Daniel Xerri – författare
380 kr
Läs direkt efter köp
Human–AI Collaboration in Research: Practical Applications, Ethical Frameworks, and Future Directions positions human–AI collaboration (HAIC) as a defining feature of contemporary research ecosystems. The book examines the incorporation of AI across the research lifecycle, including research design, literature work, data collection and processing, analysis, interpretation, academic writing, and dissemination. It highlights the opportunities created by automation and generative systems, alongside the challenges raised for research integrity, accountability, transparency, privacy, and epistemic authority. Ethical and regulatory foundations are addressed through established frameworks such as the Belmont Report and the Declaration of Helsinki, as well as European governance instruments including the Ethics Guidelines for Trustworthy AI, the General Data Protection Regulation, and the EU Artificial Intelligence Act. By combining interdisciplinary perspectives from robotics, management research, and education, the volume translates abstract ethical principles into concrete research-relevant practices, offering a coherent and human-centred approach to trustworthy AI-supported inquiry.
The book offers original, research-ready frameworks and applied guidance for responsible HAIC, combining real-world case studies with practical strategies for trustworthy AI use. It equips researchers, educators, and management scholars with tools for human oversight, transparency, bias mitigation, and accountable AI-supported workflows, ensuring scientific rigour alongside innovation.
380 kr
Läs direkt efter köp
Human–AI Collaboration in Research: Practical Applications, Ethical Frameworks, and Future Directions positions human–AI collaboration (HAIC) as a defining feature of contemporary research ecosystems. The book examines the incorporation of AI across the research lifecycle, including research design, literature work, data collection and processing, analysis, interpretation, academic writing, and dissemination. It highlights the opportunities created by automation and generative systems, alongside the challenges raised for research integrity, accountability, transparency, privacy, and epistemic authority. Ethical and regulatory foundations are addressed through established frameworks such as the Belmont Report and the Declaration of Helsinki, as well as European governance instruments including the Ethics Guidelines for Trustworthy AI, the General Data Protection Regulation, and the EU Artificial Intelligence Act. By combining interdisciplinary perspectives from robotics, management research, and education, the volume translates abstract ethical principles into concrete research-relevant practices, offering a coherent and human-centred approach to trustworthy AI-supported inquiry.
The book offers original, research-ready frameworks and applied guidance for responsible HAIC, combining real-world case studies with practical strategies for trustworthy AI use. It equips researchers, educators, and management scholars with tools for human oversight, transparency, bias mitigation, and accountable AI-supported workflows, ensuring scientific rigour alongside innovation.
988 kr
Skickas inom 10-15 vardagar
1 468 kr
Skickas inom 10-15 vardagar
1 572 kr
Skickas inom 5-8 vardagar
1 986 kr
Läs direkt efter köp
629 kr
Skickas inom 5-8 vardagar
1 572 kr
Skickas inom 10-15 vardagar
2 061 kr
Kommande
1 468 kr
Skickas inom 10-15 vardagar
1 833 kr
Läs direkt efter köp
This book advocates that teachers should play an active role in high-stakes language testing and that more weight should be given to teacher judgement. This is likely to increase the formative potential of high-stakes tests and provide teachers with a sense of ownership. The implication is that the knowledge and skills they develop by being involved in these tests will feed into their own classroom practices. The book also considers the arguments against teacher involvement, e.g. the contention that teacher involvement might entrench the practice of teaching to the test, or that teachers should not be actively involved in high-stakes language testing because their judgement is insufficiently reliable. Using contributions from a wide range of international educational contexts, the book proposes that a lack of reliability in teacher judgement is best addressed by means of training and not by barring educators from participating in high-stakes language testing. It also argues that their involvement in testing helps teachers to bolster confidence in their own judgement and develop their assessment literacy. Moreover, teacher involvement empowers them to play a role in reforming high-stakes language testing so that it is more equitable and more likely to enhance classroom practices. High-stakes language tests that adopt such an inclusive approach facilitate more effective learning on the part of teachers, which ultimately benefits all their students.