Between Innovation and Tradition: A Narrative Inquiry of Students’ and Teachers’ Experiences with ChatGPT in Philippine Higher Education

Abstract

This study investigates the integration of ChatGPT in Philippine higher education institutions (HEIs) through narrative inquiry, employing Clandinin and Connelly’s three-dimensional framework (temporality, sociality, place) to explore the lived experiences of 18 participants (10 students, 8 faculty). The research identifies three global themes: (1) the need for strong ethical guidelines amid widespread but tacit “silent acceptance” of AI use, (2) faculty efforts to adapt traditional pedagogy while addressing concerns about critical thinking erosion, and (3) strategies to optimize ChatGPT’s utility without exacerbating inequities. Participant narratives reveal divergent adoption patterns: urban stakeholders leverage ChatGPT for efficiency and learning augmentation, while rural counterparts face infrastructural barriers that deepen the urban–rural divide. Students report evolving ethical engagement, from initial dependency to reflective use, whereas faculty grapple with academic integrity and assessment redesign. The findings underscore how cultural resistance, institutional policy gaps, and technological disparities shape ChatGPT’s uneven adoption, reinforcing existing educational inequalities. This study contributes to the literature on AI in education by proposing context-sensitive strategies for equitable integration, including offline AI tools for rural areas, faculty training programs, and transparent policy frameworks. By centering stakeholder narratives, the research advocates for culturally grounded AI adoption that balances innovation with pedagogical integrity, offering a model for Global South contexts facing similar challenges.

1. Introduction

Artificial Intelligence (AI) has significantly altered educational practices, expanding pedagogical possibilities in contemporary learning environments. ChatGPT (GPT-3.5) has become an important tool among AI innovations, offering educators and learners immediate responses, customized instruction, and administrative efficiency. These features allow instructors to focus more on substantive teaching, but their effectiveness depends heavily on the institutional and cultural context. While AI tools like ChatGPT are transforming education globally, their adoption in the Philippines is uniquely shaped by the country’s urban–rural divide and cultural factors, necessitating a context-specific exploration.

In Philippine higher education institutions (HEIs), the adoption of ChatGPT is influenced by the stark contrast between urban and rural settings. Urban universities often benefit from modern technological infrastructure, reliable internet connectivity, and greater access to digital resources. In contrast, rural institutions face significant challenges, including limited internet access, inadequate infrastructure, and lower levels of technological literacy. According to recent reports, only 40% of rural areas in the Philippines have reliable internet access, compared to 80% in urban centers (Estrellado 2023). These disparities create unique opportunities and barriers for ChatGPT adoption, highlighting the need for a nuanced understanding of how rural and urban contexts influence its integration.

Despite the Philippines being one of the top five countries for ChatGPT usage (Piquero 2024) current research has not adequately examined how the unique cultural and organizational characteristics of Philippine HEIs affect the implementation and use of this technology. The high usage of ChatGPT in the Philippines may be attributed to the country’s young, tech-savvy population and the increasing availability of affordable internet services in urban areas. However, the urban–rural divide and cultural resistance to technological change hinder adoption, particularly in resource-constrained settings.

This study employs narrative inquiry as its theoretical framework to address these gaps. Narrative inquiry is a qualitative methodology that focuses on capturing the lived experiences of individuals through storytelling, allowing researchers to explore complex social phenomena in their natural context (Clandinin and Connelly 2004). This approach is particularly well-suited for understanding how cultural, institutional, and ethical factors shape the integration of ChatGPT in Philippine HEIs. By documenting the narratives of students and faculty, this study seeks to uncover the nuanced ways in which ChatGPT is adopted, resisted, and adapted within diverse educational settings. Guided by this methodology, the study analyzes participant stories through the lenses of temporality (evolution of ChatGPT use over time), sociality (interpersonal and institutional dynamics), and place (urban–rural disparities), offering a holistic understanding of AI integration challenges.

Despite ChatGPT’s global adoption being well documented, its role in reinforcing or mitigating inequality remains understudied, particularly in contexts like the Philippines, where pre-existing educational stratification intersects with technological access. The following literature review synthesizes these dual lenses: AI in education and social inequity.

2. Literature Review

Integrating AI tools like ChatGPT in education has transformed teaching, learning, and administrative practices worldwide, offering unprecedented opportunities for personalized learning and efficiency. However, its adoption varies significantly across contexts, shaped by technological infrastructure, digital literacy, and cultural attitudes. ChatGPT presents promise and challenges in the Philippines, where a stark urban–rural divide and uneven access to resources mark higher education. While it has the potential to democratize education and enhance learning outcomes, its integration raises critical ethical concerns, including academic integrity, data privacy, and the risk of exacerbating existing inequalities. This literature review explores the global trends in AI adoption, the unique challenges and opportunities in the Philippine context, and the perspectives of students, faculty, and institutions. By addressing the gap in understanding how cultural, institutional, and infrastructural factors shape ChatGPT integration, this study aims to provide insights into its equitable and culturally sensitive adoption in Philippine higher education.

2.1. AI in Education: Global Context and Trends

AI integration in educational settings has evolved significantly over the past decade, transforming from experimental technologies to essential tools that reshape teaching and learning practices worldwide (Zawacki-Richter et al. 2019). Large Language Models (LLMs) like ChatGPT represent a paradigm shift in educational technology, offering unprecedented capabilities for natural language processing, content generation, and personalized learning support (Dwivedi et al. 2023). Unlike previous educational technologies, these AI systems can engage in sophisticated conversations, generate customized learning materials, and provide immediate feedback across diverse subjects and tasks (Chang et al. 2024).

The global adoption of ChatGPT in higher education has been remarkably swift and widespread. Within months of its public release in November 2022, universities across North America, Europe, Asia, and Australia began reporting significant usage among students and faculty (Rudolph et al. 2023). This rapid adoption has prompted diverse institutional responses ranging from outright bans to strategic integration into curriculum and pedagogical practices (Strzelecki 2023).

Research by Mollick and Mollick (2023) indicates that faculty members worldwide utilize ChatGPT for various purposes, including course preparation, assignment design, and administrative tasks. Simultaneously, students have embraced these tools for research assistance, writing support, and conceptual understanding (Al-Shuaili 2025). This widespread adoption has catalyzed debates about the changing nature of assessment, academic integrity, and the development of critical thinking skills in AI-enhanced learning environments.

The global literature reveals significant variations in AI adoption patterns across regions and educational contexts. Developed nations with robust technological infrastructure and high digital literacy rates show more extensive and sophisticated integration of AI tools in education (Díaz and Nussbaum 2024). Conversely, developing regions face additional challenges related to technological access, faculty training, and alignment with existing pedagogical frameworks.

While global studies highlight ChatGPT’s efficiency gains (Al-Shuaili 2025; Annamalai et al. 2025), the Philippine context reveals infrastructural and cultural barriers, necessitating tailored adoption strategies, a gap this study addresses. The following section examines these unique challenges in Philippine HEIs.

2.2. Philippine Higher Education Landscape

Historically, innovation and inequality have characterized technology adoption in Philippine higher education. Urban centers and premier institutions have demonstrated leadership in technology integration, while provincial and smaller institutions often lag due to resource constraints (Sharma et al. 2024). The COVID-19 pandemic accelerated digital transformation across the sector, forcing institutions to rapidly adopt online learning platforms and digital tools (Talidong and Toquero 2020).

