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11 Sep 2026
8 Min Read
Jenny Heng Gek Koon (Academic Contributor), Taylor's Team (Editor)
As a media and communication lecturer, I have noticed a quieter shift in how students write, discuss and express their ideas. The issue is not simply that students are using AI to complete their work. AI is beginning to shape how they sound, how they position themselves and how quickly they move from uncertainty to a polished answer.
One area where I see students relying heavily on AI-generated language is reflective writing. Students often turn to AI when they are asked to reflect on a learning experience, evaluate their own work, or describe what they have gained from an activity.
The responses tend to sound similar. They are polished, balanced, and growth-oriented. A student might write, 'This experience has broadened my perspective and allowed me to appreciate various viewpoints.' It sounds mature and thoughtful. It carries the familiar tone of reflection.
But after speaking to the student, I sometimes realise that the thinking behind the sentence is not as developed as the wording suggests.
The habit this reinforces is subtle but significant. Reflection becomes a form of performance reporting rather than a genuine thinking process. Students learn the conventions of reflective writing: the measured tone, the appreciative language, the sense of personal growth. But they may not have spent enough time asking themselves what they noticed, what challenged them, what they misunderstood, or what they would do differently.
Their focus shifts from contemplation to phrasing. When the wording is smooth, it gives the impression that the student has processed the experience well. But the thinking behind the reflection may still be incomplete.
From a media and communication perspective, this is important because reflection is closely tied to professional reflexivity and ethical reasoning. Practitioners in advertising, public relations, journalism, broadcasting, and digital media constantly evaluate how messages are framed, whose perspectives are represented, and what impact communication has on society. If reflective writing becomes only a polished report, students may struggle to develop the deeper critical thinking needed to assess their own communication decisions.
At the same time, I do not see AI as entirely negative. For some students, especially those who struggle to articulate their thoughts, AI can help them express ideas that were previously difficult to convey. In these cases, AI can function as a scaffold rather than a substitute. The key challenge is ensuring that the final language still reflects genuine reflection.
The reliance on AI becomes even more visible when students discuss complex political, social, ethical, or moral issues. These topics involve uncertainty and the possibility of disagreement. Because of that, students often turn to AI for wording that feels safe, inclusive, and non-confrontational:
The revised version sounds more neutral and balanced. It is less confrontational. It appears responsible. But it may also remove the student’s original position.
In doing so, students may learn to avoid risk when communicating their intent. Instead of asking what they stand for and what they are willing to defend, they may resort to phrasing that sounds safe and cannot be easily criticised.
However, AI can also be used differently. Students can use it to generate counterarguments, identify assumptions, test the weaknesses of their reasoning, or compare competing perspectives. Used critically, AI can help students engage more deeply with difficult issues rather than avoid them.
In this sense, AI can become a tool for grappling with complexity rather than smoothing it away. It can help students clarify what they stand for and why. But this only happens when students use AI to challenge their thinking, not merely to soften their language.
Within media and communication practice, argumentation and framing are essential skills. Editorial writing, opinion journalism, advocacy communication, campaign messaging, and public relations all require practitioners to take positions and justify them with evidence. Difficult issues should not always be summarised into neat, safe-sounding paragraphs. The struggle, uncertainty, doubt, and tension in thought should not disappear too quickly into a conclusion that feels resolved.
When deciding whether to rely on AI output or revise it themselves, I notice that students often pay attention to whether the message sounds right. If the grammar is correct, the tone is polite, and the structure is clear, they may assume the message is ready.
Clear language does not always mean clear intention.
This is visible in classroom discussions and group communication. A student may post a carefully worded response that acknowledges multiple perspectives and maintains a diplomatic tone. It sounds thoughtful. Yet when we unpack the message together, the student sometimes realises that the response does not quite represent what they meant.
This is why framing and positioning remain human decisions. What we emphasise, what we soften, and what we leave unsaid all shape how a message is interpreted. AI can help construct sentences, but it cannot determine the stance and intent behind them.
Consider a student in a group project who wants to remind members to complete their tasks on time. AI may generate a polite and considerate message asking everyone to adhere to deadlines. But the real decision is not simply how polite the message should sound. The student must decide what the message needs to achieve. Should it convey urgency? Should it remind everyone of shared responsibility? Should it directly address unequal contribution? Should it preserve the relationship, or make the issue harder to ignore?
In media and communication practice, this is similar to drafting a social media post, public statement, internal memo, or campaign message. The phrasing may be professional, but the strategic intention lies in the positioning of the message. AI can assist with wording, but the communicator must decide the purpose.
This raises an important tension. If language arrives fully formed, are students spending less time thinking about what they actually want to say?
Meaning often develops through revision. A message drafted quickly may feel slightly off when revisited later. After reconsidering tone, emphasis, or purpose, the second version may feel closer to what we intended. Good communication rarely emerges in a single attempt. AI can accelerate drafting, but it should not replace the reflective process that shapes meaning.
The key concern is not whether young people should use AI. The media and communication industry itself is increasingly integrating AI into everyday workflows, and students will likely encounter these tools in their future careers. The more important question is what habits of thinking and communication they develop alongside AI.
In fast-moving digital spaces, students may feel pressured to respond immediately. Pausing allows emotion to settle, reduces reliance on quick AI-generated phrasing and clarifies intention. In professional communication, replying too quickly can shape narratives or escalate misunderstanding.
Students often ask AI to improve grammar, smooth tone or shorten sentences. They also need to ask, ‘Does this reflect my stand?’ and ‘Am I sounding careful because I am uncertain?’ AI can refine wording. Only the communicator can refine position.
AI-generated responses often lean towards neutrality. Taking a stance does not require absolute certainty. It means being clear about what you currently believe, why you believe it and what evidence or reasoning supports it.
Clear language must serve a purpose. A boundary needs assertiveness, a clarification needs specificity and a request needs directness. Students should ask, ‘What does this message need to do?’
If students cannot explain an idea without rereading it, the sentence may not truly be theirs. Before presenting or submitting their work, they should ask if they are prepared to stand by and defend the idea.
These habits are not only academic. They are professional and ethical. Media and communication students will enter fields where messages influence audiences, shape perceptions, and sometimes affect public debate. Owning one’s words is part of communicative responsibility.
Communication education has never been only about producing grammatically correct messages. It has always been about judgement: knowing when to speak, how to position oneself, what tone fits the situation, and what responsibility comes with expression.
AI speeds up the production of messages. But speed does not automatically strengthen judgement. For media and communication students, judgement is closely connected to editorial decisions, ethical choices, audience sensitivity, and strategic intent. These are competencies that cannot simply be handed over to automated tools.
The goal, therefore, is not to discourage AI use. It is to ensure that speed does not replace thinking, and linguistic polish does not replace ownership. In an era where wording can be generated almost instantly, the real skill may be learning to resist that speed. Students need to pause, choose words deliberately, and take responsibility for what those words do.
AI can help us sound clear and organised. But genuine voice emerges from deep thinking. Judgement forms in uncertainty. Communicative intent is revealed when we are willing to choose a position, not merely use phrases.
The question is no longer simply ‘Does this sound good?’
‘Is this really what I mean?’
About the Author
Since joining Taylor’s in 2006, Jenny has taught subjects related to media studies, journalism and advertising. Her interests in journalism, new media and advertising shape her observations on how AI is influencing the way students think, write and communicate.
