Digital Literacy and Deep Learning Teaching Materials for Strengthen Generation Z Nationalism in the Indonesia Malaysia Border Area

Digital Literacy and Deep Learning Teaching Materials for Strengthen Generation Z Nationalism in the Indonesia Malaysia Border Area | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Digital Literacy and Deep Learning Teaching Materials for Strengthen Generation Z Nationalism in the Indonesia Malaysia Border Area Syafrial Nur, Nawawi Nawawi, Moad Moad, Arif Januardi, Hadi Rianto This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8943017/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 16 You are reading this latest preprint version Abstract Youth in Indonesia–Malaysia border areas face cultural identity challenges due to exposure to Malaysian popular culture and weak nationalism. This study aims to strengthen Generation Z's national identity by developing digital teaching materials grounded in deep-learning pedagogy and local wisdom. A sequential exploratory mixed-method design was employed, starting with qualitative exploration through interviews and observations, followed by quantitative validation using Structural Equation Modeling–Partial Least Squares (SEM-PLS). A total of 90 students participated in the initial survey, and a limited trial with 30 students was conducted to assess pre- and post-intervention changes. Paired t-tests were used to evaluate the module's impact. Findings show that digital literacy mediates the influence of popular culture on nationalist attitudes, and the module significantly improved students' understanding and pride in national identity. Contributions of this study include: ( 1 ) proposing an innovative educational intervention that integrates deep-learning pedagogy with digital literacy; ( 2 ) validating a conceptual model that links popular culture, digital literacy, and nationalism; and ( 3 ) providing empirical evidence that contextual, technology-based learning can effectively reinforce civic values in culturally vulnerable regions. digital teaching materials Deep learning nationalism Generation Z border areas Figures Figure 1 Figure 2 Figure 3 INTRODUCTION The Indonesia-Malaysia border region in West Kalimantan has unique socio-cultural dynamics, such as women's life in Jagoi Babang (Rupita, 2020), food insecurity in Entikong (Atem & Niko, 2020), and multicultural learning in Sajingan Besar (Wiyono et al., 2024), where the border area is mostly inhabited by multi-ethnic communities (Dayak, Malay, and Ethnic Chinese) and is a place for cross-border cultural encounters. This condition makes the young generation at the border vulnerable to being affected by the penetration of Malaysian culture. Initial observations at SMA Negeri 1 Sajingan Besar and SMK Negeri 1 Sajingan Besar adjacent to the Negeri Aruk Cross Border Post, showed that many students were more familiar with Malaysian popular culture than Indonesian national culture. Where students often use ringgit currency for daily transactions and prefer Dayak Iban songs from Malaysia rather than national or regional songs of Indonesia. This trend reflects a serious challenge to Generation Z's national identity at the border, as foreign popular culture is closely linked to their daily lives, and tends to divert interest to local educational content. Thus, Generation Z in the Indonesia-Malaysia border area faces serious challenges in building national identity due to the dominance of foreign popular culture and the weak integration of nationalistic values in learning. These preliminary findings are consistent with (Nguitragool, 2020)social media and popular culture that have a significant impact on the behavior of the younger generation. The weak spirit of nationalism among border youth is feared to threaten national integration in the long term. Meanwhile, it was also found that there was still a need to strengthen nationalism in the Entikong border area (Nur, 2020). Therefore,(Agus et al., 2021; Januardi et al., 2025) innovative and contextual educational interventions are needed to re-instill the values of nationalism in students in border areas. So far, learning methods using conventional learning in border schools are considered less effective in building the character of nationalism, especially for generation Z who were born and grew up in the digital era. This is because conventional learning methods that are still used in border schools are not able to answer the digital-native characteristics of this generation (Nawawi & Priyani, 2023; Pendidikan Sosiologi dan Humaniora et al., n.d.). Generation Z is more familiar with gadgets (Maryanto et al., 2020), the internet, and global popular culture, so the monotonous approach to learning is less appealing to them. The absence of this innovative approach reinforces the gap between students' digital potential and the ability to understand and internalize national values. Interactive(Widodo et al., 2020), contextual(Dewi et al., 2021), and technology-based learning innovations are needed, according to the character of the world. Meanwhile, various studies show that innovative learning models such as Creative Problem Solving (Astra et al., 2020), Project-Based Learning (Lobczowski et al., 2021; Musa et al., 2012; Sumarni & Kadarwati, 2020), and Joyful Learning (Prinotama et al., 2019; Priyani, 2021) are effective in increasing students' motivation, engagement, and positive character. However, the application of this model is still rarely studied in the specific context of border areas. Although various studies have discussed the influence of popular culture on the identity of the younger generation (Day & Sullivan, 2024), there has not been a citizenship learning approach that specifically responds to the social and digital complexities faced by Generation Z in border areas. A major problem in this context is the weak integration of nationalistic values in learning that is relevant to the digital reality of students in regions with strong foreign cultural influences. Conventional learning, which is still dominant, fails to bridge the cognitive and affective needs of the digital generation that is multitasking, visual, and globally connected. This creates a void in the process of internalizing national values, because students are unable to relate nationalism material to their real life experiences. Therefore, a digital learning model is needed that not only conveys national content conceptually, but also enables students' emotional and participatory engagement through in-depth and local context-based pedagogical strategies. This research offers a new approach in the form of the use of the integration of local wisdom of the people of Sambas Regency which refers to deep learning strategies and emphasizes more conceptual understanding, critical-reflective thinking, and material relationships with students' real lives and not on artificial intelligence algorithms. Meanwhile, in border schools, has never implemented a learning model that specifically combines deep learning approaches and local wisdom to form nationalism awareness conceptually, reflectively, and contextually through the use of digital teaching materials. Meanwhile, the digital teaching materials in this study are designed to be relevant to the daily lives of Generation Z at the border, utilizing interactive technology while incorporating local wisdom content (folklore (Fatimah et al., 2023), customs (Januardi & Superman, 2022), local figures, traditional woven cloth (Fatihah et al., 2024) ) so that the nationalism material is more contextual and interesting. This step is in line with the vision of Golden Indonesia 2045 (Puspa et al., 2023), to strengthen the ideology of Pancasila and the character of the nation through educational innovation. It is hoped that through interactive digital teaching materials that are close to reality, the young generation at the border can better understand the important role of maintaining the integrity of the Republic of Indonesia and increasing their pride as an Indonesian nation. Against this background, there is a real gap in the practice and literature of nationalism education in border areas, especially regarding contextual digital learning approaches for generation Z. Therefore, technology-based educational interventions are needed that not only convey nationalistic content, but also enable students' emotional and intellectual engagement through meaningful learning experiences. Where until now, there is no learning model that combines an in-depth learning approach and local wisdom content to strengthen the national identity of students living in areas with high exposure to foreign cultures, such as on the Indonesia-Malaysia border which is presented using digital media. So through this research, it is hoped that technology based learning can be contextualized with local cultural values that have an impact on increasing nationalism and love for the homeland so as to strengthen the awareness of generation Z as agents of change. This research aims to develop and test the effectiveness of deep learning based digital teaching materials that are contextual and integrated with local wisdom to strengthen the nationalism of Generation Z in the Indonesia-Malaysia border area. In particular, this study has three main objectives, namely: ( 1 ) analyzing the influence of Digital Teaching Materials (DTM), Popular Culture (PC), and Digital Literacy (DL) on Understanding Nationalism (UN) and The Attitude of Love for the Fatherland (TALF) as the foundation for the formation of student nationalism; ( 2 ) examine the role of Understanding Nationalism (UN) and The Attitude of Love for the Fatherland (TALF) in forming The Role of Gen Z (GEN) as a representation of the national identity, attitude, and participation of the younger generation; and ( 3 ) develop, validate, and evaluate the initial practicality and effectiveness of deep learning-based digital teaching materials designed based on the findings of the SEM–PLS model to improve the understanding of nationalism, patriotism, and the role of Generation Z in border schools. Literature Review Various studies have discussed youth nationalism and educational innovation. Meanwhile, according to(Nasution & Hafizsutrisno, 2024) popular culture, it greatly influences the political attitude of youth. noted that the national identity crisis in border areas can threaten long-term integration (Nur, 2020). highlighting the need to strengthen national identity in Entikong. Meanwhile, learning models that integrate local wisdom are known to be able to strengthen civic identity (Fatihah et al., 2024; Soviana et al., 2025). 2.1. Digital Teaching Materials The use of digital teaching materials in education is increasingly crucial, especially in conveying national values to Generation Z who are familiar with technology. Digital media-based learning has been proven to increase the effectiveness of value transfer and motivate students to understand the content (Bond et al., 2018; Eva et al., 2020). The digital library system has also been used as a means of self-development for Generation Z students who are very responsive to online content (Grigoryev et al., 2019). In the context of foreign language learning, digital technology shows its effectiveness in bringing teachers and Generation Z students closer together (Remizantseva & Ablyazov, 2019). In addition, the use of digital literacy has proven to be important in filtering information and supporting value-based learning (Shinta et al., 2024). This reinforces the importance of developing digital teaching materials that are contextual with national values. 2.2. Deep Learning Pedagogy The deep learning Pedagogy approach in education refers not only to artificial intelligence technologies, but also to deep learning that shapes students' conceptual and reflective understanding. Deep learning pedagogy based learning is closely related to meaningful learning (Barron & Hammond, 2008), which is when students associate new information with the knowledge they already have, thereby creating meaningful and sustainable understanding. On the other hand, mindful learning emphasizes full awareness in the learning process which has been shown to increase students' attention, perseverance, and emotional control (Grigoryev et al., 2019). Meanwhile, joyful learning allows students to feel happy and enthusiastic in learning, which is especially important for Generation Z who tend to get bored quickly (Remizantseva & Ablyazov, 2019). All three approaches can be integrated in the development of interactive digital teaching materials that not only convey local wisdom content, but also foster deep students' emotional engagement (Pernantah et al., 2022). Thus, deep learning becomes an essential pedagogical framework in building nationalism that is not superficial, but firmly embedded through meaningful, conscious, and fun learning experiences. 2.3. Nationalism The decline in the spirit of nationalism among Generation Z is a serious challenge that must be addressed through contextual and digital approaches. The characteristics of Generation Z who are very open to global culture can cause the erosion of national identity if they are not equipped with strong national values (Adamentha Tarigan et al., 2022). The use of creative media such as historical memes has proven effective in fostering awareness of history and nationality. The cultivation of nationalism can also be strengthened through formal education based on Pancasila values and adaptive to the times (Cahya & Syafrizal, 2022). Other studies highlight that Generation Z still shows high patriotism, but with a limited understanding of national symbols and history (Suryani, 2025). Therefore, a digital and participatory approach is the main solution in reviving the spirit of nationalism. 2.4. Generation Z Generation Z is a digital native generation who grew up with the internet and technology, so they need an innovative and interactive learning approach. They show a multitasking character, are quick to adapt, but also have challenges such as declining interest in reading and critical comprehension (Aisyah, 2022; Andita, 2023). Challenges in Generation Z education encourage the development of teaching materials that are in accordance with visual and fast learning styles (Kahraman, 2020). On the other hand, they still show high potential in understanding nationalism if given an appropriate approach (Hinduan et al., 2020). Another study states that Gen Z characteristics such as quick thinking and a love of freedom need to be bridged by teachers who understand the dynamics of technology (Suntara et al., 2024). Education must be able to integrate with their digital lifestyle so that learning is more relevant and impactful. 