Provides an overview of current research on the nature of difficulties and students' thought processes in the context of learning linear algebra

Discusses the use of technology in teaching and learning linear algebra

Offers practical advice on how to improve student engagement in linear algebra courses

Inhalt

Contents.- .- Part I. Theoretical Perspectives Elaborated through Tasks.- The Learning and Teaching of Linear Algebra through the Lenses of Intellectual Need and Epistemological Justification and Their Constituents.- .- Learning Linear Algebra Using Models and Conceptual Activities .- .- Moving between the embodied, symbolic and formal worlds of mathematical thinking with specific linear algebra tasks.- .- Part II. Analyses of Learners' Approaches and Resources.- Systems of linear equations a key element in the learning of Linear Algebra.- .- Rationale for Matrix Multiplication in Linear Algebra Textbooks.- .- An Action Process Object Schema (APOS) analysis of the understanding of determinants of matrices by Zimbabwean undergraduate mathematics students.- .- Difficulties associated with understanding the concept of vector subspace: A case study of Zimbabwean teachers.- .- Stretch Directions and Stretch Factors: A Sequence Intended to Support Guided Reinvention of Eigenvector and Eigenvalue Stretch Directions and Stretch Factors: A Sequence Intended to Support Guided Reinvention of Eigenvector and Eigenvalue .- .- .- Examining Students' Procedural and Conceptual Understanding of Eigenvectors and Eigenvalues in the Context of Inquiry-Oriented Instruction.- Part III. Dynamic Geometry Approaches.- Mental Schemes of Linear Algebra Visual Constructs.- How DGS mediates students' reasoning on 3D linear transformations: a combined analysis from thinking modes and semiotic perspectives.- .- Fostering Students' Competences in Linear Algebra with digital Resources .- Part IV. Challenging tasks with pedagogy in mind .- Linear Algebra-a Companion of Advancement in Mathematical Comprehension.- .- An algebraic/computational approach to systems of linear equations in a Linear Algebra Course for students of computer science, physics, and mathematics.- .- Nonnegative Factorisationof a Data Matrix as a Motivational Example for Basic Linear Algebra .- .- Motivating Examples, Meaning and Context in Teaching Linear Algebra.- .- Holistic Teaching and Learning Holistically, exemplified through one example from Linear Algebra.- .- Using Challenging problems in Teaching Linear Algebra