Digital literacy among Filipino students and faculty presents a complex picture. Research by Estrellado (2023) indicates that while younger generations of students generally possess basic digital skills, significant disparities exist based on socioeconomic background, geographic location, and prior educational experiences. Faculty digital literacy shows even greater variation, with many educators requiring additional training and support to effectively integrate new technologies into their teaching practices (Al-Mughairi and Bhaskar 2024). Infrastructure remains a critical challenge for technology adoption in Philippine higher education. Internet connectivity varies dramatically across the archipelago, with many areas experiencing limited bandwidth, high costs, and unreliable service. A significant digital divide persists between urban and rural institutions, influencing the feasibility and effectiveness of technology-enhanced learning initiatives (Ligot 2024).

Policy frameworks governing technology in Philippine higher education have evolved in recent years. CHED has implemented various initiatives promoting digital transformation, including the Smart Campus project and guidelines for flexible learning modalities. However, specific policies addressing AI tools like ChatGPT remain limited, creating uncertainty for institutions navigating this emerging landscape (Talidong and Toquero 2020).

Recent studies examining technology adoption in Philippine higher education highlight several key factors influencing implementation success. These include institutional leadership support, faculty professional development, student readiness, and alignment with educational objectives (Espartinez 2024). Cultural factors also play significant roles, with traditional teaching paradigms sometimes conflicting with the collaborative and student-centered approaches facilitated by new technologies (Talidong and Toquero 2020). The intersection of global AI trends and the unique characteristics of Philippine higher education creates both opportunities and challenges. As Espartinez (2024) noted, successfully integrating tools like ChatGPT will require contextualized approaches that address the Philippine educational settings’ specific needs, constraints, and cultural nuances.

2.3. Comparative Analysis: Philippine ChatGPT Adoption in Global Perspective

When contextualized internationally, the Philippines’ ChatGPT adoption reveals global parallels and unique disparities. Unlike the U.S., where 67% of students use ChatGPT uniformly across urban and rural institutions (Rudolph et al. 2023), or South Korea’s standardized national integration (Kohnke et al. 2025), the Philippines exhibits a stark “high-urban/low-rural” divide. Urban universities match Global North adoption rates, while rural institutions languish below 15% (Estrellado 2023), a gap exceeding even India’s urban–rural disparity (Sharma et al. 2024). This bifurcation mirrors broader educational inequalities in the Global South, where AI tools often amplify existing privilege (Buckingham 2020; Mhlanga 2023).

Critically, the Philippines’ high English proficiency, a linguistic advantage for ChatGPT use, clashes with its infrastructural deficits. While this combination theoretically enables wider accessibility than in non-Anglophone developing nations, rural connectivity barriers create a “capability-accessibility gap” (de la Torre and Baldeon-Calisto 2024). For example, Brazilian universities mitigate this with offline AI tools for low-connectivity areas, and Thailand’s “Smart Campus” initiative that prioritizes equitable infrastructure (Achruh et al. 2024), solutions absent in the Philippines’ fragmented landscape. These contrasts highlight how systemic inequities shape AI adoption (Sharma et al. 2024).

Faculty attitudes further reflect equity concerns. Where U.S. and European educators focus on academic integrity (Mollick and Mollick 2023), and East Asian systems emphasize complementary integration (Kohnke et al. 2025), Philippine faculty express pragmatic anxiety about ChatGPT widening urban–rural divides. This contrasts with African contexts, where AI tools help compensate faculty shortages (Mhlanga 2023)—a benefit unrealized in Philippine rural HEIs due to infrastructural gaps (Talidong and Toquero 2020).

Policy fragmentation exacerbates these issues. While Nigeria and Kenya have implemented national AI education frameworks (Mhlanga 2023), Philippine governance remains decentralized, resulting in “silent acceptance”—a policy vacuum that disproportionately harms rural institutions lacking resources to self-regulate (Espartinez 2024). This governance gap perpetuates what Buckingham (2020) terms “digital redlining”, where marginalized communities face compounded disadvantages.

The Philippine case thus argues for equity-centered adaptation of global models: Brazil’s offline tools for rural areas, Thailand’s infrastructure investments, and Japan’s mentorship-aligned AI (Kohnke et al. 2025). As Sharma et al. (2024) stress, without deliberate intervention, ChatGPT risks becoming another stratification mechanism in education—a warning acutely relevant to the Philippines’ divided landscape.

2.4. ChatGPT Applications and Stakeholder Perspectives in Educational Settings

The integration of ChatGPT in education has introduced diverse applications, generating varied responses from stakeholders. As a versatile tool, it supports writing assistance, problem-solving, idea generation, and multilingual content translation for students (Bhullar et al. 2024; Rudolph et al. 2023). Educators leverage it to create teaching materials, design assessments, provide personalized feedback, and enhance interactive learning (Mollick and Mollick 2023).

Student perceptions are mainly favorable, with many appreciating its instant feedback, constant availability, and non-judgmental assistance (Zhai 2022). A study by Yang et al. (2024) found that 76% of university students reported positive learning experiences with ChatGPT. However, concerns persist about over-reliance, information accuracy, and unequal access (Espartinez 2024). Faculty exhibit greater ambivalence, acknowledging benefits while worrying about academic integrity, critical thinking erosion, and shifts in student–teacher dynamics (Al-khresheh 2024; Kung et al. 2023). These concerns are particularly pronounced among less tech-savvy educators and disciplines reliant on traditional writing and analytical skills.

Institutional responses have evolved from restrictive policies to more balanced frameworks emphasizing responsible use, digital literacy, and assessment redesign (Rasul et al. 2024). Leading institutions prioritize clear guidelines, faculty training, and robust infrastructure (Dwivedi et al. 2023). A collaborative, inclusive approach is essential to address stakeholder concerns while maximizing educational benefits.

2.5. Benefits, Opportunities, Challenges, and Concerns

ChatGPT’s implementation in higher education presents a mix of advantages and challenges. A key benefit is enhanced accessibility, offering 24/7 support that transcends geographical and temporal barriers, potentially leveling the playing field for disadvantaged students, non-native speakers, and those with learning disabilities (Gao et al. 2024; Himang et al. 2023). Studies also indicate improved engagement, knowledge retention, and writing proficiency, with AI-driven feedback fostering iterative learning and personalized pathways (Yang et al. 2024). Also, educators gain efficiency in material preparation, grading, and administrative tasks, freeing time for mentorship and high-impact teaching (Kung et al. 2023).

However, challenges remain. Academic integrity is a significant concern, as AI-assisted work complicates plagiarism detection and necessitates rethinking assessments (Sharma et al. 2024). Over-reliance on ChatGPT may hinder critical thinking and original writing skills (Al-Shuaili 2025), while disparities in digital literacy and access risk exacerbating inequities (Buckingham 2020). Privacy and data security issues further complicate adoption, requiring policies that balance personalized learning with ethical data use.

Successful integration demands comprehensive strategies, including policy development, stakeholder education, and continuous evaluation. Institutions must navigate these complexities to harness AI’s potential while mitigating risks.

2.6. Research Gap

Despite the growing body of literature on AI integration in education, there is a critical gap in understanding how cultural, institutional, and infrastructural factors specific to the Philippines shape the adoption and utilization of ChatGPT in higher education. While global studies have explored the benefits and challenges of AI tools like ChatGPT, few have examined how these tools are integrated in contexts marked by significant urban–rural disparities, limited technological infrastructure, and unique cultural attitudes toward technology. Moreover, while ethical concerns about AI use in education are widely discussed, there is limited research on how these concerns manifest in developing countries like the Philippines, where resource constraints and cultural norms may amplify or mitigate these issues.

