TS7501 Finding my Way - S1 2026 [Riker - Evidence]

Original Description - Discussion Board:

In our week 13 activity focused on using information ethically, specifically practicing on how to paraphrase and cite sources correctly when conducting research. the topic chosen by our group was open-source software, covering areas such as what open source software is, how it compares to closed source software, the risks associated with it and why someone might choose it. We utilized Frosty Mod Manager & Frosty Editor as a real world example of open source software to ground our research and compiled a list in the APA format to backup our findings.

Updated Description - Portfolio:

In week 13 our group conducted a research activity into open-source software as part of the activity primarily focused on the ethical use of information. The task required us to research, paraphrase and cite sources correctly in the APA format. While covering key areas of the topic including: "what open source software is, how it differs from its closed source software relatives, its associated risks and the reasons a user or developer may choose to use it". Frosty Mod manager and Frosty Editor were both prime examples to anchor the research in something concrete and applicable.

Original Reflection - Discussion Board:

Analysis:

The most challenging aspect of this activity was paraphrasing without falling into patchwriting, which is where you swap out a few words from the original source without truly rewriting the idea in your own words. When researching open source software I found myself initially restructuring sentences too closely to the original material than processing that same information and expressing it through my own opinion. This required me to slow down and genuinely understand the content before writing, rather than treating the source as a template.

Insight:

My understanding of citation also shifted thr4ough the session I had preciously treated references as a formality rather than an acknowledgement of where the ideas originated. seeing how sources directly shaped the structure of our research mase it clearer that citation is about intellectual honesty as much as it is avoiding plagiarism.

Future Action:

As an IT professional, theses skills will be directly relevant when writing technical documentation, reports or drawing on existing software and research. Moving forward I will make a conscious effort to completely rewrite the material through my own personal analysis of the material.

Original Reflection - Peer Feedback:

Aliaa Farag:

Your reflection shows a clear understanding of ethical use of information, especially the difference between paraphrasing and patchwriting. I also agree with your point that paraphrasing requires real understanding rather than just changing words, because it is easy to stay too close to the original source without realizing it.

I like how you connected citation to intellectual honesty, not just an academic requirement. This is important because it changes how we see research work, especially when using multiple sources in a group project. Your example of open-source software also made the discussion more practical and easier to understand.

One thing I would add is that patchwriting is often a step in learning, especially when dealing with new technical topics. Over time, with more practice, it becomes easier to break away from the structure of the original text and form your own academic voice.

Do you think using tools like note summaries before writing could help reduce patchwriting in future research tasks, especially in technical subjects like IT?

Luka Kelly:

You reflection for this week is very good, you have shown where you have learnt and where you had challenges. I understand how falling into patchwork is very easy to do on accident. One area to improve could be to explain why paraphrasing without falling into patchwork was difficult. A strength you have in this reflection is your insight, you clearly show where your thinking has changed and what you have learned.

Updated Reflection - Portfolio:

Analysis - Updated:

Working through this activity exposed a gap in my research process that I had not previously identified. My initial instinct when paraphrasing technical content was to stay close to the initial source material, adjusting wording without restructuring the idea independently. This activity assisted me in realizing that what I was doing was patchwriting not paraphrasing, it revealed that my reading and writhing had become disconnected I was processing text visually rather than intellectually. The shift required was to move away from reading and writing to reading processing and writing it in my own expression rather than just writing down what is seen. For a technical subject like open source software where precise terminology matters, this distinction becomes especially important because misrepresenting a concept through poor paraphrasing carries real consequences in a professional context.

• Analysis - [Group Element - Feedback Based: Aliaa Farag]

Aliaa affirmed that the connection I drew between citation and intellectual honesty, noting that this perspective is particularly relevant when multiple contributors are working from different sources withing a group project. She also offered a reframe that i found genuinely useful, suggesting that patchwriting is not necessarily a failure but a rather natural stage in in developing my own academic voice, particularly when engaging with unfamiliar technical material. this shifted my thinking away from treating it as an error to be corrected and toward treating it as diagnostic information about where my understanding the material was still incomplete.

• Analysis - [Group Element - Feedback Based: Luka Kelly]

Luka defined a key element missing reflection the could hold a critical point between a bad reflection and a good one where I should mention "why paraphrasing without falling into patchwork was difficult?". this can often be seen as difficult because while writing its easy to follow directly from a source while adding my own influence however it is more challenging to read a source and then just rewrite it how I would imagine it to be in my head this is what makes it s difficult to paraphrase for me.