2.5. Border Areas The border area is a strategic area but vulnerable in terms of nationalism, especially for the younger generation. Generation Z living in the Indonesia-Malaysia border area faces challenges such as foreign cultural influences, limited access to education, and lack of strengthening of national identity. The use of digital teaching materials can be a solution to expand access to national information and strengthen national ties. Studies on nationalism education in border regions highlight the importance of contextual and character-based approaches (Adamentha Tarigan et al., 2022). In addition, strengthening the local curriculum is also considered necessary to maintain the nation's identity in the midst of cultural heterogeneity. This challenge requires collaboration between educational institutions, the government, and border communities to create a young generation that loves the homeland. 2.6. Conceptual Framework The conceptual framework of the research can be seen in the image below. Assumptions The hypothesis of this research is; Digital Teaching Materials (DTM) has a positive effect on Understanding Nationalism (UN). Popular Culture (PC) has a positive influence on Understanding Nationalism (UN). Digital Literacy (DL) has a positive effect on Understanding Nationalism (UN). Popular Culture (PC) has a positive influence on The Attitude of Love for the Fatherland (TALF). Digital Literacy (DL) has a positive effect on The Attitude of Love for the Fatherland (TALF). Understanding Nationalism (UN) has a positive effect on The Attitude of Love for the Fatherland (TALF). Understanding Nationalism (UN) has a positive effect on The Role of Gen Z (GEN). The Attitude of Love for the Fatherland (TALF) has a positive effect on The Role of Gen Z (GEN). Methodology 3.1. Data Collection This study uses a mixed methods approach with a sequential exploratory design consisting of two main stages, namely qualitative exploration and quantitative validation. The qualitative stage is carried out to explore the phenomenon, needs, and socio-cultural context of Generation Z in border areas as the basis for the development of deep learning-based digital teaching materials, while the quantitative stage is used to test the effectiveness of the teaching materials developed. The research began with a literature review on nationalism, popular culture, digital literacy, and the characteristics of Generation Z, which then became the basis for the preparation of a conceptual framework covering popular culture variables, digital literacy, digital teaching materials, understanding of nationalism, attitudes of love for the homeland, and the role of Generation Z. The location of the research was determined purposively in schools around the Cross Border Post (PLBN) Aruk, Sambas Regency, West Kalimantan, which was chosen because of the intensity of exposure to popular culture and its distinctive social character as a border area. The research population includes all Generation Z students, teachers, and community leaders who play a role in the process of internalizing the values of nationalism and responding to foreign cultures in the Indonesia-Malaysia border area. The sample was determined using purposive sampling with inclusion criteria, namely; age 15–20 years, domiciled in the border area; and registered as a student at the school of the research location, while the exclusion criteria were based on the domicile of the respondent with communication barriers, cognitive impairments, or limited digital access which was subsequently excluded from the sample. The total quantitative sample consisted of 90 students who were distributed proportionally from three schools, namely; SMA Negeri 1 Galing, SMA Negeri 1 Sajingan Besar, and SMK Negeri 1 Sajingan Besar. Meanwhile, teachers and local leaders from these schools were involved as a source of qualitative data to enrich understanding of the social and educational context in the border area. All research activities have received respondent approval and are in accordance with research ethics. Meanwhile, in determining the school area, cluster sampling techniques are used to group research areas based on school clusters, considering the large area of Sambas Regency and various levels of exposure to popular culture. After the school cluster was selected, the selection of respondents was purposively carried out according to the research criteria. 3.2. Research Design The research procedure began with a qualitative stage through in-depth interviews and observations to identify issues of nationalism, popular culture use, and digital behavior of Generation Z. These findings were then used in the development of deep learning-based digital teaching materials. At the quantitative stage, the teaching materials that have been developed were tested for effectiveness through a trial on 30 students at SMA Negeri 1 Galing to assess the improvement of digital literacy and nationalism understanding in Generation Z in border areas. Data Analysis The data management in this study uses Structural Equation Modeling-Partial Least Squares (SEM-PLS) software to test the correlation between the research variables and prove the hypothesis proposed. The regression test was carried out to obtain valid data related to the questionnaire value indicators, using the Likert scale approach. This SEM model is designed to analyze the relationships between variables, where SEM is used to evaluate the relationship structure between the hypothesized independent and dependent variables. SEM allows researchers to test complex models involving many latent variables and causal relationships between them, taking into account measurement errors and construct validity simultaneously. 4.1. PLS-SEM in Analyzing the Strengthening of Generation Z Nationalism PLS-SEM is a variance-based statistical method used to analyze the relationships between latent constructs in complex research models, especially when the data is non-normal or the sample size is not very large. In the context of this study, PLS-SEM was used to test the relationship between Digital Teaching Materials (DTM), Popular Culture (PC), Digital Literacy (DL), Understanding Nationalism (UN), The Attitude of Love for the Fatherland (TALF), and The Role of Gen Z (GEN) as the main outcome variables. This approach is very much in line with the objectives of exploratory research and aims to develop a predictive model regarding the effectiveness of digital teaching materials based on local wisdom in strengthening the national identity of students in the Indonesia-Malaysia border area. In this study, PLS-SEM makes it easier for researchers to identify the main factors that contribute to the nationalism of the younger generation (Gen Z). The results of the analysis showed that Understanding Nationalism (UN) was the strongest predictor of The Role of Gen Z (GEN), followed by the influence of The Attitude of Love for the Fatherland (TALF). Meanwhile, Popular Culture (PC) and Digital Literacy (DL) play an important role in shaping students' perceptions of the effectiveness of contextual digital learning. These findings confirm that the integration of local culture and the relevance of context in digital materials have a significant impact on building the national identity of Generation Z. 4.2. Hypothesis Development This study uses a quantitative approach with data collection techniques through surveys. Model analysis was carried out using structural equation modeling based on partial least squares (PLS-SEM), in accordance with the research objectives that emphasized the exploration of factors that affect students' understanding and nationalism attitudes. The research instrument is in the form of a questionnaire that contains a number of indicators for each construct: Popular Culture (PC), Digital Teaching Materials (DTM), Digital Literacy (DL), Understanding Nationalism (UN), The Attitude of Love for the Fatherland (TALF), and The Role of Gen Z (GEN). The questionnaire was compiled based on theoretical concepts and relevant indicators, then distributed to students in schools within the Indonesia-Malaysia border zone. P;OIPOOOP Figure 2. The relationship between constructs The PLS-SEM analysis was carried out to test the relationship between constructs as shown in Fig. 2, which illustrates the path of influence ranging from Popular Culture (PC), Digital Teaching Materials (DTM), Digital Literacy (DL), to the formation of nationalistic attitudes. This model allows researchers to verify that the integration of popular culture, digital literacy and Digital Teaching Materials not only increases the understanding of nationalism, but also has a direct impact on the formation of the national identity of the younger generation RESULTS AND DISCUSSION 5.1. Research Results The outcomes of the SEM analysis can be illustrated through the following diagram: 5.2. Outer Model Outer models focus on the relationship between latent variables and indicators. Testing on the outer model aims to ensure that the instruments used to measure latent variables have good validity and reliability. There are three main types of testing in the outer model, namely Convergent Validity, Discriminant Validity, and Construct Reliability. a. Convergent Validity Convergent Validity has two value criteria that can be evaluated, namely using the loading factor value or the Average Variance Extracted (AVE) value. Convergent validity analysis is a test used to assess the validity of construct variables. 1) Value Loading Factor The output of the external loading estimation is measured from the correlation between the indicator score (instrument) and its construct (variable). An indicator is considered valid if it has a correlation value above 0.70 or 0.6 is considered sufficient. If there is an indicator that does not meet the requirements, it must be discarded. The results of the convergent validity test in this study are as follows: Table 1 Results of Outer Loading Convergen Validity (Clean Data Phase 2) Item Digital Literacy Digital Teaching Materials Popular Culture The Attitude of Love for the Fatherland The Role of Gen Z Understanding Nationalism Information DL1 0.887 Valid DL2 0.794 Valid DTM3 0.784 Valid DTM5 0.922 Valid GEN2 0.838 Valid GEN3 0.882 Valid GEN4 0.824 Valid PC2 0.878 Valid PC4 0.768 Valid PC5 0.766 Valid TALF2 0.675 Valid TALF3 0.811 Valid TALF4 0.836 Valid UN2 0.898 Valid UN3 0.679 Valid Table 1 indicates that the data for each construct variable has been validated. 5.3. Average Variance Extracted (AVE) Analysis The AVE test is used to determine whether the data from the construct equations are suitable. The results of the Average. Variance Extracted (AVE) test are presented in the following Table 2 . Table 2 AVE Test Variable Average variance extracted (AVE) Digital Literacy 0.708 Digital Teaching Materials 0.732 Popular Culture 0.649 The Attitude of Love _for the Fatherland 0.604 The Role of Gen Z 0.719 Understanding Nationalism 0.634 Table 2 shows that the AVE values are greater than 0.5, indicating that the data from the construct equations are appropriate and fit the model. 5.4. Composite Reliability Analysis Composite reliability analysis is used to determine whether the data are reliable. The results are shown in the following Table 3 . Table 3 Composite Reliability Test Variable Composite reliability Digital Literacy 0.829 Digital Teaching Materials 0.845 Popular Culture 0.847 The Attitude of Love _for the Fatherland 0.819 The Role of Gen Z 0.885 Understanding Nationalism 0.773 Table 3 indicates that the composite reliability values exceed 0.6, confirming that the data for each variable and equation are reliable. 5.5. Discriminant Validity Analysis In confirmatory factor analysis (CFA) or structural equation modeling (SEM), discriminant validity analysis assesses the extent to which the relationships within the construct equations meet the criteria for discriminant validity. The results of the Discriminant Validity analysis are presented in Table 4 . Table 4 Discriminant Validity Analysis Digital Literacy Digital Literacy Digital Teaching Materials Popular Culture The Attitude of Love for the Fatherland The Role of Gen Z Understanding Nationalism Digital Teaching Materials 0.532 Popular Culture 0.500 0.632 The Attitude of Love for the Fatherland 0.453 0.578 0.648 The Role of Gen Z 0.641 0.568 0.745 0.467 Understanding Nationalism 0.717 0.523 0.568 0.550 0.727 Based on Table 4 , it can be observed that the AVE values meet the assumptions for Discriminant Validity, as indicated by the values presented. 