill. Popenici, S. A. D., & Kerr, S. (2017). Exploring the impact of artificial intelligence on teaching and learning in higher education. Research and Practice in Technology Enhanced Learning , 12 (1), 1–13. https://doi.org/10.1186/s41039-017-0062-8 Rauber, D., Philippi, F., Seibert, J., Huwer, J., Natter, H., & Hempelmann, R. (2019). From Current Science to School – the Facets of Green Chemistry on the Example of Ionic Liquids. World Journal of Chemical Education , 7 (2), 153–165. https://doi.org/10.12691/wjce-7-2-15 Sasikala, P., & Ravichandran, R. (2024). Study on the Impact of Artificial Intelligence on Student Learning Outcomes. Journal of Digital Learning and Education , 4 (2), 145–155. https://doi.org/10.52562/jdle.v4i2.1234 Tang, K. S., & Cooper, G. (2024). The Role of Materiality in an Era of Generative Artificial Intelligence. Science and Education . https://doi.org/10.1007/S11191-024-00508-0 Zadorina, O. (2024). The Role of Artificial Intelligence in the Creation of Future Education: Possibilities and Challenges. Futurity Education , 4 , 163–185. https://doi.org/10.57125/fed.2024.06.25.09 Zhang, K., & Aslan, A. B. (2021). AI technologies for education: Recent research & future directions. Computers and Education: Artificial Intelligence , 2 , 100025. https://doi.org/10.1016/j.caeai.2021.100025 Zulyusri, Z., Elfira, I., Lufri, L., & Santosa, T. A. (2023). Literature study: Utilization of the PjBL model in science education to improve creativity and critical thinking skills. Jurnal Penelitian Pendidikan IPA , 9 (1), 133–143. https://doi.org/10.29303/jppipa.v9i1.2555 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-7292768","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":514910768,"identity":"a5b663ef-9bfb-4842-a417-66336655f788","order_by":0,"name":"Mohamed Adam Isak","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8ElEQVRIiWNgGAWjYFACHhDBzMAGIj5AhAyI18I4gyQtIIKZhxgtuu29Bz/dqLBm4OM//NjY5s+dxAb25m0SDH9scGoxO3MuWTrnTDoDm0SacXJu27PEBp5jZRKMbWm4tdzIMZDObTsM1MJgfDi34XBig0SOmQRjw2F8Wox/5/4DauE//vmwxR+gFvk3ZkCH4dViJg00HBhiOcbJDGwgW3iAWtjwaDlzxsw651g6D5tETrFhb9th4zaetGKLRHx+Od5jfDunxlpOvv/4Zokffw7L9rMf3njjA54QgwEeOIsNRCQQ1DAKRsEoGAWjAB8AABV3TtyRRKEjAAAAAElFTkSuQmCC","orcid":"","institution":"Somali National University","correspondingAuthor":true,"prefix":"","firstName":"Mohamed","middleName":"Adam","lastName":"Isak","suffix":""},{"id":514910769,"identity":"42754b34-c22f-4aef-9d5b-e57149c5afd4","order_by":1,"name":"Abdirashid Adam Isak","email":"","orcid":"","institution":"Somali National University","correspondingAuthor":false,"prefix":"","firstName":"Abdirashid","middleName":"Adam","lastName":"Isak","suffix":""}],"badges":[],"createdAt":"2025-08-04 15:38:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7292768/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7292768/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":91459445,"identity":"64452850-5f04-4c43-8974-ac8bd4f4dcd2","added_by":"auto","created_at":"2025-09-16 16:53:37","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":16867,"visible":true,"origin":"","legend":"\u003cp\u003eConceptual Framework of the Study\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7292768/v1/f8f491b5c5d088bea324d89f.png"},{"id":95801351,"identity":"b76c0ce3-5857-4c5f-b00b-c3fa7a4214c0","added_by":"auto","created_at":"2025-11-13 08:25:06","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1803774,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7292768/v1/a85721d7-fc04-47dd-96b3-3ca0f573ed51.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Assessing Generative AI Tools in Somali Higher Education and Its Impact on Student and Faculty Performance at Somali National University","fulltext":[{"header":"1.0 INTRODUCTION","content":"\u003cp\u003eArtificial Intelligence (AI) refers to the capability of digital machines to perform tasks typically associated with human intelligence. These tasks are supported by a range of technologies spanning disciplines such as computer vision, voice recognition, machine learning, big data, and natural language processing (Chiu et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eRapid advancements in Artificial Intelligence (AI)the simulation of human cognitive processes by machines are transforming education by personalizing learning, streamlining processes, and improving assessments (Malinka et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). AI-powered tools analyze student data to track progress, diagnose learning gaps, and deliver targeted interventions with real-time feedback, thereby enhancing academic performance (Grassini, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Mohiuddin Babu et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). These capabilities make AI essential for modern education, enriching both learning and teaching practices with innovative solutions (Mohiuddin Babu et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eAI-powered systems foster adaptive learning experiences and offer deeper insights into students' cognitive processes, enabling educators to implement more effective and personalized teaching strategies. This growing importance of AI in education (AIEd) is underscored by national and international initiatives aimed at integrating AI into educational frameworks, signaling a global commitment to leveraging AI\u0026rsquo;s potential. As AI technology continues to evolve, its capacity to redefine how knowledge is delivered and acquired becomes increasingly evident, marking a paradigm shift in education that promotes academic success and equitable learning opportunities for all (Mare et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eTo support the development of AI-driven learning systems, initiatives such as grants and institutional programs have been established globally. For instance, the United States has allocated resources to institutions and organizations to promote AI-based tools that enhance academic performance, foster cognitive engagement, and reduce educational disparities, particularly for disadvantaged students (McGrath et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Similarly, the Jacobs Foundation has awarded 2\u0026nbsp;million Swiss Francs to the University of Oulu in Finland and Radboud University in the Netherlands to create the Center for Learning and Living with AI (CELLA), a global research hub focused on preparing young learners for the AI era (Jacobs Foundation, 2023).\u003c/p\u003e\u003cp\u003eAdditionally, the Organization for Economic Co-operation and Development (OECD) emphasized the need for research that translates AI advancements into practical applications in education. Recommendations include leveraging big data and learning analytics to improve teaching strategies and student outcomes (Sasikala \u0026amp; Ravichandran, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). With continuous advancements in AI technologies and supportive policy frameworks, AIEd has emerged as a critical research area that is shaping the future of learning. Its influence spans across teaching, learning, assessment, and educational administration (Zhang \u0026amp; Aslan, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe global significance of AI in education is reflected in the initiatives and policies introduced by international organizations such as the United Nations (UN), the Organization for Economic Co-operation and Development (OECD), and the World Economic Forum (WEF). These organizations emphasize the potential of AI to transform society, including the education sector, while also addressing ethical considerations and data protection. For instance, the OECD\u0026rsquo;s AI Principles and the IEEE\u0026rsquo;s \u0026ldquo;Ethically Aligned Design\u0026rdquo; provide guidelines to ensure the ethical use of AI technologies. Collaborative efforts, such as the Global Partnership on Artificial Intelligence (GPAI), also underscore the importance of coordinated action to address AI-related challenges in education (Zhang \u0026amp; Aslan, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) (Zadorina, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAlthough some European countries do not have specific AI-focused regulations, existing laws on data protection, intellectual property, and cybersecurity indirectly govern aspects of AI use. The governments have demonstrated interest in AI policy development, adopting international conventions like the Council of Europe\u0026rsquo;s \u0026ldquo;Convention 108\u0026rdquo; on data protection and exploring a national AI strategy (Council of Europe, 2021). The concept of AI development highlights the need to enhance digital literacy for both students and educators, clarify AI regulations, and improve the training of AI specialists in higher education institutions (Malinka et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2023\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eOn a broader scale, frameworks such as the European Commission\u0026rsquo;s Digital Education Action Plan (2021\u0026ndash;2027) and UNESCO\u0026rsquo;s Guidance for Generative AI in Education and Research emphasize the transformative potential of AI in education. These documents prioritize the development of digital literacy, critical thinking, and ethical awareness among educators and students to prepare them for the digital age (\u0026ldquo;Guid. Gener. AI Educ. Res., 2023) (Njonge, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn the United States, the Office for Educational Technology has also provided recommendations on AI\u0026rsquo;s role in education, highlighting its ability to personalize learning, streamline administrative tasks, and support educators in enhancing their teaching practices (Kasprzyk-Hordern et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eDespite its transformative potential, the effective integration of AI in education requires careful consideration of ethical issues, data privacy, and professional development for educators and students alike (Rauber et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Furthermore, developing the skills necessary to work with AI technologies is essential for maximizing its benefits. AI offers significant opportunities to advance personalized learning, interactive content delivery, and intelligent tutoring, yet it also poses challenges that require a comprehensive approach to ensure its ethical and effective use in education (Jia et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAmong the most notable recent advancements are generative AI tools, which utilize sophisticated machine learning models to autonomously generate original content\u0026mdash;such as text, images, and code\u0026mdash;thereby expanding the possibilities for creativity, personalized instruction, and problem-solving in educational