Scholarlink

<p>School operations have changed due to information technology. Personalized teaching for preschool children requires innovative and adaptable strategies for providing the best-afford experience and learning environment. Conventional teaching approaches may not always accommodate students’ learning styles. This can lower performance and involvement. The expanding variety of pre-schoolers necessitates creative evaluation and optimization methods that promote inclusion and success for all children. The article introduces a preschool teaching evaluation model to improve the students’ learning experience. In particular, the evaluation model is designed for various assessment strategies irrespective of personalization. The proposed model inputs the students’ learning feasibility and the teaching mode to evaluate the personalization adaptability. The fuzzy decision support system improves the evaluation based on the above factors. It evaluates student-specific indicators, including attentiveness, body language, and engagement, to determine instructional flexibility. The model uses real-time classroom observations and student assessments to find realistic approaches with low-to-high fuzzy derivatives. The proposed system is designed to compute the adaptability from both factors under low-to-high fuzzy derivatives. By defining the maximum feasibility range, the teaching strategy is optimized to meet the adaptability. Thus, the low-level strategies are discarded using adaptability measures to reduce personalization failures. The proposed model is verified using adaptability, feasibility, and mode improvements. Research shows that the fuzzy decision support system makes courses more adaptive and feasible in many contexts, particularly those that involve games, audiovisual approaches, and crafts. Preschoolers, parents, and teachers indicated increased enjoyment, fewer customization failures, and greater involvement. Fuzzy-based evaluation increased feasibility ratings and approach versatility. The research provides a valuable foundation for solving classroom customization difficulties in preschool settings, emphasizing data-driven, adaptive teaching techniques. This method enables scalable applications in early childhood education through fuzzy decision-making and real-time evaluations.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Design and Implementation Evaluation of Personalized and Differentiated Teaching Strategies for Preschool Children Based on Fuzzy Decision Support Systems

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年2月27日

查看全文
  • Yali Hou

摘要

School operations have changed due to information technology. Personalized teaching for preschool children requires innovative and adaptable strategies for providing the best-afford experience and learning environment. Conventional teaching approaches may not always accommodate students’ learning styles. This can lower performance and involvement. The expanding variety of pre-schoolers necessitates creative evaluation and optimization methods that promote inclusion and success for all children. The article introduces a preschool teaching evaluation model to improve the students’ learning experience. In particular, the evaluation model is designed for various assessment strategies irrespective of personalization. The proposed model inputs the students’ learning feasibility and the teaching mode to evaluate the personalization adaptability. The fuzzy decision support system improves the evaluation based on the above factors. It evaluates student-specific indicators, including attentiveness, body language, and engagement, to determine instructional flexibility. The model uses real-time classroom observations and student assessments to find realistic approaches with low-to-high fuzzy derivatives. The proposed system is designed to compute the adaptability from both factors under low-to-high fuzzy derivatives. By defining the maximum feasibility range, the teaching strategy is optimized to meet the adaptability. Thus, the low-level strategies are discarded using adaptability measures to reduce personalization failures. The proposed model is verified using adaptability, feasibility, and mode improvements. Research shows that the fuzzy decision support system makes courses more adaptive and feasible in many contexts, particularly those that involve games, audiovisual approaches, and crafts. Preschoolers, parents, and teachers indicated increased enjoyment, fewer customization failures, and greater involvement. Fuzzy-based evaluation increased feasibility ratings and approach versatility. The research provides a valuable foundation for solving classroom customization difficulties in preschool settings, emphasizing data-driven, adaptive teaching techniques. This method enables scalable applications in early childhood education through fuzzy decision-making and real-time evaluations.