5.6. Test Model Fit The fit model test was carried out by involving the results of the Smart PLS output estimation compared to the criteria as in the following table 5. Tabel 5. Test Model Fit Model Fit Rule of Thumb Estimated Model Description SRMR Less than 0.10 0.136 FIT d_ULS > 0.05 2.203 FIT d_G > 0.05 0.546 FIT Chi-square χ² Statistics ≥ χ² table 288,129 ≥ 23,685 FIT NFI Close to Value 1 0.458 FIT GOF 0.1 (Small GOF), 0.25 (Moderate GOF), 0.36 (Strong GOF) 0.3898 FIT Q² Predictive Relevance Q² > 0 means it has predictive relevance; Q² 0 The Role of Gen Z 0.278 > 0 Understanding Nationalism 0.114 > 0 FIT 5.7. Inner Model The inner model in SEM PLS describes the relationships between latent variables and is evaluated to see the strength and significance of these relationships. The evaluation includes three main aspects; Significance of the relationship (Hypothesis testing), R Square and Effect Size. 5.7.1. Path Coefficient Testing (R Square) The R Square in PLS-SEM measures how well the latent independent variable in the model can explain the latent dependent variable. An R-value of 2 indicates the predictive power of the model as a whole. The value of R 2 ranges from 0 to 1, where a higher value indicates a better model at explaining the variable. The path coefficient testing results are (R Square) summarized in the following table 5. Table 6 R Square Test Dependent Variable R-square R-square adjusted The Attitude of Love _for the Fatherland 0.289 0.264 The Role of Gen Z 0.267 0.251 Understanding Nationalism 0.188 0.161 5.7.2. Hypothesis Testing Relationship significance tests in PLS-SEM were performed to determine whether relationships between latent variables in the model can be considered statistically significant. The results of the hypothesis testing are presented in the table below 7. Table 7 Hypothesis Testing Path T statistics P values Hypothesis Digital Literacy -> The Attitude of Love for the Fatherland 1.008 0.157 Unproven Digital Literacy -> Understanding Nationalism 2.307 0.011 Accepted Digital Teaching Materials -> The Attitude of Love for the Fatherland 1.639 0.051 Not Accepted Digital Teaching Materials -> Understanding Nationalism 0.304 0.380 Not Accepted Popular Culture -> The Attitude of Love for the Fatherland 3.810 0.000 Accepted Popular Culture -> Understanding Nationalism 2.043 0.021 Accepted The Attitude of Love for the Fatherland -> The Role of Gen Z 2.520 0.006 Accepted Understanding Nationalism -> The Role of Gen Z 4.861 0.000 Accepted The results of the analysis in Table 7 show that of the eight hypotheses tested, five hypotheses proved to be significant because they had a p< value of 0.05. First, Digital Literacy has a significant effect on Understanding Nationalism, which shows that the better the digital literacy of students, the higher their understanding of nationalism; This is in line with the findings that access to and ability to process digital information can strengthen national awareness. Second, Popular Culture has a significant influence on the Attitude of Love for the Fatherland, which indicates that popular culture can be a means of internalizing the value of love for the homeland when contextualized positively. Third, Popular Culture has also proven to be significant to Understanding Nationalism, indicating that exposure to popular culture can be an educational medium that helps Generation Z understand aspects of nationalism. Fourth, the Attitude of Love for the Fatherland has a significant effect on the Role of Gen Z, showing that a strong attitude of love for the homeland encourages an increase in the active role of Generation Z in maintaining national identity. Fifth, Understanding Nationalism has a significant effect on the Role of Gen Z, which means that the higher the student's understanding of nationalism, the greater their contribution as the next generation in maintaining national values. Meanwhile, the other three hypotheses were not proven because the p-value was above 0.05. First, Digital Literacy has no significant effect on the Attitude of Love for the Fatherland, which shows that digital skills do not necessarily form emotional or affective attitudes related to love for the homeland. Second, Digital Teaching Materials do not have a significant effect on the Attitude of Love for the Fatherland, which indicates that the digital teaching materials used have not been able to directly arouse or strengthen students' love for the homeland. Third, Digital Teaching Materials also do not have a significant effect on Understanding Nationalism, indicating that the digital modules developed may not be strong enough to convey the cognitive aspects of nationalism or are not fully integrated with the cultural context and needs of students in border areas. These findings provide an idea that culture-based variables (such as popular culture) and students' internal affective-cognitive aspects have a stronger influence than the digital material-based interventions used in this study. Table 7 Path coefficient Bootstrapping Indirect Effect Path Coefficients T statistics P values information Digital Literacy -> The Attitude of Love _for the Fatherland -> The Role of Gen Z 0.842 0.200 Unproven Digital Literacy -> Understanding Nationalism -> The Role of Gen Z 1.968 0.025 evident Digital Teaching Materials -> The Attitude of Love _for the Fatherland -> The Role of Gen Z 1.281 0.100 Unproven Digital Teaching Materials -> Understanding Nationalism -> The Role of Gen Z 0.291 0.386 Unproven Popular Culture -> The Attitude of Love _for the Fatherland -> The Role of Gen Z 1.739 0.041 evident Popular Culture -> Understanding Nationalism -> The Role of Gen Z 1.740 0.041 evident The results of the indirect effect analysis showed that of the six mediation pathways tested, there were three pathways that were proven to be significant. First, Digital Literacy → Understanding Nationalism → the Role of Gen Z proved significant, which shows that digital literacy is able to increase the role of Generation Z indirectly through increasing their understanding of nationalism. This means that the ability to access, process, and evaluate digital information helps students understand national issues more comprehensively, thereby encouraging them to play a more active role in maintaining national identity. Second, Popular Culture → The Attitude of Love for the Fatherland → Role of Gen Z have also proven to be significant, indicating that popular culture can influence the role of Generation Z through strengthening the attitude of love for the homeland. When elements of popular culture—such as music, movies, or social media—are positively contextualized, they are able to foster national pride that in turn encourages the active involvement of younger generations in national issues. Third, Popular Culture → Understanding Nationalism → Role of Gen Z is significant, which suggests that popular culture impacts not only affectively but also cognitively, as exposure to certain popular cultures can broaden students' understanding of nationalism values which ultimately increases their contribution as part of Generation Z. In contrast, the other three mediation pathways have not proven significant. The Digital Literacy → Attitude of Love for the Fatherland → Role of Gen Z path is insignificant, which shows that digital literacy does not necessarily affect the attitude of love for the homeland, so it is unable to have an indirect effect on the role of Generation Z. This indicates that technical ability in accessing digital information does not necessarily encourage emotional attitudes related to nationalism. The Digital Teaching Materials → Attitude of Love for the Fatherland → Role of Gen Z path is also insignificant, indicating that the digital teaching materials used are not strong enough to form students' affective attitudes so that they do not mediate their influence on the role of Generation Z. Similarly, Digital Teaching Materials → Understanding Nationalism → Role of Gen Z are not proven, This means that the digital modules developed have not had a significant impact on the understanding of nationalism which can contribute to increasing the role of the younger generation. These three insignificant pathways suggest that digital literacy and digital teaching materials, while important, have not exerted a strong indirect influence in the absence of a more inherent emotional or cultural context for students in border areas. Table 8 Effect size test results (f2) Digital Literacy Digital Literacy Digital Teaching Materials Popular Culture The Attitude of Love _for the Fatherland The Role of Gen Z Understanding Nationalism 0.012 0.068 Digital Teaching Materials 0.031 0.001 Popular Culture 0.142 0.051 The Attitude of Love _for the Fatherland 0.071 The Role of Gen Z Understanding Nationalism 0.191 The results of the effect size (f²) test showed that the influence of each variable in the model was in the small to medium category. The Digital Literacy variable has a small effect size on Attitude of Love for the Fatherland (0.012) and Understanding Nationalism (0.068), which means that its contribution to both variables is relatively weak. The Digital Teaching Materials also showed a very small effect size on the Attitude of Love for the Fatherland (0.031) and almost no effect on the Understanding Nationalism (0.001). On the other hand, Popular Culture had a stronger effect size than the previous two variables, namely 0.142 for Attitude of Love for the Fatherland (close to the medium category) and 0.051 for Understanding Nationalism (small category), thus showing that popular culture provides a more meaningful influence in shaping students' attitudes and understanding of nationalism. At the mediation level, the Attitude of Love for the Fatherland had an effect size of 0.071 on the Role of Gen Z (small category), while Understanding Nationalism had the largest influence in the model with a value of 0.191 on the Role of Gen Z (close to medium category), indicating that the understanding of nationalism was the strongest factor in encouraging the active role of Generation Z in border areas. 5.8 Limited Trial and Initial Effectiveness of the Module The validated digital module was implemented on a limited basis at SMA Negeri 1 Galing on 30 grade XI students, where students accessed the material through personal devices and school facilities. Before studying, students conduct a pre-test and fill out a questionnaire about nationalism. The average score of pre-test comprehension was 70.5 and the score of the attitude of love for the homeland was 3.80. After the learning process, students underwent a post-test with an average result of 80.3 and an attitude score of 4.20, showing a significant increase in understanding of 14% and an increase in love for the homeland by 0.4 points. Observation during learning demonstrates active student engagement, especially when discussing local issues, watching cultural videos, and completing reflective tasks. In addition, the results of the user questionnaire showed that 90% of students liked the presentation of the material in the module, 87% felt that the material was easier to understand, and 80% felt more proud to be part of Indonesia after taking the lesson. The teacher also gave a practicality score of 85%, assessing that this module helps teaching efficiency and increases students' active participation in discussions, in contrast to the lecture method that has been dominant. 5.9 Interpretation of Findings and Initial Implications In general, the findings of the first year of the study show that the digital teaching materials based on deep learning developed are not only applicable in terms of content and media, but are also practical and potentially effective in increasing student nationalism at the border. The high level of digital literacy of students can be used as a bridge to convey national values in a more contextual and interesting way. Although these results were obtained from a limited trial, the initial data provide a strong foundation for continuing larger-scale implementation in the second year of the study. The lessons learned from this phase also underscore the importance of providing technical guidance for teachers, adapting online-offline learning, and adapting content to the conditions of digital infrastructure in border areas. This research is the first step in developing a digital-based national learning model based on local context and character, as well as answering the challenges of Generation Z's nationalism in the global era. DISCUSSION 6.1. Development and Validation of Deep Learning-Based Digital Teaching Materials Based on the results of the initial exploration, interactive digital teaching materials were developed with the theme "Nationalism in Border Areas" for the PPKn class XI course. This digital teaching material is designed based on an immersive learning approach, which emphasizes conceptual understanding, critical reflection, and relationships with students' real lives. The digital teaching materials contain five main topics related to National Identity, Cultural Diversity, Border Figures, Challenges of the Republic of Indonesia, and the Role of Students. Each topic begins with a local narrative related to the culture of Antar Ajong in Sambas Regency, followed by nationality material, and ends with reflective activities such as writing a personal journal, group discussions, and vlog making projects with the theme of nationalism. 6.2. The Relationship of Module Components with Deep Learning Pedagogy The structure of the digital modules in this study is explicitly designed based on the principles of deep learning pedagogy which includes three main elements: conceptual, reflective, and experiential. At the conceptual stage, students are introduced to nationalism content through educational videos, historical narratives, and materials based on local wisdom that aim to build a deep understanding of national values. The reflective stage is carried out through activities such as personal journal writing, small group discussions, and open-ended questions that encourage students to relate the material to the social realities at the border. Meanwhile, the experiential stage is manifested in the form of project assignments such as the creation of vlogs themed on love for the homeland and exploration of local culture, which stimulates students' emotional and affective engagement in an authentic learning context. These three components are designed in sequence to facilitate a meaningful, comprehensive, and long-term impactful learning process. Visually, digital teaching materials are developed to be friendly to Generation Z, where the use of infographics, videos, local photos, and interactive quizzes is used. Local content such as the Dayak Gawai ceremony and the stories of border Dayak figures are also included as a form of integration of local wisdom values. Validation was carried out by two subject matter experts and two media experts with the results of 88% content validity and 90% media validity, which are in the "very valid" category. Minor revisions were made based on expert suggestions, such as color contrast adjustments, concept simplification, and the insertion of offline access features. 