Keyword: Generation Z

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Behavioral Patterns of Arab Gen Z in Consuming AI-Assisted Media Content: A Mixed-Methods Investigation Integrating Uses and Gratifications and Interactive Theory
Educational Point, 3(1), 2026, e161, https://doi.org/10.71176/edup/18793
ABSTRACT: This study explores the behavior patterns of the Arab Generation Z in relation to consumption of artificial intelligence (AI) assisted media content on digital platforms based on the Uses and Gratifications Theory (UGT) and the Interactive Theory. With the advent of AI personalization and curation of the digital experience, it is now more than ever that the way the young audience perceives and engages with the algorithmically generated content is being questioned. The research uses a mixed-methods design whereby quantitative and qualitative methods are integrated to achieve the reliability of statistics and interpretations. The quantitative stage consisted of 428 Arab Gen Z surveyed on motivations, interactive behaviors and perceived gratifications using a five-point Likert scale and applied on an online questionnaire. To examine the perceptions, attitudes, and awareness of AI as a force of influencing digital content, the qualitative phase involved ten semi-structured interviews to understand the perspective of the participants. Also, the use of a content analysis of 25 posts about AI-assisted social media on the major platforms (Tik Tok, Instagram, and YouTube) was performed to find the visual or textual signs of AI integration, including synthetic voices or auto-generated captions. The results showed that 68 percent of the respondents were strongly interested in AI-suggested content and 72 percent said they received powerful informational and entertainment satisfaction. Nevertheless, the awareness of AI presence in media production manifested itself in only 61 percent. Qualitative data implied ambivalent views the fascination with the creative possibilities of AI combined with the fear of authenticity and manipulation of emotions. Its results confirm a Hybrid Model of Gratification, where intrinsic motivations (e.g., entertainment and self-expression) are interacting with algorithmic affordances (e.g., AI personalization), and it has a significant predictive value of engagement behaviors (r = .61, p <.001). Engagement (r = .46, p < .001) and authenticity attitudes (r =.38, p <.01) were moderately related to the AI awareness. This model is the major theoretical contribution of the study to the expansion of UGT in AI-mediated situations.