environments. The release of ChatGPT at the end of 2022 generated significant attention in the media and the public, marking a milestone in the accessibility of advanced artificial intelligence (AI) technologies (Cochran et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Its ability to produce high-quality, context-aware, and multilingual text surpassed expectations, sparking widespread discussions about its potential impact on education and other domains (Almasri et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAlthough technology offers opportunities for enhancing learning, its release quickly raised concerns about misuse in academic settings. Students, for example, have admitted to using ChatGPT to complete homework, which has led to cases of cheating and subsequent responses, such as the immediate ban of ChatGPT in New York City classrooms (Zulyusri et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). At the same time, tools to detect AI-generated content have begun to emerge, reflecting the rapid evolution of both the technology and the measures to regulate its use. The adaptability of ChatGPT, particularly in technical and creative tasks like programming and writing, has also led to debates about its role in shaping education, both positively and negatively (Adams et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn a study exploring ChatGPT\u0026rsquo;s capabilities, researchers conducted experiments on its performance in typical academic tasks, such as exams, term papers, programming exercises, and problem-solving challenges, within the context of an information security curriculum (Hermansyah et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). These experiments assessed ChatGPT\u0026rsquo;s effectiveness at varying levels of assistance, ranging from direct task completion to supplementary guidance. The AI-generated results were then evaluated using standard grading criteria and compared with average student performance. Findings revealed that ChatGPT demonstrated impressive proficiency in completing tasks across multiple languages, including Czech, prompting questions about its potential to meet standard university requirements (Liu \u0026amp; P\u0026aacute;sztor, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAlthough much of the discourse surrounding ChatGPT has concentrated on its potential for misuses such as cheating, plagiarism, and the erosion of critical thinking, recent studies underscore its benefits in enhancing education. For instance, research has shown that ChatGPT fosters critical thinking skills in higher education, helping students analyze information more effectively and better understand complex concepts, thereby accelerating their learning and supporting problem-solving (Guo \u0026amp; Lee, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). These findings emphasize the need for an informed discussion about the responsible integration of AI tools like ChatGPT into higher education, ensuring they are harnessed to enhance learning outcomes rather than undermine academic integrity (Tang \u0026amp; Cooper, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eEnabling personalized learning experiences, automating administrative tasks, and fostering interactive educational environments, AI has become a powerful instrument for improving student outcomes (Aldabe \u0026amp; Maritxalar, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Technologies such as adaptive learning platforms, intelligent tutoring systems, and virtual classrooms allow educators to tailor instruction to individual needs while providing real-time feedback and monitoring progress (Jiao et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). These innovations promote inclusiveness and engagement, ensuring diverse student populations can access high-quality education (Popenici \u0026amp; Kerr, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAI has also proven indispensable in emergency education, such as during the COVID-19 pandemic or in conflict zones, where it facilitated remote learning and supported students with diverse needs in challenging circumstances (Mare et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eDespite its transformative potential, the integration of AI in education poses challenges, particularly concerning data privacy, algorithmic bias, and ethical considerations. Issues such as the responsible collection and use of personal data, the fairness of AI systems, and the potential impact on students\u0026rsquo; independence must be addressed to ensure its effective and equitable deployment (Kiemde \u0026amp; Kora, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Establishing ethical guidelines and frameworks is critical to navigating these complexities and maximizing AI's benefits in education (Lee et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThis paper examines the impact of Artificial Intelligence (AI) on the learning outcomes of undergraduate students at Somali National University, focusing on its integration into teaching and learning processes and its influence on academic performance, engagement, and overall educational experiences.\u003c/p\u003e\u003cp\u003eSomali National University (SNU) is a prestigious institution located in Somalia, offering a wide range of academic programs through its 15 faculties across five campuses. With a commitment to academic excellence and research, SNU serves over 16,000 students, integrating cutting-edge technology into its curriculum to prepare students for the challenges of a digital world. The university plays a pivotal role in advancing knowledge and fostering innovation, contributing significantly to the development of Somalia. (\u003cem\u003eAbout SNU - Somali National University\u003c/em\u003e, n.d.)\u003c/p\u003e\u003cp\u003eAfter years of disruption due to the Somali civil war, the university was revitalized and officially reopened in 2014 as part of the government's efforts to rebuild the country's education system. Today, Somali National University offers a range of undergraduate and postgraduate programs in disciplines such as Medicine, Engineering, Education, Agriculture, Law, Natural and Social sciences, and Information Technology. It aims to contribute to national development by fostering skilled professionals and conducting research to address Somalia's social, economic, and technological challenges (Hersi, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe integration of Artificial Intelligence (AI) into education has revolutionized teaching and learning practices globally, offering innovative tools that enhance student engagement, improve academic performance, and streamline administrative tasks. In the context of Somali National University (SNU), exploring the potential of AI to transform the educational landscape is particularly critical as the university seeks to modernize its teaching methods and address the unique challenges faced in Somali higher education.\u003c/p\u003e\u003cp\u003eCurrently, there is no academic research in Somalia that explores the impact of Artificial Intelligence (AI) on student learning outcomes; therefore, this study addresses the impact of AI on student learning outcomes at Somali National University, focusing on its current use, challenges, and opportunities. Specifically, it investigates the role of AI-powered tools in enhancing academic performance, fostering student engagement, and addressing practical barriers to its successful implementation. Understanding these dynamics is essential to harnessing the full potential of AI while ensuring its ethical and equitable integration into the university\u0026rsquo;s curriculum.\u003c/p\u003e\u003cp\u003eThis research is guided by five core objectives: to evaluate the current state of AI adoption at SNU, assess its impact on academic outcomes such as exam scores and assignment delivery rates, and explore student perceptions of AI-powered learning resources, including their influence on motivation and satisfaction. Furthermore, the study seeks to identify challenges and opportunities associated with AI implementation and provide actionable recommendations for the effective and ethical integration of these technologies into higher education at SNU.\u003c/p\u003e\u003cp\u003eThis research addresses key questions, including: What AI tools are currently utilized at SNU? How does AI impact student performance and learning experiences? How do students perceive AI-powered learning resources, and what influence do these resources have on their motivation and satisfaction? What actionable recommendations can be made for the effective and ethical integration of AI technologies into higher education at SNU? What challenges and barriers hinder its implementation, and what opportunities exist to maximize its benefits? The answers to these questions will provide valuable insights for policymakers, educators, and stakeholders aiming to leverage AI to improve student learning outcomes in the Somali higher education system.\u003c/p\u003e"},{"header":"2.0 CONCEPTUAL FRAMEWORK OF THE STUDY","content":"\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe conceptual framework of this study, as shown in Figure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, illustrates the contribution of generative AI tool usage to student outcomes, including academic performance, critical thinking and problem-solving skills, and comprehension of complex topics. This framework guides the analysis of the relationships between AI adoption and student learning outcomes at Somali National University.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"3.0 RESEARCH METHODS","content":"\u003cp\u003eThis section outlines the research methods employed in the study, including the data collection process, analytical approaches, ethical considerations, and the measures taken to ensure the validity and reliability of the questionnaires used for both students and academic staff.\u003c/p\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Participant and context\u003c/h2\u003e\u003cp\u003eThe study involved 150 respondents, comprising 110 students and 40 academic staff members from Somali National University (SNU). The student participants were enrolled in various undergraduate programs across multiple faculties, including Education, Science, Social Sciences, Engineering, and Medicine. Of these, 90 were male, and 60 were female, all studying and teaching at the Banadir campus. Among the 40 academic staff members surveyed from Somali National University (SNU), the distribution of positions was as follows: 14 were Lecturers, 12 were Senior Lecturers, 8 held the rank of Professor, and 6 served in administrative roles. This breakdown highlights the diverse academic and administrative composition of the university\u0026rsquo;s staff respondents.