This study addresses these gaps by employing a narrative inquiry approach to explore the lived experiences of students and faculty in Philippine HEIs, providing insights into how ChatGPT can be integrated in a culturally sensitive and equitable way. Focusing on the Philippine context, this research contributes to the broader discourse on AI in education by highlighting the importance of context-specific strategies for addressing technological, ethical, and infrastructural challenges. While global studies highlight ChatGPT’s potential, this study examines how Philippine HEIs navigate adoption amid infrastructural limitations and cultural resistance to tech-driven pedagogy, offering a model for other developing economies.

Collectively, the literature reveals ChatGPT’s potential to transform education but underscores the absence of culturally grounded frameworks for equitable adoption in the Philippines. While global studies highlight ChatGPT’s efficiency gains (Al-Shuaili 2025; Annamalai et al. 2025), few examine how infrastructural limitations and cultural resistance shape its integration in developing economies. This study addresses these gaps by centering stakeholder narratives to answer three key questions: (1) how students perceive ChatGPT’s impact on learning (RQ1), (2) how faculty navigate its pedagogical integration (RQ2), and (3) what systemic barriers perpetuate inequities in adoption (RQ3). By applying Clandinin and Connelly’s (2004) framework, this research exposes how temporality, sociality, and place mediate AI’s role in Philippine HEIs, a lens absent in prior works.

3. Methodology

Building on the research gaps identified in the literature review, this study employs narrative inquiry to explore the integration of ChatGPT in Philippine higher education. The choice of this methodological framework is informed by the need to address the complex interplay of cultural, institutional, and ethical factors that influence ChatGPT adoption, as highlighted in the literature.

3.1. Research Objectives and Questions

The study aims to achieve the following objectives:

• Investigate common experiences teachers and students have had when integrating ChatGPT into academic environments.
• Examine how ChatGPT is being adopted in education, with special attention to maintaining academic honesty, improving teaching outcomes, and how institutions implement these tools.
• Provide research-backed suggestions to education leaders and teachers for integrating ChatGPT effectively in various educational contexts while respecting cultural differences.

To achieve these objectives, the study addresses the following research questions (RQs), which explore the perspectives of students and faculty on ChatGPT integration, focusing on its impact on learning, teaching practices, and ethical considerations:

• RQ1: In what ways do students in the Philippines believe ChatGPT is affecting their learning experiences?
• RQ2: How do teachers view and respond to integrating ChatGPT as a tool within their instructional practices?
• RQ3: What ethical and practical challenges do students and faculty face in using ChatGPT, and how can these challenges inform strategies for its equitable and culturally sensitive integration in Philippine HEIs?

Integrating AI tools like ChatGPT in higher education impacts teaching, learning, and students’ future employability. In a rapidly evolving job market, where digital literacy and AI proficiency are increasingly valued, unequal access to these tools may exacerbate existing social inequalities, particularly for students from rural or underserved communities. This study explores how the urban–rural divide in ChatGPT adoption influences students’ academic experiences and, by extension, their preparedness for the labor market.

3.2. Methodological Design

Guided by the objectives and research questions outlined here, this study employs narrative inquiry as the research design because it allows for an in-depth exploration of the lived experiences of students and faculty, aligning with the study’s aim to understand how cultural, institutional, and ethical factors shape ChatGPT integration in Philippine HEIs. This approach is particularly well suited for capturing the complexity of participants’ experiences, as it emphasizes the interconnectedness of personal stories with broader social, cultural, and institutional contexts. This study applies narrative inquiry not just to document experiences but to expose how ChatGPT’s integration is mediated by structural inequities—a lens critical to social stratification research.

The study applied Clandinin and Connelly’s (2004) three-dimensional narrative inquiry framework, which examines narratives through the lenses of temporality, sociality, and place.

• Temporality: The temporal dimension focuses on how participants’ experiences with ChatGPT unfold over time. This temporal perspective allowed the study to capture the dynamic nature of ChatGPT adoption, highlighting how participants’ attitudes and practices shifted over time.
• Sociality: The social dimension explores the interpersonal and institutional relationships that shape participants’ experiences.
• Place: The place dimension examines how the physical and cultural context influences participants’ experiences. In the Philippine setting, the urban–rural divide emerged as a critical factor shaping ChatGPT adoption.

As a qualitative approach, narrative inquiry provides contextual depth and is well suited for capturing participants’ lived experiences through in-depth interviews. This qualitative approach allows participants to share their experiences, challenges, and ethical concerns related to ChatGPT integration, offering rich insights from their lived experiences.

3.3. Instruments and Data Collection

This study employed semi-structured narrative interview guides as the primary research instrument to explore participants’ lived experiences with ChatGPT in academic settings. The pre-narrative interviews gathered initial insights into usage patterns, cultural and institutional factors affecting adoption, and concerns about the urban–rural divide. These were followed by in-depth post-narrative interviews, conducted virtually via Zoom from August to September 2023, which delved deeper into personal experiences, challenges, and strategies for integrating ChatGPT into teaching and learning practices.

Interviews began with broad questions about participants’ general understanding of ChatGPT. They progressed to specific inquiries about its role in their academic workflows, ethical dilemmas encountered, and perceived impacts on their educational trajectories. Each interview lasted 45–60 min, was audio-recorded with consent, and transcribed verbatim for analysis. Before the sessions, participants received preliminary questions to help them reflect on their experiences, ensuring rich, contextual narratives. The resulting dataset comprised 18 validated transcripts, offering detailed accounts of ChatGPT adoption across diverse Philippine higher education contexts.

3.4. Data Analysis

The qualitative interviews were recorded, transcribed, and analyzed using thematic analysis (Halcomb and Davidson 2006). This process began with a thorough review of interview transcripts, going back and forth between them to identify how participants’ interwoven stories created a comprehensive picture of ChatGPT integration in academic settings.

The responses were analyzed multiple times, with particular attention given to participants’ experiences with ChatGPT. Following the steps of thematic analysis “designed to search for common or shared meaning”, as discussed by Kiger and Varpio (2020, p. 82), and adopted from Braun and Clarke (2006), the study searched for, reviewed, defined, and named the themes generated from the “patterned response or meaning” (p. 82) derived from the interview data that informed the research questions. These themes clarified participants’ experiences with ChatGPT and provided a rich context for understanding their adoption patterns and challenges.

To develop trustworthiness, credibility, and validity, narrative interpretations were shared with the participants to ensure their narrated stories matched my interpretation (Tobin and Begley 2004). This member checking (Lincoln and Guba 1985) generated new insights, with participants feeling empowered and involved in safeguarding the validity of the findings, making them active participants in the study. The audit trail for this narrative inquiry included audio–video recordings, interview transcripts, interview guides, a list of interviewees, and my notes.

The analysis focused on understanding participants’ accounts of ChatGPT integration in their academic practices. These narratives offered rich examples of how the technology was used in Philippine HEIs while maintaining participant confidentiality through coding systems (Saldana 2021). Demographic information was included to provide context for the narratives. This analytical approach enabled a detailed and layered understanding of participants’ perspectives on ChatGPT use while maintaining rigorous methodological standards.

3.5. Sampling and Final Sample Characteristics

The study included 18 participants (10 students, 8 faculty) from Philippine higher education institutions (HEIs), selected through stratified sampling to ensure diversity in gender, institution type, geographic location, and ChatGPT experience.

