Celia Hoyles is Professor of Mathematics Education, London Knowledge Lab, Institute of Education University of London, UK.Richard Noss is Professor of Mathematics Education and Co-director of the London Knowledge Lab, Institute of Education University of London, UK.Philip Kent is a Research Officer, London Knowledge Lab, Institute of Education University of London, UK.Arthur Bakker is a Research Officer in the TmL project, currently at the Freudenthal Institute, Utrecht University, the Netherlands.

Select Guide Rating

• Acknowledgements 1. Introduction 1.1 New Demands on Commerce and Industry 1.2 Information Technology and the Changing Nature of Work 1.3 Background to the Research 1.4 A Description of Key Ideas 1.5 Aims and Methods 2. Manufacturing 1: Modelling and Improving the Work Process in Manufacturing Industry 2.1 Process Improvement in Manufacturing 2.2 Workplace Observations of Process Improvement 2.3 Learning Opportunities for Process Improvement 2.4 Outcomes for Learning and Practice 2.5 Conclusions 3. Manufacturing 2: Using Statistics to Improve the Production Process 3.1 Process Control and Improvement Using Statistics 3.2 Workplace Observations of Statistical Process Control 3.3 Learning Opportunities for Statistical Process Control 3.4 Outcomes for Learning and Practice 3.5 Conclusions 4. Financial Services 1: Pensions and Investments 4.1 The Techno-Mathematics of Pensions and the Work of Customer Services 4.2 Workplace Observations in Pensions and Investments 4.3 Pensions and Investments: Tebos and Learning Opportunities 4.4 Outcomes for Learning and Practice 4.5 Conclusions 5. Financial Services 2: Mortgages 5.1 The Techno-Mathematics of the Current Account Mortgage 5.2 Workplace Observations in Mortgage Sales and Customer Service 5.3 Current Account Mortgages: Tebo and Learning Opportunities 5.4 Outcomes for Learning and Practice 5.5 Conclusions 6. Summary, Reflections and Conclusions 6.1 Key Findings 6.2 Understanding Systems with Models: Pseudo-Mathematical and Techno-Mathematical 6.3 Successes and Challenges 6.4 Conclusions and Implications Appendix: Details of Fieldwork – Companies and Organisations Which Participated In the Research Appendix: Further Reading on the Techno-Mathematical Literacies Research Bibliography

Celia Hoyles is Professor of Mathematics Education, London Knowledge Lab, Institute of Education University of London, UK.Richard Noss is Professor of Mathematics Education and Co-director of the London Knowledge Lab, Institute of Education University of London, UK.Philip Kent is a Research Officer, London Knowledge Lab, Institute of Education University of London, UK.Arthur Bakker is a Research Officer in the TmL project, currently at the Freudenthal Institute, Utrecht University, the Netherlands.

Select Guide Rating

• Acknowledgements 1. Introduction 1.1 New Demands on Commerce and Industry 1.2 Information Technology and the Changing Nature of Work 1.3 Background to the Research 1.4 A Description of Key Ideas 1.5 Aims and Methods 2. Manufacturing 1: Modelling and Improving the Work Process in Manufacturing Industry 2.1 Process Improvement in Manufacturing 2.2 Workplace Observations of Process Improvement 2.3 Learning Opportunities for Process Improvement 2.4 Outcomes for Learning and Practice 2.5 Conclusions 3. Manufacturing 2: Using Statistics to Improve the Production Process 3.1 Process Control and Improvement Using Statistics 3.2 Workplace Observations of Statistical Process Control 3.3 Learning Opportunities for Statistical Process Control 3.4 Outcomes for Learning and Practice 3.5 Conclusions 4. Financial Services 1: Pensions and Investments 4.1 The Techno-Mathematics of Pensions and the Work of Customer Services 4.2 Workplace Observations in Pensions and Investments 4.3 Pensions and Investments: Tebos and Learning Opportunities 4.4 Outcomes for Learning and Practice 4.5 Conclusions 5. Financial Services 2: Mortgages 5.1 The Techno-Mathematics of the Current Account Mortgage 5.2 Workplace Observations in Mortgage Sales and Customer Service 5.3 Current Account Mortgages: Tebo and Learning Opportunities 5.4 Outcomes for Learning and Practice 5.5 Conclusions 6. Summary, Reflections and Conclusions 6.1 Key Findings 6.2 Understanding Systems with Models: Pseudo-Mathematical and Techno-Mathematical 6.3 Successes and Challenges 6.4 Conclusions and Implications Appendix: Details of Fieldwork – Companies and Organisations Which Participated In the Research Appendix: Further Reading on the Techno-Mathematical Literacies Research Bibliography