Dimitrios ONL reflections

So the course is now finished and  I have the feeling that just when we got the hang of it and found our rhythm in the group i.e how to work together and use the tools, etc it is now over. As a complete newcomer to an online PBL based course it took me some time to feel comfortable but after that I was really looking forward to the weekly meetings and webinars. 

I learned many new things during this course from using various new online/AI tools to how to share and publish OER (using creative commons) and to even what is actually a more important parameter of how to promote meaningful and true engagement in a course. Engaging deeply with an international, multidisciplinary group has fundamentally shifted my perspective on what it means to teach and learn in the digital age. Successful online learning relies heavily on building a vibrant community/group and working together to solve weekly tasks taught me that collective intelligence, diverse viewpoints, and trust are the real drivers of that deep learning. This course demonstrated some good design practices with synchronous and asynchronous activities that can promote such learning.

This ONL course experience as a whole will directly influence my future teaching practice as I would like to incorporate some of the things we did in my future teaching. Instead of relying heavily on traditional lectures, I would like to design more interactive, collaborative activities that encourage students to co-create knowledge (and some aspects of this I already have in some courses). I now see digital tools not just as administration utilities, but as pedagogical enablers.

This is how I believe AI should be used and as I briefly touched upon this in my previous reflection I don’t want to scare students away from using neither over-rely on it but use it for the stuff that are ‘’chores’’ and instead leave the meaningful work that promotes learning to be done by the students. 

As the meme says ‘’I want AI to do the dishes and laundry for me, so I can do the writing and the reading’’ and all other creative activities that develop us as teachers and students.

 I am eager to introduce shared collaborative documents, virtual brainstorming boards, and asynchronous discussion spaces into my courses to help students engage with materials and each other outside the physical classroom wall. I would also like to create some OER resources for some of my courses but I guess that would need some more time and effort on my part  which isn’t always available. At least we now know how 😛 

Overall ONL has been a challenging, especially in the beginning, yet highly rewarding ride. It has provided me with both the theoretical tools and the practical confidence to make my own teaching environment more open, connected, and student-centered.

After this topic I think I am now beginning to understand what online learning is.

As I read other people’s reflections about this it seems that a lot of us were in a similar situation at least before this ONL course started. Especially the ones like myself with very minimal experience in online courses as a student and even less so as a teacher, especially since all of our courses in engineering follow the traditional structure. 

I realise now too as others did that online and/or blended learning (and consequently course design for that) is not about just using online tools and AI to prepare slides, record some lectures, upload necessary material and organize the assignments and tell teh students where to find these.

There must be a thought out structure that combines interaction between the students using some problem based learning activities to encourage participation and active learning.

I realise now that what I wrote on previous reflection about having students peer review each other’s assignment is a step towards that direction and one of the good practices when trying to design such a course.

It aligns with the Community of Inquiry framework by building:

• Social Presence: Peer review forces students to talk to each other, look at how someone else approached a similar engineering problem, and realize they are part of a group (as a class and as future colleagues in their professional lives later on)
• Cognitive Presence: When a student has to look at a peer’s CAD drawing, code, or structural calculation and say, “This works, but here is what you can improve….,” they aren’t just memorizing. They are analyzing and evaluating—the highest levels of critical thought.
• Teaching Presence: It shifts me as a teacher from being the sole bottleneck of feedback to the designer of the feedback loop.

And as discussed in our PBL group, having activities in such a course that cannot be done with AI helps a lot with assessment and is eventually necessary in this era of generative AI. And again the above type of activity helps in that regard too. This was also a large part of our group discussion and also during the two webinars for this topic about how much AI should be used by teachers and students

I normally caution the use of  AI and ask my students to always challenge the outputs. I guess some or most of my colleagues are of the same mindset. But recently I had a revelation moment in a discussion with one of our senior year students who are now doing their thesis work.

I was helping him with an experimental method he hadn’t used before and as I was asking him questions about it he gave me a blank stare back. I asked why he hadn’t used AI to learn the basics , theory and some understanding of it before coming (since it’s so easy now and the AI can handle this level of knowledge) and he said that AI is stupid and he’s afraid that he would get wrong answers that’s why he doesn’t like to use it. 

I was kinda shocked by such an absolute viewpoint. Are we pushing students the other way now already scared of AI? 

I believe that when designing online/blended courses clear guidelines about the use of AI should now be a staple. Students need a framework and clear instructions from the facilitator/teacher about this.

