AI and study skills: From cognitive laziness to effective learning strategies

Mapped principles  

The project is mapped to the following framework principles:

P3. Active student-centred learning

P4. Assessment and examination for learning  

P8. Flexible and structured study paths  

P13. Integrated lifelong learning  

​Definitions of the principles

Contact

Marcus Lithander researcher

mlit@kth.se , 087906599

Profile

Project number 

This project is implemented at the School of Industrial Engineering and Management (ITM) within the Future Education programme (project no. 2627-ITM) 

Project context 

The use of AI tools in education is increasing rapidly, including at KTH. Despite this, there is still a significant lack of research-based guidance on how AI affects students’ learning, particularly in relation to cognitive load, effort, and long-term knowledge development. 

Research in cognitive psychology indicates that incorrect use of AI can lead to passive information processing, known as cognitive laziness, which in turn can reduce learning and understanding. At the same time, research shows that structured use of support tools can strengthen central learning processes such as retrieval practice, metacognition, and self-regulated learning. However, access to practically oriented guides and implemented support tools remains limited. 

Purpose (outcome) 

The purpose of the project is to ensure that AI is used in a way that strengthens students’ learning rather than replacing cognitive effort, by developing practically oriented guides and implemented support tools. The intended outcomes are: 

• Increased student completion in courses 
• Reduced risk of superficial and passive AI use 
• A research-based basis for KTH’s policy and support regarding AI 
• Improved long-term knowledge development among students. 

Measurement of the effects may include: 

• Comparisons of performance and grades for the groups using the material 
• Students’ self-reported study behaviours and strategies 
• Course evaluations linked to clarity and learning support 
• Possibly conducting controlled comparative studies where we can compare how much and how well students learn material with and without our developed material. 

Project results (output) 

The project will deliver the following concrete results (to be tested in the course LD1026 Applied Cognitive Psychology: The Science of Learning): 

• An implemented Canvas module with evidence-based guidance for students’ use of AI in their studies. 
• A practically oriented guide for students (dos and don’ts for AI use). 
• A teacher guide on AI as study support, including pedagogical opportunities and pitfalls. 
• Concise guidance identifying effective strategies and risks such as cognitive laziness. 
• A workshop series on AI and learning from a cognitive and study skills perspective, to be run with the programmes that have already expressed interest*. 

^{* Björn Hedin: Master of Science in Engineering and Education (CLGYM); Pernilla Ulfvengren: Industrial Technology and Sustainability (CITEH), Deputy Director of First and Second Cycle Education; Åsa-Karin Engstrand: Industrial Engineering and Management (CINEK); Viktoria Martin: Energy and Environment (CENMI); Sandra Tibbelin, Deputy Director of First and Second Cycle Education with focus on teacher education, ITM.}

Time plan 

Start date: 2026-04-01
End date: 2026-12-31 

Project documentation

If you have a KTH ID, you can read the documents when logged in:

• Poster: The project’s first poster (in Swedish) will be available at the ”Storträffen” meetup autumn 2026
• Project directive (Swedish): Projektdirektiv_FrU26_2627-ITM_AI och Studieteknik.pdf

Result

Resultat_FrU26_2627-ITM_AI och lärande 10studier_MarcusLithander (Swedish)