Author name: Mrupset

Chapter 3: AI regulations in higher education

With the increasing integration of artificial intelligence in universities, the necessity for effective regulation becomes paramount. International organizations such as UNESCO and the OECD are proactively working to develop guidelines that ensure ethical and responsible AI usage in educational contexts. These regulations tackle pressing issues like student data privacy, algorithmic accountability, and equitable access to […]

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Chapter 2: How to implement intelligent tutoring systems in higher education?

The implementation of Intelligent Tutoring Systems (ITS) within European universities is fundamentally reshaping the way students engage with learning materials. These innovative systems provide tailored educational content while actively working to mitigate dropout rates through timely interventions for at-risk students. Utilizing predictive analytics, ITS can identify early warning signs of academic struggle, enabling educators to

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Chapter 1: What are intelligent tutoring systems?

In recent years, Intelligent Tutoring Systems (ITS) have dramatically transformed the educational landscape. These AI-driven tools are specifically designed to provide personalized learning experiences, adjusting in real-time to cater to each student’s unique needs. By harnessing advanced technologies such as data analytics and machine learning, ITS can meticulously monitor student performance, allowing educators to identify

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Imagining the HITS platform

During the first project meeting in Bucharest (RO), the Consortium started a fertile brainstorming on the features and functionalities of the HITS platform. Guided by Giordano Sanchioni from Pluriversum, the Consortium has worked to define the MUST-HAVE elements and the risks for a digital platform for students’ support in Higher Education. We are collecting views

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The HITS handbook: a European perspective on the use of AI in Higher Education to improve students’ support

The project Consortium has started a thorough desk research to investigate pros and cons of the use of AI in higher education. With a European research team, good practices, theoretical and methodological approaches together with European regulations are being investigated. The book consists of 6 chapters. The last one will arrive in autumn to present

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A European research to discover needs and priorities to better integrate AI in students’ services in Higher Education

The work of the project starts with mapping needs and priorities of higher education (HE) regarding digital education and AI-supported tutoring approaches. The objectives include mapping effective AI tutoring methods and developing ethical guidelines for AI implementation in academic settings. This group of activities will consist of desk and field research which will result into

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