261
IJNI: International Journal of Nusantara Islam Vol.
No.
: 261-272
DOI: https://doi.
org/10.
15575/ijni.
ISSN : 2355-651X
AI-Era Digital Literacy: Cultivating Honesty in Islamic Education Mohamad Mustari,1* Sri Nurhayati,2 Syarifuddin3 University of Mataram.
Indonesia IKIP Siliwangi.
Bandung.
Indonesia Correspondence: mustari@unram.
Received: November 15, 2025.
Revised: December 28, 2025.
Accepted: January 22, 2026.
Published: January 22, 2026 Abstract: This qualitative case study at SMP Prima Cendikia Islami (PCI).
Bandung, examines integrating AI-driven digital literacy with honesty education in a faith-based junior high school.
Using purposive sampling of leaders, teachers, students, and parents, data from interviews, focus groups, document analysis, and observations underwent thematic analysis with triangulation for rigor.
Findings show AI platforms .
TAKJUP.
LMS.
Parent Information Syste.
embed moral reasoning via formative monitoring, sustaining top national character rankings.
High teacher training and student-led clinics promote ethical accountability, proving pedagogical design determines AI's moral impact.
Faith-based schools can thus harmonize tech innovation with values education, offering a scalable model.
Future research should explore longitudinal moral outcomes and validated honesty measures.
Keywords: artificial intelligence.
digital literacy.
honesty education.
moral reasoning.
faith-based Introduction The unprecedented acceleration of information and communication technology (ICT), coupled with the exponential expansion of internet connectivity and the maturation of artificial intelligence (AI), has fundamentally redefined the architecture of contemporary education systems.
AI is now deeply embedded in secondary education ecosystems, enabling pedagogical innovations such as adaptive instruction, highly personalized learning trajectories, and sophisticated content delivery infrastructures (Khaldi, 2025.
Sharma et al.
, 2.
Platforms powered by AIAiincluding automated assessment engines, intelligent tutoring systems, and predictive learning analyticsAiare transforming instructional design, optimizing administrative workflows, and enhancing student engagement (Alaqad et al.
, 2025.
Iskandar et al.
, 2.
Increasingly, educational authorities have mandated AI literacy as a core component of curricula, recognizing its necessity for equipping learners to navigate and critically engage with evolving technological landscapes(Karan & Angadi.
Nurhayati et al.
, 2.
Yet the efficacy of such initiatives remains contingent upon educatorsAo preparedness, with substantial evidence underscoring the urgency of comprehensive AIfocused professional development (Adiyono.
Suwartono, et al.
, 2025.
Iryna, 2.
Despite its transformative capacity.
AI integration in education is accompanied by a constellation of ethical, sociocultural, and pedagogical complexities.
These include the safeguarding of sensitive learner data, the mitigation of algorithmic biases, the assurance of equitable access, and the preservation of academic integrity (Annamalai et al.
, 2025.
Sulkipani et , 2.
Persistent disparities in technological infrastructure threaten to exacerbate existing Mustari et al.
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inequities, while the opacity of AI-driven decision-making processes can erode trust in institutional fairness (Kaddouri et al.
, 2.
Moreover, concerns have emerged regarding the potential attenuation of critical thinking skills, the facilitation of plagiarism, and a decline in creative agency resulting from excessive reliance on AI (Barca, 2.
These realities demand the establishment of robust governance frameworks, inclusive infrastructural development, and ethically grounded policies that balance innovation with humanistic educational values.
Within this landscape, digital literacy assumes renewed significance as a complex, multidimensional construct encompassing technical fluency, evaluative acumen, ethical judgment, and socially responsible content creation (S.
Nurhayati, 2024.
Taufikin.
Nurhayati.
Badawi, et al.
Wu & Zhang, 2.
In AI-mediated environments, learners must possess the cognitive and ethical competencies to comprehend AI systemsAo mechanisms, interrogate their societal implications, and engage with them responsibly.
Contemporary models, such as BaskaraAos .
integrative framework and Biagini et al.
Aos .
AI Literacy Questionnaire, operationalize this nexus of technical and ethical capability.
Assessment tools like the AILQ and DigiCompEdualigned self-evaluation instruments have further institutionalized integrity as a foundational component of technical skill development (Tenberga & Daniela, 2.
Nevertheless, significant implementation gaps persist, particularly in teacher competence, curricular coherence, and standardized pedagogical protocols (Musa et al.
