Application of the Fuzzy Delphi Method in the Design and Development of an Interactive Arabic Grammar Module Based on Syawahid from Hadith

Application of the Fuzzy Delphi Method in the Design and Development of an Interactive Arabic Grammar Module Based on Syawahid from Hadith

Umair Nu’man Ubaidillah¹ & Mohd Fauzi Abdul Hamid^*2

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

*Corresponding Author

DOI: https://dx.doi.org/10.47772/IJRISS.2025.908000660

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

ABSTRACT

Arabic grammar is a complex yet essential branch of the Arabic language that must be learned. The difficulty in understanding information presented in traditional texts often used in Arabic language learning makes mastering this knowledge even more challenging. In the post-pandemic era, the use of digital modules such as websites has become increasingly important to support flexible and interactive self-directed learning. Therefore, this study aims to obtain expert consensus in determining the appropriate elements and components for the development of an interactive Arabic grammar module using a website platform. An interactive approach based on constructivist theory is applied through elements such as quizzes, games, and multimedia to enhance students’ motivation and comprehension. Overall, the use of websites in the teaching and learning (TnL) of Arabic grammar has great potential to improve learning effectiveness through active student engagement in a fun and flexible digital environment. The Fuzzy Delphi Method was used in this study, involving ten experts from the fields of Arabic language TnL, educational technology, and curriculum development. All experts were given a fuzzy questionnaire consisting of six sections: respondent demographics, module objectives, module content, module design, learning activities, and assessment. The data collected were analyzed using Triangular Fuzzy Numbers and the ranking of each variable was obtained through the Defuzzification Process. The Fuzzy Delphi analysis showed that expert feedback on the main components of the module was acceptable, reaching consensus with a threshold value of less than 0.2 (d<0.2) and an agreement percentage starting from 90%. Additionally, all module elements were accepted by the experts. The findings are expected to assist researchers in designing and developing a module capable of empowering Arabic grammar learning through the innovation developed, namely the Interactive Nahu Hadis Module (iN-Hadis).

Keywords: Fuzzy Delphi Method; interactive module; Arabic grammar; technology application; website.

INTRODUCTION

The COVID-19 pandemic caused a sudden shift to online learning, with the use of digital modules, e-learning, and virtual learning increasing drastically (Aristovnik et al., 2023). Despite the rapid growth of electronic modules, there remains a significant gap in Arabic language teaching in Malaysia related to e-learning. This can be seen in existing textbooks, which lack good writing features and are less suitable for non-native learners, thus requiring improvements (Abdul Ghani et al., 2021). One such improvement is through the utilization of technology in Arabic teaching and learning (TnL) via websites. Websites play an important role in modern teaching and learning activities, one of which is facilitating access to learning materials. According to Pushpa and Wijekoon (2024), websites allow students and teachers to access various resources such as notes, videos, interactive exercises, and authentic materials at any time.

In today’s digital era, websites function as a medium that simplifies the process of delivering and receiving knowledge. They provide multiple media formats such as videos, interactive exercises, and discussion forums, making the learning process more engaging and effective (Yang, 2025). For instance, websites such as Mysūr and I-Na‘T provide multimedia resources, interactive exercises, and self-access learning that enhance mastery of Arabic grammar (Hussin et al., 2023). This makes web-based interactive modules capable of simplifying complex grammar concepts while attracting students’ interest (Abdul Hamid et al., 2024).

In the educational context, websites are designed with emphasis on interactivity, systematic content organization, and accessibility, where content is broken down into smaller units focused on specific topics, thus facilitating step-by-step learning (Astuti et al., 2020). Interactive web elements include quizzes, simulations, self-practice activities, and tutorials that allow students to directly engage with the material (Sukmawati et al., 2024).

