Mathematics teachers’ professional knowledge

This paper addresses the study of teachers’ knowledge, beliefs, conceptions and practices, presenting some illustrations from the area of problem solving. In mathematics education, the teacher has attracted much less work than the student. This may be due, in part, to the different knowledge base of interest in each case. Regarding students, we are concerned with their learning of mathematics. The nature of mathematical knowledge is itself problematic, yet that does not seem to raise too many difficulties for our work. Regarding teachers, it is much less clear what is the specific knowledge (nec-essary for teaching mathematics) that we should be looking at. Is it knowledge of math-ematics content? Of mathematics pedagogy? Of students’ cognitive processes? Some mixture of several of these? In the first part of the paper I will briefly review work done on teachers’ professional knowledge and related concepts within and outside PME. Then, I will present cases taken from empirical research and discuss a few concepts used in our investigations. And in the final part I will contrast some general frameworks to study mathematics teachers’ professional knowledge and draw some perspectives for future work

Investigations and explorations in the mathematics classroom

In Portugal, since the beginning of the 1990s, problem solving became increasingly identified with mathematical explorations and investigations. A number of research studies have been conducted, focusing on students’ learning, teachers’ classroom practices and teacher education. Currently, this line of work involves studies from primary school to university mathematics. This perspective impacted the mathematics curriculum documents that explicitly recommend teachers to propose mathematics investigations in their classrooms. On national meetings, many teachers report experiences involving students’ doing investigations and indicate to use regularly such tasks in their practice. However, this still appears to be a marginal activity in most mathematics classes, especially when there is pressure for preparation for external examinations (at grades 9 and 12). International assessments such as PISA and national assessments (at grades 4 and 6) emphasize tasks with realistic contexts. They reinforce the view that mathematics tasks must be varied beyond simple computational exercises or intricate abstract problems but they do not support the notion of extended explorations. Future developments will show what paths will emerge from these contradictions between promising research and classroom reports, curriculum orientations, professional experience, and assessment frameworks and instruments

Prospective Elementary School Teachers’ Ways of Making Sense of Mathematical Problem Posing

The study tackled prospective teachers’ sense-making of mathematical problem posing and the impact of posing different contextual problems on their learning. Focus was on the generation of new problems and reformulation of given problems. Participants were 40 prospective elementary teachers. The findings provide insights into possible ways these teachers could make sense of problem posing of contextual mathematical problems and the learning afforded by posing diverse problems. Highlighted are five perspectives and nine categories of problem posing tasks to support development of proficiency in problem-posing knowledge for teaching

The Teacher, The Tasks: Their Role in Students' Mathematical Literacy

This paper reports on part of a larger study and examines the changing nature of mathematics teaching and tasks. Two Year 4 classes were compared after mathematicalmodelling tasks were undertaken with and without top-level structuring. The results indicate that mathematical-modelling and top-level structuring tasks can advance mathematical literacy. Where students are guided through information organisation and mathematising through quality teaching, they can make sense of the mathematical world. Also evident was the vital role of the teacher in creating a positive learning environment through facilitating discourse and literacy development in mathematics students. Recommendations for teaching are given. Indications evidenced here warrant further investigation

Learning by Seeing by Doing: Arithmetic Word Problems

Learning by doing in pursuit of real-world goals has received much attention from education researchers but has been unevenly supported by mathematics education software at the elementary level, particularly as it involves arithmetic word problems. In this article, we give examples of doing-oriented tools that might promote children\u27s ability to see significant abstract structures in mathematical situations. The reflection necessary for such seeing is motivated by activities and contexts that emphasize affective and social aspects. Natural language, as a representation already familiar to children, is key in these activities, both as a means of mathematical expression and as a link between situations and various abstract representations. These tools support children\u27s ownership of a mathematical problem and its expression; remote sharing of problems and data; software interpretation of children\u27s own word problems; play with dynamically linked representations with attention to children\u27s prior connections; and systematic problem variation based on empirically determined level of difficulty

Multiple perspectives on the concept of conditional probability

Conditional probability is a key to the subjectivist theory of probability; however, it plays a subsidiary role in the usual conception of probability where its counterpart, namely independence is of basic importance. The paper investigates these concepts from various perspectives in order to shed light on their multi-faceted character. We will include the mathematical, philosophical, and educational perspectives. Furthermore, we will inspect conditional probability from the corners of competing ideas and solving strategies. For the comprehension of conditional probability, a wider approach is urgently needed to overcome the well-known problems in learning the concepts, which seem nearly unaffected by teaching

Curricular orientations to real-world contexts in mathematics

A common claim about mathematics education is that it should equip students to use mathematics in the ‘real world’. In this paper, we examine how relationships between mathematics education and the real world are materialised in the curriculum across a sample of eleven jurisdictions. In particular, we address the orientation of the curriculum towards application of mathematics, the ways that real-world contexts are positioned within the curriculum content, the ways in which different groups of students are expected to engage with real-world contexts, and the extent to which high-stakes assessments include real-world problem solving. The analysis reveals variation across jurisdictions and some lack of coherence between official orientations towards use of mathematics in the real world and the ways that this is materialised in the organisation of the content for students

The challenge of complexity for cognitive systems

Complex cognition addresses research on (a) high-level cognitive processes – mainly problem solving, reasoning, and decision making – and their interaction with more basic processes such as perception, learning, motivation and emotion and (b) cognitive processes which take place in a complex, typically dynamic, environment. Our focus is on AI systems and cognitive models dealing with complexity and on psychological findings which can inspire or challenge cognitive systems research. In this overview we first motivate why we have to go beyond models for rather simple cognitive processes and reductionist experiments. Afterwards, we give a characterization of complexity from our perspective. We introduce the triad of cognitive science methods – analytical, empirical, and engineering methods – which in our opinion have all to be utilized to tackle complex cognition. Afterwards we highlight three aspects of complex cognition – complex problem solving, dynamic decision making, and learning of concepts, skills and strategies. We conclude with some reflections about and challenges for future research