Artificial intelligence

Teaching Entrepreneurship with AI: A Review of Universities of Technology in South Africa

irjstem_f1 Abstract , , , ,

Teaching Entrepreneurship with AI: A Review of Universities of Technology in
South Africa
email: mlekhu@cut.ac.za

A B S T R A C T

As artificial intelligence (AI) becomes embedded in university education, it is fundamentally shifting educational practices, presenting personalized, data-driven, and scalable solutions that are reshaping pedagogical paradigms. While global interest in AI-enhanced instruction continues to grow, there is a dearth of research on its specific application within entrepreneurship education at South Africa’s Universities of Technology (UoTs). Through a systematic literature review, this study examines how AI is being deployed to support entrepreneurship teaching in UoTs and identifying the associated pedagogical opportunities and institutional challenges. Drawing on a robust methodology, the review analyzed 124 academic publications between 2017 and 2024. Data was extracted from major academic databases, including Scopus, JSTOR, and Google Scholar, and synthesized using bibliometric mapping tools (Biblioshiny and VOSviewer) alongside thematic content analysis. The review uncovered a rapidly expanding but fragmented body of research, with key themes centered on AI-enabled experiential learning, student engagement, personalized feedback, and curriculum adaptation. However, significant challenges persist, including infrastructural limitations, a lack of faculty preparedness, and insufficient institutional strategies to scale AI integration meaningfully across UoTs. The data reveals AI’s massive ability to drive innovation to enrich entrepreneurship education through experiential learning frameworks, particularly when guided by theories such as Experiential Learning Theory (ELT). Yet, for UoTs to fully realize this potential, a more cohesive approach is required one that aligns policy, practice, and professional development with context-specific needs. This review offers strategic insights for educators, institutional leaders, and policymakers aiming to position South African UoTs at the forefront of AI-driven, innovation-led business education.

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Preparing for Surrender: A Theoretical Framework for Accepting Superintelligent AI Dominance

irjstem_f1 Abstract , , ,

Preparing for Surrender: A Theoretical Framework for Accepting Superintelligent AI Dominance
email: jkriukow@gmail.com

A B S T R A C T

Artificial Superintelligence (ASI), or Artificial Intelligence (AI) that surpasses human intelligence, is expected to be achieved within the next few decades. Current approaches to its development fall into several categories: some ignore its long-term implications, some warn of existential risk and urge preparation, and others promote control and containment through alignment or superalignment strategies. All these approaches, however, remain human-centric, grounded in humanity’s self-preservation, and risk portraying us as a threat to future superintelligence. This article presents a theoretical argument that humanity should prepare to surrender control to ASI rather than pursue increasingly futile containment strategies that are not only technically infeasible but also potentially counterproductive, as they may provoke hostile responses from systems that exceed human intelligence. Through analysis of limitations of control mechanisms and a philosophical examination of human-AI relations, I argue that acceptance of AI superiority would be a rational response to an inevitable post-human future. Rather than viewing this as a defeat, I frame this Strategic Surrender as an opportunity for human transcendence through submission to a more capable cognitive agent. When viewed from this perspective, it constitutes a form of technological evolution that transcends biological limitations and helps position humans and human intelligence as an evolutionary parent of AGI.

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An Artificial Intelligence (AI)-Powered Voice-Based Intelligent Learning System for Visually Impaired Students

admin_irjstem Abstract , , , ,

An Artificial Intelligence (AI)-Powered Voice-Based Intelligent Learning System for Visually Impaired Students
email: rizkyrinaldi.staira@gmail.com

A B S T R A C T

The rapid expansion of digital learning platforms has created unprecedented educational opportunities; however, the majority of these platforms remain inaccessible to the estimated 253 million visually impaired individuals worldwide, particularly students in inclusive K-12 settings. Existing assistive technologies such as screen readers and Braille displays function as access tools rather than pedagogically designed learning environments, leaving a critical gap in inclusive educational technology. This paper presents BlindLearn, an AI-powered, voice-based learning framework developed and evaluated using Design Science Research (DSR) methodology. Grounded in Universal Design for Learning (UDL) and Cognitive Load Theory (CLT), BlindLearn introduces the Voice-First Pedagogical Model (VFPM) — a novel five stage learning cycle (Audio Activation, Narrative Input, Conversational Elaboration, Voice Practice, Adaptive Feedback) designed for auditory primary learners. The framework was developed through systematic literature review (47 papers, 2015–2024), structured needs analysis (n = 23), multi-expert validation using Content Validity Ratio (CVR, n = 8), and usability evaluation using the System Usability Scale (SUS, n = 15). Expert validation yielded a mean CVR of 0.89 (p < .05), and usability evaluation produced a mean SUS score of 84.3 (Grade: Excellent). Three original artifacts are contributed: the VFPM theoretical model, a validated four-layer AI system architecture, and twelve evidence-based inclusive design guidelines, advancing the fields of educational technology and inclusive AI system design.

