Applying the Fuzzy Delphi Method in the Design and Development of the Ar-Kahf Module

Applying the Fuzzy Delphi Method in the Design and Development of the Ar-Kahf Module

Wan Muhd Hafizudin Wan Amri Faizal¹, Mohd Fauzi Abdul Hamid^*2, Mohamad Lukman Al Hakim Md. Noor³

^1,2Faculty of Languages and Communication, Universiti Sultan Zainal Abidin, Malaysia

³Kulliyyah of Education, International Islamic University Malaysia, Malaysia

 *Corresponding Author

DOI: https://dx.doi.org/10.47772/IJRISS.2025.908000659

Received: 22 August 2025; Accepted: 27 August 2025; Published: 25 September 2025

ABSTRACT

In recent times, Arabic language teaching and learning (TnL) activities have diversified from the use of conventional methods towards incorporating creative value-added approaches. The integration of teaching aids (TnL materials) with technology has been shown to generate positive impacts, offering students a more interactive and engaging learning experience. One promising alternative is the application of augmented reality (AR) technology in Arabic language instruction. The development of a technology-assisted module has the potential to fulfill the indicators of innovation, interactivity, and effectiveness, while also enhancing students’ comprehension of the subject matter. Accordingly, this study seeks to obtain expert consensus on the components and elements underpinning the development of an AR-based module. The Fuzzy Delphi technique was employed to establish agreement among experts regarding the proposed components and elements through a fuzzy questionnaire. The study involved ten experts specializing in Arabic language T&L, educational technology, and curriculum module development. Data collected were analyzed using the Triangular Fuzzy Numbers method, while the ranking of priorities was determined through the Defuzzification Process. The findings revealed that all experts reached consensus, with a threshold value of less than 0.2 (d < 0.2), an agreement percentage exceeding 75%, and fuzzy score values (A) greater than 0.5. Overall, the main components and elements agreed upon by the experts demonstrate strong potential for producing a module that not only provides students with an enjoyable learning experience but also benefits teachers, given its interactive and flexible nature, open accessibility, and foundation in innovative and practical elements.

Keywords: Fuzzy Delphi Method; Augmented Reality (AR); interactive; AR-Kahf module; Arabic syntax.

INTRODUCTION

Arabic syntax serves as the foundation for understanding the meaning of verses in the Qur’an. The grammatical structure and word arrangement in Qur’anic verses play a crucial role in determining the precise meaning. Without a sound understanding of syntax, one may misinterpret or fail to grasp the true intent of a given verse. The teaching and learning (TnL) of Arabic syntax today largely remain grounded in conventional methods, namely teacher-centered approaches. Although some instructional practices have begun to integrate modern technology into TnL activities, the overall impact is still limited. Norma (2021) notes that while certain teachers have successfully transitioned from conventional to student-centered approaches, such methods have yet to effectively foster meaningful learner development. This shortcoming is attributed to the lack of positive attitudes and professional commitment among teachers in mastering core knowledge and pedagogy (Aman & Zulkifli, 2024). Furthermore, conventional techniques in teaching syntax focused on teacher-centered instruction and rote memorization tend to prevent students from independently applying their knowledge once formal instruction ends (Mualif, 2019).

According to Khalid et al. (2021), the learning of Qur’anic language, for instance, must align with current trends in order to continuously capture students’ interest in attending lessons. More interactive and contemporary language teaching methods, which utilize various technological tools such as websites and digital devices, have the potential to enhance public interest in learning Arabic (Zaini et al., 2019).

In recent years, technological advancement has grown rapidly, and its application has become increasingly essential in the field of education. This priority has been reinforced with the approval of the Digital Education Policy (DEP), whose main vision is to produce digitally fluent and competitive learners through the enhancement of knowledge, skills, and values. One potential alternative for integrating technology into the teaching and learning (TnL) of Arabic syntax is the use of augmented reality (AR), which carries its own advantages and relevance in line with the fast-paced development of sophisticated technologies. Asbulah et al. (2022) highlight that AR is a widely adopted application in the education systems of developed countries, particularly as a tool for 21st-century teaching and learning (PAK-21). Moreover, the use of multimedia in Arabic language learning can make lessons more engaging and enjoyable, thereby fostering students’ interest in exploring the subject matter more deeply (Prananingrum et al., 2020; Aziz & Jaafar, 2018).

