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Students in Group 3 observed that AI-supported learning improved clarity and structure, provided simplified explanations of Interpretive Theory (IT), and enriched understanding when paired with personal notes. Their reflections on IT highlighted its core principles: focusing on meaning over words, considering the listener’s context, and applying a three-step process—comprehension, deverbalisation, and reformulation—to communicate the intended message effectively.

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From what I’ve observed, translating and interpreting involves a very complex process that requires one’s full knowledge and understanding in order to produce the best outcome. I also learnt that every theory exists relates to one another in terms of conveying the message to the audience.

The key insight that I gained was how understanding the context of a situation is essential for accurate interpretation as meaning isn’t just about the words. I also learnt that AI provides a more sophisticated explanation of a certain topic and my observations are rather simple and concise. This is why AI is an important tool that can help us understand something and provide us with a thorough understanding.

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I realized that translation isn’t just about changing words from one language to another, it’s about really understanding what someone means and making sure that meaning comes across clearly. Doing this activity showed me how much thinking and decision making goes into interpreting, especially when you want to make sure the audience understands the original message, even if the words change.I learned that deverbalization is a big part of how IT works. It means you mentally let go of the exact words from the source language and just focus on the meaning. I never thought of translation like that before, but now I see how important it is to focus on the sense of what’s being saidnot just the words themselves.I learned that deverbalization is a big part of how IT works. It means you mentally let go of the exact words from the source language and just focus on the meaning. I never thought of translation like that before, but now I see how important it is to focus on the sense of what’s being said not just the words themselves.

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I noticed that using AI helped me understand the main ideas more clearly and compare them easily with my own notes. It made the learning process faster and more organized.

I learned that Interpretive Theory (IT) is all about understanding the meaning behind what is said, then expressing it naturally in another language. It focuses on sense, context, and the listener’s understanding, not just translating words.

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I found that AI has helped me understanding more about Interpretive Theory (IT) of Translation, especially its three key stages, which are comprehension, deverbalization, and reformulation.

By uploading the article and instructing the AI to summarize its main ideas and highlight differences from other translation theories, I was able to compare the AI’s structured and detailed analysis with my notes that were taken from the article. Therefore, I can say that incorporating AI tools helps me a lot when it comes to critical thinking.

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I realized that comparing my own notes with AI-generated analysis helped me see how deeper context and examples can enhance my understanding. It showed me that while my notes were easy to comprehend, AI added more explanation that made the concepts clearer and more applicable.

I learned that Interpretive Theory (IT) emphasizes conveying the sense of a message rather than translating words literally. This involves understanding the speaker’s intention, using context and background knowledge, and reformulating the message naturally in the target language to ensure effective communication.

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I learned that comparing my own understanding with AI’s output helped me see gaps in my initial notes and improved my comprehension. The structure of the table made it easier to organize ideas and reflect critically on the theory.

I gained a deeper understanding that Interpretive Theory emphasizes sense over words meaning that interpreters prioritize the intended message and context rather than translating each word literally. This approach highlights the importance of comprehension and reformulation in effective communication.

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My journey on learning about Interpretive Theory (IT) has efficiently given me insights to understand the process of translation and interpretation. Previously, I assumed that a reliable and good translation simply converting words from one language to another accurately without any errors. However, IT has proved me that successful interpretation is not about literal translation, it moves beyond to convey meaning, or what the theory calls “sense.”

What captured my attention most is the ideology that interpreters go through three crucial steps: comprehension, deverbalization, and reformulation. This process assists the interpreter to fully comprehend the speaker’s message, separate it from the original language, and then express it naturally in the target language. I found this super beneficial in sensitive contexts, such as education or law, where tone and cultural understanding matter just as much as the words themselves.

