Lecture Reflections

The document mentions the technologies that we explored in this thematic area's workshops in the theoretical grounding section. Specifically, it lists the tools that we saw as examples of digital learning environments and computational tools developed to foster students’ computational thinking as well as their understanding of STEM concepts and practices. The emphasis here is that through these educational tools, students learn by creating computational models and artifacts. In this context, computational thinking and problem-solving in digital contexts require both technical skills and the ability to self-regulate learning.

In its 2025 cycle, PISA defines learning in the digital world as “the capacity to engage in an iterative and self-regulated process of knowledge building and problem solving using computational tools and practices”.

To my understanding, this definition is both broad, in the sense that it takes into account the multifaceted aspects of learning (cognitive, metacognitive, affective), but it is also narrow, in terms of the definition of computational problem-solving. I think this is quite a progressive approach, because it raises many challenges on its implementation. Reading the definition again, it seems very demanding to me in terms of the context, the tools and the pedagogical approaches that can be used in the learning process to "check all the boxes" that it introduces. I think it's a definition that is closely related to research in the fields of Computer Supported Collaborative Learning and socially shared regulation of learning, which made me wonder if the existing computational tools where learners engage in knowledge building and problem solving by constructing computational artefacts are enough to implement this definition, considering that "problem solving" is defined as using external factors for building on knowledge.

Besides that, I think that the PISA 2025 LDW test is very strongly grounded scientifically because it combines modern learning theories such as SRL and SSRL theories and collaborative learning theories to more traditional learning theories such as constructionism and constructivism.

I think the next PISA will include this test because it addresses current gaps in how much information there is on how people are using digital technologies, how . Therefore it could be kind of a pre-assessment to collect data on these topics from education systems around the world, in order to perhaps guide policymakers on what steps need to be made moving forward.

The big steps in programming education as "told" by Prof. Resnick

Materials

Reflection Task

Watch the videos in which Prof. Resnick discusses the life's work of Seymort Papert in the first one, introduces one of the most popular educational programming tools in the world - Scratch in the next one and Scratch Jr. with Marina Bers in the last one.

What do these videos, together or separately, tell us about programming tools for children and the pedagogical potential of NIDS?

What is NIDS?

Firstly, defining NIDS as New Instructional Design Systems I believe is essential. NIDS refers to modern frameworks or methodologies developed to enhance teaching and learning.Technology, pedagogy, and psychology are integrated to create effective and engaging educational experiences.

As Mitchel Resnick talks in the first video about his life-long inspiration from Seymour Papert, he describes the “4 Ps” that drive interactive design which are directly linked to how we learn.

Projects: Many people focus on problem-solving but the focus should be on projects - in a project you can use ideas, students learn best when they solve problems in the context of a project

Passion: "I fell in love with it" - You engage better in ideas when you care about them - help children fall in love with ideas

Peers: People learn with and from one another - there is a culture of learning

Play: Playful spirit - provide opportunities of playing with ideas and exploring, challenging themselves, experimenting, pushing their boundaries - playful approach to education

Scratch and ScratchJR, two of the most prominent programming software tools for children that are described in the videos provide the features for making those 4P's happen. More specifically, both Scratch and ScratchJR provide the opportunity to create projects, title them accordingly and provide templates for specific project themes through the sprites and the background, e.g a "car" sprite in a "road" environment. This creates a dedicated space for students to work on a specific context.

The 2nd P, "Passion" is something that the environment on its own cannot ensure. Task structure and facilitation by the teacher are key factors to how students will perceive an idea and engage with it. However, the tool does lay the foundations for helping children "fall in love" with what they are doing. The opportunity, for example to create animations inside the tool, to create stories where the characters converse with eachother, to create projects around space or underwater provide visually appealing and context-relevant spaces for children to work with. The feeling that they are creating something on their own from scratch (pun intended) which they can constantly test out and adjust also puts them in the place of a small engineer who is crafting their own product. This also helps with them connecting what they're doing to themselves.

Scratch has a vivid web community where peoples' projects are being shared with the world and commented on by other people. Remixing projects is also an opportunity that further reinforces this culture of learning, allowing the students to tinker other people's ideas, view the source code, learn from them and extend them in regards to their own personal thinking. This is very valuable to students who seek inspiration or want to boost their skills and it addresses the 3rd P, which is "Peers".

Of course, playing is a central concept both in Scratch and ScratchJR. In ScratchJR the environment is more intuitive, there are icons for each feature of the interface which is very exciting for a small child to experiment with. In my personal experience teaching ScratchJR, small children really enjoyed tinkering the ready-made characters, changing the colors, drawing over them completely, and letting their imagination run free. The same with the backgrounds. Coding with code blocks provides challenging situations for the children which can be adjusted to provide them with opportunities to grow their skills and learn from playing.

Lastly, ScratchJR and Scratch have been designed to provide a smooth transition from one tool to another, which really assists in building on their prior knowledge and creating connections with what they have learned to what they will learn next. Specifically, the colors of the code groups are kept the same, e.g the blue color refers to motion blocks, the purple one refers to appearance blocks etc.

Therefore, these programming tools and their use in education embody innovative approaches to instructional design which is exactly what NIDS is about, and the features that were described above really showcase how valuable pedagogically these softwares are.

Computational thinking? What is that? What is CT 2.0?

Materials

Matti Tedre - Computational Thinking 2.0

Computational Thinking for Professionals

Reflection Task

Prof. Matti Tedre is a computer scientist who is also interested in teaching its concepts and principles. His texts tell us about the transformation we are currently living in.

Explore the articles below to get an idea of what the phenomenon of "computational thinking" is all about and how AI is challenging it.

How can this be taught? Reflect on this in your blog.

Both articles discuss how computational thinking is evolving from CT 1.0 to CT 2.0 and how AI is challenging the basic framework.

CT 1.0 is the classical definition of computational thinking which includes skills and competencies such as abstraction, decomposition etc.

CT 2.0 is an AI-enhanced version of CT 1.0, which specifies the previous definition in the context of machine learning (ML) and artificial intelligence (AI).

To my understanding, with the infusion of AI, there is a growing need to reframe the way we think about computational thinking and avoid generic contexts like algorithms or problem-solving. There is a need for further specification and contextualization to address AI. Talking about deterministic input-process-output systems and training students to write traditional perhaps is not so valuable anymore, whereas introducing data-driven systems that have the concept of probability is more closely aligned to where the digital world is headed at.

I think that in order to move on to teach CT 2.0 to students, fundamental concepts from CT 1.0 such as algorithms, should be grasped very well by all students. Even though I do agree with the direction that the articles are proposing, there is little value in shifting to a new direction with. This would just be a spasmodic effort in staying relevant to current educational trends without having properly built the foundation for the learners first. I think that we are still quite far from achieving that, since basic computer literacy skills are still discussed, and the professional development of teachers to be able to adjust to basic integration of ICT tools in education is an ongoing process. This proves that technology is advancing in far too quick pace and education is struggling to keep up with those advancements. Talking about C.T 2.0, there is also a matter of creating space in the curriculum for facilitating all this new information.

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