Perceptions of generative AI among development communication students: insights by gender and age from the Philippines

Introduction

Generative artificial intelligence (GenAI) has rapidly emerged as a transformative force across global educational landscapes, revolutionizing methods of learning, teaching, and academic research. In the Philippines, development communication students are increasingly encountering these technologies, reshaping how information is created, disseminated, and perceived within educational contexts (Fabro et al., 2024; Vergara, 2024). This paradigm shift demands a deeper understanding of students’ perceptions of GenAI, particularly in the domain of development communication, where the intersection of technology, societal engagement, and information dissemination is critical. Recent studies highlight Filipino students’ neutral to positive attitudes toward AI integration in academic writing, paired with a growing usage of tools such as Grammarly and Quillbot (Fabro et al., 2024). However, challenges surrounding critical thinking skills and ethical considerations remain prominent, underscoring the need for balanced integration that supports authentic learning rather than hampers creativity (Fabro et al., 2024; Vergara, 2024).

An expansive body of literature converges on the role of demographic variables, especially gender and age, in shaping the perceptions and adoption behaviors associated with GenAI in education. International research consistently shows that male students tend to report greater perceived usefulness and confidence with GenAI tools than their female counterparts do, who may exhibit greater ethical concerns and anxiety toward these technologies (Kim et al., 2025; Prosen & Ličen, 2025). Likewise, age moderates interactions with GenAI, with younger learners demonstrating more familiarity and a stronger inclination toward innovative AI applications, whereas older students and faculty express caution rooted in concerns about overreliance and academic integrity risks (Tortella et al., 2025; Klar, 2025; Lyu et al., 2025). These gender- and age-based disparities yield critical implications for equitable AI literacy programs and necessitate institutional policies tailored to diverse user profiles, a concern emphasized in Filipino higher education studies (Fabro et al., 2024; Vergara, 2024).

Trust has emerged as a pivotal determinant of the adoption and meaningful use of GenAI across cultural contexts, particularly in regions such as the Philippines, where embedded sociocultural values shape technology acceptance (Zhang & Wang, 2025; Ashkanani, 2025). The interplay of perceived usefulness and trust informs students’ intentions to embrace GenAI tools, with institutional trust and collectivist orientations moderating these relationships in Chinese and Southeast Asian settings (Zhang & Wang, 2025). In the health communication domain, public confidence in AI-generated content depends heavily on transparency, accuracy validation, and ethical endorsements by professionals, reinforcing the universal need for trustworthy AI governance frameworks (Ashkanani, 2025; Barus et al., 2025). These insights bear crucial relevance for development communication students who navigate the ethical complexities of AI-mediated information dissemination in public spheres.

The educational affordances and challenges of GenAI span beyond mere adoption, embracing facets of creativity enhancement, personalized learning, and critical thinking development. Empirical findings from diverse contexts indicate that interaction with AI chatbots and feedback-generated tools can improve students’ creative problem-solving and writing skills when structured guidance and ethical use policies are in place (Song et al., 2025; Alsofyani & Barzanji, 2025; Klar, 2025). In contrast, unregulated or excessive dependence on AI risks attenuating critical faculties, promoting plagiarism, and creating ethical dilemmas, concerns voiced consistently by educators and regulatory bodies in the Philippines and beyond (Blomquist et al., 2025; Chan, 2025; Lund et al., 2025). Hence, balancing technological integration with pedagogical rigor remains a cornerstone for effectively leveraging GenAI in higher education.

The policy discourse surrounding generative AI integration at Philippine universities echoes global calls for comprehensive curricular reforms and governance mechanisms tailored to emergent AI challenges. National thought leadership advocates embedding AI literacy into higher education curricula to prepare students for AI-related professional futures, alongside initiatives promoting AI research and institutional guidelines to foster responsible AI engagement (Vergara, 2024). Institutional reports underline the variances in faculty and student readiness, necessitating targeted noncurricular interventions to build competencies and mitigate ethical pitfalls (Barus et al., 2025; Wardat & Akour, 2025). Such frameworks align with international scholarship emphasizing social reinforcement, trust calibration, and inclusive AI policy designs that accommodate diverse demographic needs (Lyu et al., 2025; Prosen & Ličen, 2025).