Technological advancement and educational transformation have become crucial for teachers in Malaysia to maximize the opportunities available. Although AR technology is recognized as an effective interactive learning tool, some educators still adhere to conventional approaches such as the chalk and talk method and rote memorization, which they perceive as more effective than modern technological applications (Moharam et al., 2021). Consequently, a significant gap exists within society regarding the acceptance and application of this technology. According to Daud et al. (2020), students’ difficulties in comprehending theoretical knowledge particularly those requiring visualization skills can be addressed through the use of AR as a learning medium. Hence, Samad (2023) emphasizes that AR technology should be more widely implemented in education due to its potential as an interactive approach that enhances student motivation and enriches their overall learning experience.

Asbulah et al. (2022) state that this information technology offers a significant advantage in enhancing students’ understanding; however, it requires sufficient knowledge and thorough preparation on the part of teachers to develop technologies such as AR as an effective learning medium. By incorporating AR, teachers can design self-directed learning activities, allowing students to engage in a more flexible environment that sparks their interest, thereby making the learning process more effective and interactive. Saforrudin et al. (2016) further highlight that the integration of virtual objects into the real world through AR technology is gaining increasing prominence in Malaysia’s education system, particularly in the teaching of the Arabic language.

Thus, this study highlights the development of components and elements for constructing an Arabic syntax learning module in the Qur’anic context, referred to as the AR-Kahf Module. Expert consensus must be carefully established to ensure the production of a pragmatic and effective module for teaching Arabic syntax. To achieve this, the researcher employed the Fuzzy Delphi method, which is designed to gather data through expert agreement on the study being conducted. According to Eshak and Zain (2020), this method provides a more precise and effective measurement approach by involving experienced experts in their respective fields. In the Fuzzy Delphi method, the margin of error in decision-making can be reduced, as the approach ensures greater consistency with fewer iterative rounds needed to reach consensus (Mohd Hassan et al., 2018). In this study, the researcher obtained agreement from a panel of experts who possess relevant expertise and experience in relation to the key components and elements of the AR-Kahf Module to be developed.

METHODOLOGY

Research Design

The development of the Arabic syntax learning module in the Qur’an (AR-Kahf) employed a Design and Development Research (DDR) approach, which consists of two phases: the needs analysis phase and the design and development phase. This study focused on the design and development phase, in which the Fuzzy Delphi method was applied to obtain data through expert consensus regarding the main components and elements of the AR-Kahf module. The Likert scale responses provided by experts in the questionnaire were converted into fuzzy scales using binary terms (0, 1). From this conversion, three values were generated; minimum, reasonable, and maximum, based on the integration of fuzzy numbering. These values were then used to calculate the Threshold (d) value, which serves to determine the level of expert consensus. According to Eshak and Zain (2020), when the average threshold (d) is equal to or less than 0.2 and expert agreement is equal to or greater than 75%, the element under consideration is deemed to meet the criteria established in the Fuzzy Delphi method. Additionally, all defuzzification Alpha-Cut values (average of fuzzy responses) must exceed α-cut = 0.5. As noted by Tang and Wu (2010) and Bodjanova (2006), the alpha-cut value must be greater than 0.5; if it falls below 0.5, the item must be excluded in order to satisfy the conditions for achieving expert consensus.

Sample of Study

This study involved ten experts who were appointed as panel members for the design and development of the Arabic syntax learning module in the Qur’an (AR-Kahf). The selected experts possessed relevant expertise and skills aligned with the context of the study, namely in the fields of Arabic language teaching and learning (TnL), educational technology and curriculum development.

The number of experts chosen ten was deemed appropriate and consistent with the recommendations of Phillips (2000), who suggested a range of seven to twelve experts, while Delbecq et al. (1975) and Adler and Ziglio (1996) recommended between 10 and 15 experts. Clayton (1997) further proposed that five to ten experts are suitable when the panel is homogeneous, representing a small sample size of experts, provided that the selected experts come from diverse disciplinary backgrounds.

