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This book is for teachers who are looking for interesting and practical ways to incorporate ICT into their daily lesson plans. It shows how ICT can be used as a tool for mathematics, but more importantly how its proper use can enhance the mathematics being taught. The authors cover all current aspects of ICT and mathematics, including: databases spreadsheets logo and the use of floor turtles and control technology handling of resources including interactive whiteboards management of ICT within the classroom how ICT can be used to present mathematical topics and links to other areas of the curriculum. With plenty of suggestions on how to use the software and hardware described in the book, this is a useful resource for all primary teachers, particularly subject co-ordinators for ICT and mathematics. It will also be of interest to students on PGCE and Initial Teacher Training courses. John Williams has worked in primary education for many years as a class teacher, headteacher, and advisor for science and technology and more recently as Senior Lecturer in Higher Education at Anglia Polytechnic University. Nick Easingwood is Senior Lecturer for ICT in Education and ICT Co-ordinator for the School of Education at Anglia Polytechnic University. 'This book should have a place on the staffroom bookshelf, and should be required reading for Primary PGCE students.' - Education Today Introduction 1. Planning the Mathematics Lesson 2. Delivering the Lesson 3. Using an Interactive Whiteboard 4. The Use of Floor and Screen Turtles 5. The Transition from Floor Turtle to Screen Turtle 6. Why does LOGO merit a place in the Primary Mathematics Curriculum? 7. Handling Data 8. Using Graphs 9. Mathematics Across the Curriculum 10. Some Ideas for Other Mathematics and the Use of ICT

This book is for teachers who are looking for interesting and practical ways to incorporate ICT into their daily lesson plans. It shows how ICT can be used as a tool for mathematics, but more importantly how its proper use can enhance the mathematics being taught. The authors cover all current aspects of ICT and mathematics, including: databases spreadsheets logo and the use of floor turtles and control technology handling of resources including interactive whiteboards management of ICT within the classroom how ICT can be used to present mathematical topics and links to other areas of the curriculum. With plenty of suggestions on how to use the software and hardware described in the book, this is a useful resource for all primary teachers, particularly subject co-ordinators for ICT and mathematics. It will also be of interest to students on PGCE and Initial Teacher Training courses.

Mathematical word problem solving is a fundamental aspect of primary mathematics education, yet students often struggle with translating textual descriptions into structured mathematical representations. In response to this challenge, this study introduces and evaluates ChatGPT-MWPS, an AI-enhanced learning system designed to support fifth-grade students in developing mathematical problem-solving skills through adaptive scaffolding and real-time, step-by-step feedback. Built on a Java-based framework and incorporating OpenAI’s generative AI technology, the system interprets problem content and delivers personalized solution guidance within a digital test paper environment. It supports key instructional functions, such as batch question import, automated test generation, and user management, enabling flexible application in both classroom and self-directed learning settings. A quasi-experimental design was employed with 52 fifth-grade participants to assess the system’s usability and potential educational effectiveness. System perofrmance was measured using a standardized usability scale with 13 dimensions . Results demonstrate that ChatGPT-MWPS achieved favorable usability ratings across the measured dimensions, with particularly strong performance in system reliability, information quality, and cognitive engagement. These findings establish the system's potential for enhancing mathematical learning experiences through its well-received usability characteristics and functional effectiveness. This research contributes to the growing domain of AI in education by demonstrating how generative AI can facilitate personalized mathematics instruction in primary school settings. The outcomes provide practical implications for the design of intelligent tutoring systems that aim to enhance mathematical reasoning and promote learner autonomy.

This paper argues for a renewed focus on statistical reasoning in the beginning school years, with opportunities for children to engage in data modelling. Results are reported from the first year of a 3-year longitudinal study in which three classes of first-grade children (6-year-olds) and their teachers engaged in data modelling activities. The theme of Looking after our Environment, part of the children's science curriculum, provided the task context. The goals for the two activities addressed here included engaging children in core components of data modelling, namely, selecting attributes, structuring and representing data, identifying variation in data, and making predictions from given data. Results include the various ways in which children represented and re-represented collected data, including attribute selection, and the metarepresentational competence they displayed in doing so. The \"data lenses\" through which the children dealt with informal inference (variation and prediction) are also reported.