6.3. Limited Trial and Initial Effectiveness of the Module The validated digital module was implemented on a limited basis at SMA Negeri 1 Galing on 30 grade XI students, where students accessed the material through personal devices and school facilities. Before studying, students conduct a pre-test and fill out a questionnaire about nationalism. The average score of pre-test comprehension was 70.5 and the score of the attitude of love for the homeland was 3.80. After the learning process, students underwent a post-test with an average result increasing to 80.3 and an attitude score rising to 4.20, showing a significant increase in understanding by 14% and an increase in the attitude of love for the homeland by 0.4 points. Conclusion Based on the results of the quantitative analysis, it can be concluded that students in border areas still have a fairly good attitude of love for the homeland and an understanding of nationalism, although on the other hand the interest in foreign popular culture is also quite high and has the potential to affect their national identity. The level of digital literacy of students is relatively high with good consistency, but the use of digital teaching materials in the learning process is still low and not optimal, thus creating a gap between the abilities of students and the learning practices that take place. Generation Z's awareness of its role in maintaining nationalism also looks quite strong, although it still requires support from the school environment so that it can be realized in real action. Overall, these findings affirm the importance of developing contextual, participatory, and reflective learning, by integrating popular culture, the use of digital technology, and strengthening national values to strengthen students' identities in the midst of globalization. Limitations and recommendations This study has several limitations. The sample size was relatively small (90 students for the SEM-PLS analysis and 30 students for the limited trial and was drawn from only a few schools in one border area of Sambas Regency, which limits the generalizability of the findings to other border regions in Indonesia. The data were mainly based on self-reported questionnaires, which may be influenced by students’ perceptions and social desirability bias. In addition, the digital module was tested only in a short-term trial without a control group, so its long-term and comparative effectiveness cannot yet be confirmed. The cultural content was also adapted specifically to the Sambas context and may not represent other border regions. Therefore, future research should involve larger and more diverse samples, use experimental designs with control groups, conduct longitudinal evaluations, and further refine the digital materials to ensure broader applicability and impact. Declarations 9. Funding Declaration The author would like to express his deepest gratitude to the Directorate General of Research and Development, Ministry of Higher Education, Science, and Technology of the Republic of Indonesia, for the financial support provided through the contract Master Number: 132/C3/DT.05.00/PL/2025 which has enabled the successful implementation of this research and its publication in leading international journals. 10. Data availability The data supporting the findings of this study are available from the corresponding author. However, due to ethical and privacy considerations, the data are not publicly accessible. Researchers who have a legitimate interest may request access to the data by contacting the authors, and such requests will be considered in accordance with applicable research ethics and data protection guidelines. Ethics Approval This study was conducted in accordance with the ethical standards of educational research involving human participants. The research protocol was reviewed and approved by the Research Ethics Committee of Universitas PGRI Pontianak No. L135/136/LPPM/VII/2025. All procedures performed in this study complied with institutional and international ethical guidelines for research involving human subjects. Consent to Participate Informed consent to participate in this study was obtained from all participants and from the parents or legal guardians of the students prior to their involvement in the research. Participants and their guardians were informed about the purpose of the study, the research procedures, potential risks and benefits, and their right to withdraw from the study at any time without any consequences. Consent for Publication Informed consent for publication of anonymized data related to the participants was obtained from the participants and from the parents or legal guardians of the students. No personally identifiable information is disclosed in this article. Conflict of Interest The authors declare that they have no conflict of interest regarding the publication of this article. Clinical trial number Not applicable References Rupita R. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8943017","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":607850832,"identity":"10175aab-398e-4728-86f7-49568c414a8f","order_by":0,"name":"Syafrial Nur","email":"","orcid":"","institution":"UNIVERSITAS PGRI PONTIANAK","correspondingAuthor":false,"prefix":"","firstName":"Syafrial","middleName":"","lastName":"Nur","suffix":""},{"id":607850833,"identity":"9a56dea8-8420-4885-a235-1bf2a1033b48","order_by":1,"name":"Nawawi 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2","display":"","copyAsset":false,"role":"figure","size":178562,"visible":true,"origin":"","legend":"\u003cp\u003eThe relationship between constructs\u003c/p\u003e","description":"","filename":"Figure2.Therelationshipbetweenconstructs.png","url":"https://assets-eu.researchsquare.com/files/rs-8943017/v1/8e8a828f39a6a4fd66b2c109.png"},{"id":104893289,"identity":"aa576291-7338-4416-ad94-2c93f52a3b72","added_by":"auto","created_at":"2026-03-18 11:13:46","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":179850,"visible":true,"origin":"","legend":"\u003cp\u003eSEM-PLS Boostrapping Result\u003c/p\u003e","description":"","filename":"Figure3.SEMPLSBoostrappingResult.png","url":"https://assets-eu.researchsquare.com/files/rs-8943017/v1/5f834c5f89a919a4541657e0.png"},{"id":105752058,"identity":"1b6b022a-a2ae-44ed-a903-62e049a176f2","added_by":"auto","created_at":"2026-03-30 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encounters. This condition makes the young generation at the border vulnerable to being affected by the penetration of Malaysian culture. Initial observations at SMA Negeri 1 Sajingan Besar and SMK Negeri 1 Sajingan Besar adjacent to the Negeri Aruk Cross Border Post, showed that many students were more familiar with Malaysian popular culture than Indonesian national culture. Where students often use ringgit currency for daily transactions and prefer Dayak Iban songs from Malaysia rather than national or regional songs of Indonesia. This trend reflects a serious challenge to Generation Z's national identity at the border, as foreign popular culture is closely linked to their daily lives, and tends to divert interest to local educational content. Thus, Generation Z in the Indonesia-Malaysia border area faces serious challenges in building national identity due to the dominance of foreign popular culture and the weak integration of nationalistic values in learning. These preliminary findings are consistent with (Nguitragool, 2020)social media and popular culture that have a significant impact on the behavior of the younger generation. The weak spirit of nationalism among border youth is feared to threaten national integration in the long term. Meanwhile, it was also found that there was still a need to strengthen nationalism in the Entikong border area (Nur, 2020). Therefore,(Agus et al., 2021; Januardi et al., 2025) innovative and contextual educational interventions are needed to re-instill the values of nationalism in students in border areas.\u003c/p\u003e \u003cp\u003eSo far, learning methods using conventional learning in border schools are considered less effective in building the character of nationalism, especially for generation Z who were born and grew up in the digital era. This is because conventional learning methods that are still used in border schools are not able to answer the digital-native characteristics of this generation (Nawawi \u0026amp; Priyani, 2023; Pendidikan Sosiologi dan Humaniora et al., n.d.). Generation Z is more familiar with \u003cem\u003egadgets\u003c/em\u003e (Maryanto et al., 2020), the internet, and global popular culture, so the monotonous approach to learning is less appealing to them. The absence of this innovative approach reinforces the gap between students' digital potential and the ability to understand and internalize national values. Interactive(Widodo et al., 2020), contextual(Dewi et al., 2021), and technology-based learning innovations are needed, according to the character of the world. Meanwhile, various studies show that innovative learning models such as \u003cem\u003eCreative Problem Solving\u003c/em\u003e (Astra et al., 2020), \u003cem\u003eProject-Based Learning\u003c/em\u003e (Lobczowski et al., 2021; Musa et al., 2012; Sumarni \u0026amp; Kadarwati, 2020), and \u003cem\u003eJoyful Learning\u003c/em\u003e (Prinotama et al., 2019; Priyani, 2021) are effective in increasing students' motivation, engagement, and positive character. However, the application of this model is still rarely studied in the specific context of border areas.\u003c/p\u003e \u003cp\u003eAlthough various studies have discussed the influence of popular culture on the identity of the younger generation (Day \u0026amp; Sullivan, 2024), there has not been a citizenship learning approach that specifically responds to the social and digital complexities faced by Generation Z in border areas. A major problem in this context is the weak integration of nationalistic values in learning that is relevant to the digital reality of students in regions with strong foreign cultural influences. Conventional learning, which is still dominant, fails to bridge the cognitive and affective needs of the digital generation that is multitasking, visual, and globally connected. This creates a void in the process of internalizing national values, because students are unable to relate nationalism material to their real life experiences. Therefore, a digital learning model is needed that not only conveys national content conceptually, but also enables students' emotional and participatory engagement through in-depth and local context-based pedagogical strategies.\u003c/p\u003e \u003cp\u003eThis research offers a new approach in the form of the use of the integration of local wisdom of the people of Sambas Regency which refers to deep learning strategies and emphasizes more conceptual understanding, critical-reflective thinking, and material relationships with students' real lives and not on artificial intelligence algorithms. Meanwhile, in border schools, has never implemented a learning model that specifically combines \u003cem\u003edeep learning\u003c/em\u003e approaches and local wisdom to form nationalism awareness conceptually, reflectively, and contextually through the use of digital teaching materials. Meanwhile, the digital teaching materials in this study are designed to be relevant to the daily lives of Generation Z at the border, utilizing interactive technology while incorporating local wisdom content (folklore (Fatimah et al., 2023), customs (Januardi \u0026amp; Superman, 2022), local figures, traditional woven cloth (Fatihah et al., 2024) ) so that the nationalism material is more contextual and interesting. This step is in line with the vision of Golden Indonesia 2045 (Puspa et al., 2023), to strengthen the ideology of Pancasila and the character of the nation through educational innovation. It is hoped that through interactive digital teaching materials that are close to reality, the young generation at the border can better understand the important role of maintaining the integrity of the Republic of Indonesia and increasing their pride as an Indonesian nation.\u003c/p\u003e \u003cp\u003eAgainst this background, there is a real gap in the practice and literature of nationalism education in border areas, especially regarding contextual digital learning approaches for generation Z. Therefore, technology-based educational interventions are needed that not only convey nationalistic content, but also enable students' emotional and intellectual engagement through meaningful learning experiences. Where until now, there is no learning model that combines an in-depth learning approach and local wisdom content to strengthen the national identity of students living in areas with high exposure to foreign cultures, such as on the Indonesia-Malaysia border which is presented using digital media. So through this research, it is hoped that technology based learning can be contextualized with local cultural values that have an impact on increasing nationalism and love for the homeland so as to strengthen the awareness of generation Z as agents of change.\u003c/p\u003e \u003cp\u003eThis research aims to develop and test the effectiveness of deep learning based digital teaching materials that are contextual and integrated with local wisdom to strengthen the nationalism of Generation Z in the Indonesia-Malaysia border area. In particular, this study has three main objectives, namely: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) analyzing the influence of Digital Teaching Materials (DTM), Popular Culture (PC), and Digital Literacy (DL) on Understanding Nationalism (UN) and The Attitude of Love for the Fatherland (TALF) as the foundation for the formation of student nationalism; (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) examine the role of Understanding Nationalism (UN) and The Attitude of Love for the Fatherland (TALF) in forming The Role of Gen Z (GEN) as a representation of the national identity, attitude, and participation of the younger generation; and (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) develop, validate, and evaluate the initial practicality and effectiveness of deep learning-based digital teaching materials designed based on the findings of the SEM\u0026ndash;PLS model to improve the understanding of nationalism, patriotism, and the role of Generation Z in border schools.\u003c/p\u003e"},{"header":"Literature Review","content":"\u003cp\u003eVarious studies have discussed youth nationalism and educational innovation. Meanwhile, according to(Nasution \u0026amp; Hafizsutrisno, 2024) popular culture, it greatly influences the political attitude of youth. noted that the national identity crisis in border areas can threaten long-term integration (Nur, 2020). highlighting the need to strengthen national identity in Entikong. Meanwhile, learning models that integrate local wisdom are known to be able to strengthen civic identity (Fatihah et al., 2024; Soviana et al., 2025).\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Digital Teaching Materials\u003c/h2\u003e \u003cp\u003eThe use of digital teaching materials in education is increasingly crucial, especially in conveying national values to Generation Z who are familiar with technology. Digital media-based learning has been proven to increase the effectiveness of value transfer and motivate students to understand the content (Bond et al., 2018; Eva et al., 2020). The digital library system has also been used as a means of self-development for Generation Z students who are very responsive to online content (Grigoryev et al., 2019). In the context of foreign language learning, digital technology shows its effectiveness in bringing teachers and Generation Z students closer together (Remizantseva \u0026amp; Ablyazov, 2019). In addition, the use of digital literacy has proven to be important in filtering information and supporting value-based learning (Shinta et al., 2024). This reinforces the importance of developing digital teaching materials that are contextual with national values.