Research Instrument

This study employed a questionnaire as the primary research instrument, with data analyzed using the Fuzzy Delphi Method (FDM) to obtain expert consensus on the main components of the Arabic syntax learning module in the Qur’an (AR-Kahf). According to Beram et al. (2021), research conducted at the development phase involves data collection through FDM to achieve expert agreement on the elements within the constructs of the proposed model.

The questionnaire was designed based on an extensive literature review and underwent a validation process involving three experts, who assessed the appropriateness of wording, language, and content before it was distributed to the full panel of experts. Furthermore, the questionnaire adopted a seven-point Likert scale and was structured into six main sections; respondent demographics, module objectives, module content, module design, learning activities and assessment.

Data Collection and Analysis Process

Several steps were carried out in the process of data collection and analysis in this study, as follows:

Step 1:
Designing the questions for the Fuzzy Delphi questionnaire was carried out using the following methods:

1. Literature review
2. Adaptation from existing questionnaires

The process of developing the questionnaire items was similar to that of constructing a conventional questionnaire. A Likert scale was employed according to the requirements of the research questions, specifically based on the aspects to be measured by the researcher, such as the level of AGREEMENT, the level of DEGREE, and the level of IMPORTANCE.

Step 2:

It was assumed that Expert A was invited to determine the importance of the evaluation criteria for the variables to be measured using linguistic variables. The process of obtaining information and data depended on the initiative of the researcher. The researcher distributed the questionnaire online, such as via email, to the identified experts who possessed expertise in the field under study.

Step 3:

This process involved converting all linguistic variables into triangular fuzzy numbers. The linguistic scale used was similar to the Likert scale in other studies, but it was supplemented with fuzzy numbering based on triangular fuzzy numbers. Three main values were represented, as shown in Figure 1:

Figure 1: Triangular Fuzzy Number

(m₁ = minimum value; m₂= moderate value; m₃= maximum value)

In other words, the linguistic h-scale was used to convert the scale of linguistic variables into fuzzy numbers.

Table 1: Example of Linguistic Variable Scale

Step 4:

After the researcher obtained all the data and information from the experts, the Likert scales were converted into fuzzy scales. The data and information were then analyzed using Microsoft Excel. For each expert, the vertex method was applied to calculate the distance between the average rij (Chen, 2000). The distance between two fuzzy numbers m = (m1, m2, m3) and n = (n1, n2, n3) was calculated using the following formula:

\[
d(m,n) = \sqrt{\frac{1}{3} \left[ (m_1 – n_1)^2 + (m_2 – n_2)^2 + (m_3 – n_3)^2 \right]}
\]

Step 5:

According to Cheng and Lin (2002), if the distance between the average and the experts’ evaluation data is less than the threshold value of 0.2, all experts are considered to have reached consensus. In addition, among the panel of experts (m x n), if the percentage of group consensus exceeds 75% (Chu & Hwang, 2008; Murry Jr & Hammons, 1995), the process can proceed to Step 6. If the data indicate otherwise, a second round of the Fuzzy Delphi method must be conducted, or the item should be eliminated.

Step 6:

The next step is the defuzzification process. This process applies the formula Amax = 1/4 × (a1 + 2am + a2). When the researcher uses Average Fuzzy Numbers or the average response, the resulting score will fall within the range of 0 to 1.

RESEARCH FINDINGS

There were three steps followed by the researcher in the process of determining the main components and elements within the module design framework. Table 2 presents the steps employed in deriving the findings related to the module design.

Table 2: Steps in Module Design

 Module Objectives

The data analysis carried out in this section aims to examine the experts’ consensus on the elements proposed as the module objectives. Table 2 shows the Threshold values for each element, the percentage of expert consensus, the average Fuzzy score, the experts’ consensus and the ranking of each element.

