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Percent is everywhere--all around in finance, shops, foods, media, surveys, and so on. Percentages may seem like a rather simple mathematical theme that has little depth. However, when one starts to pay attention to its usage, percentages can be seen as filled with surprising elements that are mathematically rich and conceptually fascinating, hence worth pondering. This is something that became quite salient for their research team, as they have been preparing experiments with students in classrooms about percentages in mental mathematical environments. Here, Proulx endeavors to raise and addresses some of these peculiarities, which they came to call \"curiosities,\" related to the concept of percentages. These musings can be seen to be as much about their usage of \"%\" in everyday life, in schools, or in mathematics in general. She addresses issues related to establishing equivalences between % increases and decreases. It is his hope that these issues, and their underlying mathematical properties, will intrigue you.

Percent is everywhere. Percentages may seem like a mathematically rather simple theme, or one with little depth. However, when one starts to pay attention to its usage, percentages can be seen as filled with surprising elements that are mathematically rich and conceptually fascinating, hence worth pondering. This is something that became quite salient in the research team, as they have been preparing experiments with students in classrooms about percentages in mental mathematical environments. Here, Proulx addresses issues related to the multiplicative structure underlying the notion of percentages.

Mental computation and mathematical reasoning are two intertwined top-level mental activities. In deciding which strategy to use when doing mental computing, mathematical reasoning is essential. From this reciprocal influence, the current study aims at examining the relationship between mental computation and mathematical reasoning. The study was carried out with 118 fifth-grade students (11-12-year-olds). As data collection tool, \"mathematical reasoning test\" and \"mental computation test\" were developed and used. In analyzing the data, Pearson's correlation coefficient (r) between participants' scores of each test was computed. Some sample student responses to some questions in both tests were also presented directly. Evidence was found that there is a significant positive correlation between mental computation and mathematical reasoning. It is noteworthy that rather than exposing students to familiar classical problems, students need to be enabled to deal with exceptional/non-routine problems, and especially young children should be encouraged to do mental computing in order for developing both skills. On the other hand, students must be asked to write the strategies they use and on which grounds they preferred them while solving the problems.

In the recent years, there has been a push to engage primary and secondary students in computer science to prepare them to live and work in a world influenced by computation. One of the efforts involves getting primary and secondary students to think computationally by introducing computational ideas such as, algorithms and abstraction. Majority of this work around computational thinking has focused on the use of digital technologies, in particular programming environments (Yadav, Stephenson, and Hong 2017). In today’s highly digitalized world, we often associate computational problem-solving processes with the use of computers. Yet, solving problems computationally by designing solutions and processing data is not a digital skill, rather a mental skill. Humans have solved problems for eons and before anyone even thought about the types of digital technologies and devices we know today. The purpose of this article is to examine the historical route of computational thinking and how history can inspire and inform initiatives today. We introduce how computational thinking skills are rooted in non-digital (unplugged) human approaches to problem solving, and discuss how mainstream focus changed to digital (plugged) computer approaches, particularly on programming. In addition, we connect past research with current work in computer science education to argue that computational thinking skills and computing principles need to be taught in both unplugged and plugged ways for learners to develop deeper understanding of computational thinking ideas and their relevance in today’s society.

The body of research surrounding the relationship between visuospatial working memory (VSWM) and mathematics performance remains in its infancy. However, it is an area generating increasing interest as the performance of school leavers comes under constant scrutiny. In order to develop a coherent understanding of the literature to date, all available literature reporting on the relationship between VSWM and mathematics performance was included in a systematic, thematic analysis of effect sizes. Results show a significant influence of the use of a standardised mathematics measure, however, no influence of the type of VSWM or mathematics being assessed, on the effect sizes generated. Crucially, the overall effect size is positive, demonstrating a positive association between VSWM and mathematics performance. The greatest implications of the review are on researchers investigating the relationship between VSWM and mathematics performance. The review also highlights as yet under-researched areas with scope for future research.