BackgroundSTEM education needs to begin in primary schools and should aim to prepare young people for active participation in their future. To produce a generation interested and skilled in STEM, the key foci within schools may best occur through teams of teachers working together in an integrated approach, based on cross-curricular teaching and learning. Teachers play a key role in STEM education, and it is important to attract high achievers with relevant backgrounds into teaching. This research study focused on the beliefs, understandings, and intentions of pre-service primary teachers to teach STEM. These beliefs, understandings, and intentions form the platform on which the pre-service teachers build their capacity to teach STEM subjects in primary schools.ResultsThe data (n = 119) collected from a designed questionnaire were analysed qualitatively and quantitatively. An interpretive practice has been used in formulating categories based on responses regarding beliefs, understandings, intentions, and ideal scenarios for future practices and a grounded theory approach for formulating scenarios based on data analysis. The qualitative data were coded into categories based on responses. Structural equation modelling (SEM) and logical regression were conducted to find relationships of the pre-service teacher’s platform for capacity building and connecting to what is required in their classrooms now and in the future. Logistic regressions were used to explore the association of all the questionnaire items and open responses related to the platform and future capacity building. Based on the results, it is evident that the platform developed for teaching STEM based on experience in their teaching degree is limited; however, they have positive intentions to take up STEM. They are not seeing any positive initiative at schools, and they have limited confidence to teach STEM. However, they were suggesting that they should be provided with more opportunities to teach STEM.ConclusionsOverall, our findings indicate that pre-service teachers do not have strong understanding; however, they have strong beliefs and intentions to teach STEM in their future career. The results of this study indicate that the capacity they have built provides them with explicit views on how to teach STEM in primary schools now and informs what they need for the future teaching of STEM. It is essential to formulate a course work and professional development in STEM, capable of integrating disciplines, providing an understanding of pedagogical approaches, and connecting to real-life relevance with the twenty-first century competencies.

First published in 2004. Routledge is an imprint of Taylor & Francis, an informa company.

Examining the way in which the internet and other information sources can be used to maximum potential within the classroom, this book bridges the gap between theory and practice and underpins how pupils can use the internet to improve their literacy and scientific skills. It also offers a range of situations and activities for direct use in the classroom. Drawing upon the most recent classroom research, this is an essential text for students, curriculum leaders and teachers who wish to improve their skills in this area.

Implementation of a National Assessment of Educational Achievement focuses on the practical tasks involved in running a large-scale national assessment program. It has four parts. Part I provides an overview of the tasks involved – how the essential activities of an assessment are organized and implemented, the personnel and resources that are required, and the tasks that follow the collection of data. In Part II, a methodology for selecting a sample of students that will be representative of students in the education system is presented. Principles underlying sampling are described, as well as step-by-step procedures that can be implemented in nearly any national assessment. An accompanying CD contains supporting data files.Part III describes procedures for cleaning and managing data collected in a national assessment, essential elements of a quality assurance process. It also describes how to export and import data, that is, make data available in a format that is appropriate for users of statistical software such as Access, SPSS, WesVar, and Excel. The primary objective of this section is to enable the national assessment team develop and implement a systematic set of procedures to help ensure that the assessment data are accurate and reliable. Following sampling, test administration, data entry, and cleaning, the next step is to prepare data for analysis.In Part IV, a series of important pre-analysis steps, including producing estimates, computing and using survey weights, and computing estimates are described. The section dealing with the computation of estimates describes how they and their sampling errors are computed from simple and complex samples. Finally, a range of special topics, including nonresponse and issues relating to over-and under-size schools, is addressed.