Integrating AI to Foster Culturally-Oriented Approaches in Design Education: Enhancing Final Assessments for Design Students in Malaysia

Integrating AI to Foster Culturally-Oriented Approaches in Design Education: Enhancing Final Assessments for Design Students in Malaysia

Khairun Nisa Mustaffa Halabi¹, Shahrul Anuwar Mohamed Yusof², Mustaffa Halabi Azahari³, Mohamed Azam Abdullah⁴

^1,4Faculty of Creative Industries, City University, Malaysia

²University Sultan Zainal Abidin (UniSZA), Terengganu, Malaysia

³City Graduate School, City University, Malaysia

DOI: https://dx.doi.org/10.47772/IJRISS.2025.908000583

Received: 14 August 2025; Accepted: 20 August 2025; Published: 22 September 2025

ABSTRACT

This research examine the integration of Artificial Intelligence (AI) in fostering culturally-oriented approaches in design education and enhancing final assessments for Design students in higher education in Malaysia. Through qualitative approach involving interviews and focus group discussions, this paper investigates the perceptions of Design students regarding AI’s role in creativity, cultural representation and its potential in the assessment process. The interviews highlighted varying degrees of trust in AI, with participants expressing both optimism about AI’s ability to expand creative possibilities and concerns about its limitations in understanding cultural nuances. The focus groups provided a platform for students to critically evaluate AI-generated and traditional artworks, leading to in-depth discussions on the authenticity and depth of cultural representation by AI. Additionally, participants explored the feasibility of incorporating AI into final assessments, recognizing its potential for consistency and efficiency but stressing the importance of maintaining human oversight, particularly in evaluating culturally sensitive designs. The findings suggest that while AI can enhance design education by offering new tools and perspectives, its integration must be carefully managed to ensure cultural authenticity and maintain the nuanced judgment that human evaluators provide. This research contributes to the ongoing discourse on the role of AI in creative industries, offering insights into how AI can be effectively leveraged in design education without compromising cultural integrity.

Keywords: AI Integration; Culturally-oriented design; Design education; Final assessment; Higher education; Malaysia

INTRODUCTION

The rapid advancement of Artificial Intelligence (AI) has revolutionized various fields, including design education, where it offers unprecedented opportunities to enhance the learning experience. This paper explores the integration of AI to foster culturally-oriented approaches in design education, specifically focusing on enhancing final assessments for design students in Malaysia. As design education increasingly embraces digital tools and methodologies, there is a critical need to balance technological innovation with cultural relevance, ensuring that students are not only proficient in the latest tools but also deeply connected to their cultural heritage [1]. ICT can revolutionize cultural heritage education by enhancing access, engagement, and preservation of cultural knowledge [1]. The potential of ICT tools to create interactive and immersive learning experiences, thereby fostering a deeper understanding and appreciation of cultural heritage among students [1], [2].

Malaysia, with its rich cultural diversity and heritage, presents a unique challenge and opportunity in this regard. The integration of AI in the educational framework can facilitate personalized learning experiences that respect and incorporate local cultural elements [3]. This research investigates how AI can be leveraged to create assessment frameworks that are both technologically advanced and culturally sensitive. The goal is to produce designers who are not only equipped with global competencies but also deeply rooted in Malaysian cultural values. For instance, Virtual Reality (VR) offers immersive learning environments that significantly enhance students’ engagement and retention of cultural heritage knowledge by providing experiential and interactive experiences that traditional methods cannot replicate [4]. AI plays a crucial role by offering transparent and understandable models that can adapt to the needs of non-technical users, including those with disabilities, thereby enhancing their ability to engage with and understand cultural heritage content [5]. Furthermore, it is important for the students aware the potential benefits of AI in preserving and promoting cultural heritage with the need to safeguard ethical considerations, such as data privacy, transparency, and the cultural sensitivity of AI applications [6].