The effectiveness of web-based learning has also been proven. As noted by Chou and Liu (2005), students in web-based virtual learning environments demonstrated higher performance, confidence, and satisfaction compared to traditional classes. Similarly, Ding and Zhang (2018) found that students engaged in web-based Problem-Based Learning (PBL) achieved higher exam scores, better self-directed learning skills, and greater satisfaction. Overall, web-based learning has been shown to be more effective in improving teacher achievement compared to face-to-face training (Wuryaningsih et al., 2019), while websites with videos and interactive exercises help students master practical skills more effectively (Barisone et al., 2019).

For Arabic grammar learning, the use of interactive websites can spark students’ interest in understanding complex information. Such websites should adopt interactive approaches such as quizzes, games, and multimedia elements to enhance learning effectiveness and comprehension. Abdul Hamid et al. (2024) emphasized that interactive and multimedia modules make learning more engaging, easier to understand, and increase students’ interest in Arabic grammar. User-friendly interactive modules also improve students’ motivation and readiness to continue learning (Sorongan & Fauji, 2023). Interactive elements further encourage active student engagement in the learning process. According to Efgivia et al. (2021), learning occurs when students actively construct knowledge in their minds, rather than simply receiving information from teachers. Therefore, web-based learning is an effective approach, as students can learn at their own time and place without being bound by a fixed schedule (Santiago et al., 2021). This form of learning is also capable of integrating various modes of delivery, including text, audio, graphics, animation, and video, by leveraging modern technology to produce more effective teaching.

Accordingly, this study focuses on the development of components and elements for an interactive Arabic grammar learning module through the syawahid of the Hadith 40, delivered via a web platform. Expert consensus serves as the main foundation in selecting appropriate elements for the module development using the Fuzzy Delphi Method. This approach is crucial to ensure that the developed module is grounded in expert consensus, follows systematic development procedures, and is academically evaluated to guarantee its quality and effectiveness as a learning module.

METHODOLOGY

Research Design

The development of the Interactive Nahu Hadis Module (iN-Hadis) was grounded in the Design and Development Research (DDR) approach, which comprised two phases: the needs analysis phase and the design and development phase. This study employed the Fuzzy Delphi Method to obtain data through expert consensus on the main components of Interactive Nahu Hadis Module (iN-Hadis). The Likert scale responses selected by experts in the questionnaire were converted into a fuzzy scale using fuzzy numbering, specifically binary terms (0, 1). The researcher then calculated the threshold value (d) to assess the level of expert agreement, since in the Fuzzy Delphi Method, the threshold value (commonly d ≤ 0.2) is used to determine whether an item or decision has achieved sufficient consensus among experts. If the threshold value exceeds this limit, the item is considered not to have reached consensus and may need to be reconsidered or discarded (Aidil et al., 2023).

Research Sample

This study involved ten experts as research respondents who were appointed to evaluate the components and elements in the design and development phase of the Interactive Nahu Hadis Module (iN-Hadis). These experts possessed expertise in areas relevant to the study’s context, namely the teaching and learning (TnL) of Arabic, educational technology, and curriculum development. The selection of ten experts was deemed appropriate and aligned with the view of Yusof et al. (2022), who stated that ten experts is a commonly recommended number for the implementation of the Fuzzy Delphi Method, as it is sufficient to achieve consensus without overburdening the analysis process.

Research Instrument

This study employed a questionnaire as the research instrument and the data were analyzed using the Fuzzy Delphi Method to obtain expert consensus on the components and elements of the Interactive Nahu Hadis Module (iN-Hadis). The questionnaire was developed based on previous studies and underwent a validation process by three experts to review the language and content before being distributed to the panel of experts. It consisted of a seven point Likert scale and was divided into six main sections: respondent demographics, module objectives, module content, module design, learning activities, and evaluation. According to Ismail et al. (2021), questionnaires are used to assess the suitability, validity, and reliability of the items or criteria intended to be developed or validated.

Data Collection and Analysis Process

There are several steps in the process of data collection and analysis carried out in this study, as follows:

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

Literature review

Adaptation from existing questionnaires

The process of developing the questionnaire items was similar to that of constructing a conventional questionnaire. A Likert scale was used according to the needs 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 is assumed that expert A is 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 depends on the researcher’s own initiative. The researcher distributes the questionnaire online, such as via email, to experts identified as skilled in the field being studied.

