Reflection

 

What did I (not) learn? Can I

… read / understand a scientific paper?

This was a major area of growth for me. At the beginning of the course, I felt overwhelmed by the complexity of academic papers in the AI field. Through the course content especially Meeting 2 understanding Writing and Meeting 3 (understanding content) I learned how to approach papers critically and recognize key structural elements like abstract, methodology, and discussion. I now know how to distinguish between a well-structured and poorly organized paper.

… obtain more information / do literature research?

The Miro board on the tools and guidance on research strategies introduced me to a much more effective way of collecting and organizing literature. Before this seminar, I didn’t use academic papers much for research. Now, I feel confident navigating databases and using tools to structure a literature review

… put research in context (with respect to the state of the art)?

Partially. I was able to place my seed paper in context while writing the survey, which helped me see how it fits into the broader conversation in the field. However, many of my peers' topics were highly technical and specific to Data and computer science, which made it difficult for me to fully understand their significance or how they connected to current research trends. I hope the upcoming final presentations will offer another opportunity to gain insights into their work in a more accessible format.

… form my own scientific opinion/judgement?

I developed this skill especially through the peer review of my seed paper. Analyzing another researcher’s work and writing constructive comments forced me to think critically and justify my assessments. Even though I didn’t critique my peers’ survey papers, reviewing my own source material gave me practice in evaluating clarity, logic, and evidence.

… present scientific results in different ways?

While I found this challenging, I made meaningful progress. The most valuable feedback I received was related to how to present key information in a short time, particularly during the pitch presentation. I learned that being selective and strategic about what to include is crucial, especially in oral formats. Writing the survey paper also helped me structure and communicate ideas clearly within a strict page limit, which was a new experience for me.

… engage in a scientific discussion, express my view, formulate criticism?

We didn’t have many opportunities to critique each other’s work directly beyond reviewing our own seed papers. As a result, I didn’t receive much detailed criticism from peers or instructors, aside from feedback on how to structure my presentation better and prioritize essential content. Still, the act of reviewing a paper and reflecting on its strengths and weaknesses improved my ability to express academic opinions. I expect the upcoming final survey paper presentation to provide more opportunity for discussion and feedback.

How do I assess my performance compared with my colleagues?

What did I do better or worse than my colleagues?

Better: I brought a unique perspective from engineering and made a strong effort to adapt to unfamiliar research methods. I approached the structure and style of academic writing with care and learned quickly, especially how to structure information. Worse: I struggled more with the technical depth of the topics chosen by peers. Since many of them had a background in computer science or Data Science, they were already familiar with key terms and technologies that were new to me. This made it harder for me to contribute in more technical discussions or fully grasp their analyses.

Where do I still need improvement?

I need to continue working on how to present complex content concisely, both in written and spoken formats. Summarizing large amounts of information without losing essential meaning is a skill I’m still building. Additionally, I would like to become more confident in engaging in academic dialogue both asking critical questions and offering constructive feedback.

What could I learn from my peers?

Their topic choices, technical understanding, and ability to quickly navigate scientific literature were impressive. Watching how they structured their arguments and approached survey writing gave me new ideas on how to organize and explain my own work more effectively.

Am I able to give & accept (constructive) criticism?

To a limited extent in this course. While I did conduct a peer review of my seed paper and reflected critically on its quality, I didn’t get to critique my peers’ survey work directly. Similarly, I received minimal criticism mainly focused on how to improve my pitch and presentation structure. Still, this limited feedback was helpful and reminded me of the importance of clarity and prioritization, especially when time or space is limited.

SMART Goal Reflection

At the start of the seminar, I set myself a SMART goal: To learn how to differentiate between a well-written and a poorly written academic paper, particularly by analyzing one paper related to my Master’s thesis topic. My goal was to focus on structure, clarity, writing style, use of sources, and argumentation quality.

While I made significant progress toward this goal, I also realized that not every part of the SMART goal was fully achieved — and that’s an important insight in itself.

What I Achieved

• Specific: I did become much better at recognizing the elements of good academic writing — especially how papers are structured and what makes arguments clear and logical. I now pay close attention to how authors introduce their topics, present evidence, and conclude.

• Measurable: I completed a full survey paper and conducted a peer review of my seed paper. These practical tasks clearly showed me how much progress I made in analyzing and writing academic texts.

• Achievable: The skills were within reach, but definitely challenging. I had never written a survey paper before, and trying to condense broad content into 4 pages was time-consuming and stressful. However, I managed it by applying the techniques we learned throughout the seminar.

Was Not Fully Achieved

• Relevant: One of the most important realizations during the seminar was that the topic I selected is no longer relevant to my Master’s thesis. In the beginning, I believed it would be connected, but the more I researched and worked on it, the more I realized that it does not align with my actual thesis focus.

  However, I consider this a positive learning experience. It’s a valuable academic skill to be able to assess and correctly evaluate the relevance of a topic — and to say, “This doesn’t fit,” is part of becoming a more critical and independent researcher. Making that judgment is, in itself, a meaningful step forward.

• Time-bound: While I completed all required tasks within the semester, the timeline was intense. Writing the survey paper — especially while also learning how to write academically in a new field — was stressful. I would have benefited from starting the survey paper phase earlier in the course, with more time to revise and reflect. That said, I enjoyed the blog posts, reading exercises, and discussions — they helped build the foundation.

Additional Reflections

Despite the SMART goal not aligning perfectly with the final outcome of my thesis topic, I still gained extremely valuable skills:

• I learned how to assess the quality and structure of academic papers a skill I can apply across any subject, not just AI.

• I gained confidence in peer reviewing, even though we didn't engage deeply in mutual critique. Reviewing my own seed paper taught me how to evaluate clarity, logic, and presentation of ideas.

• I learned to communicate complex ideas in a short format, thanks to the presentation (pitch) and the survey paper

• I realized that my engineering background shaped how I approached this work often helping with logical structure, but requiring more effort to understand highly technical or AI-specific content.