Moreover, the study examines the role of AI in providing real-time, adaptive feedback during the assessment process, allowing for a more dynamic and interactive learning experience. By incorporating AI-driven analysis and feedback mechanisms, this study proposes a novel approach to final assessments that enhances creativity, critical thinking, and cultural awareness among design students. This approach also addresses the challenges of standardization and objectivity in assessments, ensuring that students’ work is evaluated not only on technical proficiency but also on their ability to integrate cultural insights into their designs. The findings of this research are expected to contribute significantly to the development of more holistic and inclusive design education practices. Ultimately, this study aims to prepare students for the dynamic demands of the global creative industry while preserving and celebrating the cultural richness of Malaysia, ensuring that future designers can navigate both the global and local dimensions of their craft.

To bridge the gap between research and practical application in design education, this study introduced an integrated approach by leveraging AI-generated final assessments aimed at enhancing students’ culturally-oriented learning in design education. The research focused on how AI can support students in incorporating cultural elements into their designs, ensuring that their work is both innovative and contextually relevant.

LITERATURE REVIEW

Artificial intelligence is being progressively incorporated into a wide range of fields, including higher education. Previous research has examined the implementation of AI in academic settings, highlighting its uses, associated challenges, and potential opportunities.

Factors affecting attitudes toward AI in higher education

Integrating AI into design education, particularly in fostering culturally-oriented approaches, offers significant potential for enhancing final assessments for design students in Malaysia. Attitude plays a crucial role in the adoption of any new technology or system. The impact of AI on education significantly influences students’ attitudes [7]. Additionally, successful implementation of new systems is often supported by advancements in technology and the necessary infrastructure and the perceived quality of facilities within an organization can also shape the behavioural intentions of its workforce [8].

Recent research highlights the benefits of AI in education, such as personalized learning and real-time feedback, which can be crucial for developing culturally sensitive and technically proficient designers. AI tools offer personalized feedback and insights, further refining their design thought process. Integrating AI in design education improves conventional teaching, promoting a more vibrant, interactive methodology. The experimental groups using the AI and LA integrated approach demonstrated higher levels of social and cognitive engagement. This was evidenced by more frequent and meaningful interactions among peers during collaborative tasks [9]. AI’s ability to analyse and adapt to individual learning styles can help tailor educational materials that incorporate local cultural elements, ensuring that students remain connected to their heritage while acquiring global competencies. For example, Jiao et al. (2022) established criteria for predicting and transforming learning data in an online engineering course. They utilized genetic programming, an evolutionary computation technique, to identify the most effective model for predicting student academic performance. In essence, selecting appropriate AI algorithms is a crucial factor in the development of these predictive models.

Moreover, AI’s role in assessment can go beyond traditional evaluation methods by providing a more holistic approach. AI-driven assessments can analyse creativity, cultural understanding, and technical skills, offering a comprehensive evaluation of a student’s abilities. This is particularly relevant in design education, where subjective and qualitative elements are critical. The use of AI can help standardize assessments while still allowing for cultural nuances, ensuring that students are evaluated fairly and thoroughly based on their integration of cultural insights into their designs.

Culturally-oriented design with AI

Culturally oriented approaches in design involve creating products, services, or experiences that are deeply rooted in and reflect the cultural context of a specific community or group [11]. This approach considers the unique values, traditions, symbols, and practices of a culture, ensuring that design solutions are not only functional and aesthetically pleasing but also culturally relevant and sensitive [12]. However, AI significantly influences culturally oriented approaches in design, particularly in the context of students’ final assessments in design programs. AI has the potential to enhance both the design process and the evaluation of culturally relevant work by offering tools that help students create and refine their projects with greater precision and cultural sensitivity [13].

In practice, culturally oriented design might involve using local materials, incorporating traditional craftsmanship techniques, or designing products that align with cultural rituals and social norms. For example, in graphic design, this approach might mean selecting colours, typography, and imagery that resonate with the cultural identity of the target audience. In product design, it might involve creating items that meet specific cultural needs or preferences, such as traditional clothing or culturally significant artifacts. The goal of culturally oriented design is to create meaningful and authentic connections with users by honouring and celebrating their cultural heritage [14]. This approach can enhance user engagement, foster a sense of identity, and ensure that designs are more inclusive and representative of diverse cultural perspectives.