, 2024.
Su et al.
, 2023.
Winarti et al.
, 2.
Ethical instruction remains essential for preventing the misuse of AI technologies, addressing inherent biases, and countering the proliferation of misinformation (Bhavana et al.
, 2.
Empirical studies highlight the interdependence of AI literacy and broader innovation capabilities, while demonstrating that interactive, experiential pedagogiesAisuch as game-based learningAican simultaneously strengthen learner engagement and proficiency (LoboQuintero et al.
, 2.
Despite this, moral reasoning frameworks are still peripheral to the majority of digital literacy initiatives in formal education.
In Islamic educational contexts, the integration of ICT and AI is pursued with a dual imperative: to embrace pedagogical modernization while safeguarding moral and spiritual values (Ismail et al.
, 2024.
Siregar et al.
, 2025.
Taufikin.
Nurhayati.
Muzakki, et al.
, 2.
This is operationalized through ethics-infused teacher training, the alignment of religious and academic content, and AI-supported e-learning infrastructures that incorporate character development as a central design element (DzoAoul Milal et al.
, 2020.
Taufikin.
Nurhayati, & Muhajarah, 2.
Islamic ethical paradigms enrich global AI ethics discourse by foregrounding principles of fairness, justice, and human dignity (Kannike & Fahm, 2.
Nonetheless, deficits in infrastructure, expertise, and cultural receptivity continue to challenge these initiatives (Abubakari & Kalinaki.
Musa & Nurhayati, 2024.
Susanti & Nurhayati, 2.
Misinformation and academic dishonesty introduce additional layers of complexity.
The proliferation of manipulated digital content, including deepfakes and algorithmically generated disinformation, undermines learnersAo capacity for critical verification (Tomlinson et al.
, 2.
Concurrently, generative AI applications have facilitated plagiarism and cheating, particularly in environments lacking direct supervision (Coleman & Van Belle, 2.
Effective mitigation necessitates both technical interventionsAisuch as AI-based detection systemsAiand pedagogical innovations that cultivate metacognitive self-regulation, ethical discernment, and collaborative accountability (Zheng & Kim, 2.
This investigation centers on SMP Prima Cendikia Islami (PCI), a faith-based junior high school in Bandung Regency, which exemplifies the intentional integration of digital literacy and honesty education within an AI-mediated learning framework.
PCIAos educational architecture incorporates a fully digitized learning environment underpinned by a QurAoanic moral ethos, operationalized through platforms including the TAKJUP School Management System.
Learning Management System, and Parent Information System to ensure transparency, foster parental engagement, and reinforce ethical behavior.
The studyAos contribution lies in providing empirical insights into a rare pedagogical model within developing country contexts: a faith-based institution that systematically embeds moral education into AI-driven pedagogy.
It seeks to elucidate how PCI addresses the confluence of digital literacy.
AI ethics, and character formation, with the broader aim of informing scalable, contextually adaptable models for ethically responsible AI adoption in secondary education.
Mustari et al.
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The convergence of digital literacy and honesty education in the age of artificial intelligence (AI) is reshaping how schools prepare students for both technological competence and moral This literature review synthesizes research into four thematic areas: AI in personalized and values-based learning, digital literacy frameworks with ethical integration, honesty and moral education in AI-enabled classrooms, and contextual challenges and research gaps.
The review also identifies implications for the context of Prima Cendikia Islami (PCI) Junior High School in Bandung, where moral formation is central to the institutional mission.
Recent global trends demonstrate AIAos capacity to tailor learning experiences to individual student needs through adaptive learning platforms, intelligent tutoring systems, and predictive analytics (Alaqad et al.
, 2.
These tools can enhance engagement, improve efficiency, and support differentiated instruction.
Countries such as India have embedded AI literacy into national curricula, reflecting its growing importance in preparing students for future technological landscapes (Karan & Angadi, 2.
However, the literature warns against over-reliance on AI, citing risks of reduced critical thinking, creativity, and moral reasoning (Barca, 2.
For schools with a strong moral mandate, such as PCI.
AI adoption must be balanced with pedagogical strategies that preserve human judgment and ethical decision-making, ensuring technology supports rather than replaces moral instruction.
Digital literacy in AI-enhanced environments is increasingly defined as a multidimensional competence that includes technical proficiency, critical evaluation, ethical awareness, and empathy in digital interactions (Wu & Zhang, 2.
