Research and Endorsements

Three principles for competence development that genuinely changes practice

Courses and training offer little value if the knowledge is never put into practice. Lasting competence development happens when new knowledge is tested in everyday work, shared with others and used to make better decisions. Here are three principles that underpin Learnlab’s approach to organisational learning. All draw on research into learning, change and the interaction between people and AI.

• Organisations learn when knowledge is put into practice

  Competence development must be linked to specific challenges and goals within the organisation. Employees need opportunities to try new ways of working, receive feedback and examine the results together. Organisational learning occurs when these experiences lead to improved routines, better decisions and lasting changes in how work is carried out. Leaders must therefore support a coherent process, from identifying needs to testing, evaluation and further development. This is the core of the DTEC model: Define, Trial, Evaluate, Cultivate.

  Selected references supporting this principle:

  • Baldwin, T. T., & Ford, J. K. (1988). Transfer of training: A review and directions for future research. Personnel Psychology, 41(1), 63–105. https://doi.org/10.1111/j.1744-6570.1988.tb00632.x – The importance of transferring and applying new knowledge in workplace practice.
  • Doolittle, P. E., Wojdak, K., & Walters, A. (2023). Defining active learning: A restricted systematic review. Teaching & Learning Inquiry, 11. https://doi.org/10.20343/teachlearninqu.11.25 – Active participation and processing of knowledge as a foundation for learning.
  • Fullan, M. G., & Stiegelbauer, S. (1991). The new meaning of educational change (2nd ed.). Teachers College Press. – The importance of support and persistence when the introduction of new ways of working encounters difficulties.
  • Pfeffer, J., & Sutton, R. I. (2000). The knowing-doing gap: How smart companies turn knowledge into action. Harvard Business School Press. – How organisations can turn knowledge into action.
  • Salas, E., Tannenbaum, S. I., Kraiger, K., & Smith-Jentsch, K. A. (2012). The science of training and development in organizations: What matters in practice. Psychological Science in the Public Interest, 13(2), 74–101. https://doi.org/10.1177/1529100612436661 – The importance of needs assessment, learning design and systematic follow-up.
  • Skandsen, T., Wærness, J. I., & Lindvig, Y. (2011). Entusiasme for endring: En håndbok for skoleledere. Gyldendal Akademisk. – The foundation for a systematic change process.
  • Steimler, S. E., Lindvig, Y., Skandsen, T., Wærness, J. I., & Faannessen, M. (2024). Leading educational change in the era of AI: A handbook for fostering learning organizations with AI assistance. Learnlab AS. – Presents the DTEC model (Define, Trial, Evaluate, Cultivate) as a systematic process for organisational development, linking needs assessment, testing, evaluation and further development to create lasting change.
• Lasting competence development requires individual learning to become shared competence

  An organisation’s competence depends on individuals’ knowledge and skills, the quality of collaboration and the ability to exercise sound professional judgement. Competence development should therefore include joint problem-solving, sharing experiences and critical reflection on practice. When employees explore challenges together and develop shared ways of working, knowledge becomes accessible to more people and less vulnerable to the departure of individual employees. Leaders must provide the time, structure and trust this work requires.

  Selected references supporting this principle:

  • Argote, L., & Miron-Spektor, E. (2011). Organizational learning: From experience to knowledge. Organization Science, 22(5), 1123–1137. https://doi.org/10.1287/orsc.1100.0621 – How individual experience becomes collective and organisational knowledge.
  • Bryk, A. S., & Schneider, B. (2002). Trust in schools: A core resource for improvement. Russell Sage Foundation. – Trust as a central resource for improvement.
  • Edmondson, A. (1999). Psychological safety and learning behavior in work teams. Administrative Science Quarterly, 44(2), 350–383. https://doi.org/10.2307/2666999 – Psychological safety as a prerequisite for learning and sharing experiences within teams.
  • Hargreaves, A., & Fullan, M. (2012). Professional capital: Transforming teaching in every school. Teachers College Press. – The relationship between individual competence, social capital and professional judgement.
  • Lindvig, Y., Skandsen, T., & Steimler, S.-E. S. (2026). AI can improve the leadership of educational change. In A. L. Goodwin, A. Hargreaves, V. Showunmi, C. Stone-Johnson & J. Weiner (Eds.), Third international handbook of educational change (pp. 1–21). Springer. https://link.springer.com/rwe/10.1007/978-3-031-88898-4_57-1
  • Stoll, L., Bolam, R., McMahon, A., Wallace, M., & Thomas, S. (2006). Professional learning communities: A review of the literature. Journal of Educational Change, 7(4), 221–258. https://doi.org/10.1007/s10833-006-0001-8 – Collective learning through collaboration, reflection and shared responsibility.
  • Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes (M. Cole, V. John-Steiner, S. Scribner, & E. Souberman, Eds.). Harvard University Press. – The importance of social interaction, language and support from others for learning and knowledge development.
• Data and AI strengthen learning through insight, participation and professional judgement