Development communication students, positioned at the nexus of technology, media, and societal interaction, present a compelling case for examining nuanced gender- and age-based perceptions of GenAI. Their critical engagement with AI-mediated content creation and dissemination not only reflects broader educational trends but also reveals unique challenges pertinent to communication ethics, misinformation management, and participatory knowledge building (Fabro et al., 2024; Ashkanani, 2025). This necessitates interdisciplinary inquiry that synthesizes insights from AI education, cognitive science, and social communication to inform pedagogical strategies fostering critical digital literacy and ethical AI use.

In summary, this study advances the discourse on generative AI’s transformative impact on Philippine development communication education by foregrounding gender and age-based perceptual variations. By integrating empirical findings from localized and international contexts, this study seeks to provide actionable insights for educators, policymakers, and developers to cultivate inclusive, ethical, and effective GenAI-enhanced learning environments that empower the next generation of communicators.

Research Questions

This study answered the following questions:

What is the level of perception among development communication students?

Does the level of perception among development communication students vary according to gender?

Does the level of perception among development communication students vary according to age?

Review of the Literature

Generative AI in Education and Communication Studies

Generative artificial intelligence (GenAI) has increasingly permeated educational and communication fields, fundamentally transforming how knowledge is created, disseminated, and consumed. Tools powered by large language models, such as ChatGPT, Gemini, and Claude, have introduced novel ways of supporting teaching and learning by enabling personalized, interactive, and adaptive learning environments (Dwivedi et al., 2023; Howell & Potgieter, 2023). These technologies allow students to engage in self-directed exploration, simulate real-world scenarios, and access immediate, context-specific guidance, thereby promoting critical thinking, creativity, and communication skills essential to the development of competent professionals. In communication-related disciplines, such as development communication, GenAI supports students in crafting compelling narratives, analyzing audience responses, and enhancing persuasive strategies, aligning with the evolving demands of digitally mediated environments (Marchena Sekli, Godo, & Véliz, 2025).

Despite its pedagogical promise, the integration of GenAI into education raises significant challenges that require careful governance and pedagogical adaptation. Studies highlight persistent concerns regarding academic dishonesty, originality, and ethical dilemmas emerging from AI-assisted content creation (Lund, Lee, Mannuru, & Arutla, 2025; Fabro, Rivera, & Sambrano, 2024). Additionally, critics warn of possible overreliance on AI, which could erode critical thinking skills and diminish students’ capacity for independent problem solving (Ashkanani, 2025). These issues are particularly salient in communication studies, where credibility, authorship, and ethical storytelling remain central to professional identity formation. As generative AI tools increasingly mediate knowledge production, educators are confronted with the challenge of balancing technological affordances with safeguards against academic misconduct and cognitive complacency, underscoring the need for responsible and intentional adoption strategies.

Within the context of the Philippines, recent research has demonstrated tempered enthusiasm among development communication students. While learners value GenAI’s capacity to streamline academic tasks, improve productivity, and facilitate multilingual writing, they also express apprehension regarding its ethical implications and potential influence on creativity and cognitive development (Vergara, 2024; Fabro et al., 2024). Educators emphasize the need to integrate AI literacy into curricula to prepare students for ethical decision-making in an AI-driven society while also advocating for institutional frameworks that promote trust, accountability, and equitable access (Barus et al., 2025; Lyu et al., 2025). Collectively, these findings position GenAI as both a transformative learning catalyst and a source of ethical and cognitive tension. The dual necessity of maximizing pedagogical benefits while addressing emerging challenges provides the foundation upon which the present study situates its exploration of development communication students’ perceptions of generative AI.