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Deep Learning Pedagogy\u003c/h2\u003e \u003cp\u003eThe deep learning Pedagogy approach in education refers not only to artificial intelligence technologies, but also to deep learning that shapes students' conceptual and reflective understanding. Deep learning pedagogy based learning is closely related to meaningful learning (Barron \u0026amp; Hammond, 2008), which is when students associate new information with the knowledge they already have, thereby creating meaningful and sustainable understanding. On the other hand, mindful learning emphasizes full awareness in the learning process which has been shown to increase students' attention, perseverance, and emotional control (Grigoryev et al., 2019). Meanwhile, joyful learning allows students to feel happy and enthusiastic in learning, which is especially important for Generation Z who tend to get bored quickly (Remizantseva \u0026amp; Ablyazov, 2019). All three approaches can be integrated in the development of interactive digital teaching materials that not only convey local wisdom content, but also foster deep students' emotional engagement (Pernantah et al., 2022). Thus, deep learning becomes an essential pedagogical framework in building nationalism that is not superficial, but firmly embedded through meaningful, conscious, and fun learning experiences.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Nationalism\u003c/h2\u003e \u003cp\u003eThe decline in the spirit of nationalism among Generation Z is a serious challenge that must be addressed through contextual and digital approaches. The characteristics of Generation Z who are very open to global culture can cause the erosion of national identity if they are not equipped with strong national values (Adamentha Tarigan et al., 2022). The use of creative media such as historical memes has proven effective in fostering awareness of history and nationality. The cultivation of nationalism can also be strengthened through formal education based on Pancasila values and adaptive to the times (Cahya \u0026amp; Syafrizal, 2022). Other studies highlight that Generation Z still shows high patriotism, but with a limited understanding of national symbols and history (Suryani, 2025). Therefore, a digital and participatory approach is the main solution in reviving the spirit of nationalism.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Generation Z\u003c/h2\u003e \u003cp\u003eGeneration Z is a digital native generation who grew up with the internet and technology, so they need an innovative and interactive learning approach. They show a multitasking character, are quick to adapt, but also have challenges such as declining interest in reading and critical comprehension (Aisyah, 2022; Andita, 2023). Challenges in Generation Z education encourage the development of teaching materials that are in accordance with visual and fast learning styles (Kahraman, 2020). On the other hand, they still show high potential in understanding nationalism if given an appropriate approach (Hinduan et al., 2020). Another study states that Gen Z characteristics such as quick thinking and a love of freedom need to be bridged by teachers who understand the dynamics of technology (Suntara et al., 2024). Education must be able to integrate with their digital lifestyle so that learning is more relevant and impactful.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Border Areas\u003c/h2\u003e \u003cp\u003eThe border area is a strategic area but vulnerable in terms of nationalism, especially for the younger generation. Generation Z living in the Indonesia-Malaysia border area faces challenges such as foreign cultural influences, limited access to education, and lack of strengthening of national identity. The use of digital teaching materials can be a solution to expand access to national information and strengthen national ties. Studies on nationalism education in border regions highlight the importance of contextual and character-based approaches (Adamentha Tarigan et al., 2022). In addition, strengthening the local curriculum is also considered necessary to maintain the nation's identity in the midst of cultural heterogeneity. This challenge requires collaboration between educational institutions, the government, and border communities to create a young generation that loves the homeland.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Conceptual Framework\u003c/h2\u003e \u003cp\u003eThe conceptual framework of the research can be seen in the image below.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eAssumptions\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eThe hypothesis of this research is;\u003c/p\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eDigital Teaching Materials (DTM) has a positive effect on Understanding Nationalism (UN).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003ePopular Culture (PC) has a positive influence on Understanding Nationalism (UN).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eDigital Literacy (DL) has a positive effect on Understanding Nationalism (UN).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003ePopular Culture (PC) has a positive influence on The Attitude of Love for the Fatherland (TALF).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eDigital Literacy (DL) has a positive effect on The Attitude of Love for the Fatherland (TALF).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eUnderstanding Nationalism (UN) has a positive effect on The Attitude of Love for the Fatherland (TALF).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eUnderstanding Nationalism (UN) has a positive effect on The Role of Gen Z (GEN).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eThe Attitude of Love for the Fatherland (TALF) has a positive effect on The Role of Gen Z (GEN).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003c/ol\u003e \u003c/div\u003e "},{"header":"Methodology","content":"\n\u003ch3\u003e3.1. Data Collection\u003c/h3\u003e\n\u003cp\u003eThis study uses a \u003cem\u003emixed methods approach\u003c/em\u003e with a sequential exploratory design consisting of two main stages, namely qualitative exploration and quantitative validation. The qualitative stage is carried out to explore the phenomenon, needs, and socio-cultural context of Generation Z in border areas as the basis for the development of deep learning-based digital teaching materials, while the quantitative stage is used to test the effectiveness of the teaching materials developed. The research began with a literature review on nationalism, popular culture, digital literacy, and the characteristics of Generation Z, which then became the basis for the preparation of a conceptual framework covering popular culture variables, digital literacy, digital teaching materials, understanding of nationalism, attitudes of love for the homeland, and the role of Generation Z. The location of the research was determined purposively in schools around the Cross Border Post (PLBN) Aruk, Sambas Regency, West Kalimantan, which was chosen because of the intensity of exposure to popular culture and its distinctive social character as a border area.\u003c/p\u003e\u003cp\u003eThe research population includes all Generation Z students, teachers, and community leaders who play a role in the process of internalizing the values of nationalism and responding to foreign cultures in the Indonesia-Malaysia border area. The sample was determined using \u003cem\u003epurposive sampling\u003c/em\u003e with inclusion criteria, namely; age 15–20 years, domiciled in the border area; and registered as a student at the school of the research location, while the exclusion criteria were based on the domicile of the respondent with communication barriers, cognitive impairments, or limited digital access which was subsequently excluded from the sample. The total quantitative sample consisted of 90 students who were distributed proportionally from three schools, namely; SMA Negeri 1 Galing, SMA Negeri 1 Sajingan Besar, and SMK Negeri 1 Sajingan Besar. Meanwhile, teachers and local leaders from these schools were involved as a source of qualitative data to enrich understanding of the social and educational context in the border area. All research activities have received respondent approval and are in accordance with research ethics. Meanwhile, in determining the school area, \u003cem\u003ecluster sampling techniques are used\u003c/em\u003e to group research areas based on school clusters, considering the large area of Sambas Regency and various levels of exposure to popular culture. After the school cluster was selected, the selection of respondents was purposively carried out according to the research criteria.\u003c/p\u003e\u003ch2\u003e3.2. Research Design\u003c/h2\u003e\u003cp\u003eThe research procedure began with a qualitative stage through in-depth interviews and observations to identify issues of nationalism, popular culture use, and digital behavior of Generation Z. These findings were then used in the development of deep learning-based digital teaching materials. At the quantitative stage, the teaching materials that have been developed were tested for effectiveness through a trial on 30 students at SMA Negeri 1 Galing to assess the improvement of digital literacy and nationalism understanding in Generation Z in border areas.\u003c/p\u003e"},{"header":"Data Analysis","content":"\u003cp\u003eThe data management in this study uses \u003cem\u003eStructural Equation Modeling-Partial Least Squares\u003c/em\u003e (SEM-PLS) software to test the correlation between the research variables and prove the hypothesis proposed. The regression test was carried out to obtain valid data related to the questionnaire value indicators, using the Likert scale approach. This SEM model is designed to analyze the relationships between variables, where SEM is used to evaluate the relationship structure between the hypothesized independent and dependent variables. SEM allows researchers to test complex models involving many latent variables and causal relationships between them, taking into account measurement errors and construct validity simultaneously.\u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e4.1. PLS-SEM in Analyzing the Strengthening of Generation Z Nationalism\u003c/h2\u003e \u003cp\u003ePLS-SEM is a variance-based statistical method used to analyze the relationships between latent constructs in complex research models, especially when the data is non-normal or the sample size is not very large. In the context of this study, PLS-SEM was used to test the relationship between Digital Teaching Materials (DTM), Popular Culture (PC), Digital Literacy (DL), Understanding Nationalism (UN), The Attitude of Love for the Fatherland (TALF), and The Role of Gen Z (GEN) as the main outcome variables.\u003c/p\u003e \u003cp\u003eThis approach is very much in line with the objectives of exploratory research and aims to develop a predictive model regarding the effectiveness of digital teaching materials based on local wisdom in strengthening the national identity of students in the Indonesia-Malaysia border area. In this study, PLS-SEM makes it easier for researchers to identify the main factors that contribute to the nationalism of the younger generation (Gen Z). The results of the analysis showed that Understanding Nationalism (UN) was the strongest predictor of The Role of Gen Z (GEN), followed by the influence of The Attitude of Love for the Fatherland (TALF). Meanwhile, Popular Culture (PC) and Digital Literacy (DL) play an important role in shaping students' perceptions of the effectiveness of contextual digital learning. These findings confirm that the integration of local culture and the relevance of context in digital materials have a significant impact on building the national identity of Generation Z.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e4.2. Hypothesis Development\u003c/h2\u003e \u003cp\u003eThis study uses a quantitative approach with data collection techniques through surveys. Model analysis was carried out using structural equation modeling based on partial least squares (PLS-SEM), in accordance with the research objectives that emphasized the exploration of factors that affect students' understanding and nationalism attitudes.\u003c/p\u003e \u003cp\u003eThe research instrument is in the form of a questionnaire that contains a number of indicators for each construct: Popular Culture (PC), Digital Teaching Materials (DTM), Digital Literacy (DL), Understanding Nationalism (UN), The Attitude of Love for the Fatherland (TALF), and The Role of Gen Z (GEN). The questionnaire was compiled based on theoretical concepts and relevant indicators, then distributed to students in schools within the Indonesia-Malaysia border zone.\u003c/p\u003e \u003cp\u003e P;OIPOOOP\u003c/p\u003e \u003cp\u003eFigure 2. The relationship between constructs\u003c/p\u003e \u003cp\u003eThe PLS-SEM analysis was carried out to test the relationship between constructs as shown in Fig.\u0026nbsp;2, which illustrates the path of influence ranging from Popular Culture (PC), Digital Teaching Materials (DTM), Digital Literacy (DL), to the formation of nationalistic attitudes. This model allows researchers to verify that the integration of popular culture, digital literacy and Digital Teaching Materials not only increases the understanding of nationalism, but also has a direct impact on the formation of the national identity of the younger generation\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS AND DISCUSSION","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e5.1. Research Results\u003c/h2\u003e \u003cp\u003eThe outcomes of the SEM analysis can be illustrated through the following diagram:\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e5.2. Outer Model\u003c/h2\u003e \u003cp\u003eOuter models focus on the relationship between latent variables and indicators. Testing on the outer model aims to ensure that the instruments used to measure latent variables have good validity and reliability. There are three main types of testing in the outer model, namely Convergent Validity, Discriminant Validity, and Construct Reliability.