Critical thinking - some models to inform teaching and learning

 The application of critical thinking towards evaluating information has been and is now an even more crucial skill. AI generates plausible responses but these must always be checked or triangulated. Ensuring everyone understands the underlying principles of critical thinking, and how the process to apply it towards becoming better equipped to deal with the avalanche of material many people wade through daily, is now more important than ever.

Three recent articles provide guidance. Each offers a model/framework to teach and preserve critical thinking skills.

1) 

Vendrell, M. & Johnston, S-K. (2026). Scaffolding critical thinking with generative AI: Design principles for integrating large language models in higher education, Computers and Education: Artificial Intelligence, Volume 10, https://doi.org/10.1016/j.caeai.2026.100572

Firstly, an update on critical thinking from Vendrell and Johnston (2026). The paper presents an analysis of research in cognitive psychology, educational theory and AI ethics. These are then synthesised to develop a pedagogical framework for integrating LLMS into teaching and learning. The principles of critical engagement are defined as: conceptual interpretation, intellectual curiosity, inferential reasoning, evaluative judgement, metacognitive regulation, and epistemic integrity. The paper recommends design principles that preserve cognitive friction, scaffold LLMs as partners, embed evaluation as standard practice, activate metacognitive regulation, encourage humility and curiosity, foster epistemic integrity, align assessment with thinking and balance AI mediated and AI free phases. 

2) 

Brcic. M. & Frljic, S. (2026). The effortless trap: Productive struggle, AI, and the illusion of learning. https://arxiv.org/pdf/2606.26181

A preprint which extends on the article in 1). it advocates for ways to avoid cognitve debt but ensuring that there are elements of 'productive struggle' in learning. The framework involves working through the following when working through new concept:

- Prime - help learners find a reason/motivation 

- Probe - provide a 'hard' problem so that learners have to tryout new ideas, learn from making mistakes and problem solve their way through.

- Point - using Socratic guides or cognitive apprenticeship to help make the problem solving strategies visible

Attach - connect the new to already learnt or new concept

Strengthen - reinforce through deliberate practice so that the concept/process is anchored.

3) 

Liubertaitė AD (2026) EFFORT-AI: an effort-preserving module for cognitively aligned human-AI learning. Frontier of Education. 11:1849821. doi: 10.3389/feduc.2026.1849821

This article also advocates for the need to ensure cognitive effort is undertaken to assure learning takes place. Introduces the EFFORT-AI model as a way to iintegrate AI into learning without allowing AI to do all the work.

- Elicit - Help learners make known to themselves their prior knowledge on the topic and their motivations to learn.

- Formulate - undertake a first attempt at a problem, either through retrieval or explanation

- Feedback - use feedback cycle to find out progress (or not)

Organise - make sense of the concept/process

- Reflect - review, revise and work out how learning undertaken , gaps in understanding and where to move to next

- Transfer - apply and review (spaced) to keep the concept/process active.

Articles 2) and 3) provide examples, mostly in STEM topics but frameworks cane be adapted to many other disciplines. The frameworks in themselves are therefore useful as starting points for adapting signature disciplines and pedagogy towards pedagogical integration of AI.

Being you:: A new science of conciousness - book overview

e-book borrowed from the local library and read on Libby, across a wet winter weekend. This book 'Being you:: A new science of consciousness' by Anil Seth, was one of the books (and authors) featured in  Pollan's book 'A world appears'.  The book was published in 2021 and sets out a biological/evolutionary perspective on consciousness. 

The book has positive reviews - exampled by this one from the Guardian. In itself, the book undertakes an update on neuroscience understanding of how the brain works and how its organic nature, may not be easily replicated. 

The book has 13 chapters with introductory and concluding chapters as well. The 4 sections, lays out the argument, each building on the next to provide details of how the workings of the brain, provides each person with a highly individualised perspective on the world at large. Being organic, the brain draws on the various senses, memories and experiences of each person. Hence, it is inherently a 'work in progress'. Each chapter has several pages of notes at the end.

The processes described in the earlier chapters explains some of the challenges for transforming people's mind-set. It takes effort and persistence to over-ride what each person has learnt, through a life of being in the 'university of life' and to shift perspectives. This is not impossible, which is where education plays an important role, but moving one's way of being, doing, thinking and feeling, requires strong social and individual motivation. It is an intense  undertaking to shift tracks which is why items like political affiliation (see Haidt's book - the righteous mind) takes some doing.

As to whether AI will become 'conscious' is dependent on how consciousness is defined. As per this book, the argument is that 'qualia' a sense of what something is and the degree of someness, is already difficult to quantify as each sentient being, brings their senses and experiences to gauge the experience. My estimation is that currently, Gen AI does not exhibit qualia. Gen AI cannot 'feel' or be conscious of its selfhood. It remains to be seen what may happen into the future. For the moment, our humanness affords us many qualities that are unique to us. 