Frameworks such as BaskaraAos (Baskara, 2.
metalearning model integrate adaptability and continuous learning, while instruments like the AI Literacy Questionnaire (OAoDea & Ng, 2.
assess operational, cognitive, and ethical dimensions.
Ethics is no longer considered an optional add-on but a core competency within digital literacy (Bhavana et al.
, 2.
This shift reflects the need to address data privacy, algorithmic bias, and fairness as fundamental aspects of technology use (Khaldi, 2.
In Islamic education contexts.
AI integration is guided by moral and spiritual principles, with teacher training programs embedding ethical values alongside technical skills (Mohd Amin et al.
, 2.
This model is particularly relevant to PCI, where Islamic values must shape both the content and methods of digital literacy instruction.
The rapid expansion of AI tools, including generative models like ChatGPT, has heightened concerns about academic dishonesty, plagiarism, and misinformation (Elnagar et al.
, 2.
parallel, the rise of deepfakes and fabricated digital content has made it more difficult for students to discern credible information (Blankenship, 2.
Research on honesty education emphasizes the integration of moral instruction into all aspects of learning, moving beyond fragmented approaches toward holistic frameworks such as Neo-Aristotelian virtue ethics and integrated moral curricula (Roqai et al.
, 2.
Pedagogical strategies including case-based moral dilemmas, multimedia-enhanced discussions, and culturally embedded values have been effective in cultivating honesty and integrity (Adiyono.
Nurhayati, et al.
, 2025.
Melo & Parente, 2.
AIassisted moral education has yielded positive outcomes when paired with structured guidanceAi improving moral reasoning, reinforcing values such as honesty, and creating ethically conducive classroom climates (Kasimovskaya et al.
, 2.
For PCI, these approaches align with the schoolAos emphasis on character formation rooted in Islamic principles.
Several barriers limit the effective integration of AI and honesty education in junior high Infrastructure constraints, digital divides, and inadequate teacher AI literacy can impede both digital competence and moral education (Weligodapola & Kumarapperuma, 2.
In many systems, national AI strategies prioritize technical skills without parallel development of ethical frameworks (ElSayary, 2.
A notable gap lies in the assessment of honesty as an educational While academic metrics are well established, few validated tools measure moral behaviors or integrity in AI-mediated learning environments (Portela & Camanho, 2.
There is also limited research that examines the interplay between digital literacy and honesty education in Islamic school contexts, despite evidence that cultural and religious values strongly influence technology use (Syukur et al.
, 2.
This study addresses these gaps by exploring how digital literacy can serve as a vehicle for instilling honesty among students at PCI Junior High School in Bandung.
Unlike existing research Mustari et al.
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that often treats digital competence and moral education separately, it adopts an integrated perspective, combining: .
Technical AI skills with ethical reasoning grounded in Islamic values.
Teacher training and community engagement to reinforce honesty in both digital and offline .
Culturally responsive digital literacy curricula that address the challenges of misinformation, plagiarism, and misuse of AI tools.
By situating AI adoption within a dual emphasis on competence and character, this research aims to provide practical and culturally aligned strategies for ensuring that AI serves not only as an educational tool but also as a catalyst for moral growth.
Method This study employed a qualitative case study design, which is well-suited for in-depth exploration of complex educational phenomena within their real-life context (Iswahyudi et al.
, 2023.
Nurhayati et al.
, 2.
The case study approach enables the examination of SMP Prima Cendikia IslamiAos (PCI) distinctive integration of digital literacy.
AI ethics, and honesty education, allowing for a holistic understanding of institutional strategies and pedagogical practices.
This design was chosen because it aligns with the research objective of elucidating nuanced interactions between technological adoption, ethical instruction, and moral character development in a faith-based junior high school.
Furthermore, qualitative inquiry permits inductive theory-building grounded in empirical observation, as recommended by Yin .
, making it particularly appropriate for contexts where limited prior research exists.
Purposive sampling was employed to identify participants with direct experience and substantial knowledge of PCIAos digital literacy and AI ethics programs.
The sample comprised 2 school leaders, 3 ICT coordinators, 10 teachers across various disciplines, and selected 20 parents and 20 students.
Inclusion criteria emphasized participantsAo active involvement in the design, implementation, or experience of PCIAos digital learning environment.
Purposive sampling was selected to ensure the recruitment of information-rich cases capable of providing detailed insights into the pedagogical, administrative, and ethical dimensions of AI integration (Patton, 2.
