Artificial intelligence (AI) emerged as a distinct academic field in the mid-twentieth century, following its formal introduction during the Dartmouth Summer Research Project proposal (1955/1956), which is widely regarded as a foundational moment in AI research [6]. Since then, AI has evolved from a theoretical concept into a sophisticated branch of computer science concerned with developing systems capable of performing tasks traditionally associated with human intelligence. These tasks include learning, reasoning, problem-solving, language processing, and decision-making.

Contemporary definitions emphasize AI’s ability to learn from data, adapt to new contexts, and simulate complex cognitive processes. According to Russell and Norvig, AI can be understood through system capabilities such as perception, inference, and goal-directed action, offering a comprehensive framework for conceptualizing intelligent behavior in machines. This perspective positions AI not merely as a technological innovation, but as an interdisciplinary domain that draws on linguistics, psychology, education, statistics, and the social sciences.

AI systems are characterized by core features that enable them to replicate selected aspects of human reasoning through structured and data-driven processes, including knowledge representation, search, and learning. Machine learning further enhances AI performance by enabling systems to learn from experience, refine predictions, and improve accuracy over time [7]. Recent developments in AI also demonstrate adaptive behavior, including responsiveness, effective processing of linguistic and visual data, and continuous learning from new inputs, making AI increasingly suitable for educational applications.

Artificial intelligence has become an integral component of contemporary educational systems, offering potential to enhance instructional effectiveness, decision-making, and learner engagement. AI-enabled educational tools can support instructional functions by delivering content, responding to learners’ inquiries, assessing performance, and providing timely feedback through intelligent dialogue systems and adaptive learning environments. Importantly, international guidance emphasizes that AI should be implemented in ways that strengthen teacher agency, protect learners, and ensure human-centered educational goals.

AI technologies can encourage a shift from teacher-centered instruction to more interactive, learner-centered approaches by enabling adaptive feedback, automated assessment, and intelligent tutoring. In the teaching of Islamic Studies, AI applications may support lesson preparation, personalized instruction, the use of multimedia resources, and feedback processes, provided that content accuracy, religious authenticity, and ethical safeguards are maintained. However, challenges such as limited teacher proficiency, rapid technological change, insufficient infrastructure, and concerns about the appropriateness of AI in religious education highlight the need for targeted professional development and clear governance frameworks.

Although AI’s educational potential is increasingly acknowledged, systematic implementation remains limited. The literature highlights adoption barriers, including infrastructural constraints, training gaps, and governance/ethical risks such as privacy, bias, transparency, and accountability. Therefore, scholars and standards bodies emphasize the importance of ethics-aligned guidance and standards-based implementation for trustworthy AI adoption in sensitive educational contexts [8]. Moreover, there remains a need for context-sensitive research focusing specifically on teachers’ perceptions of AI integration in Islamic Studies at the intermediate level in Saudi Arabia.

This study adopted a descriptive research design to investigate teachers’ perceptions of integrating artificial intelligence (AI) into Islamic Studies instruction at the intermediate level. This design is appropriate for systematically examining attitudes, perceived challenges, and pedagogical implications in real classroom contexts without experimental manipulation. Data were gathered using a structured questionnaire to capture prevailing perceptions and practices.

The target population consisted of Islamic Studies teachers working in public intermediate schools in Dammam. A simple random sampling technique was employed, as recommended in survey research to reduce selection bias and enhance generalizability [9]. A total of 151 teachers participated in the study.

Data were collected using a researcher-developed questionnaire rated on a five-point Likert scale [10]. Content validity was ensured through expert review, and discriminant validity was examined using an extreme-group approach and nonparametric tests appropriate for ranked/ordinal comparisons in survey validation [11]. Reliability and internal consistency were evaluated using Cronbach’s alpha [12]. Descriptive statistics (frequencies, percentages, means, standard deviations, and relative weights) were computed using established quantitative analysis procedures commonly applied in educational research and SPSS-based analysis workflows [13].

Table I summarizes the demographic and professional profile of the study sample (N = 151), revealing that most participants are experienced educators, with over half reporting 11 years or more of teaching experience, followed by those with 6–10 years, while early-career teachers constitute a smaller group. This experience-rich distribution suggests that the findings largely reflect informed professional perspectives and well-established pedagogical judgment [1]. In terms of academic qualifications, the majority of respondents hold bachelor’s degrees, with fewer holding master’s degrees and only a limited number possessing doctoral qualifications, a pattern consistent with common staffing structures in many educational systems [2]. Regarding professional development, participants reported varied engagement in technology-related training, ranging from extensive participation to no prior training. This disparity points to uneven levels of readiness for technology integration and highlights the need for sustained and inclusive professional development programs to support effective and equitable educational technology use [3].