Students’ Perceptions and Attitudes toward Generative AI

Students’ perceptions of and attitudes toward GenAI reflect a complex interplay of optimism and caution shaped by technological affordances, ethical considerations, and contextual experiences. Empirical investigations across diverse contexts—including China, the United States, Saudi Arabia, Indonesia, and the Philippines—have consistently shown that students appreciate the convenience, efficiency, and academic value offered by GenAI tools (Golding et al., 2025; Zhang & Wang, 2025; Alsofyani & Barzanji, 2025). These technologies are widely perceived to enhance writing quality, assist with brainstorming, facilitate vocabulary acquisition, and streamline research processes, ultimately reducing cognitive load and academic stress (Martha, Widowati, & Rahayu, 2025; Fabro et al., 2024). For development communication students in particular, GenAI supports creativity in content design, audience targeting, and narrative development—skills essential in producing media outputs for advocacy, information dissemination, and social change.

However, this positive orientation is often tempered by significant apprehensions surrounding academic integrity, reliability, and originality. Concerns persist about misinformation, plagiarism, and dependency risks arising from uncritical reliance on GenAI (Chan, 2025; Lund et al., 2025). Trust in AI-generated content emerges as a decisive factor shaping students’ acceptance and responsible usage, depending heavily on perceptions of transparency, accuracy, and the presence of institutional safeguards (Ashkanani, 2025; Barus et al., 2025). Studies indicate that students tend to prefer GenAI outputs when validated by educational authorities or peer-reviewed mechanisms, signaling the importance of structured institutional policies in guiding responsible integration. Thus, perceptions are neither uniformly positive nor negative but instead reflect a spectrum of attitudes influenced by literacy levels, prior experience, and trust in governance frameworks.

Within the context of Philippine higher education, development communication students display readiness to use GenAI tools but express a strong preference for structured, pedagogically aligned guidance that integrates ethical considerations into practice (Vergara, 2024; Fabro et al., 2024). These findings highlight the need for targeted AI literacy initiatives designed to cultivate students’ critical evaluation skills while encouraging creativity and innovation. Furthermore, these attitudes underscore the importance of reconciling technological adoption with professional identity formation, particularly in communication disciplines where media ethics and information credibility are paramount. The present study builds on this body of work by analyzing students’ perceptions through the lenses of gender and age, offering insights into how diverse demographic profiles influence attitudes toward GenAI and its educational applications.

Differences in the effects of gender and age on perceptions of generative AI

Gender and age constitute significant demographic dimensions influencing students’ perceptions, attitudes, and behavioral engagement with GenAI. International research consistently reports gender-based differences in technology adoption, with male students tending to demonstrate greater technology self-efficacy, greater perceived usefulness, and more frequent usage of AI-powered tools (Kim et al., 2025; Prosen & Ličen, 2025). In contrast, female students often exhibit greater ethical awareness and heightened concern over issues such as plagiarism, misinformation, and academic integrity (Tortella et al., 2025). These patterns reflect broader sociocultural and psychological trends wherein gender roles and identity expectations shape engagement with emerging technologies. In communication-related fields, where ethical storytelling and responsible information dissemination are critical, such gendered differences acquire heightened relevance for understanding students’ attitudes toward GenAI.

Age similarly modulates perceptions, particularly through students’ levels of familiarity, adaptability, and confidence in navigating digital tools. Younger students, often categorized as digital natives, exhibit greater exploratory engagement with GenAI, demonstrating greater trust and openness toward its integration into academic workflows (Klar, 2025; Lyu et al., 2025). Conversely, older students and professionals tend to adopt more conservative stances rooted in caution, prioritizing skill preservation and avoiding overdependence on automated tools. Philippine-based studies mirror these trends, revealing greater GenAI awareness and usage among younger cohorts, alongside notable gender disparities in adoption linked to differing ethical priorities and academic motivations (Fabro et al., 2024; Vergara, 2024). In Southeast Asian settings, cultural orientations toward collectivism and institutional trust further mediate these dynamics, underscoring the need to consider contextual factors when interpreting students’ perceptions of AI (Zhang & Wang, 2025).