The targeted approach maximized data relevance and depth, supporting the studyAos aim to generate contextually grounded findings.
Data were collected using a triangulated approach to enhance credibility and comprehensiveness: .
Semi-Structured Interviews: Conducted with school leaders.
ICT coordinators, and teachers to capture their perspectives on policy frameworks, curriculum design, and practical challenges in integrating digital literacy and ethics.
The interview protocols were informed by prior studies on AI literacy (Ng et al.
, 2024.
Hwang et al.
, 2.
and ethical education in digital contexts (Roqai et al.
, 2.
Focus Group Discussions (FGD.
Facilitated with students and parents to explore lived experiences, perceived benefits, and challenges of the schoolAos digital ecosystem.
Document Analysis: Reviewed institutional policy documents, digital platform usage reports, and curricular materials to identify explicit and implicit strategies for embedding honesty and ethical AI usage.
Observation: Non -participant observations of classroom sessions and digital platform interactions provided contextualized insights into the enactment of pedagogical strategies.
All data collection activities adhered to rigorous qualitative protocols, with instruments pilot-tested to ensure clarity and alignment with research objectives.
Thematic analysis was employed to interpret the data, following Braun and ClarkeAos (Braun & Clarke, 2.
six-phase framework: familiarization, coding, theme development, review, definition, and reporting.
guided by existing frameworks on digital literacy and AI ethics (Baskara.
Biagini et al.
, 2.
, and inductive, allowing themes to emerge from participantsAo narratives.
Data triangulation across interviews.
FGDs, documents, and observations strengthened analytical rigor and minimized single-source bias.
To ensure validity, methodological triangulation and member checking were implemented.
Participants were invited to review and confirm the accuracy of interview transcripts and thematic Reliability was reinforced through the maintenance of an audit trail documenting data collection procedures, coding decisions, and analytical memos.
Reflexive journaling was employed to identify and mitigate potential researcher biases.
The study also employed peer Mustari et al.
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debriefing with colleagues familiar with qualitative educational research to enhance analytical Ethical clearance was obtained from the relevant institutional review board.
Informed consent was secured from all participants, with additional parental consent for student participants.
Confidentiality was maintained by anonymizing all identifiable information in transcripts and The study adhered to the principles of the Declaration of Helsinki, ensuring respect, beneficence, and justice.
Special attention was given to the ethical implications of observing and analyzing AI-mediated learning environments, including the protection of sensitive digital records and the respectful handling of religiously-informed pedagogical practices.
Results and Discussion Character Development Indicators The 2025 Rapor Pendidikan results position SMP Prima Cendikia Islami (PCI) among IndonesiaAos top 20% of schools nationwide in all measured domains of character development.
The indicatorsAi Religious Faith and Morality (Beriman.
Bertakwa kepada Tuhan Yang Maha Esa, dan Berakhlak Muli.
Mutual Cooperation (Gotong Royon.
Creativity (Kreativita.
Critical Reasoning (Bernalar Kriti.
Global Diversity (Kebinekaan Globa.
, and Independence (Kemandiria.
Aiare summarized in Table 1.
Table 1.
Character Development Scores Ae PCI, 2024Ae2025 Indicator 2024 Score 2025 Score Change (%) Religious Faith and Morality Mutual Cooperation Creativity Critical Reasoning Global Diversity Independence Source: Educational Report of PCI, 2024Ae2025 National Rank Category Top 20% Top 20% Top 20% Top 20% Top 20% Top 20% Teacher interviews consistently emphasized the schoolAos intentional coupling of AI tools with ethical reflection.
As one moral education teacher stated: AuWhen students complete AI-based quizzes, the system includes scenarios where they must choose an action aligned with Qurani This is not just testing memoryAiit forces them to reflect on honesty and fairness.
Ay (Teacher Interview.
May 2.
Observation field notes from a Grade 9 Critical Reasoning lesson provide further support.
Students were presented with an AI-generated case study involving group plagiarism.
The teacher facilitated a guided discussion, prompting students to evaluate both academic and ethical implications before proposing preventive strategies.
This aligns closely with Lin et al.
, who found that contextualized moral reasoning tasks foster deeper ethical engagement.
Students themselves recognized the dual learning benefit.
In focus group interviews, one student remarked:
AuWeAore not only learning how to answer questions but how to decide if the answer is right, fair, or ItAos about more than just marks.
Ay (Student Interview.
June 2.