By integrating cultural elements into the design process, designers can create solutions that are not only innovative but also respectful of and relevant to the cultural context in which they are used [15]. This is particularly important in today’s globalized world, where design needs to cater to a diverse range of users with varying cultural backgrounds. However, with AI, it can assist students in incorporating cultural elements into their designs by analysing vast datasets of cultural symbols, patterns, and practices. AI-driven tools can suggest culturally appropriate design elements, helping students ensure their work aligns with specific cultural contexts. For instance, AI can analyse and recommend colour palettes, motifs, and materials that resonate with a particular culture, thereby guiding students to create designs that are both innovative and culturally sensitive.

In the assessment phase, AI can be used to evaluate design projects based on cultural relevance and creativity. AI-driven assessment tools can objectively analyse how well students have integrated cultural elements into their designs, providing detailed feedback on areas of improvement. This can be particularly useful in design programs, where subjective biases can sometimes influence the evaluation process. By incorporating AI into assessments, educators can ensure that evaluations are fair, consistent, and focused on cultural sensitivity and innovation.

Benefits implementation AI in Design teaching

AI can significantly enhance the creative process by offering new tools for exploration and experimentation. It can generate design alternatives, suggest novel ideas, and help students push the boundaries of their creativity, leading to more innovative design solutions [16], [17]. AI can provide personalized learning experiences tailored to each student’s strengths, weaknesses, and cultural background. By adapting content and feedback to individual needs, AI can help students develop their design skills more effectively and with greater cultural sensitivity [17], [18].

The advancements in technology, such as artificial intelligence, robotics, the Internet of Things (IoT), and big data, are transforming various sectors, including education [19]. The need for educational institutions to adapt to these changes by incorporating digital literacy, critical thinking, and innovation into their curricula to prepare students for the demands of Industry 4.0 [19]. It also highlights the importance of lifelong learning and the development of new teaching methodologies that align with the technological advancements of the industrial revolution [20].

AI can streamline the assessment process by providing quick, consistent, and objective evaluations of student work. This is particularly beneficial in large classes where individualized feedback can be time-consuming. AI can also help identify areas where students need improvement, allowing for more targeted and effective instruction [21], [22]. AI can assist in maintaining cultural relevance in design by analyzing cultural data and suggesting design elements that align with specific cultural contexts. This can help students create more culturally sensitive and relevant designs, which is essential in a globalized design industry [23], [24].

Challenges AI in Design teaching perspectives

Ethical considerations are also paramount, as the integration of AI must be done with an awareness of potential biases and the need for inclusive education. Researchers emphasise the importance of developing ethical frameworks to guide AI’s implementation in education, ensuring that it enhances rather than hinders cultural diversity and equity. Overall, integrating AI into culturally-oriented design education in Malaysia can transform how final assessments are conducted, making them more dynamic, culturally relevant, and aligned with the needs of the global creative industry.

One of the significant challenges in integrating AI into design education is the potential for bias in AI algorithms. AI systems are often trained on data that may not fully represent diverse cultural perspectives, leading to designs that may unintentionally reflect or reinforce stereotypes. This can be particularly problematic in culturally-oriented design education, where sensitivity to cultural nuances is crucial [25], [26]. AI tools might lack the depth of cultural understanding required to support culturally-oriented design processes. While AI can assist in technical aspects of design, it may struggle to interpret and apply cultural symbols, practices, and values accurately, potentially leading to designs that are culturally insensitive or irrelevant [27]–[29].

Implementing AI in design education requires significant technical infrastructure, including advanced software, reliable internet access, and sufficient computational power [30]. Additionally, educators and students need to be trained to use these tools effectively, which can be a barrier in institutions with limited resources [31]. There may be resistance from both educators and students in adopting AI tools due to a fear of the unknown or a preference for traditional methods. This resistance can slow the adoption of AI in design education and limit its effectiveness [32], [33].