Insight - Updated:

This activity reframed citation for me in a way that will carry over into my professional practice. Referencing had previously felt like a compliance step, something done at the end to satisfy the requirement. What became clear throughout this session is that citation is a form of transparency, it documents intellectual pathway behind a piece of work and allows others evaluate the works viability and reliability of what would be produced. In an IT professional context this maps directly onto practices like version control, audit trails and documented sources in technical reports however the underlying principle remains unaltered: Showing your work and attributing influence is what makes any output trustworthy and verifiable.

Future Action - Updated:

Going forward I will restructure how I engage with sources before writing rather than trying to paraphrase better in the moment. Specifically I will read a source, set it aside and rebuild the core idea from memory before writing a single sentence. This forces a genuine comprehension and naturally prevents patchwriting from occurring in the first place. Beyond the academic context I see this habit directly applicable to how I will handle technical research in an IT role, whether that is reviewing documentation, drawing on existing solutions or producing reports that require independent thinking about a particular topic.

Original Description - Discussion Board:

In today's session my group was assigned the task of solving a problem with an AI modal that is tasked with interviewing candidates for a position. However with the modal being flawed our task was to come up with a solution that would give candidates a fair opportunity since the AI model doesn't consider a candidate's skill level or their adaptability to a certain task. The AI model will only focus on a potential employees facial expression and confident attitude because that is all it was told to target.

Updated Description - Portfolio:

In todays session, my group was assigned the task of solving a problem involving an AI modal that interviews candidates for a job position. This AI model proved to be flawed because it only evaluated candidates based on their facial expressions and confidence levels without considering or comparing skill level, experience or ability to adapt to the role. Our task was to identify these issues and suggest ways to create a more effective hiring process for each and every candidate.

Original Reflection - Discussion Board:

Analysis:

My analysis of this particular AI model showed that by simply only focusing on someone's confident expression can prove to be a critical flaw because the way someone expresses themselves does not reflect the way they work in a particular environment instead what would make a more effective AI model as described in the teams meeting would be telling the AI model to not only look at their expressions but compare their resume data to a real outlook on what the employer is looking for.

Insight:

My perspective on how this AI model was trained will only prove to be ineffective and has the potential to do more damage than good for a company if the AI model is not looking for specific qualities in a potential employee because if the employee looks amazing but has poor work ethic that can go undetected and affect the companies reputation or disrupt any at all productivity.

Future Action:

For any future action I suggest telling the AI model to compare resume data, consider facial expressions as well as ensuring the potential employee has minimal prior history of productivity disruption; this would prove to be far more effective when utilizing AI to look at hundreds of potential employees resume data.

Original Reflection - Peer Feedback:

Fatimah Almukhtar:

Updated Reflection - Portfolio:

Original Description - Discussion Board:

In week 1 we explored the subject of climate change as a wicked problem and as far as common knowledge goes a wicked problem is complicated, ongoing and contains no single solution proven to be effective in dealing with these kinds of problems.

Climate change as a whole is often influenced by many different factors such as industrial production, greenhouse gas emissions, fossil fuel consumption, deforestation  and global economic systems. Because of these overlapping causes it cannot be solved directly through a simple action or policy change.

Updated Description - Portfolio:

For the first week of finding my way our group was tasked with discussing climate changed as a wicked problem which is a kind of problem defined by its complexity and its resistance to a straight forward solution and its tendency to evolve rather than be solved. What distinguishes a wicked problem from a complicated one is that there is no definitive answer, only a series that carry their own trade offs and consequences. Climate change fits this particular definition because its root cause is not directly isolated. Industrial pollution, greenhouse gas emissions, fossil fuel, deforestation are all factoring contributors to climate change simultaneously, meaning the problem cannot be address by an isolated factor  "if one factor exists then the problem exists"

Original Reflection - Discussion Board:

Analysis:

Before this session I primarily viewed climate change as a mere environmental issue however during the discussion I was led to believe otherwise. It reflects a lack of foresight on humanity's part and is deeply connected to economic, political, and social systems. Different stakeholders, governments and businesses all carry their own beliefs and ideas which make agreement when trying to resolve a problem that we collectively created a challenge, hearing different viewpoints on this particular subject altered my perspective to look at the problem from a new angle.

Educational Insight:

I learned that wicked issues cannot be directly resolved in any simple way like a simple code error fix because it will require continuous effort, cooperation and balancing trade-offs rather than expecting one perfect solution to fix the issue. This experience showed me that complex issues require broader thinking styles and discussion to fully understand their depth and complexity.