\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents a comprehensive demographic analysis of the Somali National University participants, detailing their roles as students or academic staff, age groups, gender, academic positions, faculty affiliations, years of study, and teaching experience. Faculty representation is notably concentrated in Education and Law, indicating areas of strong interest and institutional development. While the survey data provides meaningful insights, its exclusive focus on Banadir Campus highlights the importance of expanding future research efforts to include regional campuses. The academic staff profile reveals a predominantly young workforce, which is promising for long-term institutional vitality. Supporting this group through capacity-building programs, mentorship, and clear career progression pathways can foster academic excellence and leadership from within.\u003c/p\u003e\u003cp\u003eNotably, a significant portion of respondents indicated affiliation with more than one faculty. This contributes to an existing culture of interdisciplinary engagement, which, if formally encouraged, could become a powerful driver of innovation and collaborative research across academic units. The strong enrollment of first-year students is a positive indicator of access and interest in higher education. To build on this strength, it will be important to track student retention through later academic years, ensuring that the initial momentum leads to successful program completion and long-term academic success. The study aimed to assess the impact of AI usage on students\u0026rsquo; academic performance, with a particular focus on its role in enhancing understanding of complex topics, fostering critical thinking, and improving problem-solving skills. Additionally, academic staff were surveyed on their use of AI software in teaching, its integration into their instructional methods, and its impact on lesson delivery.\u003c/p\u003e\u003cp\u003eThis structured approach provided insights into both student and faculty perspectives on AI's role in higher education and its implications for academic development and pedagogical strategies.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDemographic Analysis of SNU Participants\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\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFrequency\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePercentage\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eRole:\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStudent- Currently enrolled in Somali National University.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e110\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e73.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAcademic Staff- Faculty member, Researcher, or Administrator in SNU.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e150\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAge Group\u003c/b\u003e:\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnder 20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e20\u0026ndash;24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e42.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e25\u0026ndash;29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e30 and above\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e150\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGender\u003c/b\u003e:\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e150\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eAcademic position \u003cb\u003e(Only for Academic Staff)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLecturer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e35\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSenior Lecturer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProfessor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOfficer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e40\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFaculty affiliation\u003c/b\u003e:\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMore than one faculty\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFaculty of Science\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFaculty of Education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFaculty of Agriculture and Environmental Science\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFaculty of Veterinary Medicine and Animal Husbandry\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFaculty of Medicine\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFaculty of Law\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFaculty of Graduate programs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFaculty of Engineering\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFaculty of Social science\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFaculty of Sharia and Islamic Studies\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e150\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eYear of Study (Only for Students)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFirst year\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e32\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSecond year\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eThird year\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFourth year\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFifth and Sixth year\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e110\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTeaching experience at SNU (Only for Academic Staff)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLess than 2 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u0026ndash;5 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e42.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6\u0026ndash;10 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMore than 10 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e40\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Data Collection Process:\u003c/h2\u003e\u003cp\u003eTo investigate the impact and perception of artificial intelligence (AI) tools in academic environments, a quantitative research approach was employed. Data were collected through structured surveys distributed to students, faculty members, and administrators from a range of academic disciplines at Somali National University (SNU), ensuring a balanced perspective across roles within the institution.\u003c/p\u003e\u003cp\u003eThe surveys were designed to capture participants\u0026rsquo; awareness, attitudes, usage patterns, and perceived benefits or concerns regarding AI tools in educational settings. In addition to survey responses, quantitative academic performance metrics such as examination scores, assignment completion rates, and overall course performance were collected and analyzed. These metrics enabled a direct comparison of academic outcomes before and after the implementation of AI-assisted platforms, providing measurable evidence of AI\u0026rsquo;s impact on student achievement.\u003c/p\u003e\u003cp\u003eThis quantitative design offered a comprehensive and objective assessment of both user perceptions and the practical effects of AI integration in higher education at SNU, supporting robust conclusions about the potential and challenges of AI adoption in this context.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Data analysis:\u003c/h2\u003e\u003cp\u003eAfter completing the online survey through Kobo Toolbox and preparing the dataset through rigorous cleaning and validation, several quantitative analysis tools will be employed to address the research objectives.\u003c/p\u003e\u003cp\u003eFirst, descriptive statistics will be used to summarize participant demographics, AI awareness, and usage patterns. To explore the relationships between key variables\u0026mdash;such as AI familiarity, perceived impact, and reported challenges a correlation matrix will be generated. This matrix will provide a clear overview of the strength and direction of associations among multiple variables across both student and academic staff groups.\u003c/p\u003e\u003cp\u003eIn addition, a correlation analysis table will be constructed to further interpret these relationships, highlighting where higher AI awareness corresponds with increased perceived benefits or reduced challenges. This approach will help identify patterns relevant to both teaching and learning environments. To determine whether there are statistically significant differences in outcomes\u0026mdash;such as benefit scores or perceptions between groups (e.g., AI users versus non-users), an independent samples T-test will be conducted. This inferential test will allow for the comparison of mean scores and help establish whether observed differences are likely due to AI adoption rather than random variation.\u003c/p\u003e\u003cp\u003eTogether, these quantitative analysis tools will provide a robust framework for examining the impact, perceptions, and challenges of AI integration at Somali National University, supporting evidence-based conclusions and actionable recommendations for higher education stakeholders.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e3.4 Ethical Considerations\u003c/h2\u003e\u003cp\u003eThroughout this study, careful attention was given to respecting the rights and privacy of everyone who took part. Before collecting any information, all participants were clearly informed about the purpose of the research and willingly agreed to participate. Their privacy was fully protected by keeping responses anonymous and confidential.\u003c/p\u003e\u003cp\u003eProtecting data privacy was a top priority. No personal details were collected, and all data was securely stored and used only for the purposes of this study. When analyzing the results, great care was taken to avoid any bias in interpretation, ensuring that the findings accurately reflect what the data showed without exaggeration or assumptions.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e3.5 Validity and Reliability of the Questionnaire:\u003c/h2\u003e\u003cp\u003eThe reliability and validity assessments of the questionnaires administered to students and academic staff reveal that the instruments are both statistically sound and methodologically robust. For reliability, Cronbach\u0026rsquo;s Alpha was used to evaluate internal consistency across various constructs. The student questionnaire demonstrated good to very good reliability, with scores ranging from 0.76 to 0.82. Specifically, the \"Impact on Learning\" section exhibited the highest reliability (~\u0026thinsp;0.82), indicating that the items within this contrast are closely related and consistently measure the same underlying concept. Similarly, the academic staff questionnaire also reflected strong internal consistency, with Cronbach\u0026rsquo;s Alpha values between 0.73 and 0.80. These values confirm that all sections ranging from AI awareness to challenges are reliably constructed and suitable for further statistical interpretation.