Arianna Mazzeo, McCall MacBain Postdoctoral Fellow, Faculty of Health Sciences, McMaster University
Some medical students in Canada are collaborating in a virtual class with design engineering students in Italy. Their mutual goals are to enhance their preparedness and insights regarding their respective real-world professional challenges by working together online in a scenario.
The students log in to an online simulation of a virtual emergency room. The medical students are assigned doctor and nurse avatars, and the engineering students have IT specialist or designer avatars. The scene plays out in response to the collaborative actions the students take.
This is a real learning experience supported by educators at McMaster University’s Faculty of Health Sciences. Doctors and nurses are engaged in a continuing professional development course with professor of medicine Teresa Chan, who is also associate dean of continuing professional development.
Learning through scenarios and simulations in fields from health care to education isn’t new. But this example provides a glimpse into an expanded future of teaching and learning in post-secondary education in virtual environments.
The ‘co-learning’ open classroom
I am a design researcher, learning innovator and artist whose research focuses on education technology to look for new ways of learning and teaching.
I see students learning together through scenario-based learning, bolstered by artificial intelligence, as a growing trend, and I am interested in how universities can integrate insights from designers committed to enhancing stronger and more participatory civic engagement. Whether collaborative learning is peer-to-peer or in larger groups, the benefits for participants include enhanced critical thinking.
In order for our society to see innovation in virtual learning, we need good design principles and tools for knowledge, sharing and growing. My research, applied practice and teaching at Harvard University’s master’s program in design engineering has been about developing collaborative learning or “co-learning” as a methodology and learning style. This learning is based on design principles such as equality, accessibility, diversity, inclusion and collaboration to solve real problems.
Co-learning can unfold in positive when people collaborate either fully online or in hybrid situations (online and in-person).
Co-learning is about setting up ideal conditions for learning in a peer-to-peer context, whether in community or civic settings focused on civic change or innovation in groups or in formal education.
In an online classroom, co-learning involves interactive course content as a way to create scenarios where students can act and perform, improvise and talk about topics of relevance as a group.
Video: Doctor's high-tech home setup shows just how much things have changed (cbc.ca)
The co-learning open classroom provides students with opportunities to observe and for faculty to listen and co-learn at their own pace. Video-based learning activities and interactive virtual spaces foster students’ work as a team. Virtual learning affords opportunities for such teams to collaborate across geographies. Collaboration is a mindset and a method.
Virtual teaching assistants
Artificial intelligence (AI) also has a role in future co-learning. For example, a course instructor or facilitator video records a lecture on a subject area they want to share. This allows the same video to be viewed by one student or thousands of students.
Through a common platform, students from different parts of the world could ask for help from a virtual teaching assistant: a chatbot.
Read more: AI-powered chatbots, designed ethically, can support high-quality university teaching
The facilitator of the in-person classes could also use the virtual teaching assistant to help students learn from each other: students could use an app on their mobile devices, while the facilitator can guide, mentor and interact with the groups.
No additional facilitators are needed to teach multiple sections of the same course. The facilitator is both a guide and a mediator.
New levels of collaboration and ways of learning
Using such hybrid methods, people globally could share facts, dialogues, materials and projects on the base of common interest to learn by doing. Stories and insights from science and art could be shared and new insights co-created.
Virtual collaboration could also help break academic silos by bringing together people in different fields to realize applied interdisciplinary approaches.
These design-based research scenarios may redefine the way we can make learning more collaborative, and also increase students’ access to talented educators around the world.
This article is republished from The Conversation, a nonprofit news site dedicated to sharing ideas from academic experts.
Read more:
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Arianna Mazzeo does not work for, consult, own shares in or receive funding from any company or organisation that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.
Using artificial intelligence in health sciences education requires interdisciplinary collaboration and risk assessment
Elif Bilgic, Assistant Professor, Pediatrics, McMaster University
Over the past five years, there has been an increase in research and development related to the use of artificial intelligence (AI) in health sciences education in fields such as medicine, nursing and occupational therapy. AI-enhanced technologies have been shown to have educational value and offer flexibility for students. For example, learning scenarios can be repeated and completed remotely, and educational experiences can be standardized.
However, AI’s applications in health sciences education need to be explored further.
To better understand advances in research and applications of AI as a part of the education of health sciences students, we conducted a comprehensive literature review. We also hosted a virtual panel consisting of scholars across Canadian institutions and educational technology companies who are actively involved in AI and health sciences education.
Our panel investigated three themes: current applications of educational theories, performance assessment, and current advances; the role of educational associations and industry; and legal and ethical considerations.
Interdisciplinary collaboration
One of our key findings was that it is important to develop interdisciplinary partnerships and collaborative environments. The effective development and implementation of AI-enhanced educational technologies require different capabilities. These include: possessing the technical know-how required to build and develop AI, understanding the needs of students and educators, applying educational theories to content development and assessment, and considering any legal and ethical issues.