Data were collected using a researcher-developed questionnaire administered to female Islamic Studies teachers at the intermediate level. The instrument aimed to examine teachers’ motivation to integrate artificial intelligence (AI), determine the pedagogical and technical standards required for effective use, and identify preferences for selecting appropriate AI tools. Its design was guided by an extensive review of Arabic and international literature on technology integration and AI in education [1],[2]. The questionnaire included demographic items and three main dimensions, with responses rated on a five-point Likert scale [3]. Content validity was ensured through expert evaluation, while discriminant validity was confirmed using the extreme-group method [4],[5].

Table 2 reveals a consistently high level of agreement among expert evaluators across all questionnaire axes, which provides strong evidence of the instrument’s content validity and clarity. For Axis 1 (Motivations for Utilizing AI Technologies), agreement levels range from 87% to 93% across the 20 items, indicating a shared consensus regarding the relevance and representativeness of the motivational constructs being measured. Likewise, Axis 2 (Pedagogical Standards) demonstrates similarly high agreement percentages (87%–93%) for all nine items, suggesting that the pedagogical criteria are clearly articulated and well aligned with expert expectations. The Technical–Pedagogical Standards axis also records uniformly strong agreement (87%–93%), highlighting evaluators’ confidence in the integration of technical and pedagogical dimensions within the instrument. In addition, Axis 3 (AI Technologies Applicable in Instruction) maintains comparably high agreement levels, reflecting consensus on the instructional relevance and applicability of the selected AI tools. Collectively, the consistently high agreement rates across all axes confirm the coherence, adequacy, and relevance of the questionnaire items, thereby supporting the instrument’s suitability for subsequent empirical implementation and analysis [1],[2].

The results of the Mann–Whitney U test demonstrate strong discriminant validity for the questionnaire through extreme-group comparisons, as statistically significant differences were observed between the upper and lower groups across all domains. In Domain 1 (Motivations for Utilizing AI Technologies in Teaching Islamic Studies), the upper group achieved substantially higher mean ranks than the lower group, with the U value reaching zero and significance confirmed at the 0.01 level. Similar patterns were found in Domain 2 (Standards for Utilizing AI Technologies) and Domain 3 (Diverse AI Technologies Applicable to Teaching Islamic Studies), where the consistent separation of rank distributions indicates a high capacity of the instrument to distinguish between respondents with differing levels of perception and agreement. The uniformly significant results across all domains confirm that the questionnaire items effectively discriminate between extreme groups, thereby supporting the robustness of its construct validity. These findings align with established methodological literature advocating the extreme-group approach and nonparametric testing for validating attitudinal and perception-based instruments [1],[2].

Table 4 summarizes the demographic and professional characteristics of the study sample (N = 151), providing essential context for interpreting the findings. The distribution of teaching experience indicates that more than half of the participants (53.6%) have 11 years or more of experience, suggesting that the results largely reflect the perspectives of seasoned educators with substantial classroom exposure. Teachers with 6–10 years of experience (28.5%) and those in the early stages of their careers (17.9%) are also adequately represented, ensuring variability in professional backgrounds. Regarding academic qualifications, the predominance of bachelor’s degree holders (81.5%) aligns with prevailing qualification requirements in school education systems, while the presence of postgraduate degree holders adds analytical depth to the sample. In terms of professional development, a notable proportion of participants reported having completed five or more technology-related training courses (45.0%), indicating a relatively high level of technological readiness. Collectively, these characteristics enhance the credibility of the data and support the reliability of participants’ perceptions regarding AI integration in instructional practice [1],[2].

Table 5 presents the corrected item–total correlation coefficients (CITC) and Cronbach’s alpha values if an item is deleted (CAID) for the questionnaire domains. As shown in the table, all items across the four domains demonstrate acceptable to strong CITC values, ranging approximately from 0.42 to 0.84. These values exceed the commonly recommended minimum threshold of 0.30, indicating that each item contributes meaningfully to its respective construct and demonstrates satisfactory internal consistency [1],[2].

For the first domain (Motivations for Utilizing AI Technologies), CITC values are consistently moderate to high, confirming strong homogeneity among items measuring motivational factors. Similarly, items within the second domain, including both pedagogical standards and technical and technological criteria, exhibit robust item–total correlations, reflecting coherent measurement of standards required for effective AI integration. The third domain (AI Technologies Applicable to Islamic Studies) shows particularly high CITC values for several items, suggesting a strong alignment between individual items and the overall construct.

Furthermore, the CAID values remain high and stable across all domains, with no substantial increase observed when any item is hypothetically removed. This stability indicates that deleting any item would not improve the overall reliability of the scale, thereby supporting the retention of all items in their current form. Collectively, these results confirm the strong internal consistency and reliability of the questionnaire, supporting its suitability for subsequent statistical analysis and empirical application [3].