Students represented all undergraduate levels (20% freshmen, 40% sophomores, 30% juniors, 10% seniors), with a near-even gender split (60% female, 40% male) and ages 18–30. Faculty participants spanned early-career to senior educators (50% aged 31–40, 25% aged 41–55, 25% over 55), with teaching experience varying from ≤5 years to >15 years (13% each for ≤5 and 6–10 years; 25% for 11–15 years; 50% for >15 years).

Institutional representation balanced public (40% students, 38% faculty) and private (60% students, 62% faculty) HEIs, with urban (70% students, 50% faculty) and rural (30% students, 50% faculty) contexts. ChatGPT usage levels varied: students were predominantly adopters (50% used it for 4–7 months), while faculty included adopters (50%) and experts (25%), with minimal skeptics (10–13%). This distribution captured key demographic and experiential factors shaping ChatGPT integration in Philippine HEIs.

3.6. Researcher Positionality

As the sole investigator, I bring four decades of tertiary education experience in the Philippines to this inquiry into ChatGPT’s integration within higher education institutions. My sustained engagement with this topic, reflected in this being my third paper examining ChatGPT in educational contexts, emerged from witnessing firsthand the complex dynamics surrounding AI adoption in Philippine universities.

My position as an educator at a well-resourced urban institution in Manila has afforded me particular insights into the transformative potential and systemic barriers facing AI integration. This vantage point has illuminated how infrastructural disparities and cultural resistance shape institutional responses to emerging technologies, while simultaneously revealing the stark inequalities that risk being amplified by uneven AI adoption across the archipelago’s diverse educational landscape.

However, I acknowledge that my institutional context, characterized by financially capable students and robust technological infrastructure, represents only one facet of Philippine higher education. Most HEIs operate under significantly different conditions, serving populations with limited technological access and facing resource constraints that fundamentally alter the AI integration equation. This recognition has driven my commitment to centering participant voices from varied institutional contexts, ensuring that findings reflect the full spectrum of Philippine higher education experiences rather than merely echoing my privileged position.

My dual identity as researcher and ChatGPT user introduces additional complexity to this inquiry. While this insider knowledge provides a nuanced understanding of AI tool functionality and user experience, it also carries the risk of assumption and confirmation bias. To address this tension, I have employed systematic reflexivity throughout the research process, consistently interrogating my interpretations against participant narratives and seeking disconfirming evidence that challenges my preconceptions.

The ultimate aim of this work extends beyond academic contribution to practical impact: fostering equitable, culturally responsive AI adoption that strengthens rather than stratifies Philippine higher education. This aspiration demands acknowledging what my position enables me to see and what it might obscure—a recognition that has shaped every aspect of this investigation’s design and execution.

4. Results

This section presents our findings organized by research questions, drawing on Clandinin and Connelly’s (2004) narrative inquiry framework across dimensions of temporality (evolution of use), sociality (institutional dynamics), and place (urban–rural disparities). For each research question, key themes that emerged from participant narratives were identified, supported by representative quotations that ensure fidelity to their experiences.

4.1. RQ1: Student Experiences with ChatGPT

This investigation into student experiences revealed three predominant themes: enhanced efficiency and productivity, learning augmentation, and ethical navigation.

4.1.1. Enhanced Efficiency and Productivity

Students consistently highlighted ChatGPT’s ability to streamline academic tasks, particularly valuing its time-saving capabilities. “As a student with a 12-hour daily class schedule, ChatGPT gave me more time to rest and be productive with my tasks”, explained one participant (S4). Many described how this efficiency transformed their routines—what used to take hours could now be accomplished in minutes.

The accessibility and user-friendly interface further enhanced this efficiency. One student noted how it fit seamlessly into their workflow: “ChatGPT can answer all your questions by just searching on their website or app, just like Google” (S10). Others found it boosted their output in unexpected ways. “It makes me productive because it gives me more ideas and broadens my knowledge whenever I am using ChatGPT”, shared another (S2), describing how the tool helped overcome creative blocks.

The temporality dimension reveals evolving usage patterns. As students gained experience, their learning experiences matured. “Initially, I only relied on the copy-paste technique”, confessed one learner (S1), “but now I evaluate it carefully”. This progression from uncritical use to more measured engagement emerged as a typical trajectory among participants.

4.1.2. Learning Augmentation

Students predominantly viewed ChatGPT as a supplemental learning tool that broadened their knowledge horizons. One student explained, “It benefits me by giving me other ideas I need if I am trying to study something” (S8), emphasizing how the AI served as an intellectual tool that “opens up different perspectives I would not have considered on my own”. Another participant shared how the tool helped overcome academic obstacles, noting that “It helps me in situations like if I am stuck on a particular problem or have a question” (S1), and elaborated that this support was particularly valuable “when traditional resources like textbooks or lectures leave gaps in my understanding”.

Through the lens of sociality, we observed that students developed varied relationships with the technology, some viewing it as a collaborative partner in learning, others as merely a utility. The urban participants from well-resourced institutions (S6, S7) often described more collaborative approaches: “I think of it almost like having a study buddy who is always available” (S6). In contrast, time-pressed commuter students (S4, S9) typically adopted utilitarian views: “I use it like I would use a calculator—just for getting quick answers” (S9). This relationship dynamic shaped engagement depth, with collaborative users like S6 noting they “question and build upon what it gives me”, whereas S9 admitted to often accepting outputs without scrutiny.

4.1.3. Ethical Navigation and Dependency Concerns

Students showed clear awareness of ethical issues around ChatGPT use, though many struggled to implement their principles. One student explained her approach: “I use it to generate ideas, but I do not copy-paste it because I try to understand it in my own way. I want to make sure the learning is still happening” (S9). However, good intentions often clashed with reality. The same student who spoke about ethical use later admitted: “I sometimes find it difficult to start assignments without consulting ChatGPT first, and that worries me because I used to be able to brainstorm on my own” (S8).

This gap between what students wanted to do and what they actually did revealed a troubling pattern. Several worried they were becoming too dependent on the tool. One student put it bluntly: “It makes me think less because ChatGPT provides all of the information immediately. I catch myself not pushing through that initial confusion that used to lead to my best insights” (S2). These honest admissions show students grappling with questions that go beyond simple plagiarism. They wonder whether using ChatGPT might change their thinking, not necessarily for the better.

While students expressed concerns about dependency (S2, S8), many also developed reflective practices to mitigate overreliance (S9, S10), suggesting ethical engagement is possible with guided support.

4.2. RQ2: Faculty Integration of ChatGPT

Faculty experiences coalesced around pedagogical innovation, maintaining academic integrity, and concerns about student skill development.

4.2.1. Pedagogical Innovation

Faculty members took thoughtful approaches to ChatGPT, carefully balancing the tool’s potential with their teaching goals. Several instructors discovered it could transform how they explained difficult material. “Using ChatGPT helps me explain complex concepts to students by providing alternative words and phrases”, noted one educator (T3) who began weaving AI-generated examples into lectures when students looked confused. “I can instantly get three different ways to explain photosynthesis or supply and demand—it is like having a teaching assistant who never runs out of analogies”.

Others drew firm lines to protect what they saw as essential learning processes. A writing instructor described a careful balance: “I require complete handwritten drafts before students may use ChatGPT for refinement. The thinking must originate with them; AI only helps polish what is already there” (T5). This was not just about preventing cheating; she worried that “students might skip the messy, uncomfortable part of figuring out what they want to say, and that is where the real learning happens”.