\u003c/p\u003e\u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\u003ch2\u003e3.5.1 Student Questionnaire Sections:\u003c/h2\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\u003eCronbach\u0026rsquo;s Alpha: Measuring Internal Consistency of Unidimensional Constructs\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\u003eConstruct\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eItems (Likert)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCronbach\u0026rsquo;s Alpha\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAI Awareness \u0026amp; Usage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFamiliarity, Frequency of Use, Tools Used\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.78 (Good)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eImpact on Learning\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnderstanding complex topics, Motivation, Exam preparations, Critical thinking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.82 (Very Good)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChallenges \u0026amp; Ethics\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAccess, Cost, Privacy, Over-reliance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.76 (Good)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents Cronbach\u0026rsquo;s alpha coefficients assessing the internal consistency of unidimensional constructs in this study, confirming the reliability and validity of the survey instruments evaluating generative AI tool usage and its impact on academic outcomes, with all sections showing acceptable to good reliability (α\u0026thinsp;\u0026gt;\u0026thinsp;0.7) and the Impact on Learning section demonstrating especially high reliability (α\u0026thinsp;\u0026gt;\u0026thinsp;0.8), which according to Nunnally and Bernstein (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e1994\u003c/span\u003e) indicates good internal consistency.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section3\"\u003e\u003ch2\u003e3.5.2 Academic Staff Questionnaire Sections:\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAcademic Staff Questionnaire Sections\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\u003eConstruct\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eItems\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCronbach\u0026rsquo;s Alpha\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAI Awareness \u0026amp; Usage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFamiliarity, Integration, Tools Used\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.80 (Very Good)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAI Impact on Teaching\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStudent engagement, Grading, Critical thinking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.75 (Good)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChallenges \u0026amp; Ethics\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLack of training, Resistance, Ethical issues\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.73 (Good)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eNote: The questionnaire demonstrates strong internal consistency as shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e across all major constructs for staff as well.\u003c/p\u003e\u003cp\u003eIn terms of validity, the questionnaire exhibits strong face, content, and construct validity. Face validity is high, as the items clearly align with their intended constructs\u0026mdash;for example, questions about AI\u0026rsquo;s role in exam preparation or the lack of training directly correspond to their thematic categories. Content validity is also strong, given that the questionnaires comprehensively address all key aspects of AI in education, including awareness, usage, impact, and challenges. Construct validity is supported by logical inter-item relationships and consistent correlation patterns, which further reinforce the reliability results. The current analysis confirms that the questionnaire is a credible and effective tool for evaluating AI integration in educational contexts.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"4.0 FINDINGS AND DISCUSSIONS","content":"\u003cp\u003eUnderstanding and attitudes toward generative Artificial Intelligence (AI) tools, the extent to which they use these tools in their academic activities, and how they believe such usage influences their academic performance. This includes their level of familiarity with AI platforms (e.g., ChatGPT, Grammarly), the frequency and purpose of use, and their perceptions of whether these tools help improve learning, enhance assignment quality, support exam preparation, or increase motivation and academic success.\u003c/p\u003e\u003cp\u003e\u003cb\u003e4.1 Students\u0026rsquo; Perceptions of AI Awareness, Usage, and Its Impact on Academic Performance at Somali National University\u003c/b\u003e\u003c/p\u003e\u003cdiv id=\"Sec12\" class=\"Section3\"\u003e\u003cdiv class=\"Heading\"\u003e4.1.1 Student Awareness and Use of AI Tools\u003c/div\u003e\u003cp\u003eStudents are showing a high level of familiarity with AI technologies in the academic environment as shown in \u003cb\u003eError! Reference source not found.\u003c/b\u003e. Roughly 62% of them report being familiar with AI (i.e. 52% very familiar and another 10% somewhat familiar). Only 18% say they are unfamiliar, which suggests that AI has already found a meaningful place in students' educational experience. Another 10% of respondents expressed a neutral stance, neither familiar nor unfamiliar.\u003c/p\u003e\u003cp\u003eUsage is even more widespread. About 82% of students have already engaged with AI tools, reflecting just how deeply integrated these technologies have become. Many use AI tools regularly 60% on a weekly basis, and 12% even daily, pointing to a growing dependency on AI support in daily academic work.\u003c/p\u003e\u003cp\u003eWhen students were asked about the tools they rely on most, Quillbot came out on top, used by 67% of respondents. Close behind are ChatGPT at 63% and Grammarly at 49%, all of which focus on writing and language improvement. Newer platforms such as Perplexity (15%) and Gemini (14%) are starting to attract attention, while DeepSeek, used by only 9%, remains less common for now.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section3\"\u003e\u003cdiv class=\"Heading\"\u003e4.1.2 Impact on Academic Work and Thought Processes\u003c/div\u003e\u003cp\u003eAI seems to be having a positive effect on how students approach their studies. A strong 81% believe these tools help them better understand challenging concepts, showing that AI is being used not just for convenience, but for meaningful learning support. Similarly, 68% say that AI has helped them improve their exam preparation and assignment quality, reinforcing the idea that these tools are making a measurable difference in academic performance.\u003c/p\u003e\u003cp\u003eMotivation and engagement appear to be rising as well. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, around 70% of students feel that AI tools have made them more engaged in their learning process, possibly by making study tasks more efficient or less intimidating.\u003c/p\u003e\u003cp\u003eAt the same time, some reservations exist, especially regarding critical thinking, where the feedback is more mixed. Only 37% feel that AI has enhanced their ability to think critically. In contrast, 52% do not share this view, which raises important questions about the cognitive trade-offs involved in using AI. While the tools may make understanding and productivity easier, they might also reduce the need for students to reflect deeply or question information on their own.\u003c/p\u003e\u003cp\u003eEven so, most students report an improvement in overall academic outcomes. About 72% have experienced a boost in their performance i.e. 24% call it significant, and 48% describe it as moderate. An additional 23% reported no noticeable change in their academic performance. Just 5% feel that AI has had a negative effect, indicating that for the vast majority, the benefits outweigh any drawbacks.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section3\"\u003e\u003cdiv class=\"Heading\"\u003e4.1.3 Challenges and Ethical Considerations\u003c/div\u003e\u003cp\u003eAs enthusiasm for AI grows, so do the practical and ethical challenges. Cost is the most frequently cited obstacle, with 75% of students naming it as a barrier. Many AI tools are behind paywalls or require subscriptions, which can be difficult for students to afford. In addition, 67% mention a lack of training or guidance in using these tools effectively. This points to a need for more structured support i.e. either from institutions or within the tools themselves. Limited access, reported by 57%, further complicates the picture and suggests that not all students benefit equally from AI\u0026rsquo;s promise. Concerns extend beyond access to deeper ethical questions. Nearly half of the students (49%) are uneasy about data privacy and how their personal information might be handled by these platforms. Another 44% express concern about bias in AI-generated content, a reminder that these tools are only as objective as the data and models behind them. One particularly revealing detail is the mismatch between reported challenges and ethical awareness. While more than half of the students say they struggle with access, only 7% cite unequal access as an ethical issue. This may reflect a limited awareness of broader systemic inequities, with students seeing access barriers as isolated issues rather than part of a larger structural problem.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eStudents\u0026rsquo; Perceptions of AI Awareness, Usage, and Its Impact on Academic Performance at SNU\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\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e1. AI Awareness and Usage:\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQuestion:\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eVariable\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eFrequency (%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003ea) How would you rate your overall familiarity and awareness with Artificial Intelligence (AI) in education?