The book has many examples explaining complex concepts and processes. It is an accessible read providing a good update on current understandings of how the brain works. Important now when claims are made each day about AI and yet, there are so many things AI is not able to do. AI looks proficient, but it is still a pattern matching algorithm. The patterns look plausible to us because our brain favour tidy patterns and black and white answers. However, many aspects of life are not quantifiable, predictable or straight-forward. As such, the human brain, with its inherent malleability and ability to 'think outside the square', draw on experiences /wisdom, and actually change tack when required, will still be difficult to replace. 

A world appears: A journey into consciousness - book overview

A catch up on aspects of neuroscience, especially to inform thoughts on AI of General AI (GAI) being able to take on human consciousness. Update on readings about a decade ago including Soul Dust; Sentience; the problem of soul; Who am I? and Tell-tale brain. 

Borrowed the book - A world appears: A journey into consciousness - by Michael Pollan from the local library, published 2026 by Penguin.

I have read several of Pollan's book, due to my interest in food. His many books provide alternatives ways to view often mundane topics. He writes for the layperson, but his work draws on the corpus of literature (albeit predominantly from the Western thought canon) and interprets perspectives that connect well with everyday life.

This book is again an accessible introduction to the difficult topic of consciousness. The book brings contemporary research along with an overview of efforts in the past to understand the topic. Pollan talks to many of the researchers in the field, providing a sense of their work and interpreting how each way of understanding the difficult concept of consciousness, adds to an understanding of what might be, what might not be and the many aspects of its amorphous nature.

It is a relatively short book. The introductory chapter lays out the direction of the book. Then follows 4 interwoven chapters, sentience, feeling, thought and self. Each begins with an attempt to define the main topic and then undertakes a discussion around the many themes and variations that underpin the topic. The last chapter 'the cave' is in introspective conclusion on the many rabbit holes and directions the previous chapters traverse.

Pollan himself undertakes to be a 'test subject' in several of the projects he investigates. In previous books, he has written about his use of hallucinogens, as a way to explore alternative realities. The book wanders through the many options availed to try to understand consciousness. In short, there is no agreement or rational statement that defines consciousness. We need to be very cautious about accepting statements on 'AI attaining consciousness' when it is so difficult to pin down consciousness itself. Organic perspectives, including thinking, feeling, sensing etc. and how these contribute towards a sense of 'self' must always be carefully navigated and thought through as non-organic representations likely only 'capture' a hint of what it means to have consciousness. 

There are copious notes across the book. I will need to check out the Journal of Consciousness Studies which publishes interdisciplinary work on consciousness and several recent books.

Onwards to more reading and learning :) 

FLANZ webinar - How does a course template change teachers' teaching perspective?

 Webinar faciliated by FLANZ.

Yong Liu from Manukau Institute of Technology presents on 'How does a course template change teachers' perspective?'

Kristina Hoeppner facilitated the webinar and began with karakia.

Notes taken below:

Summarised the challenge of teachers shifting from f2f to online teaching. Always challenging but proposed the use of templates as a way forward.

After introduction, presented learning theories , then shared the course template, a teaching perspectives inventory (TPI) and a case study.

Rationalised the project as there is a trend to shift to more online learning. Teachers' challenges included technology integration, teachers' academic development (need training but time poor). An online course template provided to help ease the process.

Course template needs to include guidance and examples to provide better steer. 

Draws on constructivism (students learn by exploration and interaction); Cognitive constructivism (connecting new knowledge to existing knowledge); social constructivism (communication and collaboration - teaching and group work - involves learners); connectivism (technology integrated social constructivism). Introduced Canvas as the LMS with tools to engage learners - discussion collaboration etc.

Course template has course home page with course information (plus in-text guidance through hovering on call button). Went through the contents in each section, Information in the call buttons provide steps and required content in each section).

TPI (Pratt and Collins) is an online questionnaire to determine teachers' orientation. The teaching perspectives include: transmission; apprenticeship; developmental; nurturing; and social reform. 3 aspects in each orientation - teaching belief, teaching intention, and teaching action. 

Case study conducted with 17 participants - survey before and after using template, and along with semi-structure interviews. Firstly, established teacher beliefs, intentions and actions and repeated after template used. 

Findings shared. In general, apprenticeship, development and nurturing perspectives increased. Beliefs tended to trend towards constructivist and connectivist teaching strategies. 

Q & A followed. 

Blog on capabilities approach by Professors Leesa Wheelahan and Gavin Moody

The Society for Research in Higher Education (SRHE) in the UK are hosting a blog by Emerita Professor Leesa Wheelahan and Gavin Moodie on the capabilities approach.

The first blog introduces the approach. Following on is the blog on capability for higher education and then one on special, adult and future education. 

An important aspect of the capabilities approach is the broader range of skills. knowledge and attributes attained as outcomes of learning - whether through formalised training/education or at work and through life activities. it is especially important at this point in time to move away from tightly defined and narrow prescriptions (i.e. through competency or skills-first approaches) given the challenges brought in by AI. as educators, we need to consider the wider issues and aspects that will provide continual development to everyone. In doing, we help individuals maintain currency and develop skills to cope with the onslaught of occupational shifts. 