  Data and AI can help organisations identify competence needs, bring together experiences and track development over time. Their value emerges when employees and leaders use these insights to examine their own practice and make informed decisions. Those affected by changes should participate in defining the challenges, interpreting the information and assessing proposed actions. AI can support analysis and provide feedback, while people must assess relevance, quality and consequences.

  Selected references supporting this principle:

  • Burner, T., Lindvig, Y., & Wærness, J. I. (2025). “We should not be like a dinosaur”—Using AI technologies to provide formative feedback to students. Education Sciences, 15(1), Article 58. https://doi.org/10.3390/educsci15010058 – AI-supported feedback as part of the learning process.
  • Clark, A. (2025). Extending minds with generative AI. Nature Communications, 16, Article 4627. https://doi.org/10.1038/s41467-025-59906-9 – Generative AI as a support for human thinking, reflection and knowledge development.
  • Dewey, J. (1916). Democracy and education: An introduction to the philosophy of education. Macmillan. – Learning through experience, reflection and participation.
  • Kolbjørnsrud, V. (2024). Designing the intelligent organization: Six principles for human-AI collaboration. California Management Review, 66(2), 44–64. https://doi.org/10.1177/00081256231211020 – Principles for collaboration between people and AI in organisational decision-making.
  • Lindvig, Y., Skandsen, T., & Steimler, S.-E. S. (2026). AI can improve the leadership of educational change. In A. L. Goodwin, A. Hargreaves, V. Showunmi, C. Stone-Johnson & J. Weiner (Eds.), Third international handbook of educational change (pp. 1–21). Springer. https://link.springer.com/rwe/10.1007/978-3-031-88898-4_57-1
  • Schildkamp, K. (2019). Data-based decision-making for school improvement: Research insights and gaps. Educational Research, 61(3), 257–273. https://doi.org/10.1080/00131881.2019.1625716 – The systematic use of data as a basis for development and improvement.
  • Schildkamp, K., Fosnæs, A. R., Lindvig, Y., & Wærness, J. I. (2025). Student participation in data-informed decision making: From passive data sources to active data users. Journal of Professional Capital and Community, 10(3), 337–351. https://doi.org/10.1108/JPCC-06-2024-0100 – Participation in interpreting and using data. Applied to organisations, this means involving employees as active contributors to improvement.

Three studies: What happens when AI is used in learning and development?

Together with researchers from the University of South-Eastern Norway and NTNU, Learnlab has conducted three studies in Norwegian schools. We wanted to explore what actually happens when AI becomes part of learning, beyond what is theoretically possible.

The studies have been published in the international journals Education Sciences and Evaluation Review. These experiences have also been brought together in a chapter on how AI can strengthen the leadership of change, published in the Third International Handbook of Educational Change (Springer).

• How can AI strengthen the leadership of change and learning in organisations?

  In a chapter in the respected Third International Handbook of Educational Change (Springer), Learnlab describes how AI can support leaders throughout the change process, from identifying needs to building a lasting culture of learning.

  Key points:

  • The DTEC model (Define, Trial, Evaluate, Cultivate) shows how AI can support each phase of organisational development.
  • Employees’ voices become data: AI can make content accessible and help participants provide reasoned input, allowing their contributions to inform organisational learning and decision-making.
  • Safe, locally adapted AI: The chapter recommends solutions that draw on the organisation’s own sources, reflect local values and are transparent about data use. This improves quality, relevance and trust.
  • AI should enhance, rather than replace, human judgement.

  What does this mean for organisations? AI delivers the greatest value when it supports a clearly led change process, with employee participation and control over data.

  Published: Third International Handbook of Educational Change, Springer, July 2026
  Editors: A. Lin Goodwin, Andy Hargreaves, Victoria Showunmi, Corrie Stone-Johnson and Jennie Weiner
  Authors: Yngve Lindvig and Stig-Erik S. Steimler (Learnlab), Tore Skandsen (IMTEC)

  Read more

• Can AI make the classroom more inclusive?