For instance, in a parent-teacher meeting, a phrase like “your son needs to improve his attitude” might be too harsh if translated literally. IT teaches us that the interpreter should instead focus on the teacher’s intent and reformulate the message in a way that respects the parents' cultural expectation like saying “The teacher hopes your son can be more cooperative.” This approach not only avoids misunderstandings but also foster trust between the speaker and listener.

From this theory, I also learned that interpreters must use their background knowledge, cultural awareness, and emotional intelligence to ensure that the message is delivered accurately and appropriately. It is not just about language it is about human communication.

The usage of AI in this task also brought me in new insights. The prompt to insert in the AI chat was like a training ground for me like to think and act like a translator and interpreter like how they use their prior knowledge, linguistic choice in their field. I was really ambitious when constructing prompt for the AI to tweak its response based on my criteria’s.

In conclusion, Interpretive Theory has helped me appreciate that interpretation is a thoughtful process tailored to the context. It is about understanding your audience, not just words. This theory will definitely guide the way I approach translation tasks in the future, especially when clarity, empathy, and cultural sensitivity are essential.

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Doing this task helped me realize how AI can enhance critical thinking rather than replace it. By comparing my own notes with AI’s output, I saw how AI can offer deeper explanations, examples, and context that I might not have considered. It encouraged me to reflect more carefully on the meaning behind concepts and not just memorize definitions.

I learned that IT is centered on understanding and conveying the speaker’s intended meaning (sense), not just translating words. The concept of deverbalization—mentally detaching the message from its original language before reformulating it—is especially powerful. It shows that effective interpreting is a cognitive and communicative act, not just a linguistic one.

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One thing I noticed while doing this task:

Honestly, comparing my answers with the AI’s made me realize that I understood the basics, but the AI helped explain things in a clearer and more detailed way. It was like having someone rephrase my thoughts and fill in the gaps I didn’t know I had.

One thing I learned about IT:

I used to think interpreting was just translating words, but now I get that it’s really about making sure the message makes sense to the listener. The “bun and raisins” example stuck with me — it’s not about keeping every word in the same place, it’s about keeping the flavour of the message.

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One thing I noticed while doing this task is that the way a question is written for AI really affects the answer it gives. If the question is clear and focused, the AI gives better and more useful information. This showed me that good prompts are important when using AI for learning. After comparing my notes with the AI output, I learned that Interpretive Theory is not just about translating words from one language to another. It’s about understanding what the speaker really means and saying it in a way that makes sense to the listener. The focus is on meaning, not just the exact words.

Side note: I’ve noticed that many assessments involve AI prompting. I want to understand how this aligns with the course’s practical outcomes?

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While doing this task, I realised that AI is very helpful in explaining complicated ideas in a simple way. At first, the theory was hard to understand because there were many technical terms. But after using AI, I could see the main points more clearly. It helped me break down the information step by step, which made it easier to study and remember.

From this analysis, I learned that Interpretive Theory is not just about changing words from one language to another. It’s more about understanding the full message, including the speaker’s feelings and the situation. Then, the interpreter says the message in a way that sounds natural in the target language. This helps the listener understand the meaning.

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I realise that translation and interpreting are not just about converting words, but about understanding meaning in context. This task shows how interpreters must consider culture, tone, and audience to convey the speaker's intended message.

One key insight I gained is that deverbalisation, an essential part of interpreting, enables the interpreter to detach meaning from the original words, allowing them to reformulate the message idiomatically in the target language. This step proves that a deep understanding is more valuable than memorising vocabulary in professional interpretation.

Using AI for this task was highly beneficial. It provided clear, structured explanations that helped break down complex theoretical ideas into simple, understandable points. Comparing my notes with the AI's output helped me identify areas where I could expand my thinking and use more precise academic language.

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Through this task, I observed how AI can effectively support the analysis of complex academic content by breaking it down into simpler, more understandable parts. It also helped me see differences and similarities in interpretation more clearly, making the learning process more efficient and reflective.

