Developing Novel Intelligent Approaches to Improve National Assessments, E-Learning, and Student Attainment

开发新颖的智能方法来提高国家评估、电子学习和学生成绩

• 批准号: 2759007
• 金额: --
• 依托单位: Swansea University
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2759007
• 关键词: Developing; Novel; Intelligent; Approaches; Improve

Further to the project domain and context, there are a wide selection of aims and objectives that could be explored. For example: To identify appropriate data-driven intelligentapproaches (e.g. ML/AI) and develop an adaptive framework for analysing a diverse range of assessments. To understand how we can gather large volumes of quantifiable data about qualitative assessments to provide deeper insight. Provide learners, teachers, schools and Pearson with a range of insight and potentially recommended interventions to enhance feedback, performance and attainment.

除了项目领域和背景之外，还有多种可以探索的目的和目标。例如：确定适当的数据驱动的智能方法（例如机器学习/人工智能）并开发用于分析各种评估的自适应框架。了解我们如何收集有关定性评估的大量可量化数据以提供更深入的见解。为学习者、教师、学校和培生提供一系列见解和可能推荐的干预措施，以增强反馈、表现和成就。