Additionally, trust emerges as a key mediating construct intersecting gender, age, and cultural context. Zhang and Wang (2025) noted that collectivist societal values influence the extent to which institutional trust mitigates perceived risk among students, with younger and male students displaying greater willingness to accept GenAI outputs when endorsed by credible authorities. For development communication students, whose academic and professional trajectories involve ethically charged engagement with media and public information, calibrated trust frameworks become essential for guiding responsible AI adoption (Barus et al., 2025; Ashkanani, 2025). Pedagogical strategies tailored to diverse cognitive, affective, and cultural profiles can enhance GenAI’s educational impact while minimizing inequities across demographic groups (Dwivedi et al., 2023; Song et al., 2025). By disaggregating perceptions according to gender and age, the present study fills a critical empirical gap in Philippine higher education, providing evidence-based insights to inform inclusive policies, AI literacy programs, and pedagogical innovations.

Methodology

Research Design

This study employed a quantitative cross-sectional research design to examine the perceptions of Development Communication students toward generative artificial intelligence (GenAI) and investigate potential differences across gender and age groups. A cross-sectional design is appropriate when collecting data from a specific population at a single point in time, enabling researchers to analyze trends, relationships, and group differences without manipulating variables (Creswell & Creswell, 2017; Fraenkel et al., 2006). Data were collected via an online survey administered through Google Forms, allowing efficient distribution, accessibility, and reach among the target respondents. The research focused on measuring perception levels, assessing demographic influences, and establishing patterns relevant to students’ engagement with GenAI, which is consistent with studies advocating cross-sectional approaches for understanding attitudes toward emerging technologies in education (Cohen et al., 2002).

Participants and Sampling

The participants were 208 Development Communication students enrolled in a state university in the Philippines during the second semester of the academic year 2024–2025. The respondents were selected via total enumeration sampling, as all the students enrolled in the program were invited to participate in the study to ensure comprehensive representation. Among the respondents, 68 (32.69%) were male, and 140 (67.31%) were female. In terms of age, 116 students (55.77%) were aged 17–19 years, whereas 92 students (44.23%) were aged 20–22 years. The inclusion criteria required participants to be officially enrolled in the development communication program and willing to provide informed consent before completing the online questionnaire. The demographic data provide a basis for comparing differences in perceptions between groups, aligning with recommendations for demographic stratification in educational research (Gay, Mills, & Airasian, 2019).

Research instrument and data collection

Data were gathered via a modified survey instrument adapted from Chan and Tsi (2024). The original instrument focused on their perceptions of GenAI in academic and professional contexts. The questionnaire consists of two sections: (1) demographic information, including gender and age, and (2) items measuring perceptions toward GenAI via a 5-point Likert scale ranging from 1 (Strongly Disagree) to 5 (Strongly Agree). The online survey link was disseminated via official student communication channels, and responses were collected over a three-week period. The use of a standardized, validated instrument strengthens the reliability of findings, whereas the cross-sectional framework provides a snapshot of students’ attitudes toward GenAI at a given time (Bryman, 2016; Creswell & Creswell, 2017).

Results and Discussion

Problem 1. What is the level of perception among Development Communication students?

Table 2 presents the level of perception of generative AI among development communication students based on their responses to eleven indicator statements. Overall, the composite mean score of 3.31 (SD = 0.65) indicates a neutral perception of generative AI technologies such as ChatGPT. This suggests that, on average, students neither strongly endorse nor reject the integration of AI into their academic practices, reflecting a balanced and cautious stance.

