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Visar resultat 1 - 5 av 80 avhandlingar som matchar ovanstående sökkriterier.
1. Learning to solve problems that you have not learned to solve: Strategies in mathematical problem solving
Sammanfattning : This thesis aims to contribute to a deeper understanding of the relationship between problem-solving strategies and success in mathematical problem solving. In its introductory part, it pursues and describes the term strategy in mathematics and discusses its relationship to the method and algorithm concepts. LÄS MER
2. Improving Teaching, Improving Learning, Improving as a Teacher : Mathematical Knowledge for Teaching as an Object of Learning
Sammanfattning : This thesis concerns teaching in mathematics teacher education and is based on the implementation of a learning study at teacher training. The overall purpose was to investigate in what way teacher training could facilitate and improve student teachers’ Mathematical Knowledge for Teaching (MKT). LÄS MER
3. Multidimensional inverse problems in imaging and identification using low-complexity models, optimal mass transport, and machine learning
Sammanfattning : This thesis, which mainly consists of six appended papers, primarily considers a number of inverse problems in imaging and system identification.In particular, the first two papers generalize results for the rational covariance extension problem from one to higher dimensions. LÄS MER
4. Matematikproblem i skolan : för att skapa tillfällen till lärande
Sammanfattning : The general purpose of this dissertation is to define and explore what mathematical problem solving entails. Seven criteria for rich problems will also be formulated. Rich problems are defined as problems which are especially constructed for mathematics education in a school context. LÄS MER
5. Reinforcement Learning and Dynamical Systems
Sammanfattning : This thesis concerns reinforcement learning and dynamical systems in finite discrete problem domains. Artificial intelligence studies through reinforcement learning involves developing models and algorithms for scenarios when there is an agent that is interacting with an environment. LÄS MER