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This paper presents the results of an exploratory case study that examined a veteran secondary teacher's knowledge for teaching non-routine mathematical problem-solving with digital technologies. Data was collected through the observation of a veteran mathematics teacher, in real time, solving a mathematical problem with the digital tools of his choice. The descriptive model Mathematical Problem-Solving with Technology (MPST) was used to analyse the teacher's utterances and actions while solving a mathematical problem, with GeoGebra and a spreadsheet, and expressing his reasoning also with technology. Our findings reveal the complexity of expert problem-solving with technology, through regulation processes and several micro-cycles that mainly involve the processes integrate and explore. Mathematical problem solving with technology entails relevant mathematical knowledge as well as knowledge about the mathematical affordances of the digital tools available, and the ability to combine them to develop a conceptual model of the solution to the problem. Thus, the teacher's techno-mathematical fluency seems crucial to successfully solve the problem and express the reasoning with technology. Based on the findings, we discuss the teachers' knowledge for teaching mathematical problem-solving with technology as including a particular kind of proficiency, techno--mathematical fluency for solving-and-expressing problems with technology. The limitations of the study, further research topics and implications for professional development and teacher education programmes are discussed.

Explaining is a vital spontaneous process for human beings, as through explanations we make sense of the surrounding phenomena. While the role and structure of explanations have been explored in each science, technology, engineering and mathematics (STEM) area, little is still known regarding what counts as a good explanation for a STEM problem. This study seeks to address this void by examining the nature of 82 explanations of a STEM challenge produced by 9th grade students (years 14-16) who participated in a learning sequence designed with an integrated STEM education perspective (I-STEM). We aim to find out which types of explanations are produced by 9th grade students when engaged in an I-STEM learning sequence, as a strategy to establish/identify the core features of a good I-STEM explanation. As a subsidiary aim, we intend to propose an analytical framework that enables the characterization and understanding of the students' explanations to an integrated STEM problem, based on the combination of a theoretical view on I-STEM explanations and the qualitative analysis of explanations produced by students. Results show that a majority of the students produced STEM explanations, either descriptive or relational, that failed to demonstrate knowledge or procedures from the four STEM areas. About a quarter of the solutions entailed I-STEM explanations, thus recognizing the role of knowledge or procedures of each area, concurring to obtain the solution, from the creation of the artefact to the understanding of the underlying law. We further propose a conceptualization of a good I-STEM explanation as involving the mobilization of conceptual knowledge and processes from all STEM areas in an explicit and intentional way to present the solution devised to the STEM challenge.

This study aims at understanding the role of the tools chosen throughout the processes of solving a non-routine mathematical problem and communicating its solution. In assuming that problem-solving is a synchronous activity of mathematization and expression of mathematical thinking we take our proposed Mathematical Problem Solving with Technology (MPST) model to analyze the processes of solving-and-expressing-problems. Resorting to qualitative methods for data collection and analysis, we report on the case of an 8th grader working on a covariation problem to examine the role that paper-and-pencil and digital tools play in the development of a conceptual model of the situation. We found that the resources used throughout the solving-and-expressing activity influenced the depth of the conceptual model developed, within a process of progressive mathematization. Whereas paper-and-pencil led to the emergence of a conceptual model based on exploring particular cases, the digital transformation of the solution was triggered by the process of communicating its mathematical justification and expanded the previous model. Moreover, the complexity of this activity is evidenced by its multiple sequences of processes. Finally, the integration process seems crucial as the concomitant use of technological and mathematical resources precedes major advancements in the expansion of the conceptual model.

The research on deductive reasoning in mathematics education has been predominantly associated with the study of proof; consequently, there is a lack of studies on logical reasoning per se, especially with young children. Analytical reasoning problems are adequate tasks to engage the solver in deductive reasoning, as they require rule checking and option elimination, for which chains of inferences based on premises and rules are accomplished. Focusing on the solutions of children aged 10-12 to an analytical reasoning problem proposed in two separate settings--a web-based problem-solving competition and mathematics classes--this study aims to find out what forms of deductive reasoning they undertake and how they express that reasoning. This was done through a qualitative content analysis encompassing 384 solutions by children participating in a beyond-school competition and 102 solutions given by students in their mathematics classes. The results showed that four different types of deductive reasoning models were produced in the two venues. Moreover, several representational resources were found in the children's solutions. Overall, it may be concluded that moderately complex analytical reasoning tasks can be taken into regular mathematics classes to support and nurture young children's diverse deductive reasoning models.

This study offers a view on students' technology-based problem solving activity through the lens of a theoretical model which accounts for the relationship between mathematical and technological knowledge in successful problem solving. This study takes a qualitative approach building on the work of a 13-year-old girl as an exemplary case of the nature of young students' spontaneous mathematical problem solving with technology. The empirical data comprise digital records of her approaches to two problems from a web-based mathematical competition where she resorted to GeoGebra and an interview where she explains and describes her usual problem solving activity with this tool. Based on a proposed model for describing the processes of mathematical problem solving with technologies (MPST), the main results show that this student's solving and expressing the solution are held from the early and continuing interplay between mathematical skills and the perception of the affordances of the tool. The analytical model offers a clear picture of the type of actions that lead to the solution of each problem, revealing the student's ability to deal with mathematics and technology in problem solving. By acknowledging this as a case of a human-with-media in solving mathematical problems, the students' efficient way of merging technological and mathematical knowledge is portrayed in terms of her techno-mathematical fluency.