Among the indicators, several statements were rated positively, reflecting openness toward AI integration. The highest-rated item was “Teachers can already accurately identify a student’s usage of generative AI technologies to partially complete an assignment” (M = 3.63, SD = 0.82), interpreted as positive, suggesting that students acknowledge teachers’ growing awareness of AI-assisted work. Similarly, the students expressed positive perceptions of AI’s 24/7 availability as a learning tool (M = 3.46, SD = 0.97) and its potential to provide unique insights and perspectives (M = 3.42, SD = 1.00).

However, several items were interpreted as neutral, indicating hesitancy and uncertainty regarding AI’s broader educational implications. For example, students showed ambivalence toward statements about AI’s ability to improve academic performance (M = 3.25, SD = 0.93), enhance writing skills (M = 3.22, SD = 0.99), and offer coursework guidance comparable to that of human teachers (M = 3.39, SD = 0.93). Interestingly, the lowest-rated item was “AI technologies such as ChatGPT will replace teachers in the future” (M = 2.86, SD = 1.20), which suggests that most students are skeptical about AI fully replacing educators and still value human-led teaching.

The observed neutral perception toward generative AI (GenAI) technology among Development Communication students, with a composite mean score of 3.31 indicating neither strong endorsement nor rejection, is consistent with recent literature revealing ambivalence in student attitudes toward AI in academic settings. Fabro, Rivera, and Sambrano (2024) reported that Filipino students similarly hold a balanced stance, recognizing GenAI’s utility while simultaneously expressing caution about its limitations and ethical concerns. Students tend to acknowledge AI’s practical benefits, such as 24/7 availability and enhanced insights, as reflected in the current study’s positively rated indicators around teacher awareness of AI use, AI accessibility, and potential contributions to unique perspectives. This balanced perception parallels findings reported in other global contexts, including UK undergraduates, where scholars noted that students’ pragmatic acceptance was tempered by worries regarding misinformation and academic integrity (Chan & Zhou, 2023; Kelly, Delaney & Rogers, 2024).

Moreover, the neutrality regarding GenAI’s impact on academic performance, writing skill improvement, and parity with respect to human teachers found in this study echoes the global caution documented among students. Golding et al. (2025) and Zhang et al. (2025) highlighted how students appreciate AI as an adjunct tool but remain skeptical about its ability to replicate the depth of human teaching or fully enhance learning outcomes. The lowest-rated item—that AI will replace teachers—reflects widespread consensus endorsing the irreplaceable value of human guidance, as also observed by Vergara (2024) in Philippine educational reform discussions. This skepticism toward wholesale automation aligns with broader pedagogical caution emphasizing AI as a support rather than a substitute, underscoring emerging narratives on responsible AI adoption that preserve the centrality of educators and human-centered learning processes (Barus et al., 2025; Lyu et al., 2025). Such tempered attitudes may be crucial to preventing overreliance and promoting critical engagement, particularly within communication studies where human judgment and ethical considerations are paramount.

The implications of a neutral and cautiously optimistic outlook on GenAI for development communication education are significant. Students appear ready to integrate AI tools into their academic workflow, recognizing benefits without overestimating capabilities, which presents a strategic opportunity for curriculum designers to capitalize on enthusiasm while addressing reservations (Fabro et al., 2024; Vergara, 2024). Embedding formal AI literacy and ethics training can transform ambivalence into informed, responsible use. Institutional policies should proactively codify appropriate AI usage, emphasize critical evaluation of AI outputs, and support faculty development to guide students effectively (Barus et al., 2025; Kim et al., 2025). Such integrative approaches can ensure that AI technologies enhance rather than diminish the analytical, creative, and ethical competencies central to development communication disciplines (Song et al., 2025; Ashkanani, 2025). Ultimately, recognizing and responding to this nuanced student perception landscape will foster AI-enabled education that is equitable, trustworthy, and aligned with academic integrity.

Table 2. The level of perception among Development Communication students

Problem 2. Does the level of perception among development communication students vary according to gender?