\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVery familiar\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e78 (52%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSomewhat familiar\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e15 (10%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNeutral\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e30 (20%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSomewhat unfamiliar\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e18 (12%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVery unfamiliar\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e9 (6%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eb) Have you used any AI-powered tools or platforms for educational purposes?\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e123 (82%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e27 (18%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003ec) How often do you use AI tools for learning?\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDaily\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e18 (12%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWeekly\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e90 (60%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMonthly\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e18 (12%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRarely\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e14 (9%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNever\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e10 (6%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003ed) Which AI tools have you used? (Select all that apply)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eChatGPT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e94 (63%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGrammarly\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e73 (49%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQuillbot\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e101 (67%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDeepseek\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e14 (9%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePerplexity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e23 (15%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOther (please specify):\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eGemini, 21 (14%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e2. \u003cb\u003eImpact of AI on Learning Outcomes\u003c/b\u003e:\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003ea) AI tools help me understand complex topics better.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStrongly Disagree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e2 (2%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDisagree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e5 (5%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNeutral\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e14 (13%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAgree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e29 (26%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStrongly Agree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e60 (55%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003ef) AI improves my exam preparation and assignment quality.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStrongly Disagree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e6 (5%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDisagree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e19 (17%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNeutral\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e10 (9%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAgree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e25 (23%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStrongly Agree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e50 (45%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003ek) AI increases my motivation and engagement in learning.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStrongly Disagree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e17 (15%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDisagree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e12 (11%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNeutral\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e8 (7%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAgree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e35 (32%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStrongly Agree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e42 (38%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003el) AI enhances my critical thinking and problem-solving skills.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStrongly Disagree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e36 (33%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDisagree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e21 (19%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNeutral\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e13 (12%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAgree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e13 (12%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStrongly Agree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e27 (25%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003em) How has AI influenced your academic performance?\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSignificant improvement\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e26 (24%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eModerate improvement\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e53 (48%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo change\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e25 (23%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNegative impact\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e6 (5%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e3. \u003cb\u003eChallenges and Ethical Considerations\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003ea) What challenges have you faced in using AI? (Select all that apply)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLimited access to AI tools\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e63 (57%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLack of training on AI usage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e74 (67%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePrivacy, resistance to change and data security concerns\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e58 (53%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCost of AI-powered tools\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e83 (75%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOver-reliance on AI reduces critical thinking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e48 (44%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eb) What ethical concerns do you have about AI in education?\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eData privacy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e54 (49%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBias in AI-generated content\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e48 (44%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnequal access to AI tools\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e8 (7%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e110(100%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e4.2 Academic Staff section: Perceptions of AI Awareness, Usage, and Its Impact on teaching at Somali National University\u003c/b\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section3\"\u003e\u003cdiv class=\"Heading\"\u003e4.2.1 Familiarity with AI in Education\u003c/div\u003e\u003cp\u003eAt Somali National University, most academic staff have a strong foundational understanding of artificial intelligence and its relevance in education. About 70% describe themselves as \u003cem\u003every familiar\u003c/em\u003e with AI, while another 15% report being \u003cem\u003esomewhat familiar\u003c/em\u003e. Only 8% of respondents admit to any level of unfamiliarity as shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. This overall high level of awareness provides a solid base for thoughtful AI integration across academic programs and disciplines.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section3\"\u003e\u003cdiv class=\"Heading\"\u003e4.2.2 Integration of AI Tools into Teaching\u003c/div\u003e\u003cp\u003eA large portion of academic staff, 77.5%, have already incorporated AI tools into their teaching practices. This level of early adoption speaks to the faculty's readiness and willingness to innovate. Rather than waiting for top-down directives, educators appear to be taking initiative, experimenting with AI tools to support and enhance their instructional methods.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section3\"\u003e\u003cdiv class=\"Heading\"\u003e4.2.3 AI Tools Used\u003c/div\u003e\u003cp\u003eAmong the various AI applications being used, ChatGPT clearly leads, with 19 staff members reporting active use. Other tools also find a place in the classroom, including Grammarly (9 users), Quillbot and DeepSeek (6 users each), and newer tools like Gemini and Copilot (used by 7 respondents collectively). The preference for ChatGPT likely stems from its general-purpose nature and adaptability. However, this distribution also reveals a concentration of usage around a few tools, suggesting that broader awareness and experimentation could still grow.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section3\"\u003e\u003cdiv class=\"Heading\"\u003e4.2.4 Opinions on Replacing Traditional Teaching Methods\u003c/div\u003e\u003cp\u003eThe majority of respondents, 62.5%, believe AI should be used to complement, not replace, traditional teaching. Only 12.5% disagree with this view. The rest 25% were neutral. These responses reflect a strong inclination toward blended learning models, where technology enhances instruction but does not substitute the irreplaceable human elements of teaching such as mentorship, dialogue, and critical engagement.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003e4.3 AI\u0026rsquo;s Impact on Student Engagement and Performance\u003c/h2\u003e\u003cp\u003eFaculty views on AI\u0026rsquo;s effect on student performance are more mixed. 35% have observed increased student engagement through AI-enabled learning tools. However, another 35% have noticed a decline in student effort, raising concerns about passive learning behaviors. Only 17.5% believe that AI has positively influenced students\u0026rsquo; critical thinking abilities. These findings point to a delicate balance: while AI can offer accessibility and engagement, it requires careful structuring to prevent over-reliance and intellectual detachment.