Conceptual framework

Figure 1. Conceptual framework

This study explores the integration of AI tools in fostering culturally-oriented approaches within design education, aiming to enhance students’ engagement, creativity, and understanding of cultural elements in their work. Data collection involved qualitative methods, including interviews and focus group discussions with design students from Malaysian universities, to assess their experiences with AI-supported design processes and its influence on culturally significant projects. Thematic analysis identified key themes such as perceptions of AI, collaborative processes, learning adaptation, ethical considerations, and evaluation methods. Findings highlight the potential of AI to support culturally relevant design practices, improve learning outcomes, and provide new approaches to assessment. Based on these insights, the study proposes a framework for integrating AI into design education, focusing on cultural authenticity, iterative feedback, and hybrid assessment models. This research contributes to a broader understanding of how AI can transform design education by creating a closed-loop system that continuously improves teaching, learning, and evaluation.

METHODS

The primary purpose of this research is to explore the integration of AI-generated final assessments with culturally-oriented approaches in design education. The study aims to determine how AI can be used to enhance students’ understanding and application of cultural elements in their design projects. Additionally, the research seeks to assess the impact of this integrated approach on student learning outcomes and to propose a framework for the future integration of AI models and learning analytics in design education. The ultimate goal is to establish a closed-loop system where AI continuously improves both the educational content and the assessment process in design programs.

RQ1: What are the implications of integrating AI models and learning analytics for the future of design education?

RQ2: What differences, if any, exist in the learning outcomes of students who utilize AI-supported assessments compared to those who do not?

RQ3: How does the integration of AI-generated final assessments influence students’ engagement with culturally-oriented design approaches?

Research context and participants

The research was conducted in the context of design education, specifically focusing on how AI-generated assessments can enhance culturally-oriented approaches in student learning. The study was situated within an online design course, which was selected to evaluate the effectiveness of integrating AI tools in a digital learning environment. The course was structured to provide students with the opportunity to engage in culturally relevant design projects, with AI tools being used to assist in both the creative process and the final assessment.

Participants in this study were students enrolled in the design programmes in Selangor area. The selection of participants was done through a face-to-face recruitment process, where students were informed about the study and invited to participate voluntarily. This face-to-face interaction ensured that students fully understood the purpose of the research, the role of AI in their learning experience, and the nature of their involvement in the study. The participants included a diverse group of students, reflecting various cultural backgrounds, which was particularly important for assessing the impact of AI on culturally-oriented design education. Through this approach, the study aimed to gather a representative sample of students who could provide insights into how AI affects their engagement with culturally relevant design practices and their overall learning outcomes in a digital educational setting.

Data collection and data analysis process

The study involved 67 participants who were selected from three different universities that offer Design programs. These universities were chosen for their diverse cultural representation and their strong emphasis on design education. The participants were recruited through face-to-face interactions, where the purpose of the study was explained, and their consent to participate was obtained. The participants included undergraduate and graduate students, providing a broad spectrum of perspectives on the use of AI in culturally-oriented design education.

The data analysis process involved qualitative methods to comprehensively assess the impact of AI on students’ learning outcomes. For the qualitative analysis process, a subset of participants was selected for in-depth interviews and focus group discussions [34]. These qualitative methods aimed to gather detailed feedback on the students’ experiences with AI tools, their perceptions of cultural relevance in their design work, and the challenges they faced in integrating AI into their creative processes. The qualitative data from interviews and focus groups were transcribed and analysed using thematic analysis [35]. This involved coding the data to identify common themes and patterns related to the use of AI in culturally-oriented design education, such as the perceived benefits, challenges, and areas for improvement. This qualitative approach allowed for a more nuanced interpretation of the data, combining statistical trends with personal experiences and insights from the participants.

Focus groups discussion

In this study, data was collected through focus group discussions involving design students from several universities in Malaysia. The participants were selected based on their enrolment in Design programs, ensuring they had foundational knowledge of both traditional and AI-based design methods. The focus groups were organized to observe and critically evaluate AI-generated artwork alongside traditional artwork. The purpose was to explore how AI can foster culturally-oriented approaches in design and how it might be utilised to enhance final assessments in design education.