Table 3: Analysis of Module Objectives

Table 3 presents the final findings for the module objective elements that have gone through expert consensus. Based on the table, all experts agreed on three out of four elements, with defuzzification values of 0.900 for element 2, 0.910 for element 3, and 0.893 for element 4. Only element 1 was rejected, as it received an expert consensus percentage lower than 75%, namely 60%. Thus, three objectives were agreed upon to be outlined in the AR-Kahf Module objectives.

In terms of ranking, the first position was given to the element “Applying Arabic syntax methods in understanding the verses of Surah al-Kahf in a clearer and simpler way,” followed by the element “Integrating Augmented Reality (AR) technology with the learning of Arabic Syntax in the Qur’an to create a more interactive and engaging learning experience, aimed at improving students’ academic performance in syntax subjects,” while the third-ranked element was “Integrating AR technology and Arabic syntax in the Qur’an to increase interest in teaching and learning sessions (TnL) that are more interactive and effective.

Module Content

The data obtained from this component aims to examine the experts’ consensus on the elements within the module content. Table 4 shows the Threshold values for each element, the percentage of expert consensus, the average Fuzzy score, the experts’ consensus and the ranking of each element.

Table 4: Analysis of Module Content

Based on Table 4, the analysis results for the elements of the AR-Kahf Module content show that the threshold value (d) is < 0.2 for all elements. For the percentage of each element, expert consensus is at 90%, which means it meets the criterion for expert agreement, namely a value exceeding 75%. In addition, all defuzzification Alpha-Cut values (average of fuzzy responses) are greater than α-cut = > 0.5. This indicates that the elements of the module content component have obtained strong consensus from the evaluation experts.

Module Design

The data analysis carried out in this section aims to examine the experts’ consensus on the elements of the module design. Table 5 shows the Threshold values for each element, the percentage of expert consensus, the average Fuzzy score, the experts’ consensus and the ranking of each element.

Table 5: Analysis of Module Design

Table 5 presents the final findings on the design component elements of the module, derived from expert consensus and recommendations. Three elements namely Elements 13, 15, and 16 were unanimously rejected by the experts. Apart from these, all other elements were accepted as guiding components for the design of the AR-Kahf Module. The element titled “The selection of visually appealing colors for text, icons and graphic elements” ranked first, indicating its significance as a key consideration in the development of the AR-Kahf Module. This was followed by other features arranged according to their respective priority levels.

Module Learning Activities

The data obtained from this section aims to examine the experts’ consensus on the elements of the module’s learning activities. Table 6 shows the Threshold values for each element, the percentage of expert consensus, the average Fuzzy score, the experts’ consensus and the ranking of each element.

Table 6: Analysis of Module Learning Activities

Table 6 presents the final findings derived from the Fuzzy Delphi analysis of five proposed elements for the learning activity component of the module, based on expert consensus. According to the table, only two elements received agreement from the experts: ‘An interactive quiz conducted through the “Scan & Respond” activity to identify objects, terminology, or Arabic syntactic structures in the Qur’an’ and ‘the group-based activity “Interactive Historical Trail” engages learners in exploring selected Qur’anic narratives’. In terms of priority ranking, the “Scan & Respond” interactive quiz was placed first, followed by the second agreed-upon element. Three elements were unanimously rejected by the experts: ‘Discussion of learning outcomes via interactive digital platforms such as Padlet’ and ‘A group-based activity involving the creation of curriculum-aligned creative content designed for integration with Augmented Reality (AR) applications’. Consequently, these two elements were excluded from reference in the learning activity component. The researcher therefore adopted only the two agreed-upon elements for the development of the AR-Kahf Module, in accordance with expert consensus.

Module Evaluation

Table 7 shows the final findings of the module evaluation elements, which have gone through consensus and suggestions from the panel of experts:

Table 7: Analysis of Module Evaluation

Table 7 shows the analysis results for the evaluation elements of the AR-Kahf Module, where expert consensus was found to be satisfactory. Overall, all elements under the evaluation component of the module recorded a threshold value (d) of less than 0.2. In terms of percentage, expert consensus for each element exceeded 75%, thereby meeting the requirement for expert agreement, except for elements two and four, which had to be removed as they did not meet the minimum percentage threshold for expert consensus. Furthermore, all defuzzification values of Alpha-Cut (average of fuzzy response) were greater than α-cut = > 0.5. For this module’s evaluation component, two elements were therefore excluded as they failed to meet both criteria of expert agreement in terms of threshold value (d) and consensus percentage.