Beyond classroom instruction, professors quietly adopted ChatGPT for their own work. Many found it cut preparation time significantly. “I find ChatGPT helpful for quickly accessing concepts and definitions when developing teaching materials”, explained one instructor (T1), who used it to “double-check my explanations and catch things I might have oversimplified”. Another reported: “ChatGPT has been instrumental in aiding the development of my syllabus, providing structure and content ideas, especially for courses I am teaching for the first time” (T5).

The most significant factor in whether faculty embraced or avoided ChatGPT was often their department’s culture. Some academic units actively pushed experimentation, hosting workshops and sharing success stories. Others remained skeptical, with department heads expressing concerns about academic integrity and lowered standards. This created a patchwork of adoption across campuses, with some departments embracing the technology while others remained hesitant.

4.2.2. Maintaining Academic Integrity

Faculty struggled with preserving academic honesty while acknowledging that ChatGPT was not going away. Rather than simply banning the tool, many tried to teach students how to use it ethically. “We must encourage learners to use ChatGPT responsibly and view it as an opportunity to instill good values like humility and honesty”, explained one educator (T6), who saw this as a chance to have deeper conversations about what constitutes original work. However, the challenge remained real: “We must regulate the use of ChatGPT to maintain academic integrity; we cannot just hope students will figure it out on their own” (T6).

Practical strategies emerged from trial and error. Some instructors redesigned their assignments entirely. “To ensure students are learning effectively, I ask them to submit their writing tasks in parts for closer examination”, noted one teacher (T1), who found that “when students have to show their rough drafts and outline their thinking process, it becomes much harder to just paste in AI-generated content”. Faculty’s ad hoc adaptations (e.g., requiring handwritten drafts) reveal latent capacity for policy innovation, underscoring the need to formalize bottom-up strategies. Others made expectations explicit from day one: “I make it a point to include specific guidelines on using ChatGPT during my class orientations; I tell them exactly what is allowed and what crosses the line” (T8). She added, “I would rather spend time upfront being clear than deal with awkward conversations about cheating later”.

The temporal dimension proved crucial in understanding how faculty approaches evolved. What surprised many educators was how rapidly their attitudes shifted within months of ChatGPT’s emergence. Early adopters admitted they started with blanket bans—no AI tools allowed—but found these policies impossible to enforce and increasingly irrelevant as the technology became ubiquitous. “By mid-semester, I realized I was fighting a losing battle”, one instructor reflected (T2). “Students were using it anyway, so I had to decide whether to keep playing detective or start teaching them to use it properly”.

Within a single semester, many moved toward what one professor called “controlled integration” (T7), where students could use ChatGPT for specific tasks but had to document their process. This temporal shift was not just about policy adjustment but a fundamental reconceptualization of academic integrity. Faculty who began the academic year focused on detection and prohibition ended it by developing frameworks for transparent, pedagogically sound AI integration. Another educator observed, “We realized that academic integrity in the age of AI required new definitions and collaborative approaches, not just stricter enforcement of old rules designed for a pre-AI world” (T4).

4.2.3. Concerns About Student Development

Faculty worries ran deeper than simple cheating concerns; many feared they were witnessing fundamental changes in how students think and learn. “While ChatGPT makes learning easier, I’ve noticed a decline in students’ ability to develop critical thinking skills independently”, observed one teacher (T5), who described watching students “reach for the AI the moment they encounter any confusion, instead of sitting with the discomfort and working through problems themselves”. The concern was not just about academic shortcuts but about cognitive development. Another educator put it, “While ChatGPT is useful, it cannot replicate the nuanced understanding of existential feelings and specific emotions necessary in learning; there is something about struggling with ideas that builds intellectual muscle, and I am not sure we are giving students enough of that struggle anymore” (T5).

The practical challenges of assessment created daily frustrations. “Determining whether student submissions are original or AI-generated has become increasingly challenging, admitted one instructor (T8), who found herself “spending more time trying to detect AI use than actually providing feedback on student work”. The detective work was exhausting and often inconclusive. “I can suspect a paper was AI-generated, but proving it is nearly impossible, especially when students get smarter about editing the output”, she explained.

This uncertainty left many faculty members feeling caught between competing priorities. “I need to balance the technological benefits of AI tools with the need to uphold educational integrity”, reflected one teacher (T2), who captured the broader dilemma facing educators. “On one hand, I want my students to be prepared for a world where AI is everywhere. On the other hand, I worry that if they never learn to think without it, what happens when they need to solve problems the AI cannot handle?” This tension between embracing useful technology and preserving essential learning processes became a defining challenge for educators in the ChatGPT era.

4.3. RQ3: Challenges and Barriers to ChatGPT Integration

Our analysis identified three interconnected challenges: the urban–rural digital divide, detection and policy enforcement difficulties, and equity concerns.

4.3.1. Urban–Rural Digital Divide

The place dimension created a new form of educational inequality, with geographic location determining not just access to ChatGPT but the quality of that access. Rural students faced infrastructure barriers that turned a potentially transformative tool into a source of frustration. “Without reliable internet, ChatGPT is more of a frustration than a tool for learning”, explained one rural student (S3), who described waiting several minutes for responses that urban peers received instantly. “Sometimes I will ask it a question for homework, go make dinner, and come back to find it still loading”. Another rural student captured the broader equity concern: “In rural areas, we don’t have access to the same tools as urban students, and now that includes AI that could help level the playing field, if only we could use it properly” (S9).

The contrast with urban experiences was striking. Urban students integrated ChatGPT seamlessly into their daily routines. “I use ChatGPT every day because I have fast internet at home”, noted one city student (S6), who described rapid-fire conversations with the AI while working on assignments. The efficiency gains were substantial: “ChatGPT helps me save so much time on research and drafting. I can explore five different approaches to an essay in the time it used to take me to outline one” (S7). Meanwhile, rural students expressed frustration with their spotty connections: “It’s hard to rely on ChatGPT when the internet keeps disconnecting right when you need an answer for your homework due tomorrow” (S9).

Educators experienced parallel divides. Rural teachers watched colleagues in urban districts embrace AI integration while they struggled with basic connectivity. “In rural schools, poor internet makes it hard to integrate ChatGPT into teaching. I cannot plan lessons around a tool that might not work when I need it”, explained one rural educator (T5, rural), who described the disappointment of preparing AI-enhanced activities only to face frozen screens in class. Urban teachers, by contrast, discovered new pedagogical possibilities. “I use ChatGPT regularly for lesson planning because I have reliable internet”, noted one city educator (T3, urban), while another urban teacher celebrated the tool’s impact: “ChatGPT is a game-changer for teaching complex concepts. I can generate multiple explanations and examples on the spot” (T4, urban).

This geographic dimension created more than inconvenience; it threatened to widen existing educational gaps. Rural educators recognized the irony: “It’s frustrating to see the potential of ChatGPT but not be able to use it due to poor infrastructure. We are watching a tool that could help our students compete with urban schools, but the connectivity issues that already disadvantage us are keeping us from accessing it” (T5). As AI becomes integral to education, these place-based disparities risk creating two tiers of learning: connected classrooms where AI amplifies educational opportunities and disconnected ones where students fall further behind.

4.3.2. Detection and Policy Enforcement

Both students and faculty acknowledged challenges in detection and policy enforcement. One student observed, “Despite policies against AI use, there is widespread usage on campus, suggesting a gap between policy and practice” (S1). Another noted detection limitations: “My professor does not know how to detect AI-generated content, allowing for my undetected use” (S3).

Faculty expressed similar concerns: “The tools we currently have for detecting AI-generated content are not effective enough, which necessitates the development of better technologies” (T7). Another educator mentioned hesitancy in addressing suspected AI use: “I am hesitant to accuse students of using AI-generated content without conclusive proof, which highlights the need for clearer guidelines” (T1).

