Webinar Empowering qualitative research methods with artificial intelligence
Artificial Intelligence is one of the fastest growing disciplines, disrupting many sectors. Originally mainly for computer scientists and engineers, it has been expanding its horizons and empowering many other disciplines contributing to the development of many novel applications in many sectors. These include medicine and health care, business and finance, psychology and neuroscience, physics and biology. However, one of the disciplines in which artificial intelligence has not yet been fully explored and exploited yes is education. In this discipline, many research methods are employed by scholars and lecturers to investigate the impact of different instructional approaches on learning and on the acquisition of skills and knowledge by learners. One of these methods is qualitative research, a scientific method grounded in observations that manipulates and analyses non-numerical data. It focuses on seeking answers to why and how a particular observed phenomenon occurs rather than on its occurrences. This study is aimed at exploring and discussing the impact of artificial intelligence on qualitative research methods in education. In particular, it focuses on how artificial intelligence can empower qualitative research methods, employed in education, for enhancing teaching and learning.
Dr. Luca Longo is an Academic, National Teaching Hero, AI researcher and TEDx speaker who has a deep passion for science and has won various awards both for his research work and for his teaching. He is actively engaged in the dissemination of scientific material to the public as his TEDx talks demonstrate. With his team of doctoral and post-doctoral researchers, he conducts fundamental research in Explainable Artificial Intelligence, Defeasible Reasoning and Non-monotonic Argumentation. He also performs applied research in Machine Learning and predictive data analytics, mainly applied to the problem of mental workload modelling. He is an advocate of motivational teaching and strongly supports learning through passion. Having gained invaluable education, work experience and international recognition he is strongly motivated to revolutionise the science of mental workload, pave a new research path with a significant impact for the future societies and become a world leader in his field.
Artificial Intelligence is one of the fastest growing disciplines, disrupting many sectors. Originally mainly for computer scientists and engineers, it has been expanding its horizons and empowering many other disciplines contributing to the development of many novel applications in many sectors. These include medicine and health care, business and finance, psychology and neuroscience, physics and biology. However, one of the disciplines in which artificial intelligence has not yet been fully explored and exploited yes is education. In this discipline, many research methods are employed by scholars and lecturers to investigate the impact of different instructional approaches on learning and on the acquisition of skills and knowledge by learners. One of these methods is qualitative research, a scientific method grounded in observations that manipulates and analyses non-numerical data. It focuses on seeking answers to why and how a particular observed phenomenon occurs rather than on its occurrences. This study is aimed at exploring and discussing the impact of artificial intelligence on qualitative research methods in education. In particular, it focuses on how artificial intelligence can empower qualitative research methods, employed in education, for enhancing teaching and learning.
Dr. Luca Longo is an Academic, National Teaching Hero, AI researcher and TEDx speaker who has a deep passion for science and has won various awards both for his research work and for his teaching. He is actively engaged in the dissemination of scientific material to the public as his TEDx talks demonstrate. With his team of doctoral and post-doctoral researchers, he conducts fundamental research in Explainable Artificial Intelligence, Defeasible Reasoning and Non-monotonic Argumentation. He also performs applied research in Machine Learning and predictive data analytics, mainly applied to the problem of mental workload modelling. He is an advocate of motivational teaching and strongly supports learning through passion. Having gained invaluable education, work experience and international recognition he is strongly motivated to revolutionise the science of mental workload, pave a new research path with a significant impact for the future societies and become a world leader in his field.