\u003c/p\u003e \u003cp\u003ea. Convergent Validity\u003c/p\u003e \u003cp\u003eConvergent Validity has two value criteria that can be evaluated, namely using the loading factor value or the Average Variance Extracted (AVE) value. Convergent validity analysis is a test used to assess the validity of construct variables.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003e1) Value Loading Factor\u003c/h3\u003e\n\u003cp\u003eThe output of the external loading estimation is measured from the correlation between the indicator score (instrument) and its construct (variable). An indicator is considered valid if it has a correlation value above 0.70 or 0.6 is considered sufficient. If there is an indicator that does not meet the requirements, it must be discarded. The results of the convergent validity test in this study are as follows:\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of Outer Loading Convergen Validity (Clean Data Phase 2)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDigital Literacy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDigital Teaching Materials\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePopular Culture\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eThe Attitude of Love for the Fatherland\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eThe Role of Gen Z\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eUnderstanding Nationalism\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eInformation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDL1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.887\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eValid\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDL2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.794\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eValid\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDTM3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.784\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eValid\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDTM5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.922\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eValid\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGEN2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.838\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eValid\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGEN3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.882\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eValid\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGEN4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.824\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eValid\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePC2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.878\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eValid\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePC4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.768\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eValid\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePC5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.766\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eValid\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTALF2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.675\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eValid\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTALF3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.811\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eValid\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTALF4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.836\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eValid\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUN2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.898\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eValid\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUN3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.679\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eValid\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e indicates that the data for each construct variable has been validated.\u003c/p\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e5.3. Average Variance Extracted (AVE) Analysis\u003c/h2\u003e \u003cp\u003eThe AVE test is used to determine whether the data from the construct equations are suitable. The results of the Average. Variance Extracted (AVE) test are presented in the following Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAVE Test\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAverage variance extracted (AVE)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDigital Literacy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.708\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDigital Teaching Materials\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.732\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePopular Culture\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.649\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe Attitude of Love _for the Fatherland\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.604\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe Role of Gen Z\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.719\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnderstanding Nationalism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.634\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows that the AVE values are greater than 0.5, indicating that the data from the construct equations are appropriate and fit the model.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e5.4. Composite Reliability Analysis\u003c/h2\u003e \u003cp\u003eComposite reliability analysis is used to determine whether the data are reliable. The results are shown in the following Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComposite Reliability Test\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComposite reliability\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDigital Literacy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.829\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDigital Teaching Materials\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.845\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePopular Culture\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.847\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe Attitude of Love _for the Fatherland\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.819\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe Role of Gen Z\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.885\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnderstanding Nationalism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.773\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e indicates that the composite reliability values exceed 0.6, confirming that the data for\u003c/p\u003e \u003cp\u003eeach variable and equation are reliable.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e5.5. Discriminant Validity Analysis\u003c/h2\u003e \u003cp\u003eIn confirmatory factor analysis (CFA) or structural equation modeling (SEM), discriminant validity analysis assesses the extent to which the relationships within the construct equations meet the criteria for discriminant validity. The results of the Discriminant Validity analysis are presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDiscriminant Validity Analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDigital Literacy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDigital Literacy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDigital Teaching Materials\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePopular Culture\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eThe Attitude of Love for the Fatherland\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eThe Role of Gen Z\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eUnderstanding Nationalism\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDigital Teaching Materials\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.532\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePopular Culture\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.632\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe Attitude of Love for the Fatherland\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.453\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.578\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.648\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe Role of Gen Z\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.641\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.568\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.745\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.467\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnderstanding Nationalism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.717\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.523\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.568\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.550\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.727\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eBased on Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, it can be observed that the AVE values meet the assumptions for Discriminant\u003c/p\u003e \u003cp\u003eValidity, as indicated by the values presented.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e5.6. Test Model Fit\u003c/h2\u003e \u003cp\u003eThe fit model test was carried out by involving the results of the Smart PLS output estimation compared to the criteria as in the following table 5.\u003c/p\u003e \u003cp\u003eTabel 5. Test Model Fit\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel Fit\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRule of Thumb\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEstimated Model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDescription\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSRMR\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLess than 0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFIT\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ed_ULS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFIT\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ed_G\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.546\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFIT\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChi-square\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eχ\u0026sup2; Statistics\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026ge;\u003c/span\u003e\u0026thinsp;χ\u0026sup2; table\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e288,129\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026ge;\u003c/span\u003e\u0026thinsp;23,685\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFIT\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNFI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClose to Value 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.458\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFIT\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGOF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.1 (Small GOF), 0.25 (Moderate GOF), 0.36 (Strong GOF)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3898\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFIT\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ\u0026sup2; Predictive Relevance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQ\u0026sup2; \u0026gt; 0 means it has predictive relevance;\u003c/p\u003e \u003cp\u003eQ\u0026sup2; \u0026lt; 0 means it lacks predictive relevance. (0.03 \u0026ndash; Weak); (0.15 -Moderate); (0.35 \u0026ndash; Strong)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eQ\u0026sup2;predict\u003c/p\u003e \u003cp\u003eThe Attitude of Love _for the Fatherland\u003c/p\u003e \u003cp\u003e0.222\u0026thinsp;\u0026gt;\u0026thinsp;0\u003c/p\u003e \u003cp\u003eThe Role of Gen Z\u003c/p\u003e \u003cp\u003e0.278\u0026thinsp;\u0026gt;\u0026thinsp;0\u003c/p\u003e \u003cp\u003eUnderstanding Nationalism\u003c/p\u003e \u003cp\u003e0.114\u0026thinsp;\u0026gt;\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFIT\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e5.7. Inner Model\u003c/h2\u003e \u003cp\u003e \u003cem\u003eThe inner model in SEM PLS describes the relationships between latent variables and is evaluated to see the strength and significance of these relationships. The evaluation includes three main aspects; Significance of the relationship (Hypothesis testing), R Square and Effect Size.\u003c/em\u003e \u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003e5.7.1. Path Coefficient Testing (R Square)\u003c/h2\u003e \u003cp\u003e \u003cem\u003eThe R Square in PLS-SEM measures how well the latent independent variable in the model can explain the latent dependent variable. An R-value\u003c/em\u003e \u003csup\u003e \u003cem\u003eof 2\u003c/em\u003e \u003c/sup\u003e indicates the predictive power of the model as a whole. The value of R\u003csup\u003e2\u003c/sup\u003e ranges from 0 to 1, where a higher value indicates a better model at explaining the variable. The path coefficient testing results are \u003cem\u003e(R Square)\u003c/em\u003e summarized in the following table 5.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eR Square Test\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDependent Variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR-square\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eR-square adjusted\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe Attitude of Love _for the Fatherland\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.289\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.264\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe Role of Gen Z\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.267\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.251\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnderstanding Nationalism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.161\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section3\"\u003e \u003ch2\u003e5.7.2. Hypothesis Testing\u003c/h2\u003e \u003cp\u003e \u003cem\u003eRelationship significance tests in PLS-SEM were performed to determine whether relationships between latent variables in the model can be considered statistically significant.\u003c/em\u003e The results of the hypothesis testing are presented in the table below 7.