Components of learning and assessment in linear algebra

Linear algebra provides theory and technology that are the cornerstones of a range of cutting edge mathematical applications, from designing computer games to complex industrial problems, as well as more traditional applications in statistics and mathematical modelling. Once past introductions to matrices and vectors, the challenges of balancing theory, applications and computational work across mathematical and statistical topics and problems are considerable, particularly given the diversity of abilities and interests in typical cohorts. This paper considers two such cohorts in a second level linear algebra course in different years. The course objectives and materials were almost the same, but some changes were made in the assessment package. In addition to considering effects of these changes, the links with achievement in first year courses are analysed, together with achievement in a following computational mathematics course. Some results that may initially appear surprising provide insight into the components of student learning in linear algebra.

Understanding the Main Phases of Developing a Maturity Assessment Model

Practitioners and academics have developed numerous maturity models for many domains in order to measure competency. These initiatives have often been influenced by the Capability Maturity Model. However, an accumulative effort has not been made to generalize the phases of developing a maturity model in any domain. This paper proposes such a methodology and outlines the main phases of generic model development. The proposed methodology is illustrated with the help of examples from two advanced maturity models in the domains of Business Process Management and Knowledge Management.