TY - CHAP
T1 - Smart Learning Applications
T2 - Leveraging LLMs for Contextualized and Ethical Educational Technology
AU - Alier, Marc
AU - Casañ, María José
AU - Filvà, Daniel Amo
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
PY - 2024
Y1 - 2024
N2 - This paper introduces the concept of “Smart Learning Applications,” an emerging new category of educational technology that leverages the capabilities of Large Language Models (LLMs) like ChatGPT. Distinct from existing third-party chatbots, these proposed applications aim to provide real-time content generation, advanced query processing, and personalized learning experiences. These features are integrated within a framework managed by the educational institution, ensuring quality, relevance, and confidentiality in an ethical manner. The paper delves into the technical underpinnings necessary for the development of these applications, with a focus on the role of embeddings and context in enhancing their utility and adaptability. It also addresses challenges and ethical considerations, such as data security and academic integrity. The paper concludes by outlining a strategy for the swift, iterative development and testing of Smart Learning Applications in a secure and responsible setting.
AB - This paper introduces the concept of “Smart Learning Applications,” an emerging new category of educational technology that leverages the capabilities of Large Language Models (LLMs) like ChatGPT. Distinct from existing third-party chatbots, these proposed applications aim to provide real-time content generation, advanced query processing, and personalized learning experiences. These features are integrated within a framework managed by the educational institution, ensuring quality, relevance, and confidentiality in an ethical manner. The paper delves into the technical underpinnings necessary for the development of these applications, with a focus on the role of embeddings and context in enhancing their utility and adaptability. It also addresses challenges and ethical considerations, such as data security and academic integrity. The paper concludes by outlining a strategy for the swift, iterative development and testing of Smart Learning Applications in a secure and responsible setting.
KW - Academic Integrity
KW - ChatGPT
KW - Contextualized Learning
KW - Data Security
KW - Educational Framework
KW - Educational Technology
KW - Ethical Considerations
KW - Large Language Models
KW - Personalized Learning
KW - Query Processing
KW - Real-time Content Generation
KW - Smart Learning Applications
UR - http://www.scopus.com/inward/record.url?scp=85201966205&partnerID=8YFLogxK
U2 - 10.1007/978-981-97-1814-6_18
DO - 10.1007/978-981-97-1814-6_18
M3 - Chapter
AN - SCOPUS:85201966205
T3 - Lecture Notes in Educational Technology
SP - 190
EP - 199
BT - Lecture Notes in Educational Technology
PB - Springer Science and Business Media Deutschland GmbH
ER -