Adult learning and technology in working-class life

著者

    • Sawchuk, Peter H.

書誌事項

Adult learning and technology in working-class life

Peter H. Sawchuk

(Learning in doing : social, cognitive, and computational perspectives)

Cambridge University Press, 2003

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注記

Includes bibliographical references and index

内容説明・目次

内容説明

To date little is known about the everyday activities that make up the majority of people's learning lives. This book presents a critical approach to learning using situated learning and activity theory, drawing on the writings of Marx, Gramsci, Marxist-feminists, as well as the sociology of Bourdieu. Though many have demonstrated that schooling and adult training are deeply affected by issues of social class, this book explodes the myth that everyday learning, despite its apparent openness and freedom, can be understood as class-neutral. Based on life-history interviews, selected ethnographic observations in homes and factories, large-scale survey materials as well as microanalysis of human computer interaction, the analysis explores learning across the various spheres of 'working-class life'. The author draws on his own experience as a factory worker, labour educator and academic to offer the most detailed examination of computer literacy and lifelong learning practice amongst working-class people currently available.

目次

  • 1. Understanding learning, technology and social class: concepts and claims
  • 2. A historical materialist examination of theories of adult learning
  • 3. 'That's technology': understanding working-class perspectives on computer technology
  • 4. Microanalysis of worker's computer learning: two case studies of computer learning
  • 5. Working class computer learning networks: exploring the elements of collectivity and class habitus
  • 6. Understanding working-class standpoints in computer learning
  • 7. Oral culture, computer learning and social class
  • 8. Material barriers in working-class computer learning
  • 9. Contradiction and commodification in working-class computer learning
  • 10. Conclusions and implications.

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