ATAIN - He Ara Mauri: Asking five large language models to calculate their value

 This session of ATAIN presented by Tanya Ruka (He Herenga Waka - Victoria University of Wellington).

She presents on:

He Ara Mauri: Asking Five Large Language Models to calculate their value

He Ara Mauri is a vitality framework grounded in Indigenous relational ontologies that asks a different question of AI: does this system sustain conditions for life, or degrade them? Applied to five frontier AI systems - ChatGPT, Claude, Gemini, Grok, and Meta AI - each system was asked to evaluate itself and then peer-review the others across planetary, human, and more-than-human domains. The result: every system failed.

Notes taken of presentation:

Began with a introduction to her background - starting from Native Land Digital - maintain one of the most widely accessed indigenous platforms in the world. Their remit includes providing educational resources to be used in classrooms, museums, universities etc. Develop indigenous platform. 

At the moment, funding has ceased but continues with work by passionate people.

Between 207 and 2024, she worked on the Te Aho Tapu Hou project - a Mātauranga Māori led research to create circular / regenerative cottage industries. At Victoria, there is one paper - training Korēro AI - understanding 'value' from an indigenous perspective. What happens when AI is tasked with looking into indigenous value systems.

Introduced the He Ara Mauri framework. Started investigating aspects of data sovereignty and what is indigenous AI. Coined AIRI (Artificial Indigenous relational intelligence) as a term to try to explain through a Native Land data, land and water acknowledgement chatbot.

LLMs build on linear, grab and dash and taking/scraping models. No data is safe. It is an extractive, hierarchical and predictive/control oriented. However, indigenous AI is relational in architecture, bussing from a GNN model (e.g. Deepseek) which are relational and layered. This allows use to be less, drawing more on human knowledge.

Kōrero AI created as a co-designed learning tools to move beyond static land acknowledgement. Instead of providing scripted responses, the chatbot invites users into reflection but asking 3 questions about their relationships to land and water. Across a year Feb 2025 to 2026, a million users have engaged. 

Summarised the process of creating the He Ara Mauri framework for system vitality in socio-technical systems. From this, sought to find out larger LLMs deal with the framework. 5 AI systems evaluated and each evaluated on environmental impacts, human impacts, more than human impacts, power, reciprocity and future consequences. Each system failed as they could not account for ecological consequence, more than human relations, intergenerational responsibility, power concentration and long-term vitality.

The systems could not describe themselves, acknowledge uncertainty, bias or harm, demonstrate responsibility, account of future flourishing and could not explain what they restore, instead of just that they take. Therefore, each system's responses reflected the business model, strategic priorities, and public positioning of the organisation that developed it.

Yet integration across education, public services, etc. is ongoing!!

Proposed some solutions - especially in the education context. Recommends, humans must remain responsible, teach AI critically, protect human knowledge creatin, embed future generations into governance. 

Therefore AI is not simply about efficiencies but we need to understand impacts beyond the now.

Education should be about a community of care and includes stewardship of knowledge, culture, democracy, environmental responsibility, future responsibility and technology should strengthen rather than replace relationships.

A thought provoking presentation bringing us back to the fundamental questions of what makes us human and how AI needs to be carefully handled, not just taken as a tool, but to carefully evaluate where it might fit, how it is used, who and when it is used, and how AI literacy must move beyond just using and evaluating but putting AI through different perspectives. 

Q & A provided good discussion on clarifying the principles presented along with discussion from others on implications and challenges. 

Developing curriculum for deep learning: the knowledge revival - book overvew

This is an open access book, 'Developing curriculum for deep learning' comes at a time when educators need to think about the purposes of education and their role as teachers.

The book is published by in 2025 Springer as part of their Springer Brief series in Education. The book has  5 chapters, written by eminent educator scholars - 

• Tim Surma ,
• Claudio Vanhees ,
• Michiel Wils ,
• Jasper Nijlunsing ,
• Nuno Crato ,
• John Hattie ,
• Daniel Muijs ,
• Elizabeth Rata ,
• Dylan Wiliam ,
• Paul A. Kirschner

All contribute to the chapters.

The short introductory chapter provides a rationale for the book along with a brief overview of the book's direction.

The next chapter summarises 'how knowledge matters' . It begins with a summary of how human's learn from a neuroscience perspective. The importance of attaining prior knowledge is introduced and discussed along with the importance of reading. The sociological and democratic perspectives of knowledge are also introduced.

Chapter 3 connects how curriculum is used to bring about the attainment of knowledge. The various ways curriculum contribute are introduced and discussed including the aspects of horizontal and vertical coherence and their relationships to disciplinary knowledge.

Chapter 4 provides concluding remarks and references.

The last chapter provides an executive summary. It reiterates the ways, perspectives on learning, and sociological and democratic aspects shift the ways knowledge is expressed in the curriculum. It argues for the need to ensure that there is always a knowledge rich curriculum in education, to assure the development of the individual and in turn, society at large.

The short book provides a good foundation, especially now in the age of AI, to ensure that as humans, we still treasure learning and knowledge. Worth a read for all educators.