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An AI-powered curriculum instructional hypergraph (knowledge graph) and intelligent hint system that triages student knowledge, curriculum materials and assessments to reduce attainment gaps

An AI-powered curriculum instructional hypergraph (knowledge graph) and intelligent hint system that triages student knowledge, curriculum materials and assessments to reduce attainment gaps
人工智能驱动的课程教学超图(知识图)和智能提示系统,可对学生知识、课程材料和评估进行分类,以缩小成绩差距
批准号:
10035378
负责人:
金额:
$44.59万
依托单位:
依托单位国家:
英国
项目类别:
Collaborative R&D
财政年份:
2022
资助国家:
英国
项目状态:
已结题
起止时间:
2022 至 --

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英文摘要
The COVID-19 pandemic, closed down schools, thereby disrupting learning and increasing the need for personalised learning platforms that improve transparency, efficacy and accountability of public education systems. Student attainment gaps are deepening inequality, costing national economies tens of billions in future GDP growth. The UK alone estimates that improving attainment for a single cohort (2030 students) can add £60-90bn to GDP (DfE 2022). Adaptive learning and assessment can help optimise the large sums of public and private funds invested in high-dosage tutoring and school intervention programs.Study Hall (SH) is developing a cutting-edge AI-based adaptive learning and assessment platform that can accelerate student progress on both high-stakes (summative) and low-stakes (formative) assessments. SH's Knowledge Graph (KG) maps individual student knowledge against curriculum and standardised assessments to identify who has learned it, who has mastered it, and who has dropped off so teachers can intervene. The innovative, AI-based, Intelligent Hint System (IHS) provides scaffolded Socratic hints. SH's social features motivate learners to study together inside and outside of school. Study Hall boosts engagement, and increases teaching and learning efficiency, saving taxpayers, teachers, parents and students time and money.Study Hall has an experienced team including Paul Butcher (CTO), Professor Paul Schrater (behavioural neuroscience and deep learning scientist), Micheal Milchiadis (Lead Engineer), Gary Shiels (Data Scientist), Aisling Henihan (Instructional Design Lead), Nathan Llewellyn (Product Owner) and Sofia Fenichell (Chief Product Officer).
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