With generative AI tools such as ChatGPT and Co-pilot being more widely used across academia, many students are likely using them for a range of purposes. However, you’re expected to practice good scholarship and uphold academic integrity in all assessments. It’s really important for you to become familiar with and understand the requirements for acknowledging, describing, and referencing the use of Generative AI tools in assessed work. To learn more about upholding academic integrity, please refer to relevant resources available on Learn. In addition to understanding issues around academic integrity, are you aware of the many short-term and long-term negative consequences of relying on them too heavily or too frequently?

A study conducted by Fan et al. (2025) introduces the term metacognitive laziness, which means that when you outsource your thinking skills to an external tool, you become gradually reliant on it, resulting in a habit of avoiding effortful thinking processes. Such reliance can result in negative outcomes, including poorer memory retention, reduced mastery of knowledge, and hindered development of independent and critical thinking skills¹, all of which are clearly undesirable in academic contexts.

So how can you avoid becoming metacognitively lazy? Start by making your own notes.

Why should I make my own notes?

During lessons, while generative AI tools can help capture your lecturers’ or professors’ words and provide a summary at the end, you should still make your own notes because of the following reasons:

1. Inaccurate transcription – This is a very common issue among generative AI tools, especially for nuanced or complex points. Several factors contribute to these inaccuracies, including variations in speech (such as accents, dialects, and informal expressions), poor audio quality, interruptions, subject-specific terms, and words that sound the same but have different meanings.
2. Increased engagement – You’ll be more actively involved during lectures, seminars, and workshops, as making notes requires effort in understanding the content.
3. Better consolidation of learning – Writing your own notes helps reinforce what you’ve learnt and deepens your understanding.
4. Promotion of critical thinking – Note-taking encourages you to evaluate what’s more important and how best to organise and summarise the information.
5. Avoidance of copyright issues – Using generative AI tools to produce notes might raise copyright concerns, especially if your professor or lecturer hasn’t explicitly given permission to record or transcribe.

Find out more about note taking here.

Why is reading so important?

In addition to making your own notes, you should also actively engage in reading and ultimately, read critically. But what do these two actions mean exactly? Here are a few things you can do:

1. Make notes as you read, and keep a list of key words to track important concepts.
2. Ask yourself some basic questions: What is the author’s main argument? What are the key points and supporting evidence?
3. Assess different sections of a source critically, such as the methodology, key concepts and theories, evidence and data, and the overall approach and conclusion.
4. Compare sources: Can you find out any similarities and differences among them?
5. Create a research matrix to help you organise your ideas clearly and systematically.

Find out more about critical reading here.

Research Matrices

What is a research matrix? It’s used to organise, summarise, and compare information from various sources in the form of a table. As shown in the example below, the sources you’ve read are listed across the top row, while the topics in the first column typically represent the recurring key terms across those sources.

Once you’ve entered the sources and topics, you fill each grid with your own notes related to the corresponding key term. Some grids may be left blank – don’t be surprised! This usually means you need to conduct more research on that particular topic. Some people prefer to add an extra column at the end of the table to summarise the findings or include personal comments.

	Source 1	Source 2	Source 3
Topic 1
Topic 2
Topic 3

Below is an example of a research matrix that addresses the question, ‘Do generative AI tools bring more advantages than disadvantages in educational contexts?‘

As you can see, there is currently limited evidence regarding memory retention, which suggests that further research is needed in this area.

Find out more about research matrices here.

Alternatively, join our in-person Academic Writing workshop on Arguments and Paragraph Structure on Wednesday, 29th October 2025, from 3:00pm to 4:00pm. Sign up for this workshop or other Academic Writing workshops here.

Written by Bess Chan, EAP Tutor

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References:

1. Grinschgl, Papenmeier and Meyerhoff, 2021; Fan et al., 2025; Gerlich, 2025; Li, Liu and Dong, 2025; Revesai, 2025) ↩︎