From the analysis, I gained a deeper understanding of Interpretive Theory. It emphasises that interpreters should not translate word-for-word but instead focus on grasping and conveying the speaker’s intended meaning. This involves understanding the context, mentally processing the sense of the message, and then expressing it naturally in the target language so the listener can fully grasp the intended idea.

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I realized that AI can provide detailed and structured insights that helped me go deeper into the topic than I would on my own. Comparing my answers with AI's made me reflect more critically on what I had understood and how to improve my analysis. I learned that the Interpretive Theory of Translation focuses more on understanding and conveying the sense or intended meaning of a message, rather than doing a literal word-for-word translation. This makes it especially useful in real-time interpreting where clarity and audience understanding are key.

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By comparing my own reading with the AI-generated analysis, I realized how much context and prior knowledge affect interpretation. While my notes focused on the basic ideas, the AI helped expand those ideas with deeper explanations and examples, especially about how interpreters must adapt based on the audience’s understanding. This task showed me the value of combining personal reading with AI support to get a more complete picture.

I learned that Interpretive Theory emphasizes “sense” over words. It taught me that professional interpreters don’t just translate word-for-word—they focus on understanding the speaker’s intended message and then reformulate it naturally in the target language. This process involves three key steps: comprehension, deverbalization, and reformulation, which help ensure clear and accurate communication.

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Based on this task, I noticed how much clearer things became when I compared my own understanding with the AI. It helped me spot details I hadn’t paid attention to before and gave me a fuller picture of what Interpretive Theory is really about.

One key thing I learned about IT is that it’s not about translating every word exactly. Instead, it’s about understanding what the speaker truly means and then expressing that meaning naturally in the target language, especially by considering the context and culture.

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One important observation that I learned from doing this task is that AI provided more details explanation. AI also would give examples to make it understandable while I only give general explanation.

One knowledge that I gained about IT from this analysis is how interpreting requires so much more that just changing words to another language. It requires careful thinking and the ability to adjust meaning so the target audience can understand clearly. It made me realise how much skill these interpreters have and the mental effort during interpreting.

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One thing I noticed while doing this task is how much context and background knowledge matter in interpreting. It’s not just about knowing the words—it's about really understanding what someone means. Comparing my notes to the AI’s answers helped me see that using AI can bring out deeper ideas and make things clearer.

I learnt that interpretive theory is all about focusing on the meaning behind the words. Instead of translating word-for-word, interpreters try to understand the message, remove the exact wording, and then say it in a way that makes sense for the listener. It’s more about understanding the feeling and intention than just the language itself.

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From this task, I learned that using AI with clear instructions can help me understand ideas better and explain things more clearly. One thing I learned about IT is that translation is not just about changing words, but about understanding the full meaning, including feelings and context, and then expressing it in a natural way in the other language.

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one important observation I learned from this task is that AI's output is slighlty general compared to mine. It doesnt digest much information as I expected it to.

one knowledge I gained about IT is that to always make sure to not run from the original context eventhough the way its interpreted is slightly different in tone and language.

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One thing that I observed while doing this task is that AI can help me understand complex ideas better because it organize the ideas clearly.

One knowledge I gained about IT is interpreting is not about translating words literally, but about understanding and conveying the speaker's meaning.

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I realized how important it is to understand the bigger picture when we communicate. It’s not just about knowing the meaning of each word but what really matters is figuring out what the speaker truly means and the situation they’re in. By comparing my understanding with how AI interpreted things, I saw how helpful these tools can be in making the real message clearer.

This experience also helped me better understand interpretive theory. It is not about literal translating, but it is about getting the main idea and feeling behind the message. A good interpreter doesn’t just repeat words, they understand the meaning, take it in, and then say it in a way that makes sense and feels right to the listener. It’s about capturing the heart of the message, not just the exact words.

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From what I observed while doing this task, the AI provided deeper theoretical insights and more detailed explanations, while my notes were simpler and focused more on practical understanding.

