The Intertwined Histories of Artificial Intelligence and Education

Doroudi, Shayan

doi:10.1007/s40593-022-00313-2

Cited by 29 publications

(12 citation statements)

References 94 publications

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“…Another way we could define artificial intelligence is as computational models of human cognition. This is not how AI has traditionally been defined, however, it does reflect the goals of many early AI researchers who were also cognitive scientists (Doroudi, 2022). There are two different forms of computational models on human cognition: 1) ones that can actually emulate aspects of human cognition (e.g., a model that actually learns) and 2) ones that merely simulate aspects of human cognition (e.g., a model that simulates a learning process).…”

Section: Computational Models Of Human Cognitionmentioning

confidence: 99%

Learning About AI to Learn About Learning: Artificial Intelligence as a Tool for Metacognitive Reflection

Ojeda-Ramirez,

Rismanchian,

Doroudi

2023

Preprint

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Artificial intelligence (AI) has become ubiquitous in recent decades, but using AI in education is not a recent idea. Since the emergence of AI, there has been an interest in the relationship between AI and education, not only looking at AI as an applied tool to advance education but also investigating its value as an analogy to human intelligence. In this paper, we build on AI’s power to act as an analogy to human intelligence to conceptualize it as a tool for metacognitive reflection. This idea itself is actually several decades old but it has been largely ignored. Given the recent wave of interest in AI literacy, we position the value that AI can bring in helping children reflect on their own thinking and learning as another rationale for teaching AI, in addition to economic, social, and ethical considerations. Moreover, we propose four different approaches to AI that can serve as metacognitive tools: (1) viewing computation as AI, (2) mainstream data-driven AI, (3) large language models, and (4) computational models of human cognition. We contrast the potential of each strand to promote metacognition and provide some toy problems where AI can foster students’ learning about their own learning.

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Section: Computational Models Of Human Cognitionmentioning

confidence: 99%

Learning About AI to Learn About Learning: Artificial Intelligence as a Tool for Metacognitive Reflection

Ojeda-Ramirez,

Rismanchian,

Doroudi

2023

Preprint

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“…This systematic review explores the historical developments of AI integration for technical literacy, tracing its evolution, and highlighting key advancements and challenges (Adekanmbi, et. al., 2024, Doroudi, 2023. The early history of AI in education can be traced back to the 1960s and 1970s when researchers began exploring the potential of computers to enhance learning.…”

Section: History Of Advancements and Challenges In Ai Integration For...mentioning

confidence: 99%

Advancements and Challenges in Ai Integration for Technical Literacy: A Systematic Review

Babajide Tolulope Familoni,

Nneamaka Chisom Onyebuchi

2024

Eng. sci. technol. j.

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This systematic review explores the advancements and challenges associated with the integration of artificial intelligence (AI) in promoting technical literacy. Technical literacy is increasingly important in today's digital age, where understanding and utilizing technology are essential skills. AI has the potential to enhance technical literacy by providing personalized learning experiences, facilitating hands-on learning, and offering innovative tools and resources. However, the integration of AI in education also presents challenges, such as ensuring equitable access, addressing ethical considerations, and overcoming technical barriers. The review examines a range of studies and literature related to AI integration for technical literacy, focusing on key themes such as personalized learning, hands-on learning, and innovative tools. It highlights the potential of AI to transform technical education by providing tailored learning experiences that cater to individual needs and preferences. AI-driven tools, such as simulations, virtual laboratories, and intelligent tutoring systems, have been shown to enhance student engagement and understanding of technical concepts. Despite the benefits, the review also identifies challenges associated with AI integration, including the need for teacher training, concerns about data privacy, and the risk of reinforcing existing inequalities. Addressing these challenges requires careful planning, collaboration between educators and technology developers, and a commitment to ensuring equitable access to AI-driven educational resources. Overall, this review provides insights into the current state of AI integration for technical literacy and highlights the opportunities and challenges associated with this approach. By addressing these challenges and leveraging the potential of AI, educators can enhance technical literacy and prepare students for success in a technology-driven world. Keywords: Advancement, Challenges, AI, Integration, Technical Literacy.

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“…Artificial intelligence relies on computer systems to execute tasks and activities that functionally and traditionally rely on human cognition, especially in terms of learning and problem-solving [19,20]. AI comprises a wide range of technologies, including algorithms, machine learning, and neural networks [21,22].…”

Section: Artificial Intelligencementioning

confidence: 99%

You Can Handle, You Can Teach It: Systematic Review on the Use of Extended Reality and Artificial Intelligence Technologies for Online Higher Education

Lázaro

Duart

2023

Sustainability

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Over the past year, defined by the COVID-19 pandemic, we have witnessed a boom in applying key emerging technologies in education. In such challenging situations, technology and education expanded their work together to strengthen and interactively impact the learning process in the online higher education context. From a pedagogical perspective, extended reality (XR) and artificial intelligence (AI) were accessible toolboxes to amplify an active and learner-centered teaching method. Whether and how such activities will continue in a post-COVID-19 situation remains unclear. In this systematic literature review, we document the application of XR and AI in online higher education settings and build up an accurate depiction of their influence after the COVID-19 pandemic outbreak. A significant contribution of the thorough analysis conducted was the corroboration of the growing interest of these fast-emerging technologies and their impact on learner agency and outcomes, making online education more accessible, effective, engaging, collaborative, self-paced, and adapted to the diverse academic trajectories. The momentum brought about by the pandemic has served as an impulse for educators and universities to expand the use of these technologies progressively, meet new challenges, and shape the future of online higher education.

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The Intertwined Histories of Artificial Intelligence and Education

Cited by 29 publications

References 94 publications

Learning About AI to Learn About Learning: Artificial Intelligence as a Tool for Metacognitive Reflection

Learning About AI to Learn About Learning: Artificial Intelligence as a Tool for Metacognitive Reflection

Advancements and Challenges in Ai Integration for Technical Literacy: A Systematic Review

You Can Handle, You Can Teach It: Systematic Review on the Use of Extended Reality and Artificial Intelligence Technologies for Online Higher Education

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