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHypothesis Testing\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePath\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT statistics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP values\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHypothesis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDigital Literacy -\u0026gt; The Attitude of Love for the Fatherland\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUnproven\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDigital Literacy -\u0026gt; Understanding Nationalism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.307\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAccepted\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDigital Teaching Materials -\u0026gt; The Attitude of Love for the Fatherland\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.639\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNot Accepted\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDigital Teaching Materials -\u0026gt; Understanding Nationalism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.304\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.380\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNot Accepted\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePopular Culture -\u0026gt; The Attitude of Love for the Fatherland\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.810\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAccepted\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePopular Culture -\u0026gt; Understanding Nationalism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAccepted\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe Attitude of Love for the Fatherland -\u0026gt; The Role of Gen Z\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.520\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAccepted\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnderstanding Nationalism -\u0026gt; The Role of Gen Z\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.861\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAccepted\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe results of the analysis in Table \u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e show that of the eight hypotheses tested, five hypotheses proved to be significant because they had a p\u0026lt; value of 0.05. First, Digital Literacy has a significant effect on Understanding Nationalism, which shows that the better the digital literacy of students, the higher their understanding of nationalism; This is in line with the findings that access to and ability to process digital information can strengthen national awareness. Second, Popular Culture has a significant influence on the Attitude of Love for the Fatherland, which indicates that popular culture can be a means of internalizing the value of love for the homeland when contextualized positively. Third, Popular Culture has also proven to be significant to Understanding Nationalism, indicating that exposure to popular culture can be an educational medium that helps Generation Z understand aspects of nationalism. Fourth, the Attitude of Love for the Fatherland has a significant effect on the Role of Gen Z, showing that a strong attitude of love for the homeland encourages an increase in the active role of Generation Z in maintaining national identity. Fifth, Understanding Nationalism has a significant effect on the Role of Gen Z, which means that the higher the student's understanding of nationalism, the greater their contribution as the next generation in maintaining national values.\u003c/p\u003e \u003cp\u003eMeanwhile, the other three hypotheses were not proven because the p-value was above 0.05. First, Digital Literacy has no significant effect on the Attitude of Love for the Fatherland, which shows that digital skills do not necessarily form emotional or affective attitudes related to love for the homeland. Second, Digital Teaching Materials do not have a significant effect on the Attitude of Love for the Fatherland, which indicates that the digital teaching materials used have not been able to directly arouse or strengthen students' love for the homeland. Third, Digital Teaching Materials also do not have a significant effect on Understanding Nationalism, indicating that the digital modules developed may not be strong enough to convey the cognitive aspects of nationalism or are not fully integrated with the cultural context and needs of students in border areas. These findings provide an idea that culture-based variables (such as popular culture) and students' internal affective-cognitive aspects have a stronger influence than the digital material-based interventions used in this study.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePath coefficient Bootstrapping Indirect Effect\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePath Coefficients\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT statistics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP values\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003einformation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDigital Literacy -\u0026gt; The Attitude of Love _for the Fatherland -\u0026gt; The Role of Gen Z\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.842\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUnproven\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDigital Literacy -\u0026gt; Understanding Nationalism -\u0026gt; The Role of Gen Z\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.968\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eevident\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDigital Teaching Materials -\u0026gt; The Attitude of Love _for the Fatherland -\u0026gt; The Role of Gen Z\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.281\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUnproven\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDigital Teaching Materials -\u0026gt; Understanding Nationalism -\u0026gt; The Role of Gen Z\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.291\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.386\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUnproven\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePopular Culture -\u0026gt; The Attitude of Love _for the Fatherland -\u0026gt; The Role of Gen Z\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.739\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eevident\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePopular Culture -\u0026gt; Understanding Nationalism -\u0026gt; The Role of Gen Z\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.740\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eevident\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe results of the indirect effect analysis showed that of the six mediation pathways tested, there were three pathways that were proven to be significant. First, Digital Literacy \u0026rarr; Understanding Nationalism \u0026rarr; the Role of Gen Z proved significant, which shows that digital literacy is able to increase the role of Generation Z indirectly through increasing their understanding of nationalism. This means that the ability to access, process, and evaluate digital information helps students understand national issues more comprehensively, thereby encouraging them to play a more active role in maintaining national identity. Second, Popular Culture \u0026rarr; The Attitude of Love for the Fatherland \u0026rarr; Role of Gen Z have also proven to be significant, indicating that popular culture can influence the role of Generation Z through strengthening the attitude of love for the homeland. When elements of popular culture\u0026mdash;such as music, movies, or social media\u0026mdash;are positively contextualized, they are able to foster national pride that in turn encourages the active involvement of younger generations in national issues. Third, Popular Culture \u0026rarr; Understanding Nationalism \u0026rarr; Role of Gen Z is significant, which suggests that popular culture impacts not only affectively but also cognitively, as exposure to certain popular cultures can broaden students' understanding of nationalism values which ultimately increases their contribution as part of Generation Z.\u003c/p\u003e \u003cp\u003eIn contrast, the other three mediation pathways have not proven significant. The Digital Literacy \u0026rarr; Attitude of Love for the Fatherland \u0026rarr; Role of Gen Z path is insignificant, which shows that digital literacy does not necessarily affect the attitude of love for the homeland, so it is unable to have an indirect effect on the role of Generation Z. This indicates that technical ability in accessing digital information does not necessarily encourage emotional attitudes related to nationalism. The Digital Teaching Materials \u0026rarr; Attitude of Love for the Fatherland \u0026rarr; Role of Gen Z path is also insignificant, indicating that the digital teaching materials used are not strong enough to form students' affective attitudes so that they do not mediate their influence on the role of Generation Z. Similarly, Digital Teaching Materials \u0026rarr; Understanding Nationalism \u0026rarr; Role of Gen Z are not proven, This means that the digital modules developed have not had a significant impact on the understanding of nationalism which can contribute to increasing the role of the younger generation. These three insignificant pathways suggest that digital literacy and digital teaching materials, while important, have not exerted a strong indirect influence in the absence of a more inherent emotional or cultural context for students in border areas.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEffect size test results (f2)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDigital Literacy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDigital Literacy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDigital Teaching Materials\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePopular Culture\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eThe Attitude of Love _for the Fatherland\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eThe Role of Gen Z\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eUnderstanding Nationalism\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.068\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDigital Teaching Materials\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePopular Culture\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe Attitude of Love _for the Fatherland\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.071\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe Role of Gen Z\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnderstanding Nationalism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.191\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe results of the effect size (f\u0026sup2;) test showed that the influence of each variable in the model was in the small to medium category. The Digital Literacy variable has a small effect size on \u003cem\u003eAttitude of Love for the Fatherland\u003c/em\u003e (0.012) and Understanding Nationalism (0.068), which means that its contribution to both variables is relatively weak. \u003cem\u003eThe Digital Teaching Materials\u003c/em\u003e also showed a very small effect size on \u003cem\u003ethe Attitude of Love for the Fatherland\u003c/em\u003e (0.031) and almost no effect on the Understanding Nationalism (0.001). On the other hand, \u003cem\u003ePopular Culture\u003c/em\u003e had a stronger effect size than the previous two variables, namely 0.142 for Attitude of Love for the Fatherland (close to the medium category) and 0.051 for \u003cem\u003eUnderstanding Nationalism\u003c/em\u003e (small category), thus showing that popular culture provides a more meaningful influence in shaping students' attitudes and understanding of nationalism. At the mediation level, the Attitude of Love for the Fatherland had an effect size of 0.071 on \u003cem\u003ethe Role of Gen Z\u003c/em\u003e (small category), while Understanding Nationalism had the largest influence in the model with a value of 0.191 on the Role of Gen Z (close to medium category), indicating that the understanding of nationalism was the strongest factor in encouraging the active role of Generation Z in border areas.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec25\" class=\"Section2\"\u003e \u003ch2\u003e5.8 Limited Trial and Initial Effectiveness of the Module\u003c/h2\u003e \u003cp\u003eThe validated digital module was implemented on a limited basis at SMA Negeri 1 Galing on 30 grade XI students, where students accessed the material through personal devices and school facilities. Before studying, students conduct a pre-test and fill out a questionnaire about nationalism. The average score of pre-test comprehension was 70.5 and the score of the attitude of love for the homeland was 3.80. After the learning process, students underwent a post-test with an average result of 80.3 and an attitude score of 4.20, showing a significant increase in understanding of 14% and an increase in love for the homeland by 0.4 points.\u003c/p\u003e \u003cp\u003eObservation during learning demonstrates active student engagement, especially when discussing local issues, watching cultural videos, and completing reflective tasks. In addition, the results of the user questionnaire showed that 90% of students liked the presentation of the material in the module, 87% felt that the material was easier to understand, and 80% felt more proud to be part of Indonesia after taking the lesson. The teacher also gave a practicality score of 85%, assessing that this module helps teaching efficiency and increases students' active participation in discussions, in contrast to the lecture method that has been dominant.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section2\"\u003e \u003ch2\u003e5.9 Interpretation of Findings and Initial Implications\u003c/h2\u003e \u003cp\u003eIn general, the findings of the first year of the study show that the digital teaching materials based on deep learning developed are not only applicable in terms of content and media, but are also practical and potentially effective in increasing student nationalism at the border. The high level of digital literacy of students can be used as a bridge to convey national values in a more contextual and interesting way. Although these results were obtained from a limited trial, the initial data provide a strong foundation for continuing larger-scale implementation in the second year of the study. The lessons learned from this phase also underscore the importance of providing technical guidance for teachers, adapting online-offline learning, and adapting content to the conditions of digital infrastructure in border areas. This research is the first step in developing a digital-based national learning model based on local context and character, as well as answering the challenges of Generation Z's nationalism in the global era.