Participants were first presented with a curated selection of both AI-generated and traditional artworks. The selection included designs that incorporated cultural elements relevant to Malaysian heritage, such as traditional motifs, colour palettes, and themes, as well as AI-generated interpretations of similar concepts. Students were asked to carefully observe each piece, taking note of how cultural elements were represented, the creativity involved, and the overall aesthetic quality.

Figure 2. Comparison of traditional and AI creative outputs during focus group discussions.

RESULTS

Integrating AI can close the loop between AI model development and its educational application, offering a promising direction for future research and practice in AI-enhanced education as concur with findings [9]. This integrated approach not only improves student performance but also fosters a more engaging and collaborative learning environment.

Table 1. Key Themes and Sub-Themes from Qualitative Data Collection.

This research identified five key themes that shape the integration of AI in design education and practice, each with distinct sub-themes. The first theme, perception of AI in design, includes sub-themes of creativity and autonomy and trust and reliability. The second theme, collaborative processes with AI, is divided into subthemes, integration in workflow and co-creative partnerships. Learning and adaptation, the third theme, covers subthemes, skill development and resistance to change, which explores reluctance in adopting AI due to comfort with traditional methods. The fourth theme, ethical considerations, features sub-themes of bias and cultural sensitivity and intellectual property. Finally, the fifth theme, evaluation and interpretation, includes subthemes criteria for assessing ai-generated content and audience engagement and reception, considering how audiences perceive and engage with AI-generated art. Together, these themes and sub-themes offer a comprehensive overview of the challenges and opportunities presented by AI in the design field. Table 1 illustrates the alignment between participant feedback and identified themes, showcasing a clear trend of cautious optimism regarding AI’s role in creative autonomy.

In this study, various AI platforms and applications were employed to facilitate both the design process and the final assessment of student projects within Malaysian design education programs. Among the most prominently used tools were DALL·E 2, Midjourney, and Adobe Firefly, all of which are generative AI platforms capable of producing visual outputs based on text prompts. These platforms allowed students to experiment with ideation, mood board creation, and preliminary visual exploration by generating culturally inspired imagery rooted in Malaysian motifs and design traditions. Additionally, tools such as ChatGPT and Notion AI were used to assist with conceptual development, content generation and reflective writing components, enhancing the research narrative and design rationale in students’ project reports. For assessment and feedback purposes, AI-based evaluation support tools such as GrammarlyGO, Canva Magic Write, and Jasper AI were also introduced to guide students in improving their documentation, layout presentation, and communication quality. These tools were not intended to replace educator judgment but were instead integrated to complement human feedback, offering real-time, formative insights. Importantly, the study ensured that all platforms used were accessible and user-friendly, requiring minimal technical onboarding so that students could focus on creativity and cultural interpretation rather than software mastery. The variety of tools enabled a comparative exploration of how AI can be meaningfully embedded in both the design creation and evaluation stages, especially in culturally nuanced contexts. The strategic use of these platforms also opened discussion around AI’s limitations particularly in areas such as cultural sensitivity, aesthetic authenticity, and intellectual ownership further enriching the qualitative findings of the study.

DISCUSSIONS AND IMPLICATIONS

The discussion of key themes in the research highlights various aspects of how AI is perceived, integrated, and evaluated within the design process, based on participant interviews. The theme of perception of ai in design focusses on the investigation of participants’ perspectives on the involvement of AI in creativity and its dependability in design processes. The responses from participants on the subtheme creativity and autonomy were conflicted; although some participants acknowledged AI’s ability to come out with ideas, but others questioned whether AI could develop in the sense that authentic creativity required human intuition and touch. As one participant suggested, AI has the potential to broaden creative opportunities, but it does not replace their creative autonomy. Within the Trust and reliability sub-theme, participants expressed concerns about depending on AI for complex assignments that demand significant contextual understanding. The participants frequently experienced the need to verify AI-generated material extensively, as well as indicating a cautious trust in AI as an assistant rather than an independent tool.