  A study in lower secondary schools shows that AI-powered real-time translation in Learnlab helped multilingual pupils understand subject content, participate in shared activities and contribute on more equal terms.

  Findings:

  • Multilingual pupils rated the tool as significantly more useful and reported significantly greater inclusion than monolingual pupils.
  • Pupils gave inclusion an average score of 4.2 out of 5.
  • Pupils could write in the language they felt most confident using, while the class read their contributions translated into Norwegian.

  What does this mean for education authorities? Language support embedded in whole-class teaching enables teaching to be adapted to pupils’ needs without removing them from the classroom.

  Sample: 148 pupils in eight classes across five lower secondary schools. Half spoke languages other than Norwegian at home, representing 27 home languages in total.
  Authors: Professor Tony Burner (University of South-Eastern Norway), Yngve Lindvig, Stig-Erik S. Steimler and Kristine Østbye (Learnlab)

  Read the full study

• How can AI improve formative assessment for pupils?

  A study across five schools shows that AI-generated feedback in Learnlab provided pupils with immediate, specific and subject-relevant guidance. It also freed up teachers’ time to support pupils.

  Findings:

  • Both pupils and teachers valued the feedback. Some pupils wrote considerably longer texts than before.
  • Teachers used the time saved to be more available in the classroom.
  • The impact was greatest where school leaders provided follow-up and teachers planned for the entire term. Teachers and pupils believed that the teacher should always have the final say.

  What does this mean for education authorities? AI has the greatest impact when its use is supported by school leadership and embedded in school planning. It should go beyond being a tool that individual teachers experiment with independently.

  Sample: 26 pupils and 13 teachers across five schools, as part of a development project involving 50 schools.
  Authors: Professor Tony Burner (University of South-Eastern Norway), Yngve Lindvig and Jarl Inge Wærness (Learnlab)

  Read the full study

• How can teachers and AI collaborate on assessment and feedback?

  A case study at a Norwegian lower secondary school shows that teachers using Learnlab’s AI assistant received draft feedback they found well structured and academically sound. Pupils also received guidance precisely when they needed it. Teachers retained professional responsibility. AI produces the draft, and the teacher decides.

  Findings:

  • Teachers felt that the AI-generated drafts saved time and provided a useful starting point, rather than having to start from scratch.
  • Several described the feedback as consistent with assessment for learning principles and often worded as they would have written it themselves.
  • Immediate feedback freed up teachers’ time for the pupils who needed the most help.

  What does this mean for education authorities? The study suggests that school leaders and local authorities should allocate time for shared training and opportunities to exchange experiences when introducing AI. This helps prevent teachers from either rejecting the tool or using it uncritically.

  Sample: 21 teachers at one lower secondary school in Norway, teaching subjects including Norwegian, English, mathematics, science, social studies and foreign languages.
  Authors: Jostein Kleveland, Professor Michail Giannakos and Yngve Lindvig (Learnlab)

  Read the full study

What readers are saying about the book:

• Professor Kim Schildkamp at University of Twente

  “If you are interested in how AI can help in leading educational change in organizations, this is a must-read!”

• Professor Emeritus Michael Fullan at University of Toronto

  “This book effectively integrates the most effective change models with the power of AI, exploring the evolution of our shared humanity and the future it holds. What I love about this book is how Learnlab, alongside students and lead learners, actively creates and tests the best ideas.”

• Professor Steve Munby, former CEO of the National College for School Leadership in England

  “This book is ground-breaking. It provides us with a rigorous analysis of leadership and change management issues, whilst also outlining helpful models and processes that leaders can work through to improve their organization. Anyone who wants to improve their school and to understand how to use AI in doing so should get hold of a copy. I know of no other book like it.”

• Professor Emeritus Louise Stoll, UCL IOE London and former President of the International Congress for School Effectiveness and Improvement

  “What a bonus! A resource that demonstrates in so many ways that AI can support deep educational change. Learnlab and IMTEC colleagues have skilfully combined their extensive knowledge and experience of EdTech, AI and leadership of educational change in one unique publication. A thought-provoking, valuable and radical call for international action.”