The important knowledge I gained about IT from this analysis is that it focuses on conveying meaning rather than just translating words directly. This approach has changed the way people study and understand translation.

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Doing this task helped me understand Interpretive Theory in a clearer way. At first, it felt a bit confusing, but breaking it down into simple parts made it easier to get. I learned that interpreting is not just about changing words into another language. It is really about making sure the meaning is understood. Using AI also helped me explain things better and gave me new examples I would not have thought of on my own.

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Doing this task helped me understand Interpretive Theory in a clearer way. At first, it felt a bit confusing, but breaking it down into simple parts made it easier to get. I learned that interpreting is not just about changing words into another language. It is really about making sure the meaning is understood. Using AI also helped me explain things better and gave me new examples I would not have thought of on my own.

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One important observation from doing this task is the value of integrating AI tools into the analysis process. By uploading the article and providing clear instructions or prompts, I realized that AI can efficiently process and summarize complex materials, helping to highlight key points and patterns that might be overlooked during manual analysis. This not only saves time but also enhances the depth and breadth of understanding by offering alternative perspectives or interpretations that complement human analysis

Through this exercise, I gained a deeper understanding of how AI can support interpretive theory (IT) analysis in information technology. Specifically, I learned that AI applications can be leveraged to compare different analytical outputs such as contrasting my own reading with AI generated insights. This process revealed that AI can identify both similarities and differences in interpretation, which helps to validate or challenge my own understanding. Additionally, I discovered that AI’s ability to process large amounts of text and extract relevant themes makes it a powerful tool for qualitative analysis in IT research, enhancing accuracy and objectivity when examining complex theoretical concepts

One knowledge I gained about Interpretive Theory (IT) after doing the analysis is that IT emphasizes understanding the subjective meanings and perspectives of individuals within a specific context. By comparing my own analysis with the AI’s output, I realized that IT is less about finding objective truths and more about interpreting how people construct meaning based on their experiences and social interactions. This approach helps uncover deeper insights into how individuals or groups perceive and respond to information, highlighting the importance of context and interpretation in IT research.

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The important observation I learned from doing this task is to read the article thoroughly, understand the article and the context of the article, transform it into my own words to gain an understanding to the whole concept.

The knowledge I have gained from conducting the IT analysis is that IT is more about understanding than translating a context in the form of word-for-word. It emphasises the conveyance of the meaning of the message rather than to literal translation.

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One important observation:

I observed that AI can explain complex ideas like Interpretive Theory in a simple, easy-to-understand way, which helped me compare and deepen my own notes.

One knowledge I gained about IT:

I learned that IT focuses more on understanding and expressing the sense or message, not just translating words, which is key for clear and accurate communication across languages.

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One important observation I realized that doing my own notes and using AI has a significant difference when generating ideas. Using the right prompt when using AI can help me understand some of the contexts clearly.

One key piece of knowledge that I have gained about the Interpretive Theory (IT) is that it was developed by practicing interpreters, not by linguists or language teachers, and it is a holistic theory not based on prior linguistic or psychological theories.

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One key takeaway from this task is realising that interpretation is more about conveying meaning than translating words. Analysing the concept with AI helped me better understand deverbalisation as the process of detaching from exact wording to focus on the intended message. This deepened my appreciation of Interpretive Theory and its emphasis on audience understanding.

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I observed that context and background knowledge is very important in interpretation. As an interpreter, you need to understand the context of the speaker before interpreting, and you need to have a prior background knowledge to understand the context. An interpreter also should understand their target audience and their demographics before interpreting to ensure the audience fully captures the meaning.

I learnt that interpretation is beyond word-for-word translation. It is how an interpreter grasps the meaning of the original context and re-express it to the audience. This is how I understood this theory: A teacher helps students understand a poem by first absorbing its deeper meaning (not just its words but the poet’s emotions and intent). The teacher then separates the meaning from the poem’s original phrasing and re-expresses it naturally, adjusting the explanation based on the students' background knowledge so they fully grasp the essence of the poem.