Step 3:

This process involves converting all linguistic variables into triangular fuzzy numbers. The linguistic scale used is similar to the Likert scale in other studies, but it is supplemented with fuzzy numeration based on triangular fuzzy numbers. The three main values ​​are shown in Figure 1:

Figure 1: Triangular Fuzzy Number

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

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

Table ‎1: Example of Linguistic Variable Scales

Step 4:

After the researcher obtained all the data and information from the experts, the researcher needs to convert all the likert scales to fuzzy scales. The data and information will be analyzed using Microsoft Excel software. For each expert, the vertex method is used to calculate the distance between the averages rij (Chen, 2000). The distance between two fuzzy numbers, m = (m1, m2, m3) and n = (m1, m2, m3) is 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 expert assessment data is less than the threshold value of 0.2, then all experts are considered to have reached a consensus. In addition, among m x n experts, if the percentage of group agreement exceeds 75% (Chu & Hwang, 2008; Murry Jr & Hammons, 1995), then the process can proceed to step 6. If the data shows otherwise, a second round of the Fuzzy Delphi method should be performed or the item should be discarded.

Step 6:

The next step is the defuzzification process. This process applies the formula A_max = 1/4 * (a₁ + 2a_m + a₂). If the researcher uses Average Fuzzy Numbers or the average response, the resulting score will be a number within the range of 0 to 1.

RESEARCH FINDINGS

There are three steps followed by the researcher in the process of determining the main components and elements within the module design. Table 2 presents the steps used in deriving the findings for the module design.

Table 2: Module Design Steps

Module Objectives

Table 3 shows the final findings for the module objective components that have been agreed upon and recommended by the expert panel. The findings of this study show the threshold value for each item, percentage of expert agreement, average value of fuzzy score, expert agreement and position of each item.

Table 3: Module Objective Analysis

 Table 3 shows that the analysis results for the elements of the iN-Hadis Module objectives based on expert consensus were favorable. All elements under the module objectives component recorded a threshold value (d) < 0.2. However, there were two elements that did not reach consensus among experts 4 and 6, namely elements 1 and 2. This indicates that some experts held differing views and did not achieve full agreement on certain elements. Nevertheless, if the average threshold (d) value obtained is less than 0.2, the element is considered to have achieved good expert consensus (Aidil et al., 2023). In terms of percentage, expert consensus exceeded 75% for all elements, which meets the required criterion for consensus. In addition, all defuzzification Alpha-Cut values (average of fuzzy responses) were greater than α-cut = > 0.5. This demonstrates that the elements of the module objectives component attained strong consensus among the evaluation experts.

Module Contents

Table 4 shows the final findings for the module content items that have been agreed upon and recommended by the expert panel.

Table 4: Module Content Analysis

 The analysis results for the content elements of the iN-Hadis Module show a threshold value (d) < 0.2 for almost all elements. There is one element that did not reach expert agreement with a threshold value (d) < 0.2, which is on the fifth element by the second expert, but if the average threshold value (d) is less than 0.2, then the element has reached good expert agreement. For the percentage of each element, the expert agreement is at a value of 100%, which means that it meets the conditions of expert agreement. In addition, all defuzzification Alpha-Cut (average of fuzzy response) values ​​exceed α-cut = > 0.5. This shows that the elements for the content components of the module have received good agreement from the evaluation experts.

Module Design

Table 5, on the other hand, shows the final findings of the module design elements that have been agreed upon and recommended by the expert panel.

Table 5: Module Design Analysis

Overall, the analysis results for the design elements of the iN-Hadis Module show a threshold value (d) < 0.2 for all elements except elements 9 and 12 by the third expert. As for the percentage of each element, the expert agreement is at a value of 100% except for the ninth element, which means it meets the expert agreement requirements. In addition, all defuzzification Alpha-Cut values ​​(average of fuzzy response) exceed α-cut = > 0.5. This shows that the elements for the module design components have received good agreement from the experts.