BackgroundThe preparation for critically ill children involves calculating drug and fluid volumes using the commonly taught WETFLAG (weight, energy, endotracheal tube, fluids, lorazepam, adrenaline, glucose) acronym. While smartphone applications (apps) are increasingly used for these calculations in clinical practice, limited studies have explored their accuracy and safety.AimTo assess the accuracy of three calculation methods for paediatric emergency drug doses and fluid volumes: a smartphone app, reference charts and traditional calculation methods. The secondary aims were to investigate the effect on the time taken and self-reported stress levels.MethodsA convenience sample of healthcare professionals from four hospitals contributed. Participants calculated drug and fluid doses for fictional patients using the three different methods. The method and case order were randomised centrally. The study recorded the number of errors made during the calculations, healthcare professionals’ self-reported stress levels on a scale of 0 (no stress) to 10 (maximum stress) and the time taken for each case. The app was developed at the direct request of the study team.ResultsNinety-six participants calculated values for six fictional cases, resulting in 576 calculations. Traditional calculation methods showed a statistically significant higher rate of error compared with the use of a smartphone app or reference charts (mean=1, 0, 0, respectively). The smartphone app outperformed both traditional calculation methods and reference charts for time taken and user-reported stress levels.ConclusionsTraditional methods of ‘WETFLAG’ drug and fluid calculations are associated with a statistically significant increased risk of error compared with the use of reference charts or smartphone app. The smartphone app proved significantly faster and less stressful to use compared with traditional calculation methods or reference charts.

This review is aimed at synthesizing current findings concerning technology-based cognitive offloading and the associated effects on learning and memory. While cognitive externalization (i.e., using the environment to outsource mental computation) is a highly useful technique in various problem-solving tasks, a growing body of research suggests that the offloading of information into the environment (and digital storage in particular) can have negative effects on learning. Based on this review, a model of offloading with cognitive load at its core is developed to summarize when learners offload information. A high intrinsic cognitive load (i.e., a high difficulty), a high extraneous load (i.e., unnecessary design elements), and a low perceived or actual working memory capacity trigger offloading. Crucially, the value attributed to information also affects whether information is externalized. In this model, extraneous cognitive load in the design of technology-enhanced learning acts as a triple barrier: (1) It prevents information from entering working memory, (2) it inhibits information being stored in long-term memory, and (3) it can prevent learners from externalizing information using technology. As a result, in many instances, only the gist of information (or its location) is retained, while learners often gain the illusion of having memorized that information. Furthermore, offloading substantially increases the risk of memory manipulation, potentially posing a societal problem. Consequently, educational approaches should maximize the meaningfulness of the residual information that is often retained in the form of “biological pointers.” In addition, current issues surrounding the use of generative artificial intelligence pertaining to externalization are discussed.

Percent is everywhere-all around us in finance, shops, foods, news/media, surveys, and so on. Percentages may seem like a rather simple mathematical theme that has little depth. However, when one starts to pay attention to its usage, percentages can be seen as filled with surprising elements that are mathematically rich and conceptually fascinating, hence worth pondering. This is something that became quite salient for our research team, as we have been preparing experiments with students in classrooms about percentages in mental mathematical environments. My columns presently endeavour to raise and address some of these peculiarities, which we came to call \"curiosities,\" related to the concept of percentages. These musings can be seen to be as much about our usage of \"%\" in everyday life, in schools, or in mathematics in general. This fourth column addresses issues related to the addition and cancellation of %. It is my hope that these issues, and their underlying mathematical properties, will intrigue you

In this paper we investigate whether computer programming has an impact on high school student's reasoning skills, problem solving and self-efficacy in Mathematics. The quasi-experimental design was adopted to implement the study. The sample of the research comprised 66 high school students separated into two groups, the experimental and the control group according to their educational orientation. The research findings indicate that there is a significant difference in the reasoning skills of students that participated in the \"programming course\" compared to students that did not. Moreover, the self-efficacy indicator of students that participated in the experimental group showed a significant difference from students in the control group. The results however, failed to support the hypothesis that computer programming significantly enhances student's problem solving skills.

Spatial skills can predict mathematics performance, with many researchers investigating how and why these skills are related. However, a literature review on spatial ability revealed a multiplicity of spatial taxonomies and analytical frameworks that lack convergence, presenting a confusing terrain for researchers to navigate. We expose two central challenges: (1) many of the ways spatial ability is defined and subdivided are often not based in well-evidenced theoretical and analytical frameworks, and (2) the sheer variety of spatial assessments. These challenges impede progress in designing spatial skills interventions for improving mathematics thinking based on causal principles, selecting appropriate metrics for documenting change, and analyzing and interpreting student outcome data. We offer solutions by providing a practical guide for navigating and selecting among the various major spatial taxonomies and instruments used in mathematics education research. We also identify current limitations of spatial ability research and suggest future research directions.