• Dennis Shirley, Professor at Lynch School of Education and Human Development, Boston College

  “With clear and compelling prose, this book offers a cornucopia of best practices based on rigorous research designed to provide busy school leaders with all of the tools needed to make the most of AI in their schools and systems. An indispensable resource, it belongs on every thoughtful educator’s bookshelf.“

• Professor Andy Hargreaves, University of Ottawa, President of ARC Education and former President of the International Congress for School Effectiveness and Improvement

  “This easy-to-read book is not just a set of speculations about the pros and cons of AI; it transforms those issues in schools, not instead of skilled professional judgement, but with it. Accessible, practical and wise, the best book on AI in education improvement anyone has written yet.“

What readers are saying about the book:

• Michail Giannakos, professor at Norwegian University of Science and Technology

  “Humans and AI can ethically and synergistically combine their strengths to support teaching and learning. This book provides distinct ways teachers and AI can complement each other’s abilities and effectively integrate AI into educational settings. Thoughtfully written and deeply relevant, it is an essential read for anyone invested in the future of education.”

• Lee Elliot Major, Professor of Social Mobility, University of Exeter

  “This book gives real hope that in the hands of expert teachers AI tools can help provide the powerful feedback that all students deserve – whatever their background. We must do all we can to make it a great equalizer in education, creating more equitable classroom practice that nurtures all our children.”

• Barbara Wasson, Professor at Centre for the Science of Learning Technology, University of Bergen, Norway

  “This book provides the educational practitioner with easy to read, practical down to earth insights into how to utilize AI to enhance feedback and assessment. It also provides much needed insights into being a leading EdTech developer in Europe with a focus on safeguarding digital education.”

• Marlen Faannessen, Deputy Director, IMTEC Foundation

  “AI can free teachers to focus on what truly matters – mentoring and guiding students. It’s time to move beyond standardized testing and adopt assessment practices that drive real growth. Packed with practical strategies and inspiration, this book is essential for anyone shaping the future of education.”

• Dennis Shirley, Professor at Lynch School of Education and Human Development, Boston College

  “With refreshing clarity and an impressive command of the research, this book lays out a step-by-step blueprint for how we can marshal the spectacular new resources of AI while keeping pedagogy in the lead, keeping a clear focus on our students and their flourishing. Here is an up-to-date, reader-friendly guide to the brave new world of AI and education that belongs on every thinking person’s bookshelf and in every school’s library.”

Progressive Pedagogy at Learnlab involves student-centered learning where students learn by acting and producing, tailored to individual needs with the opportunity to be creative and engaged, and by reflecting on the learning process. This approach is inspired by the theories of renowned educators and psychologists such as John Dewey, Lev Vygotsky, Maria Montessori, Ludwig Wittgenstein, Howard Gardner, and Michael Fullan. These theories promote an educational system that values practical learning, critical thinking, and reflection—principles that are embedded in both the pedagogical content and the technological development of the Learnlab platform. Learnlab aims to foster an environment where learning is not only informative but also transformational, promoting personal growth and societal contributions.

• John Dewey: Experience-Based Education and Reflective Thinking

  

  John Dewey, a philosopher and educational reformer, argued for an experience-centered education, emphasizing that learning occurs through experience and reflection on those experiences. Dewey believed that education should prepare students to fully engage with their society and environment, encouraging a continuous cycle of action and reflection that enhances both personal and intellectual growth. Learnlab offers digital tools that support reflection and student production. Presentation is particularly beneficial for reflection, while Book, Mind map, Video and Podcast serve as excellent student production tools. Additionally, the AI assistant is developed to help students reflect on what they have achieved and what they can do next. For “learning by doing,” we recommend combining our platform with analog student activities to leverage the strengths of experience-based learning, creative student productions, and thoughtful reflections.

  Real-World Applications:Dewey’s idea that education should be closely tied to real-world experiences is a cornerstone of Learnlab’s approach, where teachers are encouraged to create rich tasks that engage students with their local environment and showcase their products to a broad audience, not always just the class.

   

• Lev Vygotsky: Mediated Learning, The Zone of Proximal Development, and Scaffolding

  

  Lev Vygotsky, a key figure in psychology and education, introduced and laid the foundation for several key concepts that have had significant influence on modern pedagogical practices. Central to his theory is the idea of mediated learning, which postulates that learning occurs through interaction with one’s social environment, particularly through tools and language. This interaction often occurs within the “Zone of Proximal Development” (ZPD), which is the difference between what a learner can do independently and what they can achieve with guidance. Learnlab facilitates mediated social learning where students receive support (scaffolding) through technology, with language, collaborative learning, and AI support being central.