This led to what participants termed “silent acceptance”—a tacit tolerance of undisclosed AI use due to unclear policies or detection limitations. One student noted, “There is a silent acceptance of AI tool usage among students and teachers, suggesting a need for open discussions on AI ethics” (S10). A teacher confirmed this behavior: “Even though I detect the use of AI tools, the lack of concrete evidence makes it difficult to address this issue openly” (T1).

4.3.3. Equity and Future Implications

Our findings highlight how unequal ChatGPT integration may exacerbate social inequalities in graduate employment outcomes. With better access to AI tools, urban students develop advanced digital literacy and critical thinking skills, making them more competitive in the job market. In contrast, rural students who face significant barriers to accessing ChatGPT may struggle to acquire these skills, further marginalizing them in the labor market.

To address this, HEIs must prioritize bridging the digital divide by investing in infrastructure and providing equitable access to AI tools. Additionally, institutions should integrate AI literacy and digital skills training into the curriculum to ensure that all students, regardless of their geographic location, are prepared for the demands of the modern workforce.

4.4. Summary of Key Findings

Through the lenses of temporality, sociality, and place, our results reveal ChatGPT integration in Philippine HEIs as a complex phenomenon with significant implications for educational equity. The technology offers substantial benefits for productivity, learning, and teaching practices, but introduces challenges related to academic integrity, critical thinking development, and digital divide concerns.

Most critically, the narratives reveal how ChatGPT adoption is not merely a pedagogical shift but potentially a stratification mechanism that may perpetuate existing inequalities if not addressed through thoughtful policy development and infrastructure investment. These findings provide direct responses to our research questions while highlighting the interconnected nature of student experiences (RQ1), faculty integration strategies (RQ2), and implementation challenges (RQ3).

Findings reveal that ChatGPT is viewed as a valuable tool for enhancing productivity, learning, and teaching practices. However, its integration is accompanied by significant challenges, including ethical concerns, dependency issues, and the urban–rural divide. Students and educators emphasized the need for clear guidelines, equitable access, and strategies to balance technological innovation with academic integrity.

5. Discussion

Three critical findings dominate participants’ narratives about ChatGPT integration in Philippine HEIs: (1) urban–rural divides in access mirror broader Philippine educational inequities; (2) “silent acceptance” of AI use reflects institutional policy gaps between official prohibitions and classroom realities; and (3) ethical tensions emerge as stakeholders balance technological innovation with traditional academic values. These findings reveal how ChatGPT adoption in Philippine HEIs is mediated by infrastructure gaps (place), policy ambiguities (sociality), and evolving stakeholder attitudes (temporality), urging context-sensitive integration frameworks.

5.1. Theoretical Contributions: How Framework Dimensions Clarify Key Patterns

Clandinin and Connelly’s (2004) framework revealed insights beyond those typically captured in technology adoption studies. The temporality dimension uncovered that ethical reasoning evolved differently in urban versus rural settings—a notable extension of the original model. Urban students progressed from initial skepticism through experimental use to strategic integration, as evidenced in Section 4.1.1, where one student reflected, “Initially, I only relied on the copy-paste technique, but now I evaluate it carefully” (S1). In contrast, rural peers experienced stagnation due to persistent infrastructural barriers, as documented in Section 4.3.1.

The sociality dimension exposed how institutional policy ambiguities created a paradoxical “silent acceptance” culture where ChatGPT use was tacitly permitted despite formal prohibitions. This was clearly illustrated in Section 4.3.2, where one student observed, “Despite policies against AI use, there is widespread usage on campus, suggesting a gap between policy and practice” (S1). This manifested differently across contexts: in well-resourced institutions, faculty developed informal detection strategies, while in resource-constrained settings, the ambiguity reinforced existing power imbalances. These dynamics operate through “ethical displacement”, shifting moral responsibility from institutions to individual actors lacking clear guidance.

The place dimension revealed that geographic location functioned as a physical constraint and a determinant of ethical agency—the ability to make meaningful technological choices. This is evident throughout Section 4.3.1, which details the stark disparities between urban and rural experiences. This represents a theoretical advancement in understanding how digital divides operate in developing contexts, extending beyond binary access questions to encompass qualitative differences in how technologies are encountered, evaluated, and incorporated into educational practice.

These dimensions create ethical ecosystems, contextually specific configurations of temporal adaptation, social norms, and place-based constraints that collectively shape AI integration. For example, dependency and reliance behavior (Section 4.1.3) emerged from the interaction of temporal shifts in student attitudes with place-based access limitations. In contrast, “silent acceptance” (Section 4.3.2) resulted from the collision between rapidly evolving technology (temporality) and institutional policy gaps (sociality).

It is also worth noting that participant narratives revealed tensions not fully captured by the three-dimensional framework. For instance, urban students’ strategic use (S6) contrasted with rural peers’ infrastructural barriers (S3), yet both groups expressed ethical agency—a nuance requiring further study.

5.2. Research Question Analysis: From Theoretical Insights to Practical Understanding

Having examined how temporality, sociality, and place shape ChatGPT integration broadly, we now address our specific research questions to translate these conceptual insights into a practical understanding of stakeholder experiences and institutional implications.

5.2.1. Student Perceptions of ChatGPT’s Impact on Learning (RQ1)

Students demonstrated a nuanced understanding of ChatGPT’s role in their academic lives, recognizing its transformative potential and inherent risks. As detailed in Section 4.1.1, the tool was widely valued for enhancing productivity and time management, particularly among students with heavy workloads who reported significant efficiency gains in completing assignments: “As a student with a 12-hour daily class schedule, ChatGPT gave me more time to rest and be productive with my tasks” (S4). However, this appreciation was counterbalanced by growing concerns about cognitive dependency, as many admitted struggling to initiate or complete tasks without AI assistance, a pattern documented in Section 4.1.3 where one student acknowledged: “I sometimes find it difficult to start assignments without consulting ChatGPT first” (S8). This suggests potential erosion of independent problem-solving skills.

Geographic disparities profoundly shaped these experiences, as evident in Section 4.3.1. Urban students, benefiting from reliable internet and modern devices, integrated ChatGPT strategically into their learning workflows, using it for brainstorming, drafting, and supplemental research. One urban student noted: “I use ChatGPT every day because I have fast internet at home” (S6). In contrast, rural students faced compounded challenges: intermittent connectivity, inadequate hardware, and limited institutional support rendered the tool more frustrating than helpful, with one rural student lamenting: “Without reliable internet, ChatGPT is more of a frustration than a tool for learning” (S3). These disparities exacerbate existing educational inequalities.

Three distinct adoption patterns emerged across these contexts. First, strategic integrators treated ChatGPT as a selective aid for specific tasks while maintaining active engagement with learning materials. Second, ethically conscious users self-regulated their AI interactions by developing personal guidelines to avoid plagiarism and ensure content comprehension, as illustrated in Section 4.1.3: “I use it to generate ideas, but I do not copy-paste it because I try to understand it in my own way” (S9). Third, adaptive learners progressed from simplistic copy-pasting to more sophisticated interactions involving critical output evaluation and iterative prompting, reflecting increasing AI literacy over time.

These findings highlight an urgent tension between technological efficiency and pedagogical integrity. While ChatGPT undeniably streamlines academic workflows, its unguided use risks creating a generation of students who prioritize speed over depth, as suggested by the student concern in Section 4.1.3: “It makes me think less because ChatGPT provides all of the information immediately” (S2). The Philippine context amplifies these concerns, where infrastructural gaps turn AI adoption into another educational stratification axis.