Table 6 presents the internal consistency reliability of the questionnaire domains using Cronbach’s alpha (N = 45). The findings indicate that all domains demonstrate strong internal consistency, confirming the reliability of the measurement instrument. Domain 1, which examines motivations for utilizing AI technologies in teaching Islamic Studies, shows an excellent reliability coefficient (α = 0.941) across its 20 items. Likewise, Domain 2, addressing the standards required for AI utilization, achieves a high level of reliability (α = 0.884) for its 17 items, surpassing the minimum acceptable threshold for educational research instruments. Domain 3, focusing on AI technologies applicable to teaching Islamic Studies, also records a strong reliability coefficient (α = 0.910) despite its smaller number of items. Overall, the questionnaire attains a Cronbach’s alpha of 0.95, reflecting excellent internal consistency for the complete 45-item scale. These results confirm that the instrument is methodologically sound and appropriate for further statistical analysis and empirical investigation, in line with established reliability criteria in educational research [1].

The analysis of responses to the first research question indicates that Saudi intermediate-level Islamic Studies teachers hold a strongly positive perception of the pedagogical value of integrating artificial intelligence (AI) technologies into their instructional practices. Overall, teachers perceive AI as an enabling pedagogical tool that enhances lesson delivery, promotes student engagement, and improves instructional efficiency, rather than as a substitute for the teacher’s central instructional role. The high mean scores recorded across motivation-related items suggest that teachers are primarily motivated by AI’s capacity to diversify teaching strategies, support differentiated instruction, and facilitate clearer explanations of abstract or cognitively demanding religious concepts. These findings reflect teachers’ recognition of AI as a means to address learners’ individual differences and varied learning abilities while maintaining pedagogical control and religious authenticity, a perspective consistent with prior research on technology-enhanced teaching and teacher-centered integration models [1],[2].

Table 7 presents the criteria used to interpret the arithmetic mean scores of the questionnaire items, dimensions, and overall domains based on a five-point Likert scale. The table clearly maps specific mean score ranges to qualitative judgment levels, ranging from Very Low to Very High, thereby providing a standardized framework for data interpretation. This classification ensures consistency in evaluating respondents’ perceptions across all measured constructs and facilitates meaningful comparison among items and domains. Higher mean values within the scale indicate stronger agreement or more positive perceptions, whereas lower values reflect weaker agreement or less favorable evaluations. Adopting such a criterion enhances the clarity, transparency, and rigor of the quantitative analysis and aligns with established practices in attitude measurement research [1].

The results reported in Axis 1 reflect a clear and largely positive outlook among teachers toward the pedagogical value and motivational factors associated with integrating AI technologies into instructional practice. The consistently high levels of agreement across all items indicate that teachers generally perceive AI as a supportive and beneficial tool for teaching rather than a disruptive innovation. Mean scores ranging from 3.74 to 4.32, together with relative weights exceeding 74%, suggest strong confidence in AI’s capacity to enhance classroom practices. Teachers place particular value on AI’s ability to support personalized learning and to promote responsible and ethical use under teacher guidance, highlighting their commitment to learner-centered instruction while preserving professional accountability. The strong agreement on issues related to data privacy, verification of AI-generated information, and avoidance of plagiarism further demonstrates teachers’ awareness of the ethical and governance dimensions of AI integration, in line with current educational technology standards [1], [2]. Although items related to time-saving functions such as grading received comparatively lower mean scores, they still fall within the high agreement range, indicating thoughtful acceptance rather than skepticism. Taken together, these findings show that teachers view AI as a complementary pedagogical resource that enhances instructional quality, student engagement, and teaching efficiency, echoing conclusions drawn in previous studies on AI-supported teaching and responsible digital pedagogy [3], [4].

The second research question sought to identify the criteria that should guide the effective integration of artificial intelligence technologies in teaching the Islamic Studies curriculum at the intermediate level. To address this question, the study employed descriptive statistical techniques, including frequencies, percentages, means, standard deviations, and relative weights for each questionnaire item. The items constituting the second axis of the questionnaire were ranked according to their mean scores, in addition to calculating the overall mean for this axis. Interpretation of the results was guided by the same mean score criteria adopted in the analysis of the first research question. The findings are summarized and presented in Table 9, providing a clear overview of participants’ perceptions regarding the recommended criteria for AI integration.