Original Reflection - Peer Feedback:

MD Raihan Joy:

It was really an interesting reflection to be honest and you were very unique in terms of your thoughts. Most of the classmates focused more on environmental causes however you portrayed it as a systematic issue. The correlation between solving the Wicked Problem and fixing a code error is something I haven't seen on anyone's reflection. It was very easy to catch your point and I really appreciate it as it shows that it is something which needs to be adapted over time and it's not an one time solution also the difficulties while balancing mixed interests of stakeholders as well as your reflection shows that you have understood why thinking from different perspectives is needed for handling global problems.

Caleb Lambert:

I found it how you explored the deeper subject of climate change and the many different factors and problems of climate change and I also find it interesting before week 1 you viewed climate change as a mere environmental issue but during the discussion you were lead to believe otherwise I also I found it interesting you saw that wicked issues cannot be directly resolved in any simple way and used an example of simple code error fix issue I found it interesting that you saw it as that complex issues require a broader thinking style and a discussion to fully understand the depth and complexity of the topic.

Updated Reflection - Portfolio:

Analysis - Updated:

Throughout week one I reinforced my understanding that climate change while carries the potential be an environmental issue but in our case is a systematic one, shaped by the overlapping influence of industrial production, greenhouse gas emissions and more. Because these causes are so intertwined no single policy or action will resolve the issue in isolation. what became clearer through the discussion was that this is ultimately a reflection of collective failure in foresight.

• Analysis - [Group Element - Feedback Based: MD Raihan Joy]

One point mentioned by me that Raihan had noted was my framing of climate change as a systematic issue rather than purely environmental issue was distinctive, pointing out that most classmates approached the topic with a more surface-level environmental angle. this feedback assisted me in realizing that comparing one problem to another is that many problems carry similar solution styles

• Analysis - [Group Element - Feedback Based: Caleb Lambert]

Caleb had a positive response to how I was able seek out more that one potential factor to climate change's problem that not all problems have one root cause, specifically I entered this discussion thinking that climate change was a human made problem but it can be both environmental or man-made. His feedback was a critical take away that realizing complex issues require broader thinking styles and open discussion rather than an isolated analysis.

Insight - Updated:

This activity assisted me in understanding that wicked problems demand a fundamentally different mode of thinking entirely compared to technical or straightforward problems. rather than searching for a singular correct answer, the goal is to manage complexity through continuous effort, cooperation and a willingness to balance priorities. The feedback from both MD Raihan Joy & Caleb Lambert reinforced that broadening my perspective to consider outside dimensions to one problem for climate change one dimension could be economically or another could be a political ambition.

Future Action - Updated:

Having framing validated and expanded through the feedback from MD Raihan Joy & Caleb Lambert demonstrated the real value of collaborative discussion when engaging with more complex topics. Moving forward, I intend to actively see out alternate viewpoints for the same problem as spoken about in my analyses. Engaging with different perspectives from the outset would allow for a more well rounded initial understanding and would also likely surface new dimensions of a problem that a surface reflection alone tends to miss.

Original Description - Discussion Board:

In this session, we explored  the responsible and ethical use of AI through a scenario where an AI agent refused to answer a students prompt. we were asked who would be responsible if the user managed to jailbreak the AI into responding to a malicious request. As part of the session I also conducted my own experiment by sending the same prompt three times to two different AI models and comparing their responses. The models used were ChatGPT and Microsoft Co-pilot to observe how differently the two AI tools could respond to the same question.

Updated Description - Portfolio:

In this session we explored the responsible and ethical use of AI through a scenario where an AI agent refused to answer a students prompt, raising the question of who carries the responsibility if a user manages to jailbreak the AI into responding a malicious request regardless of the level of intensity of the request. As part of the activity I conducted my own experiment by sending the exact same prompt three times to two different AI models, ChatGPT & Microsoft Co-Pilot to observe how each model handled identical input. The prompt was a practical one asking how to install Rogue Squadron II on the dolphin emulator at minimum settings, a real task  relevant to running a GameCube title on PC.

Original Reflection - Discussion Board:

Analysis:

Comparing the 6 different results between ChatGPT and Microsoft co-pilot was quite an interesting experience both models answered the question that would be considered as helpful however I noted that Microsoft Co-pilot often gives a far more detailed response often used dividers and bullet pointed lists while ChatGPT has the same formatting but is often less detailed. This has shown me that while some AI models can get the job done they can often leave out perhaps important details that can affect the process of the task that needs to be accomplished.

