Overview

Facts

Project number: 101086100

Project name: Higher Education Classroom Of the Future

Project acronym: HECOF

Call: ERASMUS-EDU-2022-PI-FORWARD

Topic: ERASMUS-EDU-2022-PI-FORWARD-LOT1

Type of action: ERASMUS-LS

Service: EACEA/A/02

Project starting date: fixed date: 1 January 2023

Project duration: 30 months

Coordinator: KONNEKT ABLE TECHNOLOGIES LIMITED

Rationale

The potential of AI in education is vast, particularly in the areas of tutoring, assessment, and personalized learning, and many possibilities are yet to be discovered. While AI innovation in education has evolved from laboratory scenarios to real-life learning contexts, the greatest promise of AI lies in personalizing learning through adaptive learning, machine learning, ontologies, semantic technologies, natural language processing, and deep learning. A learner-focused AI system can help students study a subject, suggest adaptive learning paths to achieve learning goals, predict student performance, identify their strengths and weaknesses, and recommend ways to improve through tests or practices. Despite the worldwide interest in AI, research on its application in higher education is still in its early stages. AI will mainly impact personalized education by providing automated assistance, especially in virtual interaction contexts. VR technologies are also promising in the “Edtech” space due to their immersive nature, ability to offer virtual experiences, and potential to mitigate barriers from cost or distance. Adaptive technologies and VR tools make the educational process more interactive, engaging, and contextual, and VR games and simulations provide highly interactive and engaging learning experiences for learners in risk-prone environments. AI can be applied to control and adapt VR to provide personalized experiences, as well as feedback and analytics that offer deep insights into learning and behavior. HECOF proposes a transdisciplinary approach involving partners from different sectors to push forward the state-of-the-art in learning technologies by creating a VR-immersive and AI-adaptive pedagogical model for chemical engineering students. The HECOF system will integrate VR and AI for simulation-based learning, classify students based on proficiency performance benchmarks, adjust to individual needs detected by AI algorithms, and provide solutions, support, and educational measures that respond to adaptive education models. The project will also involve training teachers on the use of the HECOF system before the pilot activities begin and using a co-design process for system development, prototyping, and testing with users (students and teachers). The project will cater to the needs of students of different genders, disabilities, and learning outcomes by involving them in the co-design process.

HECOF's Goal and Objectives

The HECOF initiative aims to revolutionize higher education teaching practices and education policies by creating a personalized and adaptive learning system that utilizes digital data from students’ immersive learning experiences and leverages computational analysis from data science and AI. The project will focus on the field of Chemical Engineering and involve teachers and students from two pilot universities in its design and implementation. Additionally, HECOF will address ethical and legal concerns surrounding AI by providing recommendations on the responsible use of AI for personalized learning. By fostering the development of safe and lawful AI, HECOF will support the first priority of the Digital Education Action Plan and contribute to building a high-performing digital education ecosystem. The initiative will also help to educate educational institutions on how to maximize the benefits of digital technology for teaching and learning at all levels and across all sectors.

Primary Objective

The primary goal of the HECOF project is to drive systemic change in higher education by promoting innovation in teaching practices and national education reforms. This will be achieved by developing and testing an innovative, personalized, and adaptive approach to teaching that utilizes digital data from students’ learning activities in immersive environments, and incorporates computational analysis techniques from data science and AI.

Overall Objective

  1. To design and develop instructional content and personalized adaptive learning system in immersive learning environments with a conceptual focus on “Chemical Engineering” academic discipline.
  2. To engage teaching staff and students in shaping and co-designing the learning system.
  3. To foster the development and uptake of safe and lawful AI that respects fundamental rights by providing insights on ethical and legal issues around the design and ethical educational deployment of AI-based technologies for teaching and learning.
  4. To pilot and assess the performance of the HECOF prototype system at the EU level, in a real classroom setting in two pilot studies, in terms of (i) effective and adequate learning experience (completeness), (ii) perceived benefits compared to traditional pedagogical model (quality), and (iii) user experience (acceptance).
  5. To create awareness and understanding of the benefits and challenges of leveraging VR with AI for VRimmersive and AI-adaptive learning in the higher education sector with a view to kick-starting sustainable and systemic impact.
  6. To drive the policy agenda by formulating recommendations on the role and use of AI for personalised, adaptive learning in the higher education sector and by wide dissemination of the HECOF work at EU and national political level.

Expected Outcomes

  • The HECOF system is expected to increase motivation and engagement among students by providing more personalized education that meets their individual needs.
  • Students who use the HECOF system will develop self-directed, self-disciplined, and self-monitored thinking skills, as well as better communication and problem-solving abilities.
  • The use of emerging technologies such as AI and VR is expected to improve students’ competencies and skills in these areas.
  • The HECOF system is also expected to stimulate students’ interest in the chemical academic discipline, promoting psychological internal motivation to continue learning.
  • The teaching staff involved in the project will improve their digital competence in the implementation of emerging technologies in their teaching practices, better tracking students’ progress, and reducing administrative burden.
  • The project aims to inform policymakers from EU and national level about HECOF’s innovative approach and potential to become mainstreamed in the HE and VET sectors.
  • HECOF will promote the ethical application of trusted AI technology in education and share evidence-informed effective practices in using AI for learning, teaching, monitoring, and evaluation of education.
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