Based on our work, majority of the published studies do not have interdisciplinary teams, hence the call for interdisciplinary collaborations. However, one example that was successful in bringing together individuals from different disciplines is an intelligent tutoring system designed to help medical students with their diagnostic reasoning skills through virtual patient cases.
Therefore, an interdisciplinary team would be able to produce and deliver AI-enhanced education effectively. To achieve this, partnerships should include industry, educational societies, hospitals and universities. Collaborative teams would include researchers and practitioners from health sciences, law, ethics, education, computer science, engineering and other fields.
Enhancing education with educational societies
Educational societies not only play an important role in supporting research and development, but also the use of AI-enhanced educational technologies across health sciences programs.
Future health scientists will require new skills in technology and AI, and the ability to apply them during training and clinical duties. These include understanding issues related to privacy, discrimination, ethical and legal concerns and inherent biases that may create health inequities.
Read more: Artificial intelligence in medicine raises legal and ethical concerns
For example, the Royal College of Physicians and Surgeons of Canada, which oversees the training of medical specialists in Canada, has a role in creating new initiatives and support systems to address these emerging needs. The college could add an additional component to the medical curriculum that focuses on core information necessary to use these AI-enhanced technologies. Practising physicians will also need the support of the college to develop technology-supported clinical skills.
Ultimately, if we want to enhance research and applications of AI in health sciences education, collaboration across different fields is key. This is so that both effective and equitable AI technologies can be developed, and that in the future, health scientists can use these technologies while understand their risks and benefits.
This article is republished from The Conversation, a nonprofit news site dedicated to sharing ideas from academic experts.
Read more:
Healthcare’s technology revolution means a boost for jobs in IT
Why medical technology often doesn’t make it from drawing board to hospital
Jason M. Harley receives funding from The Social Sciences and Humanities Research Council of Canada.
Elif Bilgic does not work for, consult, own shares in or receive funding from any company or organisation that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.
Elif Bilgic, Assistant Professor, Pediatrics, McMaster University
Jason M. Harley, Assistant Professor, Medicine and Health Sciences, McGill University
Over the past five years, there has been an increase in research and development related to the use of artificial intelligence (AI) in health sciences education in fields such as medicine, nursing and occupational therapy. AI-enhanced technologies have been shown to have educational value and offer flexibility for students. For example, learning scenarios can be repeated and completed remotely, and educational experiences can be standardized.
However, AI’s applications in health sciences education need to be explored further.
To better understand advances in research and applications of AI as a part of the education of health sciences students, we conducted a comprehensive literature review. We also hosted a virtual panel consisting of scholars across Canadian institutions and educational technology companies who are actively involved in AI and health sciences education.
Our panel investigated three themes: current applications of educational theories, performance assessment, and current advances; the role of educational associations and industry; and legal and ethical considerations.
Interdisciplinary collaboration
One of our key findings was that it is important to develop interdisciplinary partnerships and collaborative environments. The effective development and implementation of AI-enhanced educational technologies require different capabilities. These include: possessing the technical know-how required to build and develop AI, understanding the needs of students and educators, applying educational theories to content development and assessment, and considering any legal and ethical issues.
Based on our work, majority of the published studies do not have interdisciplinary teams, hence the call for interdisciplinary collaborations. However, one example that was successful in bringing together individuals from different disciplines is an intelligent tutoring system designed to help medical students with their diagnostic reasoning skills through virtual patient cases.
Therefore, an interdisciplinary team would be able to produce and deliver AI-enhanced education effectively. To achieve this, partnerships should include industry, educational societies, hospitals and universities. Collaborative teams would include researchers and practitioners from health sciences, law, ethics, education, computer science, engineering and other fields.
Enhancing education with educational societies
Educational societies not only play an important role in supporting research and development, but also the use of AI-enhanced educational technologies across health sciences programs.
Future health scientists will require new skills in technology and AI, and the ability to apply them during training and clinical duties. These include understanding issues related to privacy, discrimination, ethical and legal concerns and inherent biases that may create health inequities.
Read more: Artificial intelligence in medicine raises legal and ethical concerns
For example, the Royal College of Physicians and Surgeons of Canada, which oversees the training of medical specialists in Canada, has a role in creating new initiatives and support systems to address these emerging needs. The college could add an additional component to the medical curriculum that focuses on core information necessary to use these AI-enhanced technologies. Practising physicians will also need the support of the college to develop technology-supported clinical skills.
Ultimately, if we want to enhance research and applications of AI in health sciences education, collaboration across different fields is key. This is so that both effective and equitable AI technologies can be developed, and that in the future, health scientists can use these technologies while understand their risks and benefits.
This article is republished from The Conversation, a nonprofit news site dedicated to sharing ideas from academic experts.
Read more:
Healthcare’s technology revolution means a boost for jobs in IT
Why medical technology often doesn’t make it from drawing board to hospital
Jason M. Harley receives funding from The Social Sciences and Humanities Research Council of Canada.
Elif Bilgic does not work for, consult, own shares in or receive funding from any company or organisation that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.
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