The second theme is collaborative processes with AI delves into the integration of AI technologies into the work processes of designers and the level to which AI is perceived as a collaborative contributor. The participants consistently stated that the integration of AI was more effortless than anticipated, while they still extensively depended on traditional methods for the final details. Their adaptation involved acquiring the skills to collaborate with the recommendations provided by AI, rather than regarding them as the final products. The participants also highlighted that while certain designers perceive AI as a productive contributor that enhances the ultimate design, however other participants expressed their doubts. They believe AI’s capacity to comprehend the cultural and emotional sensitivities required for authentically meaningful collaboration is limited, which restricts its potential as a creative partner.

The third theme highlights learning and adaptation where the participants addressed of how AI is affecting their ability to learn new skills and the difficulties they experience when adapting to new technology. Several participants stated that acquiring proficiency in AI tool usage enhanced their set of skills and strengthened their flexibility as designers. Nevertheless, some participants believed that depending on AI reduced their self-assurance in their skills, as they started to doubt their intuitive abilities. Resistance to change was apparent, as a few participants preferred conventional design approaches and perceived AI as a novelty rather than a vital instrument, highlighting the persistent conflict between innovation and existing practices.

The fourth theme emphasises on ethical considerations about the influence of AI on cultural sensitivity and intellectual property. The sub-theme of bias and cultural sensitivity highlighted issues that AI might perpetuate cultural biases or disregard cultural nuances, which led to the production of insensitive designs. The participants also expressed significant concerns in the ownership of designs produced by artificial intelligence. The complex legal and ethical landscape surrounding AI in design was reflected in the questions that arose regarding who owns the final product whether the AI, the designer, or the company that produced the AI.

Finally, the final theme is evaluation and interpretation highlight the significance of developing new frameworks to assess content generated by artificial intelligence and the ways on how consumers perceive the AI art. Participants emphasised that the current standards for evaluating AI-generated content are inadequate for assessing AI’s creative outputs. Participants suggested more specific guidelines must take into consideration to monitor the unique characteristics of AI-generated creative outputs. Moreover, this research also demonstrated that despite AI art generates fascination among audiences, there is still doubt regarding its worth in comparison to works generated by humans. The findings suggest that AI tools can serve as facilitators rather than replacements, augmenting the creative process by providing initial frameworks that require human refinement. This highlights the need to develop better engagement strategies that specifically address these concerns. Future integration strategies must prioritize AI training datasets enriched with diverse cultural elements to mitigate biases and enhance relevance.

CONCLUSIONS

The findings from this research reveal a nuanced understanding of how AI is perceived and integrated into the design process, highlighting both the potential benefits and significant challenges that accompany its use. Perception of AI in Design indicates that while AI can generate ideas and assist in creative processes, it still falls short of achieving true creative autonomy. Designers trust AI for efficiency but remain cautious, particularly with complex tasks that require cultural sensitivity and deep contextual understanding. In the collaborative processes with AI, the integration of AI into existing workflows is generally smooth, though designers still rely on traditional methods for final refinement. The perception of AI as a co-creative partner varies, with some designers embracing its role in generating ideas, while others remain sceptical about AI’s ability to truly understand and contribute to the emotional and cultural dimensions of design.

The dual impact of AI on skill development. While some participants feel that AI has broadened their skill set and adaptability, others worry that over-reliance on AI could diminish their confidence and creative problem-solving abilities. This tension between innovation and traditional methods reflects a broader resistance to change among some designers. Moreover, ethical considerations emerge as a critical concern, particularly in terms of cultural sensitivity and intellectual property. The potential for AI to perpetuate biases and the uncertainty surrounding ownership of AI-generated designs highlight the need for clearer ethical guidelines and legal frameworks to navigate these issues. The evaluation and interpretation points to the necessity of developing new frameworks for assessing AI-generated content. Traditional metrics are often inadequate, and there is a need for criteria that reflect the unique nature of AI’s contributions to design. Audience engagement with AI art remains mixed, with fascination tempered by scepticism, underscoring the importance of better strategies for showcasing and evaluating AI-generated work.