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I observed something while comparing my notes and AI's output. Comparing my quick, simple notes with the AI’s fuller answers showed me that it’s helpful to start with plain summaries to get the main point, but adding more detail later, I might miss a few things.

Knowledge gained about IT is I learned that interpreters first turn words into a basic idea in their mind using the exact phrase before speaking, which explains why literal word-for-word translation often doesn’t work. I learned that meaning matters more than word-to-word translation.

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One important observation - I noticed that AI explanations helped simplify complex concepts like deverbalization and equivalence, making them easier to understand and apply in real-life interpreting situations.

One knowledge I gained about IT - I learned that the term "sense" in IT is more than just word meanings. It includes the speaker’s intent, context, tone, and the listener’s background knowledge, which are all crucial for an accurate interpretation.

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One important thing I observed from doing this task is that comparing my notes with the AI’s answers helped me understand Interpretive Theory more deeply. My notes focused on the main ideas in simple words, while the AI gave more complete and detailed explanations.

One key thing I learned about Interpretive Theory is that it focuses on meaning, not just words. Interpreters need to understand the speaker’s full message, not just translate word by word.

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i realised that when i compared my notes with the AI's, mine felt more natural and easier to follow, while the AI’s sounded more formal and detailed. it actually made me feel more confident because i understood the big ideas in my own way.

i learned that IT is all about getting the real meaning across, not just the words. interpreters need to catch what the speaker really means and say it in a way the audience will get, even if that means changing how it’s said.

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One important observation from doing this task is that AI, when prompted effectively, can provide a comprehensive and structured overview of a topic, often reinforcing or elaborating on key points that I had already identified. It was particularly useful in creating deeper analysis that I might have simplified in my initial notes.

One knowledge I gained about IT after doing the analysis is the emphasis on the "functionalist" view of interpreting, where the primary aim is to convey the speaker's message in a way that is adapted to the listeners' background, allowing them to have as many interpretations as those listening to the original speech. This goes beyond simply understanding the message to ensuring its effective reception and comprehension by the target audience.

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One important observation I learned from doing this task is how context shapes meaning in interpreting. By comparing Part 1’s notes with the article’s detailed analysis, I realized that Interpretive Theory (IT) prioritizes the speaker’s intended message over literal, word-for-word translation. This highlights that effective interpretation requires deep engagement with both linguistic and extralinguistic elements to truly convey the intended meaning.

One knowledge I gained about IT after doing the analysis is that its concept of deverbalization is supported by neuropsychological evidence. This scientific foundation deepens my understanding of why IT emphasizes “forgetting” the original words to focus on the underlying sense. It is not just a technique. It reflects how our brains process meaning during interpretation.

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Based on the task I realized that interpreting is not just linguistic exercise or the mechanical conversation of one language to another it's a complex one because we need to consider many aspects.

One knowledge I gained about IT after doing the analysis is the concept of deverbalization the idea that once the interpreter fully understands the speaker’s message, the original words can be discarded. What remains is “sense”, which is then reformulated into the target language. This separates IT from traditional models and highlights how interpretation is an active, creative process, not just linguistic transfer.

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One important observation that I have learned from doing this task is IT emphasizes the importance of understanding the meaning behind words, not just translating them literally.

One knowledge I gained about IT after doing the analysis is the concept of 'sense' in IT relies heavily on context and background knowledge to convey the intended meaning effectively.

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One important insight I gained from this task is that comparing my notes with the AI’s responses helped deepen my understanding of Interpretive Theory. While my notes captured the main ideas in simpler terms, the AI provided more thorough and detailed explanations.

A key takeaway about Interpretive Theory is that it emphasizes the importance of conveying meaning rather than just translating individual words. Interpreters must grasp the speaker’s overall message to accurately communicate it, rather than focusing on a word-for-word translation.