An independent samples t-test was conducted to examine the difference in the level of perception of generative AI among development communication students when grouped according to gender. The results revealed a statistically significant difference in the level of perception of generative AI between male and female development communication students, t (206) = 8.94, p < .001, indicating that gender plays a meaningful role in shaping perceptions (see Table 3). Compared with their female counterparts, male students (M = 3.81, SD = 0.28) reported higher levels of perception (M = 3.07, SD = 0.65). The calculated Cohen’s d of 0.55 suggests a moderate effect size, meaning that gender accounts for a practically meaningful proportion of the variance in perception scores. These findings imply that male students demonstrate greater engagement, confidence, and receptiveness toward generative AI technologies than females do, who appear to express more caution or uncertainty regarding their academic applications.

These results are corroborated by a growing body of literature documenting gender disparities in the perception and adoption of generative AI technologies, particularly in educational settings. For example, Fusco et al. (2025) reported that women consistently report higher AI-related anxiety and lower perceived efficacy than men do, which correlates with lower usage rates and less favorable attitudes toward AI tools. This aligns with findings by Kim et al. (2025) and Tortella et al. (2025), who similarly noted that male students exhibit greater technological self-efficacy and more positive acceptance of AI-driven educational tools, whereas female students tend to emphasize ethical concerns, academic integrity, and potential risks associated with AI use. These trends have been observed across various cultural contexts, including Western, Asian, and Philippine educational environments (Fabro et al., 2024; Vergara, 2024). For example, Zhang and Wang’s (2025) research in China highlights how gendered socialization and cultural expectations shape differentiated trust and adoption patterns, a factor resonant with the Filipino context where gender is expressed in digital literacy and AI adoption.

The gender gap in perceptions is also attributable to differential exposure to technology and variations in familiarity with AI-assisted tools. Vo and Nguyen (2024) reported that familiarity breeds confidence and given that male students often have more access to or self-initiated exploration of AI technologies, they are inclined toward greater perceived academic utility of such tools in communication tasks. Conversely, female students’ wariness may stem from limited exposure coupled with heightened sensitivity to ethical and privacy issues, which is consistent with findings by Prosen and Ličen (2025). This finding points to a feedback loop where differential experiential engagement with GenAI reinforces gendered perceptions, potentially limiting equitable usage and benefits. The growing literature on AI gender disparities also shows that male students are more likely to use AI for cognitive tasks, while female students prioritize the social and ethical dimensions of technology use, adding complexity to the understanding of gendered AI perceptions (Gross, 2023; Chauhan et al., 2024).

In the specific context of development communication education, where students are expected to critically engage with media production, digital platforms, and ethical communication, these findings reinforce the urgency of designing inclusive and gender-sensitive AI literacy interventions. Integrating gender-aware instructional strategies could bridge the engagement gap by fostering balanced perceptions and improving AI self-efficacy among female students, thus eliminating barriers to effective GenAI adoption (Barus et al., 2025; Fabro et al., 2024). Institutional support, such as targeted workshops, mentorship programs, and curricular adaptations that explicitly address gendered experiences with AI, can empower underrepresented groups and create a more just technological learning environment (Lyu et al., 2025). Importantly, this approach not only facilitates equitable academic access but also prepares all students to responsibly leverage GenAI in professional communication contexts, where ethical dilemmas and societal impacts converge (Ashkanani, 2025; Vergara, 2024).

Table 3. Independent Samples t test on the difference in the level of perception among development communication students when grouped according to gender

Problem 3. Does the level of perception among development communication students vary according to age?

An independent samples t test was conducted to examine the difference in the level of perception of generative AI among development communication students when grouped according to age. The results revealed that the perceptions of students aged 17–19 years (M = 3.28, SD = 0.63) and those aged 20–22 years (M = 3.33, SD = 0.66) did not differ significantly, t (206) = -0.52, p = 0.61. The computed effect size, Cohen’s d = 0.65, indicates a moderate effect, yet the result was not statistically significant.

