Knowledge and Perception/Reception of AI Automation in Journalism Practice among Higher Education Student-Journalism  

This descriptive study examined knowledge and perceptions of AI automation in journalism among student-journalists at St. Rita’s College of Balingasag (N = 170). Using a validated researcher-administered questionnaire adapted from prior work, respondents who actively contribute to campus publications reported their primary media exposure, familiarity with AI technologies, and attitudes toward automation. Data were collected via online forms and summarized with frequencies, means, and standard deviations. Results show students are predominantly engaged with online platforms (118 of 170, 69.4%), with television (23.5%), print (5.3%) and radio (1.8%) trailing. Overall, AI knowledge was moderate but uncertain (overall mean = 2.24 on a 1–3 scale; “not sure”), while perceptions were similarly ambivalent (mean = 2.22). Students agreed most strongly that AI organizes data and speeds up production (item means = 2.49) and that AI creates demand for new technical skills (mean = 2.39), yet they remained unsure about AI’s reliability and its effects on journalistic quality and jobs. The findings indicate a gap between high digital exposure and limited institutional preparation: journalism programs should integrate targeted AI literacy, hands-on training in AI-assisted reporting, and ethics modules, alongside faculty upskilling and newsroom partnerships, to equip future journalists to use automation responsibly.

Keywords: Artificial intelligence; AI automation; Journalism education; AI literacy; Student journalists

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