Cultural Intelligence in Teaching and Learning

Rajaram, Kumaran

doi:10.1007/978-981-19-9201-8_2

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Cited by 4 publications

References 178 publications

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Deep Intelligence: Fostering Human Deep Learning, Amplifying Our Intelligence, and Supporting a Human Rennaisance

Bauschard,

Quidwai

2023

SSRN Journal

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Deep Intelligence: Fostering Human Deep Learning, Amplifying Our Intelligence, and Supporting a Human Rennaisance

Bauschard,

Quidwai

2023

SSRN Journal

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Disrupting Algorithmic Culture

Hutson,

Plate

2023

Generative AI in Teaching and Learning

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Academia must reevaluate its model in the face of AI and ML. Disciplinary boundaries are outdated, requiring interdisciplinary research and collaboration to understand algorithms and ML. Institutions should integrate new technologies while recognizing the importance of human oversight and collaboration in the human-AI partnership. The “human-in-the-loop” model enables new knowledge creation. Human fact-checking and critical evaluation are vital due to AI limitations. Empathy builds trust between humans and AI, ensuring alignment with human values. The illogical, irrational, and emotional aspects of human cognition drive creativity. Through interdisciplinary collaboration, human oversight, empathy, and leveraging unique human qualities, academia can navigate technological advancements and foster a symbiotic relationship with AI.

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The Dawn of the Algorithmic Researcher

2024

Advances in Knowledge Acquisition, Transfer, and Management

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The first chapter traces the ascension of artificial intelligence (AI) within the academic sphere, highlighting pivotal developments that have shaped its role in research. First, an historical overview illustrates how AI evolved from simple computational tools to complex systems capable of performing tasks that traditionally required human intelligence. This section discusses key milestones in AI development and adoption across various disciplines, underscoring the transformative impact of these technologies on academic inquiry and methodology. Next, the technical and theoretical foundations of LLMs, such as GPT and GANs, shall be discussed. It explores their architecture, training processes, and the underlying algorithms that enable their ability to understand and generate human-like text, setting the stage for their application in academic research and beyond.

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Cultural Intelligence in Teaching and Learning

Cited by 4 publications

References 178 publications

Deep Intelligence: Fostering Human Deep Learning, Amplifying Our Intelligence, and Supporting a Human Rennaisance

Deep Intelligence: Fostering Human Deep Learning, Amplifying Our Intelligence, and Supporting a Human Rennaisance

Disrupting Algorithmic Culture

The Dawn of the Algorithmic Researcher

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