Module Learning Activities

Table 6, on the other hand, shows the final findings of the module learning activity elements that have been agreed upon and recommended by the expert panel.

Table 6: Analysis of Module Learning Activities

Table 6 shows the results of the analysis of the learning activity elements of the iN-Hadis Module. All four elements achieved a threshold value (d) < 0.2. Three elements exceeded 2.0, indicating that they had met the expert consensus requirements. As for the percentage of each element, the expert consensus was at a value exceeding 75%, which is 100%, except for the fourth element, which was only 90%, indicating that it met the expert consensus requirements. In addition, all defuzzification Alpha-Cut values ​​(average of fuzzy response) exceeded α-cut = > 0.5. In conclusion, all the proposed elements have received expert consensus and could be used.

Module Evaluation

Table 7, on the other hand, shows the final findings of the module evaluation elements that have been agreed upon and recommended by the expert panel.

Table 7: Module Evaluation Analysis

Table 7 shows the results of the analysis for the evaluation elements of the iN-Hadis Module according to expert consensus, are good. Overall, all elements for the module evaluation components show a threshold value (d) of less than 0.2. For the percentage of each element, the expert consensus is at a value exceeding 75%, which means that it meets the expert consensus requirements. In addition, all defuzzification values ​​Alpha-Cut (average of fuzzy response) exceed α-cut = > 0.5. For the evaluation elements of this module, all of them meet the expert consensus requirements.

DISCUSSION

Through the analysis conducted using the Fuzzy Delphi Method, the findings indicated that expert consensus on all five components of the design and development of the Interactive Nahu Hadis Module (iN-Hadis) was at a satisfactory level. All elements were accepted by the expert panel, and the components of the module design and development consisted of module objectives, module content, module design, module learning activities, and evaluation.

For the module objectives, all experts agreed on the five elements, with defuzzification values of 0.880 for element 1, 0.873 for element 2, 0.907 for element 3, 0.937 for element 4, and 0.917 for element 5. This shows that all five objectives were agreed upon to be outlined in the iN-Hadis Module. In terms of prioritization, the highest-ranked element was “Enable students to apply the Arabic grammar method through the Syawahid Hadith 40 practically through online activities”, followed by “Increase student engagement through interactive modules based on multimedia principles” in second place, “Improve students’ digital skills by searching, evaluating, and utilizing the Gamma website related to learning Arabic grammar” in third place, “Explain the correct use of the basic content of Arabic grammar” in fourth place, and finally “Explain the continuity between the text of Hadith 40 and the application of Arabic grammar”. This aligns with Hussin et al. (2023), who highlighted that interactive websites such as Mysūr and mobile applications designed specifically for Arabic grammar learning significantly improve students’ language skills.

Similarly, the second component, module content, was also agreed upon by the experts, with 100% consensus on all items except for the fifth element. In terms of ranking, the element “discussion/exercise on the concept of al-Ism, al-Fi‘l and al-Harf” was placed first, followed by “division of al-Mansubaat with syawahid from Imam Nawawi’s 40 hadiths”, “discussion/exercise on i’rab al-Mansubaat” and “introduction and concept of al-Majrurat”, all in second place. The third-ranked elements included “definition of al-Ism, al-Fi‘l, and al-Harf”, “introduction and concept of al-Marfua‘at”, “division of al-Marfua’at with syawahid from Imam Nawawi’s 40 hadiths”, “discussion/exercise on i’rab al-Marfuaat”, “introduction and concept of al Mansubaat”, “division of al-Majruraat with syawahid from Imam Nawawi’s 40 hadiths”, “introduction and concept of I’rab” and “discussion/exercise on i’rab al-Majruraat”. In fourth place was “examples from Imam Nawawi’s 40 hadiths for al-Ism, al-Fi’l and al-Harf” and finally “division of i’rab lafziy and i’rab takdiriy”. The prioritization highlights the importance of understanding the fundamental concepts and divisions of kalām in Arabic. As noted by Genon-Sieras (2020), ism, fi‘l, and ḥarf are the primary categories in grammar that form the structure of sentences; without strong mastery, students will face difficulties in constructing correct sentences and grasping their intended meaning.