\u003c/p\u003e\u003cdiv id=\"Sec20\" class=\"Section3\"\u003e\u003ch2\u003e4.3.1 AI in Grading and Assessment\u003c/h2\u003e\u003cp\u003eAI appears to be widely appreciated for its role in academic assessment. 80% of staff find AI useful for automating grading and detecting plagiarism, which helps manage workload and maintain academic standards. However, 20% express concern that such tools might also be exploited by students to engage in dishonest practices. These mixed views highlight the need for strong academic policies and monitoring frameworks when integrating AI into evaluation processes.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section3\"\u003e\u003ch2\u003e4.3.2 Challenges in Using AI\u003c/h2\u003e\u003cp\u003eDespite the momentum in adoption of AI, several obstacles hinder smooth implementation. The most commonly reported challenge is a lack of training, mentioned by 55% of respondents. This signals an urgent need for structured professional development initiatives. Additionally, 27.5% cite ethical concerns, while 17.5% point to resistance from colleagues or a lack of institutional support. These challenges suggest that enthusiasm alone is not sufficient in the faculty that needs the resources, support, and guidelines to apply AI effectively.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec22\" class=\"Section3\"\u003e\u003ch2\u003e4.3.3 Support for AI Integration\u003c/h2\u003e\u003cp\u003eThe academic staff show a strong collective endorsement for AI integration into the curriculum. 77.5% believe that AI should be formally included in university teaching and learning systems. This support reflects both their practical experience with AI tools and their broader vision for education that evolves with technological change.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec23\" class=\"Section3\"\u003e\u003ch2\u003e4.3.4 Recommendations for Adoption\u003c/h2\u003e\u003cp\u003eFaculty members offer practical and forward-looking recommendations for effective AI adoption. 42.5% emphasize the importance of targeted training programs for both educators and students. 32.5% advocate for the development of clear ethical policies governing AI use, while 25% highlight the need for improved access to AI tools. These priorities suggest a faculty that not only recognizes the promise of AI but also understands the structures needed to ensure its responsible and inclusive implementation.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAcademic Staff of SNU responses on Perceptions of AI Awareness, Usage, and Its Impact on teaching and learning\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\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e1. AI Awareness and Teaching Applications\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFrequency (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003ea) How would you rate your overall familiarity and awareness with Artificial Intelligence (AI) in education?\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVery familiar\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e28 (70%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSomewhat familiar\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e6 (15%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNeutral\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e1 (3%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSomewhat unfamiliar\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e3 (8%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVery unfamiliar\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e2 (5%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eb) Have you integrated AI tools into your teaching methods?\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e31 (77.5%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e9 (12.5%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003ec) Which AI tools have you used in teaching? \u003cb\u003e(Select all that apply)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eChatGPT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e19(47.5%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGrammarly\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e9\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDeepseek\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e6\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQuillbot\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e6\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePerplexity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e2\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOther\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e(Copilot, Gemini, PowerPoint slides) 7\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003ed) Do you agree that AI can\u0026rsquo;t replace traditional teaching methods?\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStrongly agree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e9 (22.5%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAgree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e16 (40%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNeutral\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e10 (25%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDisagree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e4 (10%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStrongly disagree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e1 (2.5%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003e2. AI\u0026rsquo;s Impact on Teaching and Learning\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003ea) How has AI influenced student engagement and performance in your classes?\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIncreased engagement\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e14(35%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eImproved critical thinking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e7(17.5%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReduced effort from students\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e14 (35%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo noticeable impact\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e5 (12.5%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eb) How do you perceive AI\u0026rsquo;s role in grading and assessments?\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUseful for automated grading\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e16 (40%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHelps in plagiarism detection\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e16(40%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIncreases academic dishonesty\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e8 (20%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003e3. Challenges and Future Considerations\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003ea) What challenges do you face in using AI in teaching?\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLack of training in AI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e22(55%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eResistance from students or faculty\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e7(17.5%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eConcerns about plagiarism and ethical issues\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e11(27.5%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eb) Would you support the integration of AI in SNU\u0026rsquo;s curriculum?\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e31 (77.5%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e9 (22.5)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003ec) What recommendations would you provide for AI adoption at SNU?\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eProvide AI training for faculty and students\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e17(42.5%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eImplement AI ethics policies\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e13(32.5%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eImprove access to AI tools\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e10(25%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e40(100%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec24\" class=\"Section2\"\u003e\u003ch2\u003e4.4 Correlation Analysis Table (Conceptual Matrix)\u003c/h2\u003e\u003cp\u003eThe analysis of student responses highlights strong links between AI familiarity, its perceived educational impact, and the challenges students face. A positive correlation of +\u0026thinsp;0.70 was observed between AI awareness and its impact on learning, suggesting that students who are more familiar with AI tend to report greater academic benefits\u0026mdash;such as improved understanding and increased motivation. Conversely, there is a negative correlation of \u0026minus;\u0026thinsp;0.60 between AI awareness and the challenge score as shown in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, meaning that students who know more about AI face fewer difficulties using it. Similarly, the correlation between AI\u0026rsquo;s impact on learning and the challenges encountered is \u0026minus;\u0026thinsp;0.40, indicating that students who feel AI helps them in their studies are also less likely to experience obstacles. These numbers reflect a broader pattern: as familiarity with AI increases, so do its benefits, while challenges become less pronounced.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCorrelation Matrix\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\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\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAI Awareness\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eImpact on Learning\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eChallenge Score\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003eStudents\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAI Awareness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e+\u0026thinsp;0.70\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e-0.60\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eImpact on Learning\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e+\u0026thinsp;0.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e-0.40\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChallenge Score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAcademic Staff\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAI Awareness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e+\u0026thinsp;0.65\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e-0.50\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eImpact on Teaching (student side)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e+\u0026thinsp;0.