• Maria Montessori: Emphasis on Self-Directed, Hands-On Learning (and “Peace”)

  

  Maria Montessori revolutionized early childhood education by introducing a child-centered approach that emphasizes practical, self-directed learning within a carefully prepared environment. Her philosophy is based on the idea that children learn best when they are free to explore materials and concepts at their own pace, guided by intrinsic motivation rather than external rewards or pressure. Learnlab’s various tools, such as Mind map, Book, Video and Podcast, facilitate such exploration in interaction with both analog and other digital sources. Montessori’s focus on “peace” in a broad sense is something we support at Learnlab by creating thought-provoking content that can contribute to socially engaged citizens who seek both external and internal peace. For sensory-based and active learning, we recommend using our platform in combination with experience-based learning in the real world. Our learning assistant, helps students have a more self-directed learning process, providing help when needed and allowing teachers to focus their support where it’s most needed.

• Ludwig Wittgenstein: Philosophy of Language and Learning

  

  Ludwig Wittgenstein, a pivotal figure in modern philosophy, greatly influenced the understanding of language and its role in learning. He argued that the meaning of words depends on context, and that language gains its meaning from its use in various “forms of life.” We understand a concept only when it is used in practice. Therefore, we focus on having students concretize learning through products and actions, and these become the basis for demonstrating competence. This perspective encourages a focus on practical language use within specific activities and communities, emphasizing the importance of context in communication and understanding. Learnlab’s AI assistant, is designed to engage students in language use rooted in the teacher’s chosen learning objectives and key concepts for the topic.

• Howard Gardner: Theory of Multiple Intelligences

  Howard Gardner’s theory of multiple intelligences has had a significant impact on educational philosophy by suggesting that intelligence is not a single general ability, but rather distinct dimensions. According to Gardner, education should be tailored to individual strengths and learning styles to maximize students’ potential.

  1. Linguistic intelligence
  2. Logical-mathematical intelligence
  3. Spatial intelligence
  4. Bodily-kinesthetic intelligence
  5. Musical intelligence
  6. Interpersonal intelligence
  7. Intrapersonal intelligence
  8. Naturalistic intelligence
  9. Critical evaluation

  Particularly linguistic, logical-mathematical, interpersonal, intrapersonal, and critical evaluation are areas where the Learnlab platform excels in developing students. For the other types of intelligence, it depends on the activities the teacher sets up in planning. Analog activities can be easily integrated with digital activities on the Learnlab platform.

• Michael Fullan: Deep Learning

  Michael Fullan, a renowned educational researcher best known for his thoughts on deep learning, is a major inspiration for LK-20. Fullan identifies six crucial competencies—often referred to as the six Cs—that are essential for students in the 21st century:

  1. Character: Learnlab platforms encourage the exploration and development of identity through engagement with rich tasks and the creation of creative student products.
  2. Citizenship: By developing content and involving students in projects that address real-world issues, Learnlab promotes global awareness and respect for diversity.
  3. Collaboration: Collaboration is a key feature of Learnlab’s tools, with excellent opportunities for co-writing.
  4. Communication: Learnlab tools are designed to lower the threshold for participation and form the basis for discussions and presentations. Students can use text, audio, images, or video to express themselves.
  5. Creativity: Idea conceptualization tools such as mind maps and flowcharts stimulate creative thinking. Students can experiment with different ways of representing information, develop unique solutions to problems, and express themselves through digital media.
  6. Critical Thinking: Learnlab platforms challenge students to use logical reasoning, analyze information, evaluate sources, including feedback from AI.
• Hargreaves & Shirley: Student Engagement

  Dennis Shirley and Andy Hargreaves highlight the need for a better balance between performance and well-being in schools. They have identified five pathways that promote and five that hinder student engagement. The hindrances include dissatisfaction, disconnection from school and curriculum, dissociation from societal norms, disempowerment, and distraction. To promote student engagement, the focus must be on mastery, empowerment, intrinsic value in schoolwork, understanding the importance of what one is learning, and linking learning to the culture one is part of.

  Digital tools can enhance engagement when used with clear goals and purpose, while standardized tests are seen as the arch-enemy of student engagement. At Learnlab, we work towards period-based teaching that promotes relevance, mastery, and student involvement, based on a portfolio mindset. This has previously been challenging for teachers, but with AI, this task is now easier. We offer learning resources that teachers can copy and adapt to local conditions. In addition, we have a strong focus on Sami content, which supports a language and culture under great pressure.