The third component, module design, consisted of twelve elements. All were accepted by the experts, with consensus levels ranging from 90% to 100%. Experts agreed that the module design must include features such as underlining key words as guidance for readers, enlarging the size of relevant graphics, using attractive colors, emphasizing visual content such as data, images, and words, keeping text concise, using clear icons and images, selecting legible text sizes and fonts, limiting the number of font types, and ensuring that interactive text colors are minimal but effective. They also emphasized the importance of accessible interactive websites across devices, user-friendly navigation with a search button for each title, appealing layouts, integration of YouTube videos as learning resources, interactive mind maps, learning chatbots (for quick Q&A), user-friendly search displays, clear topic division across web pages, and concise information per page. These features are consistent with the characteristics of effective interactive websites, as highlighted by More et al. (2024), who found that students using interactive websites achieved higher academic scores compared to those using traditional methods.

The fourth component, learning activities, included four elements, all of which reached expert consensus. The top-ranked activities were “Interactive quizzes such as Wordwall, Kahoot and Quizziz applications” and “Group activities produce interactive information using Canva”, followed by two other agreed-upon activities. The researcher applied all these elements in the development of the iN-Hadis Module according to expert prioritization. Pham (2023) noted that gamified quizzes make learning more enjoyable, increase motivation, and help students identify weaknesses quickly. Group learning, meanwhile, promotes interaction, discussion, and deeper understanding of concepts, where lower-performing students especially benefit when paired with high-achieving peers (Haataja et al., 2022). Thus, the use of gamified quizzes and group discussions in virtual settings serves as an effective medium in the iN-Hadis Module, enabling students to engage interactively and meaningfully in Arabic grammar learning.

The fifth component, evaluation, consisted of four proposed elements, all of which fulfilled the conditions for expert consensus. In terms of ranking, “Oral Test” and “Written Assignment” were placed first, followed by “Video Assignment” and “Online Objective Test”. Based on this consensus, the primary instrument agreed upon by experts for assessing the effectiveness of the module was the oral test. According to Delson et al. (2024), oral assessments as an early intervention can boost confidence and performance among weaker students. Likewise, written assignments provide opportunities for self-expression, creativity, and enhanced interest in learning (Mayo & Wheaton, 2024).

In summary, the development of the Interactive Arabic Grammar Website Module (iN-Hadis) has demonstrated positive potential in supporting 21st-century, technology-enhanced Arabic grammar teaching and learning. The module not only provides an interactive and user-friendly learning resource but also supports self-directed learning that can strengthen students’ foundational understanding of Arabic grammar. Moreover, it assists learners in comprehending Arabic sentence structures more clearly through digital activities and interactive exercises. The use of the Fuzzy Delphi Method in the design phase ensured that the module was developed based on expert consensus, guided by systematic development procedures, and academically validated, thereby guaranteeing its quality and effectiveness as a learning module.

CONCLUSION

Based on the analysis of the findings, a module entitled the Interactive Nahu Hadis Module (iN-Hadis) will be developed, incorporating the elements agreed upon by experts through the Fuzzy Delphi Method. The development of this web-based module is divided into five main components: objectives, content, design, learning activities, and evaluation. The findings indicate that expert feedback on the main components was at a strong level, with consensus percentages ranging from 90% to 100%. Furthermore, all elements were accepted by the panel of experts. In conclusion, all the information obtained through the Fuzzy Delphi study, including the suggested improvements, was carefully considered in order to develop an effective learning module aimed at strengthening Arabic grammar learning through technology-based approaches.

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