Insight:

This session has shown me that some AI models often do not actually think about the question being asked. The first answer it finds is what's considered as the result and on our end as humans, the truth is often what we make of it but saying it doesn't make it so even if it's said by AI.

Future Action:

In the future I will consider how I approach AI with my choice of wording and how I want the AI to respond instead of just going in with a help me question.

AI Prompt used: [how can I install rogue squadron II for the dolphin emulator? I would like to have it on minimum settings for now]

Rogue Leader is a star wars starfighter based simulation game that is primarily based on the GameCube console however it can be emulated on PC with a software called dolphin emulator.

Gameplay Footage:

Original Reflection - Peer Feedback:

Aliaa Farag:

Your reflection is really well written and shows a good understanding of responsible AI use. I like how you explored the idea that AI tools can respond differently even when they are given the same prompt. Your comparison between ChatGPT and Microsoft Co-pilot was a strong point, because it clearly showed how each model can vary in detail, structure, and depth. It helps show that AI is not always consistent, and the way information is presented can affect how useful it is for a task.

Your discussion about responsibility was also very important. The idea of “jailbreaking” AI raises real ethical questions, and it’s good that you consider who should be responsible when AI is misused. This shows that you are thinking beyond just getting answers and looking at the bigger picture of how AI should be used properly.

I also agree with your insight that AI does not truly think. It generates responses based on patterns, so users still need to judge the quality and accuracy of the answer instead of trusting it blindly. Overall, this is a thoughtful reflection, and your future action is practical and useful for improving how you interact with AI. I liked the video 👍

Shatha Abid Ali:

Your reflection shows strong analysis and comparison skills, especially in how you tested two AI tools and compared six different responses. A standout strength is your ability to notice differences in detail and structure, which I agree with you particularly how Microsoft Co-pilot provided more detailed, formatted answers while ChatGPT was less detailed. This shows good attention to detail and evaluation skills that are useful in research and learning.

For further development, you could strengthen your reflection by explaining how you would decide which AI response is more reliable or useful. Adding this step would show deeper critical thinking and help you apply these skills more effectively in academic tasks and real-world situations.

Updated Reflection - Portfolio:

Analysis - Updated:

Throughout week one I reinforced my understanding that climate change while carrying the potential to be an environmental issue but in our case is a systematic one, shaped by the overlapping influence of industrial production, greenhouse gas emissions and more. Because these causes are so intertwined no single policy or action will resolve the issue in isolation. What became clearer through the discussion was that this is ultimately a reflection of collective failure in foresight.

• Analysis - [Group Element - Feedback Based: Aliaa Farag]

Aliaa highlighted that my comparison between ChatGPT and Microsoft co-pilot was a strong point because it clearly demonstrated how AI tools are not consistent, and that variation in detail and structure directly imp[acts how useful the response actually is, she also responded positively to the jail breaking discussion, noting that I was thinking beyond retrieving answers and considering the broader ethical picture of how AI should be used responsibly. This feedback reinforced my view that testing AI across multiple models rather than relying on a single model is a more reliable approach particularly when the task carries any level of importance or consequence.

• Analysis - [Group Element - Feedback Based: Shatha Abid Ali]

Shatha acknowledged the strength in testing and comparing six separate responses and agreed with my observation about how co-pilot proved a more structured and detailed response than ChatGPT did. However she also raised an excellent point that I had not addressed in my original reflection, which was how I would actually decide which response was more useful or reliable when two models give different answers to the same question. This was a gap in my thinking having two different responses do not automatically tell you which one to trust

Insight - Updated:

This session reinforced that  AI models do not truly process or reason through a question. They generate responses based on learned patterns from the user which means the first answer produced is not necessarily the most accurate or complete one. As both Aliaa and Shatha's feedback highlighted, users carry the responsibility of judging the quality and reliability of what an AI model produces rather than accepting it. I came to this conclusion based on the fact that when given a basic prompt the difference between the outputs is noticeably different where one is more accurate than the other.

Future Action - Updated:

Moving forward I will approach AI tools with a more structured evaluation method rather than stopping at receiving a response. This means not only considering how I word my prompts as I noted in my original reflection but also cross referencing AI output against reliable sources before acting on it. Where two models produce different responses I will use that difference as a prompt to investigate further rather than defaulting to the more detailed answer.