Table 9 presents teachers’ overall perceptions of the criteria required for the effective adoption of AI technologies in teaching the Islamic Studies curriculum at the intermediate stage (N = 151). The findings indicate a consistently high level of agreement across all dimensions, as reflected by arithmetic means above 4.16 and relative weights exceeding 83%, which points to a strong consensus among respondents. The dimension related to the standards governing the use of AI technologies ranked first (M = 4.172, SD = 0.729, RW = 83.4%), underscoring teachers’ emphasis on the importance of clear pedagogical, ethical, and technical guidelines to ensure responsible and effective AI integration. This was followed closely by the dimension addressing the pedagogical value and motivations for integrating AI technologies (M = 4.160, SD = 0.661, RW = 83.2%), reflecting teachers’ awareness of AI’s potential to enhance instructional quality, learner engagement, and instructional efficiency. Moreover, the overall mean score for the axis (M = 4.166, SD = 0.695, RW = 83.3%) confirms a high level of readiness and acceptance among teachers, suggesting that successful AI implementation in Islamic Studies depends on aligning perceived pedagogical benefits with well-defined implementation standards, in line with prior research on educational technology integration [1], [2].

The results presented in Tables 10 and 11 reveal a consistently high level of agreement among Saudi intermediate-level Islamic Studies teachers concerning the pedagogical, technical, and ethical standards necessary for the effective integration of artificial intelligence (AI) in teaching. As shown in Table 10, all pedagogical standards attained high to very high mean values (M = 4.07–4.23), reflecting a strong shared belief that AI integration must be firmly grounded in doctrinal accuracy, the preservation of the authenticity of Islamic knowledge, and the promotion of higher-order thinking skills. The highest-ranked item, which emphasizes safeguarding the authenticity of Islamic knowledge, highlights teachers’ acute awareness of the religious, moral, and educational responsibilities inherent in Islamic Studies instruction. In addition, the high ratings assigned to AI-supported critical and reflective thinking, real-life learning transfer, and enhanced student engagement indicate that teachers recognize the pedagogical value of AI when it is applied within clear instructional and value-based boundaries. Complementing these findings, Table 11 underscores teachers’ strong emphasis on technical and ethical prerequisites, particularly secure access control, data privacy, accurate Arabic language support, and transparent ethical governance. The prominence of privacy, confidentiality, and fairness concerns reflects heightened awareness of the potential ethical risks associated with AI systems in educational environments. Collectively, the strong mean scores across both tables suggest that teachers view AI integration not as an ad hoc technological adoption, but as a structured, standards-driven process that requires careful alignment between pedagogy, technology, and ethics. This perspective is consistent with contemporary scholarship, which emphasizes that responsible AI adoption in education depends on robust governance frameworks, teacher preparedness, and context-sensitive implementation [1],[3].

The findings addressing the third research question indicate that Saudi intermediate-level Islamic Studies teachers’ concerns regarding the integration of artificial intelligence (AI) technologies are grounded in professional responsibility rather than resistance to innovation. Teachers emphasize doctrinal accuracy and content reliability, reflecting awareness of the ethical and religious sensitivity of Islamic Studies and the potential risks of unverified AI-generated outputs. Reported technical limitations and insufficient professional training are perceived as institutional challenges, underscoring the need for structured support, targeted capacity-building programs, and clear regulatory frameworks. Teachers’ cautious engagement with diverse AI tools further highlights the importance of pedagogically sound selection and contextual alignment with Islamic values. Overall, AI integration is viewed as a value-driven and systematic process requiring coherence between technology, pedagogy, and ethics, consistent with prior research on sustainable AI adoption in education [1],[3].

Table 12 summarizes Saudi intermediate-level Islamic Studies teachers’ perceptions of various artificial intelligence (AI) technologies applicable to curriculum delivery, revealing an overall high level of agreement (M = 3.94) that reflects positive yet carefully considered acceptance. Teachers showed a clear preference for specialized AI applications for Islamic Studies, which ranked first (M = 4.13, RW = 82.6%), emphasizing the importance of doctrinal accuracy, contextual relevance, and alignment with religious content. Immersive technologies, including metaverse, virtual reality, and augmented reality, as well as AI-based image generation and recognition tools, also received high ratings (M ≥ 4.00), indicating teachers’ recognition of their potential to enhance visualization, engagement, and experiential learning of abstract or historical Islamic concepts. In contrast, educational data mining and big data analysis technologies received comparatively lower mean scores, suggesting limited familiarity, perceived technical complexity, or uncertainty regarding their immediate pedagogical value at the intermediate stage. Generative AI and conversational tools, although positively evaluated, ranked lower than domain-specific applications, reflecting teachers’ cautious attitudes toward open-ended AI systems that may require rigorous content verification. Overall, the findings indicate that teachers’ acceptance of AI technologies is driven primarily by pedagogical relevance, content reliability, and contextual suitability rather than technological novelty alone. This trend is consistent with previous research emphasizing that sustainable AI integration in education depends on teachers’ trust in AI outputs, curricular alignment, and adequate professional preparation supported by clear ethical and governance frameworks [1],[3].