DISCUSSION

Based on the analysis conducted using the Fuzzy Delphi method, the findings revealed that expert consensus on the five components of the design and development of the Arabic syntax learning module in the Qur’an (AR-Kahf) was at a satisfactory level. Nearly all elements were accepted by the expert panel, except for nine elements that had to be eliminated due to the lack of consensus. The five components that received expert agreement for the design and development of this module are; module objectives, module content, module design, module learning activities, and module assessment.

For the module objectives component, only one proposed element was rejected as it did not meet one of the criteria, as it received only 60% expert consensus, which is less than the required 75%. Therefore, the element “Identifying the actual use of Arabic syntax methods in the Qur’an through Surah al-Kahf” had to be excluded from the development of this module. The remaining three elements were agreed upon by the panel of experts, obtaining consensus percentages ranging from 80% to 90%, with defuzzification values of 0.900 for element one, 0.910 for element two, and 0.893 for element three. There are three objectives of the AR-Kahf module development according to the ranking agreed upon by the experts. The first is “Applying Arabic syntax methods to understand the verses of Surah al-Kahf more clearly and easily”, followed by “Integrating Augmented Reality (AR) technology with the learning of Arabic syntax in the Qur’an to create a more interactive and engaging learning experience towards improving students’ academic performance in syntax”, and in third place is “Integrating AR technology and Arabic syntax in the Qur’an to increase interest in more interactive and effective T&L sessions.”

Based on this ranking, it is clear that the integration between AR technology and Arabic learning in the Qur’an can provide added value in strengthening teaching and learning materials for both students and teachers in understanding Qur’anic verses more effectively and interactively. This statement is in line with the opinion of Wijaya et al. (2024), who stated that AR technology gives a positive impact as a learning medium, particularly for educators, as it creates a more interactive learning environment that can enhance students’ interest in the teaching and learning process. The researcher also added that during the learning process, there are students who are shy due to a lack of confidence in communicating with teachers or adults, unable to maintain eye contact when speaking, speak less or are not very open, while some students prefer learning through visual means, and others prefer using audio or kinesthetic approaches.

Next, all the elements in the second component, namely the module content, were agreed upon by the panel of experts with a consensus percentage of 90% for each element. The arrangement of these elements, according to the ranking, relates to topics from the syllabus of Ibn Hisham’s Syntactic Text Studies, which were placed first for all elements, beginning with the topics of Al-Fā‘il, Nā’ib al-Fā‘il, Al-Maf‘ūl al-Mutlaq, Al-Maf‘ūl Lahu (مفعول لأجله), Al-Maf‘ūl Fīh, Al-Maf‘ūl Ma‘ah, Al-Ḥāl, and Al-Tamyīz. These topics are part of the syllabus of the syntax subject, involving al-Marfu‘āt and al-Manṣūbāt. According to Dj (2019), emphasis on strong mastery of theory along with practical understanding of the rules and functions of syntax allows the relationship between the meanings of words in a sentence structure to be understood more clearly. This, in turn, facilitates a deeper appreciation of the narratives in the verses of the Qur’an.