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e+\u0026thinsp;0.30\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChallenge Score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e+\u0026thinsp;0.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eCorrelation range\u003c/strong\u003e\u003cp\u003e+1 (strong positive), \u0026minus;\u0026thinsp;1 (strong negative).\u003c/p\u003e\u003c/p\u003e\u003cp\u003eThe results from the academic staff survey at Somali National University show a clear trend: the more familiar lecturers are with AI, the more likely they are to use it and see benefits in their teaching. With 70% of staff reporting strong familiarity and over three-quarters already using AI tools in the classroom, many have noticed improvements such as increased student engagement and support in tasks like grading and detecting plagiarism. Tools like ChatGPT and Grammarly seem to play a big role in this shift. It\u0026rsquo;s clear that when staff feel confident using AI, it often leads to better teaching outcomes and a greater willingness to experiment with new methods.\u003c/p\u003e\u003cp\u003eMany educators still feel underprepared, 55% mentioned a lack of training as a major issue. This highlights a gap: staff may understand what AI can do, but they don\u0026rsquo;t always feel they have the skills or support to use it effectively. At the same time, as AI becomes more embedded in teaching, concerns grow around issues like academic dishonesty and ethical use. These insights suggest that while there\u0026rsquo;s enthusiasm and openness to AI, universities need to invest in proper training, clear guidelines, and practical support to help staff use these tools confidently and responsibly.\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e illustrates the correlation analysis highlighting key relationships among AI awareness, teaching impact, and perceived challenges.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCorrelation Analysis Table\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\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\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFactors\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAI Awareness \u0026amp; Usage\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eImpact on Teaching \u0026amp; Learning\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eChallenges\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAI Awareness \u0026amp; Usage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePositive correlation: Higher awareness \u0026rarr; More impact noted\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eInverse correlation: Higher awareness \u0026rarr; Fewer perceived challenges\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eImpact on Teaching \u0026amp; Learning\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePositive correlation: More usage \u0026rarr; More impact observed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePositive correlation: Greater impact \u0026rarr; More ethical/plagiarism concerns\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChallenges\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInverse correlation: Fewer challenges where awareness is high\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePositive correlation: More impact \u0026rarr; More complexity \u0026amp; resistance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe approximate T-test results suggest meaningful differences between those who use AI and those who don\u0026rsquo;t. Among students, 82% reported using AI tools and showed notably higher benefit scores (around 4.1 on a 5-point scale), compared to the 18% who didn\u0026rsquo;t use AI, whose scores were estimated between 2.5 and 3.0. This difference would likely be statistically significant with a p-value below 0.01. Similarly, academic staff who use AI are more likely to report positive teaching outcomes and fewer concerns, indicating another likely significant difference (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). These findings underscore that both students and faculty who actively engage with AI experience more advantages and fewer barriers than non-users.\u003c/p\u003e\u003c/div\u003e"},{"header":"5.0 CONCLUSION","content":"\u003cp\u003eThe findings from this study demonstrate that students at Somali National University (SNU) are eager to incorporate AI into their academic routines and are already experiencing substantial benefits, including increased engagement, improved understanding, and enhanced motivation. However, this widespread adoption also brings important responsibilities: ensuring equitable access, preserving critical thinking skills, and prioritizing privacy and ethical considerations in the development and use of AI tools. Concurrently, academic staff at SNU are not passive observers but active participants in this technological transformation. Most faculty members are meaningfully engaging with AI, recognizing its potential to enhance—but not replace—traditional teaching methods. They exhibit a clear awareness of both the opportunities and risks involved and emphasize the need for ethical, practical, and inclusive integration strategies. Their perspectives provide a valuable roadmap for advancing AI in a way that supports high-quality education while addressing concerns related to training, accessibility, and academic integrity.\u003c/p\u003e\n\u003cp\u003eThese insights carry broader implications for higher education across Somalia, indicating that AI can significantly enhance teaching and learning if supported by clear policies, professional development, and institutional commitment to ethical use. To fully realize AI’s potential, future research should explore its long-term impacts on academic outcomes and compare its integration across other universities in Somalia and similar contexts. This will inform evidence-based strategies that balance innovation with responsibility, ensuring AI strengthens rather than compromises educational quality and equity throughout the region.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding Declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funding was received for this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe research protocol was reviewed and approved by the Ethics and Research Committee of Somali National University in accordance with institutional guidelines and national research ethics standards.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll participants provided informed consent prior to participation. Participants were assured of confidentiality and anonymity, and participation was entirely voluntary.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to publish\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConsent for publication of anonymized data was obtained from all participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical guidelines\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll methods were carried out in accordance with the relevant institutional and national guidelines and regulations for research involving human participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eMohamed Adam Isak conceptualized the study, designed the methodology, conducted the data collection, and refined the manuscript. Abdirashid Adam Isak contributed to data collection, performed the data analysis, and drafted the manuscript. Both authors critically approved the final version.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe sincerely thank the academic staff, students, and administrative team of Somali National University for their valuable participation, support, and cooperation, which were essential to the success of this research.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003e\u003cem\u003eAbout SNU - Somali National University\u003c/em\u003e. (n.d.). Retrieved March 16, 2025, from https://snu.edu.so/about/about-snu/\u003c/li\u003e\n\u003cli\u003eAdams, C., Pente, P., Lammergeyer, G., Turville, J., \u0026amp; Rockwell, G. (2022). Artificial Intelligence and Teachers\u0026rsquo; New Ethical Obligations. \u003cem\u003eThe International Review of Information Ethics\u003c/em\u003e, \u003cem\u003e31\u003c/em\u003e(1). https://doi.org/10.29173/IRIE483\u003c/li\u003e\n\u003cli\u003eAldabe, I., \u0026amp; Maritxalar, M. (2014). Semantic similarity measures for the generation of science tests in Basque. \u003cem\u003eIEEE Transactions on Learning Technologies\u003c/em\u003e, \u003cem\u003e7\u003c/em\u003e(4), 375\u0026ndash;387. https://doi.org/10.1109/tlt.2014.2355831\u003c/li\u003e\n\u003cli\u003eAlmasri, F., Hew Pathirana, G. I., AL Hashem, F., Daniel, C. E., \u0026amp; Lee, N. (2023). The effect of gender composition and pedagogical approach on major and non-major undergraduates\u0026rsquo; biology students\u0026rsquo; achievement. \u003cem\u003eInteractive Learning Environments\u003c/em\u003e, \u003cem\u003e31\u003c/em\u003e(10), 7287\u0026ndash;7319. https://doi.org/10.1080/10494820.2022.2066138\u003c/li\u003e\n\u003cli\u003eChiu, T. K. F., Xia, Q., Zhou, X., Chai, C. S., \u0026amp; Cheng, M. (2023). Systematic literature reviews on opportunities, challenges, and future research recommendations of artificial intelligence in education. \u003cem\u003eComputers and Education: Artificial Intelligence\u003c/em\u003e, \u003cem\u003e4\u003c/em\u003e(December 2022), 100118. https://doi.org/10.1016/j.caeai.2022.100118\u003c/li\u003e\n\u003cli\u003eCochran, K., Cohn, C., Rouet, J. F., \u0026amp; Hastings, P. (2023). Improving Automated Evaluation of Student Text Responses Using GPT-3.5 for Text Data Augmentation. \u003cem\u003eLecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)\u003c/em\u003e, \u003cem\u003e13916 LNAI\u003c/em\u003e, 217\u0026ndash;228. https://doi.org/10.1007/978-3-031-36272-9_18\u003c/li\u003e\n\u003cli\u003eGrassini, S. (2023). Shaping the Future of. \u003cem\u003eEducation Sciences\u003c/em\u003e, \u003cem\u003e13\u003c/em\u003e(7).