5.2.2. Teacher Attitudes Toward ChatGPT Integration (RQ2)

Faculty perspectives on ChatGPT revealed complex professional and pedagogical considerations. As noted in Section 4.2.3, several teachers expressed concerns about ChatGPT’s impact on students’ critical thinking skills, with one educator observing: “While ChatGPT makes learning easier, I’ve noticed a decline in students’ ability to develop critical thinking skills independently” (T5). This concern directly relates to the temporal dimension’s observation of increasing student dependency over time.

The place dimension manifested strongly in faculty experiences, with the urban–rural divide significantly influencing attitudes and implementation capabilities, as documented in Section 4.3.1. Urban educators, with access to robust technological infrastructure, reported regular use of ChatGPT: “I use ChatGPT regularly for lesson planning because I have reliable internet” (T3, urban). In contrast, rural teachers faced substantial challenges: “In rural schools, poor internet makes it hard to integrate ChatGPT into teaching” (T5, rural). These disparities align with the “infrastructure–institutional double bind” identified in our place analysis (Section 5.1), highlighting systemic barriers to equitable AI integration.

The sociality dimension was evident in teachers’ responses to the ethical dilemmas posed by ChatGPT. Many expressed hesitancies in addressing suspected AI use without concrete evidence, as captured in Section 4.3.2: “I am hesitant to accuse students of using AI-generated content without conclusive proof, which highlights the need for clearer guidelines” (T1). This hesitancy contributes to the “silent acceptance” pattern noted in our sociality analysis. This ethical tension is further complicated by detection challenges, with one teacher noting: “The tools we currently have for detecting AI-generated content are not effective enough, which necessitates the development of better technologies” (T7).

Faculty attitudes toward ChatGPT reflect a complex interplay of professional values, practical constraints, and contextual factors. This underscores that successful integration requires addressing infrastructure inequities, providing targeted professional development, and fostering institutional cultures of responsible innovation.

5.2.3. Ethical Concerns, Practical Challenges, and Pathways to Equitable Integration (RQ3)

The integration of ChatGPT in Philippine HEIs revealed a tension between technological innovation and ethical accountability, shaped by three interrelated factors that span our theoretical dimensions: evolving stakeholder attitudes (temporality), systemic inequities (place), and institutional policy gaps (sociality).

Students demonstrated a clear temporal trajectory in ethical reasoning—from initial skepticism to cautious acceptance—as they developed personal guidelines to navigate ChatGPT’s use without compromising academic integrity. This evolution is evident in Section 4.1.3, where students reflect on their developing approaches to ethical use. Faculty, meanwhile, struggled to balance the tool’s pedagogical benefits with concerns about critical thinking erosion and academic honesty, often adapting assessments (e.g., staged submissions, oral defenses) to mitigate risks, as illustrated in Section 4.2.2: “To ensure students are learning effectively, I ask them to submit their writing tasks in parts for closer examination” (T1).

Geographic disparities (place dimension) profoundly influenced these dynamics, as comprehensively documented in Section 4.3.1. Urban participants, while more likely to embrace ChatGPT’s efficiency, acknowledged its uneven accessibility. In contrast, rural stakeholders faced compounded barriers: limited internet connectivity, inadequate devices, and fewer institutional supports, which rendered AI tools more aspirational than practical. This infrastructure–institutional double bind exacerbated existing inequities, with rural students and faculty reporting frustration over exclusion from AI-enhanced learning opportunities available to urban peers, as one rural student noted: “In rural areas, we don’t have access to the same tools as urban students” (S9).

Equity-focused solutions must address the “infrastructure–institutional double bind” (Sharma et al. 2024) by pairing connectivity investments with pedagogical support. Thailand’s centralized “Smart Campus” initiative (Achruh et al. 2024) offers a model for harmonizing policy and place-based needs.

The sociality dimension manifested in the “silent acceptance” of ChatGPT use that permeated both groups, reflecting disconnection between formal prohibitions and classroom realities, as detailed in Section 4.3.2. Faculty often lacked reliable detection methods, while students exploited this ambiguity, resulting in unspoken tolerance of AI assistance. This gap underscores the need for policies that reconcile ethical ideals with on-the-ground constraints, such as tiered usage guidelines (e.g., permitting ChatGPT for brainstorming but not drafting) or transparency mandates (e.g., requiring AI-use declarations).

To achieve equitable integration, Philippine HEIs must adopt context-sensitive frameworks that address challenges across all three dimensions:

• Temporal challenges: Develop adaptive policies that evolve alongside stakeholder literacy and AI capabilities;
• Social Challenges: Create a transparent dialogue and collaborative guideline development;
• Place-Based Challenges: Implement infrastructure solutions for rural connectivity and develop offline alternatives.

These solutions must be implemented systemically through infrastructure investment, policy development, and stakeholder engagement to ensure that ChatGPT enhances rather than diminishes educational equity.

5.3. Theoretical Implications

The findings from this study have significant implications for the theoretical understanding of AI integration in educational contexts. This research demonstrates the value of Clandinin and Connelly’s (2004) three-dimensional framework for understanding technology integration in education. This approach reveals the following theoretical contributions:

• The temporality dimension captures the evolutionary nature of AI adoption, showing how initial skepticism can transform into either strategic integration or problematic dependency—insights that contribute to technological adoption theories and are evident in student narratives throughout Section 4.1.
• The sociality dimension clarifies how institutional cultures and interpersonal dynamics shape AI use patterns, contributing to educational policy theories by highlighting the gap between formal regulations and lived practices, as demonstrated in Section 4.2.2 and Section 4.3.2.
• The place dimension underscores how geographic and institutional contexts mediate technology access, reinforcing theoretical perspectives on digital divides while providing specific insights into Philippine higher education contexts, as thoroughly documented in Section 4.3.1.

These contributions enhance the literature on educational technology by emphasizing context-sensitive approaches that account for multiple intersecting dimensions. The study’s findings on the “silent acceptance” phenomenon and the urban–rural digital divide extend existing theoretical frameworks by highlighting how socio-spatial factors influence technological adoption in ways not fully captured by traditional diffusion models.

5.3.1. Literature Synthesis: Philippine Patterns in Global Context

These Philippine-specific patterns both confirm and challenge emerging global trends in AI integration. The “silent acceptance” phenomenon documented in Section 4.3.2 aligns with Rudolph et al.’s (2023) observations in U.S. higher education, suggesting a cross-cultural pattern of institutional hesitancy to develop proactive policies. However, the intensity of the urban–rural divide in the Philippines, as detailed in Section 4.3.1, exceeds disparities reported in middle-income peers like Thailand (Achruh et al. 2024) and Malaysia (Sinnappan et al. 2023), underscoring the need for localized solutions rather than imported policy frameworks.

Our findings on student dependency trajectories in Section 4.1.3 complement but also complicate earlier work by Espartinez (2024), whose Q-methodology study identified similar attitudinal clusters but missed the temporal dimension of how these attitudes evolve. Similarly, while our documentation of faculty ethical concerns in Section 4.2.3 echoes global patterns (Verano-Tacoronte et al. 2025), the Philippine context adds distinctive cultural dimensions, particularly around collective learning values that sometimes conflict with Western individualistic assessment frameworks underlying many AI detection tools.

