Tag: Education

Project Update: SysTemutvecklingsmetodeR för dIigital Arbetsmiljö (STRIA)

After several years of dedicated research and development, the SysTemutvecklingsmetodeR för dIigital Arbetsmiljö (STRIA) project is coming close. Led by Professor Åsa Cajander, working with Dr Magdalena Stadin and Professor Marta Larusdottir, this project has been a pioneering effort to address the critical issue of digital workplace health and usability in IT systems. The project was funded by AFA.

The Problem
In today’s fast-paced digital landscape, many IT systems fail to support efficient work processes, ultimately contributing to health issues within organizations. Research has highlighted a lack of focus on workplace health in current system development practices. There’s also a shortage of practical methods for incorporating a workplace health perspective into digitalization efforts.

The Mission
The STRIA project aimed to collaborate with IT developers to create effective and practical methods for designing sustainable digital work environments. This endeavor included promoting these methods, developing educational materials, and advocating for their adoption.

The Three Focus Methods
The project focused on three key methodologies:

Contextual Think Aloud Method: This method involves users verbalizing their thought processes while interacting with software, enabling evaluators to gain insights into user thinking.
Vision Seminars: Involving a group of evaluators who individually assess software using predefined heuristics, this method helps identify usability problems.
Contextual Personas Method: Originally introduced by Cooper (2004), this method creates hypothetical archetypes of real users, allowing for more targeted and empathetic system design.

Project Phases
The project followed a structured plan, as outlined in Figure 1, which included:

  1. Understanding Digital Workplace: Assessing challenges related to different IT systems and digital workplaces in healthcare and administrative settings.
  2. Developing System Development Methods: Crafting new methods for system development based on insights from previous phases.
  3. Creating Educational Materials: Developing materials to teach developers how to apply these methods effectively.
  4. Evaluation and Refinement: Testing and refining the methods with IT developers and gathering feedback.
  5. Dissemination of Results: Publishing research findings, articles, and blog posts to share the knowledge with the wider community.

As the STRIA project concludes, it leaves a legacy of knowledge, recommendations, and methodologies for assessing digital workplace aspects. The project’s findings has been shared through academic publications, industry-focused journals, conferences, blogs, and educational programs. Stay tuned for the final report and further updates on this important work.

Frontiers in Education Conference 2023

The education conference Frontiers in Education (FIE) 2023 was held in College Station, Texas. It is a quite large conference, and there were many tracks during the three days that the conference was on. College station is situated between Dallas and Houston, and it is a, well, lets say interesting city, and incorporates another apparently a bit older city, Bryant, in the close vicinity. There was not that much time for sight-seeing so it was mainly the road from the hotel to the conference centre that became the major view during the conference.

The conference offered a large number of very interesting presentations and I did in fact not sit through any bad or boring presentations, Before the main conference there was also one day of workshops, as usual so many that it was difficult to chose one of them. I attended one on inclusive mentoring, which was very inspiring as a supervisor/mentor in general . I am of course very happy to find that there were quite a few presentations, work shops and special sessions that dealt with the issue of inclusion of students on various levels.

The special session on “Disabled Students in Engineering” was held by four Ph.D. students, and was very well prepared, rendering lots of inspiration for the teaching. The organizers also shared very good working material, which can be reused, e.g., in course seminars (I have just started a 15 credit course on non-excluding design).

All in all, the conference felt well worth the effort and time spent. It is always a good feeling when you return home and feel inspired, and just long for putting all the experiences at work in your own teaching. I have already added several new ideas to the course, and I think that this will improve the course a lot.

Still, maybe the most inspiring part of the conference was the (positive and constructive) critique I received on my presentation and paper: “New Perspectives on Education and Examination in the Age of Artificial Intelligence,” which I almost wanted to retitle as “Old perspectives…” since it looks back at older forms of examination, where there was a closer connection between teacher and student. This closer connection and the way it is achieved does make it more difficult for the student to “cheat” or use the AI chat bots.

The picture shows An old Greek teacher and his student, probably discussing a difficult problem during the examination.
An old Greek teacher and his student discussing some interesting problem during the examination

This post is already long enough, so I will not present the paper in any more detail here, but should you want to have a copy of the paper, please contact me with an email. You are also free to comment/criticize this post in the comment section below.

Feedback – the key to success in higher education?

I recently took a pedagogical course in Assessment, grading and feedback in relation to teaching in higher education, and one topic that stood out to me as particularly interesting was the role of feedback for learning. Did you know that research shows that receiving feedback is essential for learning and considered the most powerful means of enhancing student achievements? Still, many teachers experience challenges in their feedback practice such as students not recognizing the value of feedback or students exhibiting defensive responses to feedback. In relation to these challenges, feedback literacy has been introduced by the research arena of higher education studies as a concept describing the ability to interpret and to make productive use of feedback.