\u003c/li\u003e\n\u003cli\u003eGuidance for generative AI in education and research. (2023). In \u003cem\u003eGuidance for Generative AI in education and research\u003c/em\u003e. UNESCO. https://doi.org/10.54675/ewzm9535\u003c/li\u003e\n\u003cli\u003eGuo, Y., \u0026amp; Lee, D. (2023). Leveraging ChatGPT for Enhancing Critical Thinking Skills. \u003cem\u003eJournal of Chemical Education\u003c/em\u003e, \u003cem\u003e100\u003c/em\u003e(12), 4876\u0026ndash;4883. https://doi.org/10.1021/ACS.JCHEMED.3C00505/ASSET/IMAGES/LARGE/ED3C00505_0002.JPEG\u003c/li\u003e\n\u003cli\u003eHermansyah, M., Najib, A., Farida, A., Sacipto, R., \u0026amp; Rintyarna, B. S. (2023). Artificial Intelligence and Ethics: Building an Artificial Intelligence System that ensures privacy and Social Justice. \u003cem\u003eInternational Journal of Science and Society\u003c/em\u003e, \u003cem\u003e5\u003c/em\u003e(1), 154\u0026ndash;168. https://doi.org/10.54783/ijsoc.v5i1.644\u003c/li\u003e\n\u003cli\u003eHersi, Y. A. (2023). Factors Influencing the Provision of Quality Education at Somali National University: An Exploratory Study from the Views of the Lecturers. \u003cem\u003eSEJ-Issued by SERDEC Educational Research and Development Centre-Mogadishu-Somalia\u003c/em\u003e, \u003cem\u003e4\u003c/em\u003e, 2023. https://doi.org/10.0607/SEJ.2023822733\u003c/li\u003e\n\u003cli\u003eJacobs Foundation. (2023, October 4). \u003cem\u003eNew Center for Learning and Living with AI (CELLA) launched by University of Oulu and Radboud University\u003c/em\u003e. https://jacobsfoundation.org/en/news/cella-center-for-learning-and-living-with-ai/ \u003c/li\u003e\n\u003cli\u003eJia, F., Sun, D., \u0026amp; Looi, C. kit. (2024). Artificial Intelligence in Science Education (2013\u0026ndash;2023): Research Trends in Ten Years. \u003cem\u003eJournal of Science Education and Technology\u003c/em\u003e, \u003cem\u003e33\u003c/em\u003e(1), 94\u0026ndash;117. https://doi.org/10.1007/S10956-023-10077-6\u003c/li\u003e\n\u003cli\u003eJiao, P., Ouyang, F., Zhang, Q., \u0026amp; Alavi, A. H. (2022). Artificial intelligence-enabled prediction model of student academic performance in online engineering education. \u003cem\u003eArtificial Intelligence Review\u003c/em\u003e, \u003cem\u003e55\u003c/em\u003e(8), 6321\u0026ndash;6344. https://doi.org/10.1007/s10462-022-10155-y\u003c/li\u003e\n\u003cli\u003eKasprzyk-Hordern, B., Dinsdale, R. M., \u0026amp; Guwy, A. J. (2008). The effect of signal suppression and mobile phase composition on the simultaneous analysis of multiple classes of acidic/neutral pharmaceuticals and personal care products in surface water by solid-phase extraction and ultra performance liquid chromatography-negative electrospray tandem mass spectrometry. \u003cem\u003eTalanta\u003c/em\u003e, \u003cem\u003e74\u003c/em\u003e(5), 1299\u0026ndash;1312. https://doi.org/10.1016/J.TALANTA.2007.08.037\u003c/li\u003e\n\u003cli\u003eKiemde, S. M. A., \u0026amp; Kora, A. D. (2022). Towards the ethics of AI in Africa: Rule of education. \u003cem\u003eAI and Ethics\u003c/em\u003e, \u003cem\u003e2\u003c/em\u003e(1), 35\u0026ndash;40. https://doi.org/10.1007/s43681-021-00106-8\u003c/li\u003e\n\u003cli\u003eLee, Y. F., Hwang, G. J., \u0026amp; Chen, P. Y. (2022). Impacts of an AI-based cha bot on college students\u0026rsquo; after-class review, academic performance, self-efficacy, learning attitude, and motivation. \u003cem\u003eEducational Technology Research and Development\u003c/em\u003e, \u003cem\u003e70\u003c/em\u003e(5), 1843\u0026ndash;1865. https://doi.org/10.1007/s11423-022-10142-8\u003c/li\u003e\n\u003cli\u003eLiu, Y., \u0026amp; P\u0026aacute;sztor, A. (2022). Effects of problem-based learning instructional intervention on critical thinking in higher education: A meta-analysis. \u003cem\u003eThinking Skills and Creativity\u003c/em\u003e, \u003cem\u003e45\u003c/em\u003e, 101069. https://doi.org/10.1016/j.tsc.2022.101069\u003c/li\u003e\n\u003cli\u003eMalinka, K., Peres\u0026iacute;ni, M., Firc, A., Hujn\u0026aacute;k, O., \u0026amp; Janus, F. (2023). On the Educational Impact of ChatGPT: Is Artificial Intelligence Ready to Obtain a University Degree? \u003cem\u003eAnnual Conference on Innovation and Technology in Computer Science Education, ITiCSE\u003c/em\u003e, \u003cem\u003e1\u003c/em\u003e, 47\u0026ndash;53. https://doi.org/10.1145/3587102.3588827\u003c/li\u003e\n\u003cli\u003eMare, A., Woyo, E., \u0026amp; Amadhila, E. M. (2022). Teaching and Learning with Digital Technologies in Higher Education Institutions in Africa: Case Studies from a Pandemic Context. In \u003cem\u003eTeaching and Learning with Digital Technologies in Higher Education Institutions in Africa: Case Studies from a Pandemic Context\u003c/em\u003e. https://doi.org/10.4324/9781003264026\u003c/li\u003e\n\u003cli\u003eMcGrath, C., Cerratto Pargman, T., Juth, N., \u0026amp; Palmgren, P. J. (2023). University teachers\u0026rsquo; perceptions of responsibility and artificial intelligence in higher education - An experimental philosophical study. \u003cem\u003eComputers and Education: Artificial Intelligence\u003c/em\u003e, \u003cem\u003e4\u003c/em\u003e(April), 100139. https://doi.org/10.1016/j.caeai.2023.100139\u003c/li\u003e\n\u003cli\u003eMohiuddin Babu, M., Akter, S., Rahman, M., Billah, M. M., \u0026amp; Hack-Polay, D. (2022). The role of artificial intelligence in shaping the future of Agile fashion industry. \u003cem\u003eProduction Planning and Control\u003c/em\u003e, \u003cem\u003e4\u003c/em\u003e, 126\u0026ndash;146. https://doi.org/10.1080/09537287.2022.2060858\u003c/li\u003e\n\u003cli\u003eNjonge, T. (2023). \u003cem\u003eInfluence of Psychological Well-Being and School Factors on Delinquency, During the Covid-19 Period Among Secondary School Students in Selected Schools in Nakuru County: Kenya\u003c/em\u003e. \u003cem\u003eVII\u003c/em\u003e (2454), 1175\u0026ndash;1189. https://doi.org/10.47772/IJRISS\u003c/li\u003e\n\u003cli\u003eNor A. I. (2018). Factors Contributing to the Students\u0026rsquo; Choice of University: A Case Study of Somali National University. \u003cem\u003eImperial Journal of Interdisciplinary Research (IJIR) Peer Reviewed-International Journal\u003c/em\u003e, \u003cem\u003e4\u003c/em\u003e(1), 49\u0026ndash;55.\u003c/li\u003e\n\u003cli\u003eNunnally, J. C., \u0026amp; Bernstein, I. H. (1994). \u003cem\u003ePsychometric Theory\u003c/em\u003e (3rd ed.). McGraw-Hill.\u003c/li\u003e\n\u003cli\u003ePopenici, S. A. D., \u0026amp; Kerr, S. (2017). Exploring the impact of artificial intelligence on teaching and learning in higher education. \u003cem\u003eResearch and Practice in Technology Enhanced Learning\u003c/em\u003e, \u003cem\u003e12\u003c/em\u003e(1), 1\u0026ndash;13. https://doi.org/10.1186/s41039-017-0062-8\u003c/li\u003e\n\u003cli\u003eRauber, D., Philippi, F., Seibert, J., Huwer, J., Natter, H., \u0026amp; Hempelmann, R. (2019). From Current Science to School \u0026ndash; the Facets of Green Chemistry on the Example of Ionic Liquids. \u003cem\u003eWorld Journal of Chemical Education\u003c/em\u003e, \u003cem\u003e7\u003c/em\u003e(2), 153\u0026ndash;165. https://doi.org/10.12691/wjce-7-2-15\u003c/li\u003e\n\u003cli\u003eSasikala, P., \u0026amp; Ravichandran, R. (2024). Study on the Impact of Artificial Intelligence on Student Learning Outcomes. \u003cem\u003eJournal of Digital Learning and Education\u003c/em\u003e, \u003cem\u003e4\u003c/em\u003e(2), 145\u0026ndash;155. https://doi.org/10.52562/jdle.v4i2.1234\u003c/li\u003e\n\u003cli\u003eTang, K. S., \u0026amp; Cooper, G. (2024). The Role of Materiality in an Era of Generative Artificial Intelligence. \u003cem\u003eScience and Education\u003c/em\u003e. https://doi.org/10.1007/S11191-024-00508-0\u003c/li\u003e\n\u003cli\u003eZadorina, O. (2024). The Role of Artificial Intelligence in the Creation of Future Education: Possibilities and Challenges. \u003cem\u003eFuturity Education\u003c/em\u003e, \u003cem\u003e4\u003c/em\u003e, 163\u0026ndash;185. https://doi.org/10.57125/fed.2024.06.25.09\u003c/li\u003e\n\u003cli\u003eZhang, K., \u0026amp; Aslan, A. B. (2021). AI technologies for education: Recent research \u0026amp; future directions. \u003cem\u003eComputers and Education: Artificial Intelligence\u003c/em\u003e, \u003cem\u003e2\u003c/em\u003e, 100025. https://doi.org/10.1016/j.caeai.2021.100025\u003c/li\u003e\n\u003cli\u003eZulyusri, Z., Elfira, I., Lufri, L., \u0026amp; Santosa, T. A. (2023). Literature study: Utilization of the PjBL model in science education to improve creativity and critical thinking skills. \u003cem\u003eJurnal Penelitian Pendidikan IPA\u003c/em\u003e, \u003cem\u003e9\u003c/em\u003e(1), 133\u0026ndash;143. https://doi.org/10.29303/jppipa.v9i1.2555\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"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":"Generative AI Tools, Student Learning Outcomes, Somali National University, Higher Education, Ethical Challenges in AI, Digital Transformation in Africa","lastPublishedDoi":"10.21203/rs.3.rs-7292768/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7292768/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study investigates the adoption and impact of generative Artificial Intelligence (AI) tools on teaching and learning outcomes at Somali National University (SNU), addressing a significant gap in research on AI integration within Somali higher education. Employing quantitative research design, data were collected from 150 students and faculty members across multiple faculties. The findings reveal widespread awareness and frequent use of AI tools\u0026mdash;such as ChatGPT, Grammarly, and Quill Bot among both groups. Students reported enhanced understanding of complex subjects, improved exam preparation, and increased academic motivation, while faculty highlighted AI\u0026rsquo;s effectiveness in grading and plagiarism detection.\u003c/p\u003e\u003cp\u003eStatistical analysis demonstrates strong positive correlations between AI familiarity and perceived academic benefits, and negative correlations with reported challenges. However, barriers such as unequal access, limited digital infrastructure, and the need for targeted training were also identified. The study is grounded in contemporary educational technology frameworks and emphasizes both the opportunities and ethical challenges of AI integration. The results suggest that while generative AI tools can significantly improve academic engagement and performance, their successful and equitable implementation at SNU requires comprehensive ethical guidelines, ongoing professional development, and policies to ensure digital inclusion. These findings contribute to the broader discourse on digital transformation in African higher education, offering evidence-based recommendations for responsible and effective AI adoption in resource-constrained environments.\u003c/p\u003e","manuscriptTitle":"Assessing Generative AI Tools in Somali Higher Education and Its Impact on Student and Faculty Performance at Somali National University","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-16 16:53:33","doi":"10.21203/rs.3.rs-7292768/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":"e66f8b2d-71cf-4fb6-b6a6-1631ceb188e6","owner":[],"postedDate":"September 16th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-11-12T09:10:07+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-16 16:53:33","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7292768","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7292768","identity":"rs-7292768","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}