From Classroom Design to Newsroom Practice: Assessment Intervention Designing GenAI

Synthesis: This paper presents a practice-based curriculum intervention that embeds generative AI (GenAI) into an undergraduate journalism Assessment item, framed by an ethical model integrating Colin Beard's experiential learning design with Bloom's revised taxonomy. GenAI promises efficiencies and new creative possibilities for students yet threatens academic integrity, authorship, and the core values of the profession. The triadic values–processes–competencies framework scaffolds students from human-only reporting to AI-integrated work and critical reflection, converting their intuitive concerns into explicit competencies in ethical decision-making, prompt engineering and verification. Qualitative data from a second-year journalism unit at an Australian global campus in Sarawak, Malaysia show students already use GenAI strategically but hold deep concerns about accuracy, originality and disclosure.

Key Findings

Ethical framework as a scaffold for GenAI integration: A triadic values–processes–competencies model — foregrounding the journalistic values of disclosure, independence, accuracy and integrity — provides an ethical grounding that moves students through Bloom's cognitive anchors (applying → analysing/evaluating → creating) within Beard's experiential learning cycle.
Purpose-built context enables meaningful use: Students framed AI as "best support system", "reflect better", "useful for ideas and structure" and "better accuracy," positioning themselves as active participants in the journalism assessment process; all nine participants agreed AI tools were useful in completing their assessment.
Confidence vs. depth of ethical understanding: Eight of nine students (89%) reported confidence in making ethical decisions, yet survey items on authorship and ethics suggested superficial understanding — most disagreed that GenAI tools carry biases that could undermine news accuracy, reflecting an assumption that technology is unlikely to be biased.
Improved prompt literacy over ethical depth: The intervention primarily influenced the depth rather than the level of ethical understanding, but it enhanced engagement with prompt literacy — students reported structured prompting strategies including role-playing, verb-first instructions and specifying tone, audience or length.
Intervention drives higher-order reflection: Experiential learning activities engaged students cognitively and affectively, moving them toward evaluative and reflective judgement; they expressed a stronger sense of responsibility for accuracy and originality and voiced possibilities of becoming curators/editors who supervise algorithmic content rather than producing it from scratch.
Tension between traditional values and technological utility: Students self-reported concern about reduced professionalism among journalists who use GenAI, reflecting a transformative phase of experiential learning in which they confront previously held assumptions.

Study Design & Method

The study adopts a design-based approach to develop a practice-based Assessment intervention for the second-year core unit Interactive Storytelling within the Bachelor of Media and Communication at an Australian global campus in Sarawak, Malaysia. Nine of 13 enrolled journalism students participated over one academic semester, selected through purposive sampling. The intervention scaffolds movement from human-only reporting to AI-integrated reflection using Beard's experiential learning design, anchored by Anderson & Krathwohl's revised Bloom's taxonomy.

The framework integrates Beard's experiential learning sequence (concrete experience, reflective observation, abstract conceptualisation, active experimentation) with Bloom's levels used as "anchors" rather than a strict ladder. Pre- and post-intervention surveys (Qualtrics, ~10 minutes, anonymous and voluntary) were distributed before and after journalism assessment deadlines. Students completed two assessment tasks and four classroom activities (contrasting research on student GenAI use, debating authorship, discussing bias in GenAI image generation, and reviewing AI-generated work presented as human-authored). Responses were coded thematically using in vivo coding. Trustworthiness followed Lincoln and Guba's framework (credibility, transferability, dependability, confirmability), supported by peer review, triangulation across two campuses and an audit trail. The framework aligns with Australian quality expectations (TEQSA Higher Education Standards Framework) and institutional practice (Swinburne's Educational Quality Excellence Framework).

Implications for AI in Education

From detection to design: Rather than relying on unreliable AI-detection and punitive approaches, the paper advocates designing authentic, scaffolded assessments that embed GenAI explicitly, extending Perkins et al.'s Artificial Intelligence Assessment Scale (Level 4: "AI Task Completion, Human Evaluation") by adding a process dimension — explicit classroom activities that build the ethical reasoning underpinning disclosure decisions.
Values as a bridge to assessable competencies: Clear rubrics that express high-level values (e.g., disclosure) in discrete, assessable terms provide students a bridge between ethical principles and concrete competencies such as statements addressing conflict of interest or omission of sources.
Transferable framework beyond journalism: The core elements — four values, experiential sequencing, and the values–processes–competencies model — are deliberately high-level and adaptable to other disciplines, while context-specific elements (unit learning outcomes, local journalism codes, choice of GenAI tools) adjust per application.
Educator guidance is critical: Effective GenAI integration requires strong guidance from the lecturer/educator; the paper positions ethical AI use not as a discrete technical skill but as part of a broader culture of academic quality and integrity embedded in higher education.
Workplace readiness and human oversight: Students learn to specify source requirements, flag factual uncertainties, and maintain authorship clarity — preparing graduates for newsrooms where AI-assisted content generation is normalised and journalists increasingly supervise algorithmic content (human-in-the-loop roles).
Cultural context matters: The study highlights limited GenAI integration in Malaysian journalism education and industry, and notes the framework may need adaptation to local norms and ethical guidelines — a caution echoed for non-Western and non-South-East Asian contexts (Global South-relevant gap).

Connected Concepts

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Citation

Ngu, I.-Y., & Weller, D. (2026). From Classroom Design to Newsroom Practice: Assessment Intervention Designing GenAI. Journal of University Teaching and Learning Practice, 23(5). https://doi.org/10.53761/4281ht04