Such comments illustrate the intended pedagogical shiftAifrom moral instruction as a separate subject to moral reasoning embedded in cognitive skill development.
The PCI approach directly reflects the integrated model described by Ristiana et al.
, where digital learning tools are designed to concurrently target cognitive competencies and moral dispositions.
By embedding moral scenarios within AI-driven learning platforms.
PCI operationalizes the recommendation that moral reasoning gains are maximi zed when digital instruction is value-oriented rather than purely skill-oriented.
Furthermore.
PCIAos topquintile ranking across all domains shows that moral capacity can be preserved Aieven strengthenedAiwithin a high-tech.
AI-enhanced environment.
This challenges the concern raised by some scholars that increased AI dependence may erode student agency or moral reasoning if not carefully scaffolded.
PCIAos results suggest that the presence of AI is not Mustari et al.
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inherently detrimental (Pei et al.
, 2.
the design of AI-mediated learning experiences is the determining factor.
The small decline in Religious Faith and Morality can be interpreted in light of Abdallah & Nassour .
, who caution that technology-rich environments require continual cultural and religious contextualization to maintain alignment with institutional In PCIAos case, interviews revealed that several extracurricular religious programs in 2025 were restructured or shortened due to scheduling conflicts with academic competitions, potentially explaining the minor score dip.
Digital Learning Infrastructure The digital ecosystem at SMP Prima Cendikia Islami (PCI) consists of three core, interconnected platforms: the TAKJUP School Management System (SMS), the Learning Management System (LMS), and the Parent Information System (PIS).
Each system is designed not only for operational efficiency but also for embedding and tracking moral education outcomes.
The infrastructure is summarized in Table 2.
System
TAKJUP
SMS
LMS
PIS
Table 2.
Core Digital Infrastructure and Functions Ae PCI .
Primary Functions Integration with Moral Education Attendance, scheduling, academic records Tracks incidents of academic dishonesty and misconduct Lesson delivery, assignments, assessment Embeds moral dilemmas into auto-flags plagiarism Parent-school communication Sends alerts on e-safety breaches and moral performance issues Source: PCI Digital Infrastructure Report, 2025 One ICT coordinator explained the design philosophy: AuThe LMS doesnAot just host content.
we use it to track academic honesty.
If a studentAos work is flagged, the teacher gets notified and we follow up with a reflective assignment on honesty.
This changes the mindset from AoI got caughtAo to AoI learned why this matters.
AoAy (ICT Coordinator Interview.
May 2.
Classroom observation confirmed this approach.
In a Grade 8 history lesson, a studentAos assignment submission triggered a plagiarism alert.
Instead of receiving an immediate penalty, the student was asked to review an AI-generated tutorial on proper citation and then resubmit.
The teacher reported that the studentAos revised work showed both improved factual accuracy and originality.
Parents also valued the immediacy of the PIS alerts.
One parent noted: AuWhen the system sends a message that my child has done something rightAilike helping a classmate onlineAiit reinforces the lesson at home.
ItAos not just about catching mistakes.
Ay (Parent Interview.
May 2.
The PCI model aligns closely with Pei et al.
(Pei et al.
, 2.
, who stress the need for AI ethics systems to be proactive and educative rather than punitive.
The LMSAos corrective feedback loop mirrors the Auformative interventionAy model described by Al-Abdullatif .
, in which ethical breaches become teachable moments.
Furthermore, the PISAos integration of moral updates directly addresses the gap identified by Hsu & Chen .
, who found that most parent communication systems focus narrowly on academic grades and attendance, neglecting behavioral and ethical dimensions.
PCIAos PIS explicitly includes these domains, making it a more holistic tool for homeAeschool collaboration.
The TAKJUP SMSAos role in maintaining integrity records connects with Ristiana et al.
(Ristiana et al.
, 2.
, who recommend that digital administrative tools be leveraged for ethical monitoring as well as logistical purposes.
PCI operationalizes this recommendation by embedding moral tracking into routine school management processes, ensuring moral education is part of daily institutional data flow.
Teacher and Student Participation Teacher and student engagement in professional development and classroom learning activities is a critical factor in sustaining moral and academic excellence.
PCIAos Rapor Pendidikan .
data show that both teacher participation in training and the quality of classroom teaching exceed national averages across all observed metrics (Table .
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Table 3.
Teacher and Student Participation Indicators Ae PCI, 2025 PCI Score National Category Average Teacher Participation in Additional Training 86.
