Archives for academic performance
Exploring Artificial Intelligence Tool Adoption in a Higher Education Faculty’s Pedagogical Practices through CHAT: Supporting International Students in Improving Academic Performance
Artificial Intelligence tools are increasingly utilised across various domains, including higher education, owing to their potential to enhance teaching and learning. This study examines how tutors in a UK higher education faculty adopt AI tools to help international students improve their academic performance. International students often encounter challenges, such as language barriers, cultural differences, and adapting to new educational systems, which can adversely affect their academic success and learning experience. AI tools can potentially mitigate these challenges and support international students. Findings from semi-structured interviews with four tutors reveal the types of AI tools used, factors influencing their adoption, and their perceived effectiveness. The study identifies challenges in integrating AI tools, framed as secondary contradictions through Cultural Historical Activity Theory (CHAT), and offers recommendations for effective integration. These insights can guide faculty policies and training programmes to improve international students' academic outcomes and enhance AI integration in teaching practices.
Impact of Knowledge Management Strategies on Academic Performance in the Context of the Transition to Education 4.0
The concept of Education 4.0 emerged linked to trends regarding Industry 4.0 and Internet 4.0 and is based on the integration of emerging technologies to revolutionize the way education is delivered. In the current paper, the authors analyse the current trends regarding knowledge management strategies deployed in Education 4.0 and propose a set of possible approaches which take into account knowledge management practices for an efficient transition to Education 4.0. The set of possible approaches and Industry 4.0 tools that could facilitate the transition have been organized in a structured, easy to follow model based on a four-stage process that relies on the feedback loops from both the process inputs and outputs. Using the proposed model facilitates the transition to Education 4.0 and helps practitioners understand the main aspects of each stage and select the Industry 4.0 tools that can be used in their respective context in order to yield most benefits.