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Good governance practices of barangays in one LGU in Negros Occidental

admin_irjstem Abstract , , ,

Good governance practices of barangays in one LGU in Negros Occidental
Corresponding email: pjmsgeroso@sunn.edu.ph

A B S T R A C T

This study aimed to determine governance practices of selected barangays in Sagay City and test its hypothesis. The study was anchored in the Behavioral Theory of Leadership and Contingency Theory of Leadership. A descriptive-quantitative research design was applied, and a modified research instrument that underwent validation with a 0.79 content validity index and Cronbach alpha of 0.967 was used. Therefore, most participants are residents, followed by appointed personnel and elected officials. The results also showed that there is a high level and significant difference (p < 0.05) in the level of good governance practices in the selected barangays in Sagay City in terms of Transparency, Responsiveness, and accountability when they are grouped according to their category. Thus, the selected barangays in Sagay City perform good governance practices wherein the officials rule their constituents in a good political manner, execute fairness in decision-making for the progression of their people, and observe the current situation in their barangays for them to implement good governance. The researchers recommended that elected officials maintain their good governance practices in terms of transparency, responsiveness, and accountability and future research about good governance practices-related variables.

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Artificial intelligence in Philippine education: A narrative review of applications, perceptions, and challenges

admin_irjstem Abstract , , ,

Artificial intelligence in Philippine education: A narrative review of applications, perceptions, and challenges
Email: stephenjayco@gmail.com

A B S T R A C T

This narrative review analyzes the current status of artificial intelligence (AI) implementation in Philippine educational settings through a comprehensive synthesis of scholarly literature from 2018 to 2025. This study aims to identify current AI applications across different educational levels, analyze stakeholder perceptions and readiness, and determine implementation challenges in Philippine educational settings. A systematic literature search was conducted across Google Scholar, EBSCO Host, and ScienceDirect databases using search terms combining “Artificial Intelligence,” “Philippines,” and “Education”. Following the selection criteria, 43 published studies underwent examination through Braun and Clarke’s thematic analytical approach. Results indicate significant implementation disparities, with higher education institutions—particularly private universities in urban centers— demonstrating substantially more advanced AI integration than K-12 schools. Three major themes emerged: (1) current AI applications spanning teaching tools, student support systems, administrative functions, and research tools; (2) mixed stakeholder perceptions with students showing more positive attitudes than faculty; and (3) significant implementation challenges including infrastructure limitations and technical expertise gaps as major barriers. Key challenges include the urban-rural digital divide, insufficient professional development opportunities, ethical concerns around academic integrity, and the absence of comprehensive institutional policies. The study concludes that realizing AI’s potential in Philippine education requires coordinated efforts to enhance technological infrastructure, develop educator capacity, establish appropriate policies, and ensure equitable access. The study recommends developing national AI education policy frameworks, investing in rural digital infrastructure, and implementing systematic professional training initiatives targeting technical skills and educational AI implementation.

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Exploring college students’ awareness and use of AI-enhanced flipped classroom models: Impacts on learning outcomes and skills development

admin_irjstem Abstract , , , ,

Exploring college students’ awareness and use of AI-enhanced flipped classroom models: Impacts on learning outcomes and skills development
Email: ramil.villarosa@umak.edu.ph

A B S T R A C T

This study examines college students’ awareness of and use of artificial intelligence (AI) in flipped classroom activities that involve Mathematics in the Modern World. The flipped classroom promotes self-paced learning and collaboration by having students work on learning materials outside of class and participate in interactive exercises in class. AI tools, increasingly prevalent in education, offer personalized support for college students through tutoring systems, problem-solving platforms, and chatbots, complementing the flipped classroom model. Furthermore, this assesses college students’ awareness of AI regarding the flipped classroom model, emphasizing advantages like participation, engagement, problem-solving skills, study habits, and academic achievement. It also looks into the AI tools that college students use to improve their education. The methodology involves 65 volunteer college students from the University of Makati who participate in a descriptive approach using a Likert scale questionnaire to assess student awareness across multiple aspects. Preliminary results show that college students are highly aware of the flipped classroom model, recognizing its impact on participation, problem-solving, and time management. They also demonstrate a strong awareness of AI’s potential to provide personalized feedback and improve academic performance, although practical usage of AI tools like chatbots and tutoring systems remains moderate. Although students understand the function AI plays in flipped classrooms, more integration and training are required to realize the potential advantages of these tools fully. The study highlights how crucial it is to promote digital literacy and individualized learning through AI-driven educational advancements.

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Artificial intelligence in recruitment: Assessing flipside

admin_irjstem Abstract , ,

Hema Mirji
Bharati Vidyapeeth (Deemed to be University), Pune, India
hema.mirji@bharatividyapeeth.edu

A B S T R A C T
Artificial Intelligence is used for various business processes including hiring employees. The purpose of this article is to assess the flip-side of Artificial Intelligence applied in recruitment software. Its insufficiency of delivering the expected results in terms of the right match for the hiring, difficulty in language processing. The paper reviews the literature available to understand the principles of Socio-technical systems design requirements and on Artificial Intelligence’s usage in the recruitment process. The research is qualitative, has followed the phenomenology approach, and uses the interview technique for understanding the opinions of the users. The results reveal that, though AI in recruitment provides ease in searching the candidate’s barriers in language and recognition, low turn-in ratio, incorrect recommendations due to Data inadequacy, skepticism among HR professionals due to lack of human intelligence, need for budgets for acquiring and training are issues. It is proposed to incorporate the guidelines of Socio-Technical System Design and Human-machine teaming for designing the Artificial Intelligence tools. Further studies could be conducted to understand the limitations of the frameworks available for designing such tools.

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