Developing for personalised learning: the long road from educational objectives to development and feedback

Tsatiris, George; Karpouzis, Kostas

doi:10.48550/arxiv.2101.11333

Cited by 3 publications

(3 citation statements)

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“…Another significant advantage of GenAI-driven personalized learning is the heightened level of student engagement it fosters [2], [7]. GenAI tools can ignite a deeper interest and motivation in learners by aligning educational content with students' interests and proficiency levels.…”

Section: Personalization In Educationmentioning

confidence: 99%

Tailoring Education with GenAI: A New Horizon in Lesson Planning

Karpouzis,

Pantazatos,

Taouki

et al. 2024

Preprint

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The advent of Generative AI (GenAI) in educationpresents a transformative approach to traditional teaching methodologies, which often overlook the diverse needs of individual students. This study introduces a GenAI tool, based on advanced natural language processing, designed as a digital assistant for educators, enabling the creation of customized lesson plans. The tool utilizes an innovative feature termed ’interactive mega-prompt,’ a comprehensive query system that allows educators to input detailed classroom specifics such as student demographics, learning objectives, and preferred teaching styles.This input is then processed by the GenAI to generate tailored lesson plans. To evaluate the tool’s effectiveness, a comprehensive methodology incorporating both quantitative (i.e., % of time savings) and qualitative (i.e., user satisfaction) criteria was implemented, spanning various subjects and educational levels, with continuous feedback collected from educators through a structured evaluation form.Preliminary results show that educators find the GenAI-generated lesson plans effective, significantly reducing lesson planning time and enhancing the learning experience by accommodating diverse student needs. This AI-driven approach signifies a paradigm shift in education, suggesting its potential applicability in broader educational contexts, including specialeducation needs (SEN), where individualized attention and specific learning aids are paramount. The paper has been accepted for presentation at IEEE EDUCON 2024.

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Section: Personalization In Educationmentioning

confidence: 99%

Tailoring Education with GenAI: A New Horizon in Lesson Planning

Karpouzis,

Pantazatos,

Taouki

et al. 2024

Preprint

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“…In this case, educators can adapt their content with respect to scientific depth or language, making it more relevant to students with different skills and competencies. This approach is very popular with language learning (Tsatiris, 2021), and recently found its way to commercial applications, such as Duolingo. In this context, educators, either humans or an application, can select the suitable content with respect to the learning objectives of a particular module, the individual learning needs and preferences of a student, and the means of presentation and testing predicted to be more interesting for them.…”

Section: Generative Ai As An Opportunity For Educationmentioning

confidence: 99%

Legal and ethical considerations regarding the use of ChatGPT in education

Panagopoulou-Koutnatzi¹,

Parpoula²,

Karpouzis³

2023

Preprint

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Artificial intelligence has evolved enormously over the last two decades, becoming mainstream in different scientific domains including education, where so far, it is mainly utilized to enhance administrative and intelligent tutoring systems’ services and academic support. ChatGPT, an artificial intelligence-based chatbot, developed by OpenAI and released in November 2022, has rapidly gained attention from the entire international community for its impressive performance in generating comprehensive, systematic, and informative human-like responses to user input through natural language processing. Inevitably, it has also rapidly posed several challenges, opportunities, and potential issues and concerns raised regarding its use across various scientific disciplines. This paper aims to discuss the legal and ethical implications arising from this new technology, identify potential use cases, and enrich our understanding of Generative AI, such as ChatGPT, and its capabilities in education.

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“…Alshammari et al (2016) discussed adaptivity in the context of e-learning and their results indicated that the adaptive version of their learning system had better results in learning effectiveness and perceived usability level, which (according to their analysis) may lead to learners who are more satisfied, engaged, and motivated. The conceptual advantages of adaptivity in a learning system have to do with identifying or selecting the particular areas of interest for each learner and providing them with teaching material and activities suited to those needs; beyond this approach, Mavrikis et al (2019) and Tsatiris and Karpouzis (2021) designed an adaptive system which responds not only to the particular aspects of language that need to be taught but also to the competence level of each learner: beginning students are presented with introductory material, which they need to master in order to proceed to more advanced aspects, while better performing or more advanced learners skip this part and focus on more sophisticated gameful exercises, avoiding the inevitable boredom of going through a content that is too easy for someone's level, according to Karpouzis and Yannakakis (2016).…”

Section: Introductionmentioning

confidence: 99%

Adaptive game-based learning in education: a systematic review

Chiotaki

Poulopoulos

Karpouzis

2023

Front. Comput. Sci.

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The advent and abundance of mobile devices and network connectivity have provided learners of all ages with access to potentially unlimited sources of educational material, from pre-school activities to conventional and after-school courses and continuing education. One of the challenges that learners face is how to locate and access interesting contents suited to their preferences and, more importantly, to the level of expertise and individual needs. From the point of view of content creators and educators, adapting the content and the experience to each learner usually leads to better user retention and a more meaningful and deeper learning experience. In this study, we utilized the PRISMA review methodology to examine research on content and experience adaptivity in educational contexts and report on the authors' findings. Consisting of well-defined steps (keyword-based retrieval, study scope definition, result filtering, and grouping and analysis), the systematic nature of this methodology ensures its objectivity and replicability at a future stage or replicated by other researchers.

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Developing for personalised learning: the long road from educational objectives to development and feedback

Cited by 3 publications

References 0 publications

Tailoring Education with GenAI: A New Horizon in Lesson Planning

Tailoring Education with GenAI: A New Horizon in Lesson Planning

Legal and ethical considerations regarding the use of ChatGPT in education

Adaptive game-based learning in education: a systematic review

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