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，还有许多可供探索的目的和目标。例如：确定适当的数据驱动的智能方法(例如ML/AI)，并开发一个分析各种评估的适应性框架。了解我们如何收集大量有关定性评估的可量化数据，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洞察力和潜在建议的干预措施，以提高反馈、绩效和成就。