The finding that age does not significantly influence perceptions toward generative AI (GenAI) among development communication students aligns with a nuanced and sometimes mixed body of literature on the role of age in AI acceptance and usage within higher education. Some studies have suggested that younger students, often termed digital natives, express greater adaptability, greater ease of use, and greater perceived importance of GenAI tools in their academic success than older students do (Yoshida et al., 2024; Venkatesh et al., 2003). For example, Wong and Zhang (2024) highlighted that younger learners tend to integrate AI tools more readily into their learning activities, reflecting higher digital literacy cultivated through early and frequent technology exposure. Conversely, older students often report discomfort or reticence around new technologies, which is attributed to less familiarity and concerns with ethical use (Lund et al., 2025; Huang & Liao, 2015). However, the moderate, nonsignificant effect size in the current study suggests a levelling of perceptions among the age groups sampled, possibly due to shared academic environments and comparable exposure to AI tools in the Development Communication program (Fabro et al., 2024).

In support of this interpretation, cross-sectional analyses by Kelly et al. (2024) and Tsiani et al. (2025) indicate that perceptions and attitudes toward GenAI often do not exhibit age-related differences within student populations who engage in similar curricular and technological contexts. Their findings suggest that the cognitive and motivational factors influencing AI acceptance, such as perceived usefulness and trust, may transcend age boundaries in structured academic environments. Specifically, consistent exposure to AI-integrated pedagogy and peer usage appears to mediate potential age-related divides (Barus et al., 2025). This phenomenon aligns with Venkatesh and Morris’s (2000) technology acceptance framework, which points to external support mechanisms and social influence as moderators that can buffer age-based disparities in technology uptake. The current results corroborate these frameworks, emphasizing the potential for orchestrated exposure and curriculum design to homogenize perceptions across diverse age cohorts in communication studies.

Moreover, the implications of these findings for development communication education are multifaceted. Since students across age groups demonstrate similar levels of perception toward GenAI, educational interventions can adopt a more unified approach to AI literacy without excessive segmentation by age. This allows institutions to focus resources on creating comprehensive, inclusive AI literacy programs that address generic barriers such as ethical awareness, information literacy, and critical thinking with technology (Vergara, 2024; Barus et al., 2025). However, the moderate effect size indicates awareness of subtle variations that could surface in larger or more varied samples, underscoring the value of continuous assessment of AI perceptions as students progress through academic stages (Kim et al., 2025). The development of cross-age peer learning and mentorship initiatives could further synergize these perceptions, enhancing the collective capacity for responsible GenAI use in academic research and media production—a priority in communication disciplines characterized by rapid digital transformation (Fabro et al., 2024; Song et al., 2025).

Table 4. Independent samples t test on the difference in the level of perception among development communication students when grouped according to age

Conclusion

This study examined the perceptions of development communication students toward generative AI technologies, focusing on their overall attitudes and possible demographic variations. The findings reveal that students generally hold a neutral perception of generative AI, demonstrating a balanced view of its advantages and potential challenges. While students recognize AI’s ability to enhance writing, research, and access to information, they remain cautious about its ethical implications, reliability, and potential role in replacing traditional teaching practices.

The results also indicate that gender significantly influences students’ perceptions, with male students showing more favorable attitudes toward adopting generative AI than female students do, suggesting possible differences in digital confidence and familiarity. Conversely, age does not appear to affect perceptions, as younger and older students exhibit comparable attitudes toward the integration of AI in their learning experiences. These findings suggest that openness to AI is more strongly associated with technological self-efficacy than with generational differences.

In light of these findings, it is recommended that higher education institutions integrate AI literacy into academic programs, ensuring that students are equipped with the knowledge and critical skills necessary for responsible AI use. Gender-inclusive training initiatives should be prioritized to address differences in technological confidence and promote equitable access to AI-related opportunities. Furthermore, universities should develop clear guidelines and policies on the ethical and effective use of generative AI in learning and research, enabling students to maximize its benefits while maintaining academic integrity and fostering responsible digital citizenship.

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