Ovezova G.
PERSONALIZED LEARNING PATHS, INTELLIGENT TUTORING SYSTEMS, AND ADAPTIVE LANGUAGE ASSESSMENT: A SYNERGISTIC APPROACH *
Аннотация:
this research paper explores the convergence of personalized learning paths, intelligent tutoring systems (ITS), and adaptive language assessment. It investigates how these technologies can be integrated to create a more effective and efficient language learning experience. By leveraging data-driven insights and artificial intelligence, personalized learning paths can tailor educational content and strategies to individual learners needs, while ITS can provide real-time feedback and guidance. Adaptive language assessment can further enhance the learning process by continuously evaluating learners progress and adjusting instruction accordingly. This paper discusses the theoretical underpinnings, practical applications, and potential challenges associated with this synergistic approach.
Ключевые слова:
Personalized Learning, Intelligent Tutoring Systems, Adaptive Language Assessment, Data-Driven Instruction, Artificial Intelligence, Machine Learning, Natural Language Processing
Introduction.The landscape of language education has undergone significant transformations in recent years, driven by technological advancements and a growing emphasis on personalised learning. The integration of personalised learning paths, Intelligent Tutoring Systems (ITS) and adaptive language assessment represents a significant opportunity for transformative change in language instruction.The concept of Personalised Learning Paths is an important one in the context of language education. Such pathways are designed to cater to the specific needs, preferences and learning styles of individual learners. Such approaches entail the creation of bespoke learning experiences, informed by data-driven insights and learner profiles.Intelligent Tutoring Systems (ITS) ITS employ artificial intelligence to provide individualised instruction, feedback, and guidance. Such systems are capable of adapting to the progress of individual learners, identifying any deficiencies in their knowledge base, and offering targeted support.Adaptive Language Assessment This approach entails the continuous evaluation of learners performance, with subsequent adjustments to the instructional approach as needed. This enables more accurate assessment of language proficiency and more efficient learning.The integration of these components enables educators to establish a more effective and engaging language learning environment. The objective of this paper is to examine the theoretical underpinnings, practical applications, and potential challenges associated with this synergistic approach.Theoretical Foundations: Constructivist Learning Theory This theory places emphasis on the active role of learners in the construction of their own knowledge. The concept of personalised learning paths, when aligned with the principles of constructivism, serves to foster learner autonomy and agency.Adaptive learning is a method of education that employs data-driven algorithms to continuously adjust instruction based on learners performance. Adaptive learning systems employ data-driven algorithms to enable continuous adjustments to instructional content based on the performance of the learners in question. This approach is of central importance with regard to the concept of personalised learning paths and the field of adaptive language assessment.Intelligent Tutoring Systems (ITS) ITS are founded upon the principles of cognitive science and artificial intelligence. Such systems employ knowledge representation, machine learning, and natural language processing to provide intelligent tutoring.The convergence of personalised learning paths, intelligent tutoring systems (ITS) and adaptive language assessment is informed by a number of theoretical frameworks. These foundations provide the conceptual basis for the development and implementation of these technologies.1. Constructivist Learning Theory.The key principles of this theory are as follows:Active learning is defined as: Learners construct their own knowledge through interaction with the environment, thereby developing their understanding of the subject matter.The role of social interaction in this process is also significant. Collaborative learning and peer feedback are indispensable for the construction of knowledge.Reflective thinking is a cognitive process whereby an individual engages in conscious, thoughtful consideration of a particular subject or experience, allowing for the formulation of insights and the development of understanding. It is essential that learners engage in reflection on their experiences, facilitating the establishment of connections between new and existing knowledge.The relevance of this approach to personalised learning is as follows: The constructivist approach emphasises the importance of adapting the instructional design to align with the individual needs and experiences of learners. The implementation of personalised learning pathways and intelligent tutoring systems (ITS) can facilitate active learning, social interaction and reflective thinking.2. The key principles of Adaptive Learning Theory are as follows:The process of continuous assessment is integral to the constructivist approach to learning. The progress of learners is subject to regular monitoring and evaluation.Adaptive instruction is a pedagogical approach that entails modifying the instructional methods employed in response to the observed performance and needs of the learners. Instruction is modified in accordance with the performance and requirements of the learners.The process of making decisions based on data. Instructional decisions are I formed by data on learner behavior and outcomes.The relevance of this approach to personalized learning is as follows: The theoretical framework of adaptive learning provides the foundation for the development of adaptive language assessment and the capacity of Intelligent Tutoring Systems (ITS) to modify instructional approaches in real-time.The practical applications of personalized learning paths include:The creation of learner profiles based on demographic data, learning styles, and prior knowledge.The adaptation of content, activities and assessments to suit the specific requirements of each individual.The provision of personalized recommendations and resources.Intelligent Tutoring Systems:The provision of real-time feedback and explanations.The identification of knowledge gaps and the provision of targeted remediation.The ability to adapt to the pace and difficulty levels of learners is a key feature of effective learning environments.Adaptive Language Assessment:The continuous monitoring of learners progress allows for the adjustment of instructional methods in a timely manner.The provision of formative and summative assessments.The identification of areas of strength and weakness.The advantages of the Synergistic Approach include an enhanced level of learner engagement. The provision of personalized learning pathways and Intelligent Tutoring Systems (ITS) has the potential to enhance the engagement and motivation of language learners by catering to their individual interests and learning styles.It is reasonable to anticipate enhanced learning outcomes. The provision of tailored instruction and support enables these technologies to facilitate enhanced learningIn conclusion, the convergence of personalized learning paths, Intelligent Tutoring Systems (ITS), and adaptive language assessment represents a promising approach to enhancing language learning. By employing data-driven insights and artificial intelligence, educators can develop more effective, efficient, and engaging learning experiences. Further research should concentrate on the difficulties inherent in this approach and investigate potential new avenues for innovation.
Номер журнала Вестник науки №9 (78) том 1
Ссылка для цитирования:
Ovezova G. PERSONALIZED LEARNING PATHS, INTELLIGENT TUTORING SYSTEMS, AND ADAPTIVE LANGUAGE ASSESSMENT: A SYNERGISTIC APPROACH // Вестник науки №9 (78) том 1. С. 104 - 108. 2024 г. ISSN 2712-8849 // Электронный ресурс: https://www.вестник-науки.рф/article/17100 (дата обращения: 20.05.2025 г.)
Вестник науки © 2024. 16+