The third component is the module design, which consists of 27 elements. Within this component, only three elements namely elements 13, 15, and 16 were rejected because they did not meet the minimum threshold value (d)<0.2 and recorded expert consensus below 75%. Meanwhile, the remaining elements were all accepted, with expert agreement ranging from 80% to 100% and threshold values (d)<0.2. All experts agreed that the module design should include several key features: a user-friendly interface that presents information interactively, an interface that makes content easy to understand even for first-time users, visually appealing and consistent graphics in 3D or 2D with high quality without being overly complex, attractive color schemes across multimedia elements, and effective integration of multimedia such as text, images, animation, 3D, and others. The design should also focus on visual data, images, and words; use clear graphics and images; apply minimal text or graphic colors; adopt concise texts; provide readable font sizes; select an appropriate number and type of fonts based on display needs; and ensure readability of fonts, icons, and graphics with appealing colors. In addition, clear audio pronunciation, appropriate background sounds, multiple presentation formats (such as mind maps and comparison tables), narrative or contextual elements for abstract concepts, clear and well-organized graphics, interactive features with 3D or 2D objects (such as rotate, zoom, or click for more information), real-world simulations through AR-based storytelling of selected narratives, QR-code-enabled content access, topic-specific modular pages, device compatibility for AR applications, easily recognizable AR markers suited to the chosen theme, fast and reliable marker detection under various lighting conditions, and printable AR-enabled markers were also emphasized. These expert-approved features align with López-Faican and Jaen (2020), who noted that teachers and students with access to such resources can independently produce Mobile Augmented Reality (MAR) learning modules and interact with digital objects in formats such as 3D, 2D, audio, video, images, and text anytime and anywhere, in both formal and informal learning contexts. They further explained that AR technology refers to “content produced and displayed via mobile devices in mobile environments encompassing multiple applications,” commonly termed Mobile Augmented Reality (MAR).

Furthermore, the fourth component involves the module’s learning activities, which consist of four elements: interactive quizzes through the “Scan & Answer” activity to identify Arabic objects, terms, or syntax in the Qur’an; discussions of learning outcomes through interactive online platforms such as Padlet; a group activity titled “Interactive Historical Trail” to understand selected Qur’anic narratives; and group tasks to generate creative content based on the curriculum integrated with AR. Out of these, two elements were accepted, namely the first element with 100% consensus and the third element with 80% consensus, and these will be applied in the development of the AR-Kahf Module. This aligns with Amal and Anwar (2024), who highlighted that interactive quizzes serve as media or applications containing learning materials in the form of interactive questions that help learners enhance comprehension and knowledge while also functioning as an alternative for self-directed learning. Rai et al. (2023) further emphasized that teaching and learning practices are shifting from teacher-centered to student-centered approaches, with collaborative learning particularly through group work emerging as a key pedagogical strategy to improve learning effectiveness.

In addition, the fifth component is the module evaluation. The researcher proposed four elements within this component: online objective tests, oral assessments, written assignments, and video tasks. Of these, only the first and third elements were accepted, with expert consensus of 100% and 90% respectively, while the oral test and video task were rejected. Therefore, based on expert consensus, the evaluation instruments agreed upon for assessing the module’s effectiveness are through tests. This finding is supported by Maharani et al. (2023), who stated that using diverse techniques such as written tests, oral assessments, and assignments provides a more comprehensive picture of students’ mastery levels. The researcher also emphasized that evaluation instruments not only measure learning outcomes but also assist teachers in assessing the effectiveness of teaching processes while strengthening students’ competencies in knowledge, skills, and attitudes.

Overall, the development of the Arabic Syntax Learning Module in the Qur’an (AR-Kahf) can make a significant impact on Arabic language teaching and learning. Specifically, it enriches Arabic syntax learning materials in the Qur’an with technology-based resources, enhances critical thinking skills through flexible learning with the module, and serves as a guide for understanding Qur’anic verses using syntax analysis and word-by-word translation. The application of the Fuzzy Delphi method in securing consensus and refinement from experienced experts enabled the researcher to design and develop an effective module that meets its intended objectives.

CONCLUSION

Based on the analysis of the study findings, an Arabic syntax learning module in the Qur’an, known as AR-Kahf, will be developed based on the elements agreed upon by experts through the Fuzzy Delphi method. This module will take the form of an e-module supported by AR technology and is divided into five main components: objectives, content, design, learning activities and assessment. The results indicate that expert feedback on these five components is at a good level, with a percentage of consensus ranging from 78% to 93%. Out of a total of 47 elements, 39 elements were accepted, while only 8 elements were rejected. In conclusion, all the information obtained through the Fuzzy Delphi method, including the improvement suggestions put forward by the experts, was carefully considered in order to develop an effective learning module that can strengthen the learning of Arabic syntax in the Qur’an based on technology, particularly Augmented Reality (AR).

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