Multimodal assessment of learning through educational games

通过教育游戏对学习进行多模式评估

• 批准号: 577563-2022
• 负责人: Khan, NaimulNM
• 金额: $ 3.5万
• 依托单位: Ryerson University
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=752528
• 关键词: Multimodal; assessment; learning; through; educational

In partnership with UNLTD Inc., the proposed research project will create a framework to remotely deliver interactive educational content to children through gamification. The COVID-19 pandemic has highlighted the need for intelligent platforms for automated delivery of learning elements. In this project, the aim is to gamify some of the core learning elements through interactive 3D (regular and augmented/virtual reality) games. Recent evidence has shown that gamification (i.e., serious games) has the potential to achieve and sustain a higher level of motivation and engagement in learning compared to traditional means. An important aspect in such game-based evaluation is the assessment of learning outcomes, which is often tied to assessing learning emotions accurately. In this project, a major aspect of the research will be on how to assess such learning emotions in a robust and efficient manner through physiological (e.g. ECG, EEG) and behavioral (e.g. facial expression, voice) data. We will focus on three key aspects: 1) Robust AI-based multimodal assessment of learning emotions: we will ensure that the developed algorithms can work under resource-constrained environments where one or more modalities of data could be missing. 2) Objective annotation for data-driven assessment of emotions: Since AI algorithms are data-driven, we will create evidence-based task-driven gaming applications which can help us in bridging the gap between subjective and objective annotations. 3) Cloud-based framework for rapid prototyping: we will create an easily scalable module that can help UNLTD in scaling up the project quickly and efficiently to multiple gaming titles. The potential outcome of the proposed project is a robust and universal framework for delivering interactive educational games efficiently. The project will train two PhD, two MSc., and multiple research assistants and software developers. The project can create an engaging channel for supplemental learning for children in Canada in addition to traditional learning in the classroom. The technical innovations will also enhance Ontario and Canada's position as a technical hub, creating new job opportunities for the HQPs involved in the project.

与UNLTD Inc.合作，拟议的研究项目将建立一个框架，通过游戏化向儿童远程提供互动教育内容。COVID-19疫情凸显了对智能平台的需求，以自动提供学习元素。在该项目中，目标是通过交互式3D（常规和增强/虚拟现实）游戏将一些核心学习元素游戏化。最近的证据表明，游戏化（即，与传统方式相比，严肃游戏）有可能实现并保持更高水平的学习动机和参与度。这种基于游戏的评估的一个重要方面是对学习成果的评估，这通常与准确评估学习情绪有关。在这个项目中，研究的一个主要方面将是如何通过生理（例如ECG，EEG）和行为（例如面部表情，语音）数据以稳健和有效的方式评估这种学习情绪。我们将专注于三个关键方面：1）基于人工智能的学习情感多模态评估：我们将确保开发的算法可以在资源受限的环境下工作，其中一个或多个数据模态可能会丢失。2)数据驱动情绪评估的客观注释：由于人工智能算法是数据驱动的，我们将创建基于证据的任务驱动游戏应用程序，这可以帮助我们弥合主观和客观注释之间的差距。3)基于云的快速原型框架：我们将创建一个易于扩展的模块，帮助UNLTD快速有效地将项目扩展到多个游戏。 拟议项目的潜在成果是一个强大的和通用的框架，有效地提供互动教育游戏。该项目将培养两名博士，两名硕士，以及多名研究助理和软件开发人员。除了传统的课堂学习之外，该项目还可以为加拿大儿童的补充学习创造一个吸引人的渠道。技术创新还将加强安大略和加拿大作为技术中心的地位，为参与该项目的HQP创造新的就业机会。