Overall, these findings suggest that while AI holds significant promise for enhancing design processes, its integration must be approached with caution, mindful of the ethical, creative, and practical challenges it presents. The study concludes that while AI offers transformative potential in design education, its implementation must be underpinned by ethical guidelines that prioritize cultural sensitivity and inclusivity. Future research and development should focus on refining AI tools to better understand and respect cultural contexts, establishing clear intellectual property guidelines, and creating robust frameworks for evaluating AI-generated content. This will ensure that AI becomes a valuable, trusted partner in the creative industries, rather than a source of uncertainty or division.

LIMITATIONS AND SUGGESTIONS FOR FUTURE RESEARCH

One of the primary limitations of this research is its focus on a relatively small sample size, drawn from 67 participants across three universities. While this provided valuable insights, the findings may not be fully generalizable to a broader population of design students or professionals in different cultural contexts or educational settings. Additionally, the study’s reliance on self-reported data from surveys and interviews introduces potential biases, such as social desirability bias, where participants may respond in ways, they believe are expected rather than reflecting their true thoughts and behaviours. Furthermore, the research primarily explored the integration of AI in design education from the perspective of students, with limited input from educators and industry professionals who might offer different viewpoints on the challenges and benefits of AI adoption. Another limitation is the scope of AI tools examined in the study. The research focused on specific AI applications and may not have fully captured the rapidly evolving landscape of AI technologies in design. This narrow focus could limit the applicability of the findings to new or emerging AI tools that were not included in the study. Moreover, the study did not deeply explore the long-term impacts of AI on design education and practice, such as how continued AI integration might influence the development of design curricula or the future job market for designers.

Future research should consider expanding the sample size and including participants from a wider range of educational institutions and cultural backgrounds to enhance the generalizability of the findings. Including perspectives from educators, industry professionals, and a diverse student body would provide a more comprehensive understanding of the challenges and opportunities associated with AI in design education. To advance the scope and depth of future research in integrating Artificial Intelligence (AI) into culturally-oriented design education, it is crucial to broaden the range of study participants beyond students alone. While this study has provided meaningful insights from student perspectives particularly in how AI influences creativity, assessment, and cultural sensitivity. These insights represent only one dimension of the educational ecosystem. Including educators and industry professionals in subsequent research would offer a more comprehensive and triangulated understanding of how AI can be ethically, effectively, and sustainably embedded in design education.

Educators, as the architects of curriculum and assessment strategies, possess critical knowledge about pedagogical goals, teaching limitations, and student learning outcomes. Their experiences with implementing emerging technologies, including AI, can highlight both opportunities and practical constraints in the classroom. Moreover, educators are best positioned to comment on how AI tools align or misalign with culturally responsive teaching frameworks and institutional standards for academic integrity and creativity. Incorporating industry professionals into the research provides yet another layer of insight by bridging the gap between educational training and professional expectations. These practitioners can offer grounded perspectives on the relevance of AI-assisted design in real-world contexts, the skillsets currently valued in the design market, and the ethical challenges surrounding the use of generative AI in commercial or cultural projects. Their input would help validate whether the AI applications being explored in academic settings are adequately preparing students for the demands and nuances of the design industry.

By expanding future research to include these two additional groups, the findings would become more holistic and applicable, reflecting the collaborative nature of design education and practice. Such an inclusive approach would not only improve the generalizability of the results but also contribute to the development of balanced, ethically-informed, and culturally-sensitive AI frameworks in design pedagogy. Ultimately, this would foster a more informed and collaborative environment for integrating AI in creative education systems across diverse Malaysian institutions.

Additionally, longitudinal studies could be conducted to explore the long-term effects of AI integration on students’ learning outcomes and career trajectories in the design field. Research could also benefit from examining a broader array of AI tools, including emerging technologies that may offer new capabilities for design. Comparative studies that evaluate different AI tools and their effectiveness in various design contexts would provide valuable insights into best practices for integrating AI into design education. Furthermore, future studies should delve deeper into the ethical implications of AI in design, particularly regarding cultural sensitivity, intellectual property, and the potential for AI to influence creative autonomy. Developing frameworks for evaluating the artistic merit of AI-generated content and understanding audience reception of AI-created works would also be important areas for future exploration. By addressing these areas, future research can help shape the role of AI in design education, ensuring that it enhances creativity while maintaining cultural relevance and ethical integrity.

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