A well-cited paper by Carless and Boud describes how many students struggle with understanding, interpreting, and using feedback effectively and the authors emphasize that we as teachers need to help them develop this skill of feedback literacy. To support us in this, they provide a framework suggesting that a set of three interrelated features underpin students’ ability to take action in response to feedback. The three features are:

  • Appreciating feedback: understanding and appreciating that feedback aims at improving the work
  • Making judgments: developing self-evaluative capacities to make sound judgments about one’s own work as well as the work of others
  • Managing affect: avoiding defensiveness when receiving critical feedback and developing habits of striving for continuous improvement based on internal and external feedback.

This leaves the important question of how teachers, such as myself and my colleagues in the HTO group, can support the development of these skills in our students. In the paper, the authors highlight for example the use of peer feedback as a learning activity which explicitly aims towards the development of students’ feedback literacy. The idea is that to provide peer feedback exposes the students to the work of others which helps them compare between their own work and the work of their peers. Which, in turn, benefits the ability to self-evaluate their own production. Providing feedback to peers could also be helpful for students to see that feedback aims to help and suggest solutions and improvements.

Another strategy, and something I believe is important, is to model the uptake of feedback in front of our students. This could be done, for example, by discussing how we as academics are constantly exposed to feedback in the form of peer review. We could also make sure to continuously ask for feedback on our teaching, and then (preferably) handle the comments in an exemplary manner and model how to receive and use feedback as a tool for learning and growth. 

To receive feedback is something I think not only students struggle with from time to time. However, thinking about this in the terms of ‘feedback literacy’ can be helpful as it makes it less static by highlighting this as an ability – and abilities can be improved. So next time you either provide or receive feedback, see it as a possibility for individual skill development.

How do you work with feedback processes and activities? 

Reference: Carless, D. & Boud, D. (2018). The development of student feedback literacy: enabling uptake of feedback. Assessment & Evaluation in Higher Education, 43(8), 1315—1325.

AI and How Education Needs to Change

But will the new tools really make it possible to cheat that much? Well, if we maintain the old style of teaching and examining, the answer is undoubtedly “yes”. However, we can also see this as a possibility to improve, or even revolutionize both education and examination. This, of course, need some changes to be implemented. I will explain my thoughts a bit more in the following.

When we look at our teaching obligation, we need to pose the question: “What do we want our students to learn?”. Well, knowledge about the topic at hand, of course. But is that really true? In the first run, what do we define as knowledge? In many cases, the things that appear on the exams are questions about details, details that they will be able to google as soon as they get outside of the examination hall. Home exams are slightly better, since the students will have to synthesize the answers to the exam, rather than just look them up. But now you can ask a program like chatGPT to do the synthesis for you. And is that cheating? In our old apperception of examination, of course it is. What has the student done to get the piece of text written? Not very much!

Is the classical teaching doomed? No, but it needs to adapt to the new conditions. (Source: L. Oestreicher)

However, when we look closer at this, we can change the question a little, and see what happens? The new question would be something in the way of: “How could we change the way of teaching and examination so that this kind of helping tool will not be a cheating possibility (but maybe even a learning tool)?”. My answer to this question is to focus on understanding. My favourite meme for teaching is: “You can lead a camel to the water, but you cannot force it to drink”. As teachers in higher education, teaching will have to focus more on the “How it works” and “Why it works” of the topics, rather than the “How can I implement it”. The students’ understanding of the (role of the) acquired knowledge in the applicable context has to be the most important teaching goal.

But don’t we do this? Some people may already do so, but we still see many exam questions that focus on the student memorizing the content of the course, rather than understanding how to synthesize the answers through their understanding and their skills in reusing this understanding in transferring their knowledge to new domains.

I have in my teaching changed my examination of the students in my courses (one more theoretical, and two practical programming courses) changing the written examination into an oral “discussion”. That may sound like a lot of work, but in fact, it does not take more time than having a written exam. After 30 minutes of this “academic conversation” style of examination, I have most of the time no problem grading the student according to understanding and reasoning, rather than remembering a lot of details (which are most of the time forgotten fairly quickly after the course). This change was in fact introduced many years ago, way before the occurrence of chatGPT and similar systems.

The benefits here are also the new possibilities of actually allowing the students to use any kind of supportive tool, including in this case the chatGPT, for their projects and learning experiences. The only condition that they have to fulfill is that they themselves have to understand the answers they get from the various tools they use. In the programming courses, that, e.g., means they will have to explain any piece of code that they have not written all by themselves. They will also be told that errors that stem from the information source that remain, will affect their grades negatively. This of course applies to both text and code.

With this approach both to teaching and examination we will turn this risk of “cheating” into an improved pedagogical view of courses and the role of the teacher. Of course, it will still require the teacher to be well educated in the topic, in order to both teach and examine the students.

Lars Oestreicher