\u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cdiv id=\"Sec28\" class=\"Section2\"\u003e \u003ch2\u003e6.1. Development and Validation of Deep Learning-Based Digital Teaching Materials\u003c/h2\u003e \u003cp\u003eBased on the results of the initial exploration, interactive digital teaching materials were developed with the theme \"Nationalism in Border Areas\" for the PPKn class XI course. This digital teaching material is designed based on an immersive learning approach, which emphasizes conceptual understanding, critical reflection, and relationships with students' real lives. The digital teaching materials contain five main topics related to National Identity, Cultural Diversity, Border Figures, Challenges of the Republic of Indonesia, and the Role of Students. Each topic begins with a local narrative related to the culture of Antar Ajong in Sambas Regency, followed by nationality material, and ends with reflective activities such as writing a personal journal, group discussions, and vlog making projects with the theme of nationalism.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec29\" class=\"Section2\"\u003e \u003ch2\u003e6.2. The Relationship of Module Components with Deep Learning Pedagogy\u003c/h2\u003e \u003cp\u003eThe structure of the digital modules in this study is explicitly designed based on the principles of \u003cem\u003edeep learning pedagogy\u003c/em\u003e which includes three main elements: conceptual, reflective, and experiential. At the conceptual stage, students are introduced to nationalism content through educational videos, historical narratives, and materials based on local wisdom that aim to build a deep understanding of national values. The reflective stage is carried out through activities such as personal journal writing, small group discussions, and open-ended questions that encourage students to relate the material to the social realities at the border. Meanwhile, the experiential stage is manifested in the form of project assignments such as the creation \u003cem\u003eof vlogs\u003c/em\u003e themed on love for the homeland and exploration of local culture, which stimulates students' emotional and affective engagement in an authentic learning context. These three components are designed in sequence to facilitate a meaningful, comprehensive, and long-term impactful learning process.\u003c/p\u003e \u003cp\u003eVisually, digital teaching materials are developed to be friendly to Generation Z, where the use of infographics, videos, local photos, and interactive quizzes is used. Local content such as the Dayak Gawai ceremony and the stories of border Dayak figures are also included as a form of integration of local wisdom values. Validation was carried out by two subject matter experts and two media experts with the results of 88% content validity and 90% media validity, which are in the \"very valid\" category. Minor revisions were made based on expert suggestions, such as color contrast adjustments, concept simplification, and the insertion of offline access features.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec30\" class=\"Section2\"\u003e \u003ch2\u003e6.3. Limited Trial and Initial Effectiveness of the Module\u003c/h2\u003e \u003cp\u003eThe validated digital module was implemented on a limited basis at SMA Negeri 1 Galing on 30 grade XI students, where students accessed the material through personal devices and school facilities. Before studying, students conduct \u003cem\u003ea pre-test\u003c/em\u003e and fill out a questionnaire about nationalism. The average score of pre-test comprehension was 70.5 and the score of the attitude of love for the homeland was 3.80. After the learning process, students underwent \u003cem\u003ea post-test\u003c/em\u003e with an average result increasing to 80.3 and an attitude score rising to 4.20, showing a significant increase in understanding by 14% and an increase in the attitude of love for the homeland by 0.4 points.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eBased on the results of the quantitative analysis, it can be concluded that students in border areas still have a fairly good attitude of love for the homeland and an understanding of nationalism, although on the other hand the interest in foreign popular culture is also quite high and has the potential to affect their national identity. The level of digital literacy of students is relatively high with good consistency, but the use of digital teaching materials in the learning process is still low and not optimal, thus creating a gap between the abilities of students and the learning practices that take place. Generation Z's awareness of its role in maintaining nationalism also looks quite strong, although it still requires support from the school environment so that it can be realized in real action. Overall, these findings affirm the importance of developing contextual, participatory, and reflective learning, by integrating popular culture, the use of digital technology, and strengthening national values to strengthen students' identities in the midst of globalization.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"Limitations and recommendations","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThis study has several limitations. The sample size was relatively small (90 students for the SEM-PLS analysis and 30 students for the limited trial and was drawn from only a few schools in one border area of Sambas Regency, which limits the generalizability of the findings to other border regions in Indonesia. The data were mainly based on self-reported questionnaires, which may be influenced by students\u0026rsquo; perceptions and social desirability bias. In addition, the digital module was tested only in a short-term trial without a control group, so its long-term and comparative effectiveness cannot yet be confirmed. The cultural content was also adapted specifically to the Sambas context and may not represent other border regions. Therefore, future research should involve larger and more diverse samples, use experimental designs with control groups, conduct longitudinal evaluations, and further refine the digital materials to ensure broader applicability and impact.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e9. Funding Declaration\u003c/p\u003e\n\u003cp\u003eThe author would like to express his deepest gratitude to the Directorate General of Research and Development, Ministry of Higher Education, Science, and Technology of the Republic of Indonesia, for the financial support provided through the contract Master Number: 132/C3/DT.05.00/PL/2025 which has enabled the successful implementation of this research and its publication in leading international journals.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;10. Data availability\u003c/p\u003e\n\u003cp\u003eThe data supporting the findings of this study are available from the corresponding author. However, due to ethical and privacy considerations, the data are not publicly accessible. Researchers who have a legitimate interest may request access to the data by contacting the authors, and such requests will be considered in accordance with applicable research ethics and data protection guidelines.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eEthics Approval\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThis study was conducted in accordance with the ethical standards of educational research involving human participants. The research protocol was reviewed and approved by the Research Ethics Committee of Universitas PGRI Pontianak No. L135/136/LPPM/VII/2025. All procedures performed in this study complied with institutional and international ethical guidelines for research involving human subjects.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003eConsent to Participate\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eInformed consent to participate in this study was obtained from all participants and from the parents or legal guardians of the students prior to their involvement in the research. Participants and their guardians were informed about the purpose of the study, the research procedures, potential risks and benefits, and their right to withdraw from the study at any time without any consequences.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003eConsent for Publication\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eInformed consent for publication of anonymized data related to the participants was obtained from the participants and from the parents or legal guardians of the students. No personally identifiable information is disclosed in this article.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003eConflict of Interest\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThe authors declare that they have no conflict of interest regarding the publication of this article.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003eClinical trial number\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRupita R. 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Penguatan Nasionalisme Generasi Z pada Era Disrupsi sebagai Upaya Peningkatan Nilai-Nilai Karakter Bangsa di SMA Negeri 1 Kelapa Kabupaten Bangka Barat, \u003cem\u003ePengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat\u003c/em\u003e, vol. 9, no. 1, pp. 74\u0026ndash;40, Jan. 2024, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.33084/pengabdianmu.v9i1.5792\u003c/span\u003e\u003cspan address=\"10.33084/pengabdianmu.v9i1.5792\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-education","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"diedu","sideBox":"Learn more about [Discover Education](https://www.springer.com/journal/44217)","snPcode":"44217","submissionUrl":"https://submission.nature.com/new-submission/44217/3","title":"Discover Education","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"digital teaching materials, Deep learning, nationalism, Generation Z, border areas","lastPublishedDoi":"10.21203/rs.3.rs-8943017/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8943017/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eYouth in Indonesia\u0026ndash;Malaysia border areas face cultural identity challenges due to exposure to Malaysian popular culture and weak nationalism. This study aims to strengthen Generation Z's national identity by developing digital teaching materials grounded in deep-learning pedagogy and local wisdom. A sequential exploratory mixed-method design was employed, starting with qualitative exploration through interviews and observations, followed by quantitative validation using Structural Equation Modeling\u0026ndash;Partial Least Squares (SEM-PLS). A total of 90 students participated in the initial survey, and a limited trial with 30 students was conducted to assess pre- and post-intervention changes. Paired t-tests were used to evaluate the module's impact. Findings show that digital literacy mediates the influence of popular culture on nationalist attitudes, and the module significantly improved students' understanding and pride in national identity. Contributions of this study include: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) proposing an innovative educational intervention that integrates deep-learning pedagogy with digital literacy; (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) validating a conceptual model that links popular culture, digital literacy, and nationalism; and (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) providing empirical evidence that contextual, technology-based learning can effectively reinforce civic values in culturally vulnerable regions.\u003c/p\u003e","manuscriptTitle":"Digital Literacy and Deep Learning Teaching Materials for Strengthen Generation Z Nationalism in the Indonesia Malaysia Border Area","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-18 11:13:39","doi":"10.21203/rs.3.rs-8943017/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-04-13T03:48:35+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-03T12:41:12+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-30T01:30:05+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-29T00:28:52+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-23T23:03:34+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"50594218890440141957395920399781100415","date":"2026-03-23T22:27:48+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-23T03:46:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"191238779143133510692807070998384088352","date":"2026-03-22T15:18:46+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"12826896508473937377545557986444055887","date":"2026-03-19T13:16:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"333445749265009481104056817968324763349","date":"2026-03-19T11:59:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"289111540784665841007807399913977333962","date":"2026-03-17T21:03:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"8612813036430299901270275447253237338","date":"2026-03-17T15:43:45+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-17T11:03:24+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-06T09:56:35+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-04T22:12:23+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Education","date":"2026-03-04T15:02:52+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-education","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"diedu","sideBox":"Learn more about [Discover Education](https://www.springer.com/journal/44217)","snPcode":"44217","submissionUrl":"https://submission.nature.com/new-submission/44217/3","title":"Discover Education","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ec09b92a-fbfa-426a-bed0-c26164a492d3","owner":[],"postedDate":"March 18th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-18T11:13:39+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-18 11:13:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8943017","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8943017","identity":"rs-8943017","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}