In conclusion, true online learning design requires us to stop digitizing old habits and start engineering completely new experiences. By transforming our assessment strategies to focus on collaborative problem-solving, leveraging the peer-review process, and having generative AI as a useful tool rather than a shortcut, we can build courses that are much more engaging based in active, critical thinking.

Another fortnight, another topic 🙂

This time we try to examine (true) collaboration in groups. I write true because as others have mentioned in their reflections and also became apparent as a common experience in our group discussion, we and often our students mix cooperation with collaboration.

We have been engrained throughout all our student and professional lifes in a specific mode of working together as in ‘’sharing the tasks and combine in the end’’ which I believe originated from a place of ‘’being time efficient’’ as well as lack of online capabilities in the past that it is now difficult to move away from, although we live in an era that we can easily meet online with others with no real effort. The time constraint is still there though and I believe it is one of the main drivers why we still like to work as before. Especially in a world where things move so fast and everyone wants and likes a quick outcome.

Trying to bring this all together in my discipline which is engineering and more specifically materials engineering adds another challenge since most of our courses involve some kind of group work that is happening either during or after a laboratory exercise. The students and often we (the teachers) view this as a rather linear process: Sample preparation, then characterization of the material and finally data analysis. This naturally encourages “task-splitting”.

I would like to use some online tools to help students get away from this traditional practice so they actually don’t need to spend the time traveling to university and physically meet. Instead I would like to promote some synchronous data interpretation using some online tool such as miro (we used that in our group for this topic 😛) to analyze and discuss for instance microscopy images in real-time and then decide on their discussion part for the report together.

Another thing (I am already doing in one course) is that before the final submission each group has to peer review another group’s report and give feedback. This can actually take the form of an online seminar where the discussion happens in real time instead of just sending back some written comments as we are doing now.

All this creates of course some extra effort from the teachers and also students. As we discussed in our group, the benefits of working like this should be clearly explained to the students so they don’t feel like doing extra work for nothing. It’s a complex problem to introduce new ways of working in traditional fields that requires some balancing between time management and digital tools/AI as well as helping students understand this shift.

These past 2 weeks our group started with discussing the “theory” of openness and ended up with a very practical, action-oriented strategy towards open learning (which eventually guided our presentation). We kinda identified that the transition to Open Educational Practices (OEP) isn’t just a technical shift, but a cultural and emotional one as well. It also helped broaden my perspective a bit: currently, my comfort zone is rooted in Open Access for reasearch—sharing finished, peer-reviewed material. However, the transition to Open Educational Resources (OER) feels significantly more vulnerable. Our group discussions highlighted that this “exposure anxiety” is rather common. 

Another point of discussion came up as we were investigating some web tools during our group work that use AI to adapt and transform simple text material into fancy graphics and various ways of presenting stuff that can eventually be a possible OER. And here is where the emergence of Generative AI, can fundamentally change the stakes of openness (if it hasn’t already). We are no longer just sharing content; we are sharing the processes of learning. With just a few clicks on the current technology tools, static resources can turn into interactive, global, and inclusive ecosystems. This is very helpful for example if a student struggles with a concept in an open textbook, the platform can instantly generate a simplified summary or a practice quiz tailored to their level or convert a research paper into a podcast for easier digestion. Openness is now a tool for inclusion and social diversity. By making materials free and accessible, we dismantle the financial barriers that often gatekeep high-quality education. A recent study (in Swedish)[1] actually showed just that: students are more keen to use AI and digital resources than traditional ”literature” as we kwow it.

On the other hand there is a growing tension between “closed” AI models and the “open” movement. We can get help from AI tools to generate educational materials and make a nice looking OER (even helping with the fear of making mistakes since the tools can ‘’polish’’ our content), but the need for open licensing becomes even more critical. My reflection on this topic has led me to believe that OER is the best defence against the “black box” of AI. By applying creative commons licenses to one’s work, we can ensure that our human-vetted knowledge remains a public good, even as it is ingested by future AI training sets. 

I believe that AI and where it is going has made openness essential. It forces us to embrace a more authentic and transparent way of teaching, one where the value of an educator is no longer measured by the proprietary “secrets” we hold, but by the quality of the guidance we offer to our students. 

References

[1] https://www.uka.se/om-oss/nyheter/nyhetsartiklar/2026-04-01-ny-kartlaggning-om-hur-studenterna-anvander-kurslitteratur

Hi,

Very excited to start this ONL course. Never done any blogging before. A lot of new things to learn.