5.3.2. Implications for Higher Education

Integrating AI tools like ChatGPT in higher education has significant implications across various domains, all of which connect to our core findings:

• Pedagogical Implications: As demonstrated in our analysis of student perceptions (Section 4.1), ChatGPT can enhance teaching and learning when strategically integrated, but requires intentional approaches that mitigate dependency risks identified in Section 4.1.3.
• Ethical Implications: Our findings on “silent acceptance” (Section 4.3.2) underscore the need for transparent policies that address academic integrity concerns while acknowledging practical realities.
• Infrastructure Implications: The urban–rural divide documented in Section 4.3.1 necessitates targeted investment to ensure technology access does not become another vector of educational inequality.
• Policy Implications: Our analysis of institutional dynamics in Section 4.2.2 and Section 4.3.2 highlights the need for collaborative policy development that includes diverse stakeholder perspectives.
• Cultural Implications: The resistance and adaptation patterns observed in student and faculty experiences suggest the need for cultural shifts that embrace responsible innovation.

These implications directly from the research findings provide a roadmap for Philippine HEIs seeking to harness ChatGPT’s potential while minimizing risks.

5.3.3. Reimagining Education in the AI Era: Futurities for the Global South

The introduction of ChatGPT in Philippine universities has sparked fundamental questions about what education should accomplish in developing nations. While wealthy countries often discuss AI to make learning more efficient or personalized (Zawacki-Richter et al. 2019), this research reveals that countries like the Philippines need something different—an approach to education with AI that puts local needs, fairness, and cultural wisdom at the center (Spero 2024).

Consider how participants quietly accepted ChatGPT without much discussion or debate. This silence tells a deeper story about the clash between promises of technological transformation and the day-to-day struggles of Philippine education—overcrowded classrooms, limited resources, and students juggling multiple jobs to afford their studies (Talidong and Toquero 2020).

Rather than viewing AI as a force that will inevitably reshape education, we might instead see it as a conversation partner in creating the kind of learning experiences our students need. Paulo Freire’s (1968) vision of education as dialogue, where teachers and students learn together, offers a powerful alternative to treating AI as another way to deliver information. When ChatGPT becomes part of genuine conversations about learning, rather than replacing human connection, it can support the kind of critical thinking that helps students navigate their complex realities.

These insights point toward educational approaches that weave AI capabilities with local ways of knowing, creating something uniquely suited to the Global South context—neither rejecting technology nor surrendering to it, but thoughtfully integrating it into education that serves communities and upholds human dignity.

5.4. Limitations

This study of ChatGPT integration in Philippine HEIs presents several limitations that warrant acknowledgment:

First, while narrative inquiry effectively captured rich stakeholder experiences, our sample size (16 students, 12 faculty) and specific Philippine focus limit generalizability to other educational contexts. The findings are context-specific to the Philippine educational landscape. However, many challenges, such as the urban–rural divide, ethical concerns, and balancing innovation with tradition, likely resonate across developing nations in Southeast Asia (Zhao 2024) and Latin America (de la Torre and Baldeon-Calisto 2024).

Second, the rapid evolution of AI technologies means some findings may become less relevant as these tools advance. Particularly, the urban–rural adoption disparities identified in Section 4.3.1 may shift as technologies and institutional policies evolve. This temporal limitation underscores the need for longitudinal research to track how changing technologies reshape access, attitudes, and pedagogical practices.

Third, while offering depth, the qualitative methodology cannot quantify the prevalence of identified patterns or establish causal relationships between ChatGPT usage and educational outcomes. Further, while ChatGPT offers pedagogical benefits, our findings reveal two under-examined risks in Global South contexts that warrant further investigation. First, the tool’s potential to erode critical thinking aligns with participant concerns about dependency (Section 4.1.3), contrasting sharply with Freire’s (1968) vision of “problem-posing education” that fosters independent analysis. Second, ChatGPT’s homogenized outputs, observed in standardized responses to diverse students, may inadvertently suppress creative expression (Buckingham 2020), raising questions about its compatibility with culturally responsive pedagogies. Future research could compare ChatGPT with locally adapted AI tools to assess these risks. Also, the study’s exclusive focus on ChatGPT may limit its applicability to other AI tools used in education.

These constraints reflect intentional methodological choices prioritizing depth over breadth, aligning with qualitative research norms (Braun and Clarke 2006). The rich, contextual data yielded insights that would remain inaccessible through larger-scale quantitative approaches. Despite these limitations, this study provides a foundation for understanding AI adoption in higher education. It identifies valuable directions for future research, including comparative studies across diverse geographical contexts and mixed methods approaches that could complement these findings while building on the foundational understanding established here.

6. Conclusions and Recommendation

This study’s narrative inquiry, grounded in Clandinin and Connelly’s framework, reveals how temporality, sociality, and place shape ChatGPT integration in Philippine HEIs. The urban–rural divide emerged as a critical barrier, with rural stakeholders excluded from AI’s benefits due to infrastructural gaps, a disparity exacerbating existing educational inequalities. Both students and faculty emphasized ChatGPT’s dual role: enhancing productivity while risking dependency and academic integrity.

6.1. Synthesis of Findings

Our analysis demonstrates that the path forward for Philippine HEIs lies neither in uncritical adoption nor rejection, but in integration that centers equitable access and pedagogical values. The “silent acceptance” phenomenon documented in urban institutions and the complete absence of AI tools in many rural settings reflect broader systemic inequalities that must be addressed through coordinated policy and infrastructure development.

6.2. Practical Recommendations

Drawing directly from our findings on urban–rural disparities and stakeholder experiences, we recommend the following actions:

• Infrastructure Investment: Prioritize connectivity solutions for rural areas, including offline AI capabilities and public–private partnerships for expanding internet access.
• Faculty Development: Implement targeted professional development programs addressing technical skills and ethical considerations to overcome teacher uncertainty.
• Policy Development: Combat “silent acceptance” by developing realistic, collaborative AI integration policies. Prioritize offline-capable AI tools and digital literacy programs for rural faculty to ensure AI reduces rather than reinforces the Philippines’ educational inequalities.
• Ethical Education: Respond to student dependency concerns by incorporating AI literacy and critical evaluation skills throughout the curriculum.
• Cultural Transformation: Foster institutional cultures that balance innovation with integrity through transparent stakeholder dialogue.

6.3. Future Research Directions

This narrative inquiry provides a qualitative foundation for future research on ChatGPT’s role in Philippine higher education. Based on our findings, we recommend the following:

• Longitudinal mixed-methods research: Track how AI integration evolves over extended periods, combining quantitative outcome measures with qualitative exploration of experiences.
• Comparative cross-cultural studies: Expand research to other Global South contexts (e.g., ASEAN, Latin America, Africa) to assess the universality of themes like “silent acceptance” and ethical displacement, while identifying scalable strategies for overcoming digital divides. This would both validate this study’s framework and reveal context-specific adoption dynamics.
• Experimental approaches: Test the validity of faculty concerns about critical thinking erosion through controlled studies measuring AI’s impact on specific learning outcomes.
• Policy effectiveness studies: Evaluate how different institutional approaches to addressing “silent acceptance” impact compliance and learning outcomes.

As quantitative breadth is integrated with qualitative depth, future research can extend this study’s contributions while addressing its limitations. Prioritizing equity-focused designs, especially for marginalized populations, will ensure AI tools like ChatGPT serve as catalysts for educational justice rather than accelerants of inequality. By addressing these challenges comprehensively, Philippine HEIs can harness AI to reduce, rather than reproduce, social inequalities in education and future employment, transforming technological disruption into an opportunity for educational advancement.