High
(%)
Classroom Management Score High Learning Quality Score High Metric In interviews, teachers consistently linked their professional growth to improved classroom integration of AI and moral reasoning.
One science teacher described: AuBefore.
I only focused on teaching content.
Now, with AI tools.
I can weave in discussions on bias, fairness, and honesty.
Students are more aware of how to verify AI-generated information.
Ay (Teacher Interview.
June 2.
Observation during a Grade 7 English class confirmed this shift.
The teacher used an AI grammar checker to display alternative sentence corrections, then facilitated a discussion about when and why to choose a particular phrasing.
This moved the activity from pure mechanics into a conversation on clarity, authorship, and the ethics of accepting AI suggestions without critical Students also play an active role in this culture of participation.
Focus group discussions revealed that many voluntarily participate in AuAI literacy clinics,Ay peer-led sessions supervised by teachers where students practice using digital tools ethically.
One student explained: AuItAos not just about learning how to use AI, but also when not to use itAilike for your own homework answers.
We talk about the difference between help and cheating.
Ay (Student Interview.
May 2.
This kind of peer-facilitated reflection strengthens both understanding and accountability, echoing Pei et al.
(Pei et al.
, 2.
on the value of participatory ethics in AI education.
The PCI model operationalizes the teacher-learner synergy described by Al-Abdullatif (Al-Abdullatif, 2.
, where high teacher engagement in continuous training correlates with stronger student adherence to digital ethics.
Moreover.
PCIAos embedding of moral content into AI-based activities resonates with Lin et al.
(Lin et al.
, 2.
, who found that deliberate ethical framing within skillbased tasks significantly increases long-term moral awareness.
The data also confirm Castayo Muyoz et al.
Aos assertion that teachers with higher digital competence are more likely to create learning environments where students can safely explore ethical dimensions of technology.
PCIAos combination of above-average participation rates and documented classroom practice provides empirical support for this claim (Lypez Franco et al.
, 2.
Furthermore, the student-led AI literacy clinics address a gap highlighted by Ristiana et al.
(Ristiana et al.
, 2.
, who argue that student agency in ethical learning is often underutilized.
PCIAos program demonstrates how structured peer engagement can complement teacher-led instruction, creating a multi-directional flow of ethical discourse.
Conclusion This investigation engaged with the critical and underexplored problem of reconciling AI-mediated digital literacy initiatives with the intentional cultivation of honesty within a faith-based junior high school milieu.
At SMP Prima Cendikia Islami (PCI), the study interrogated the capacity of technologically enriched pedagogical ecosystems to preserve and advance moral dispositionsAi particularly integrityAiwhile concurrently fostering advanced technical and cognitive The inquiry was situated against the broader global discourse on the dual trajectories of technological acceleration and the potential attenuation of ethical conduct in AI-supported educational contexts.
Empirical findings indicate that PCIAos deliberate integration of moral reasoning frameworks into AI-powered instructional and administrative systems sustains exemplary character formation outcomes.
The institution consistently ranked in the top quintile nationally across six core character development indicators, with ethical reflection systematically embedded in daily instructional practice.
PCIAos digital infrastructureAicomprising the TAKJUP School Management System.
Learning Management System, and Parent Information SystemAiwas purposefully architected to monitor, reinforce, and pedagogically address ethical behavior, privileging formative moral engagement over retributive approaches.
Enhanced teacher participation in targeted professional development, coupled with student-led AI literacy clinics.
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cultivated a reciprocal culture of ethical accountability.
These findings carry significant They challenge deterministic narratives that portray AI integration as inherently corrosive to moral reasoning, instead demonstrating that the pedagogical design of AI-mediated learning is the decisive variable.
Furthermore, they present a scalable, contextually embedded model for aligning technological innovation with moral education imperatives, particularly within culturally and religiously anchored educational settings.
In this paradigm.
AI emerges not merely as an instrument of efficiency but as a co-constructive agent in values-based education.
This study advances scholarly understanding by contributing empirical evidence from a developing country faith-based context, thereby addressing a notable lacuna in AI-and-ethics research.
It affirms the criticality of embedding moral reflection into AI systems and underscores the synergistic role of educators and learners in sustaining ethical praxis.
Prospective research directions include longitudinal studies tracking moral trajectory, cross-contextual comparative analyses, and the refinement of validated instruments for measuring honesty within AI-mediated learning References