NFeedback - improving online learning outcomes

NFeedback将使用人工智能，特别是自然语言处理（NLP）、计算机视觉（CV）和知识图谱（KG），为Note Taking Express当前的数字教室解决方案创建实时和离线反馈。在网络教学环境中，与传统的课堂教学相比，许多互动被忽略了，比如参与者的数量、学生的面部情绪、肢体语言等。这些人工智能服务将提供有关非语言情感和信号的宝贵信息。然后，根据每个用户的个人资料，可以为教师和学生生成自动反馈，以及改进和支持建议。KG（有时也被称为Ontology）是一种结构化描述概念和概念之间关系的技术，因此AI系统可以发现数据的模式并在数据中给出连接。这一推理过程为高等教育管理人员、教师和学生提供了反馈。可访问性是考虑学习风格多样性的反馈的重要组成部分。例如，如果是在线讲座，聋哑学生可能需要打开封闭字幕，而视障学生可能需要文本来朗读屏幕上的文本或图像描述。在更细粒度的层面上，我们将构建一些工作包来收集更多关于讲座的信息，并将其输入到KG中，这样我们的人工智能解决方案就可以决定需要向学校管理人员、讲师和学生反馈什么。我们将与南安普顿大学（UoS）合作，从开放数据集（例如南安普顿开放数据服务）和其他客户当前的课程管理系统（如BlackBoard或Moodle）中获取数据。根据上述内容，我们将使用现有数字教室解决方案中录制的讲座音频/视频内容，并生成半结构化数据存储以供进一步分析。由此，我们可以进一步增强NLP和CV模块，以准备自动反馈所需的数据。目前的解决方案，如Zoom和Microsoft Teams，很难在混合（在线/离线）教学环境中使用，并且主要用于会议和会议。BlackBoard协作已被广泛用于在线教学，然而，软件的成本以及设置和用户界面的复杂性一直是许多用户感到沮丧的原因。从根本上说，这些解决方案缺乏神经多样性学习者的可访问性和任何形式的个性化反馈。因此，NFeedback将被设计成一个简单易用的交互式云软件服务，它可以为所有学生安全地捕获讲座内容，包括学生的反馈内容和可访问工具。在寻求实施COVID-19缓解措施时，实施社交距离和新技术很可能会大大增加高等学校的管理费用。NFeedback正寻求通过为不同背景和学习偏好的学生提供人工智能支持的评估和反馈系统来直接解决这一问题，并至少在一定程度上重现课堂和校园课程以可承受的价格提供的学习的参与度和体验部分。

NFeedback will use AI, especially Natural Language Processing (NLP), Computer Vision (CV) and Knowledge Graphs (KG) to create both live and offline feedback for Note Taking Express's current digital classroom solution. In an online teaching environment, many interactions are missed compared with traditional classroom teaching, such as the number of attendees, students' facial emotions, body language etc. These AI services will provide valuable information on non-verbal emotions and signals. Then based on each user's profile, automatic feedback can be generated for teachers and students, together with suggested improvements and support.KG (sometimes also referred to as Ontology) is a technology which structurally describes the concepts and relations between concepts, so that AI systems can spot patterns of data and give connections within the data. This reasoning process offers feedback to HEI administrators, teachers and students. Accessibility is an important component of the feedback to consider diversity of learning styles. If it's an online lecture, for example, a deaf student may require Closed Captioning turned on whereas a visually impaired student may need text to speech to read out text on the screen or description of images.At a more granular level we will be structuring a number of work packages to collect more information about the lecture to feed into the KG, so that our AI solution can decide what needs to be feedback to school admins, lecturers and students. We will be collaborating with University of Southampton (UoS) to obtain the data from open datasets (Southampton Open Data Service, for example), and other clients current course management systems, such as BlackBoard or Moodle.Following the above, we will use lecture audio/video content recorded from our existing digital classroom solution and generate a semi-structured data store for further analysis. From this we can further enhance the NLP and CV modules to prepare data that is needed for automatic feedback.Current solutions, such as Zoom and Microsoft Teams are difficult to use in a blended (online/offline) teaching environment and designed mainly for meetings and conferences. BlackBoard Collaborate has been widely used for online teaching, however the cost of the software and the complexity of both the setup and UI have been a cause of frustration for many users. Fundamentally these solutions lack accessibility for neurodiverse learners and any form of personalised feedback. NFeedback will therefore be designed as a simple to use interactive cloud-based software service, which captures lectures securely for all students, including feedback content for students and accessibility tools.It is likely that the implementation of social distancing and new technology will increase overheads significantly for HEIs as they seek to put in place COVID-19 mitigation measures. NFeedback is seeking to solve this problem directly by providing AI supported assessment and feedback systems for students with different backgrounds and learning preferences and to recreate, at least in part, the engagement and experiential component of learning which in-class and on campus courses deliver at an affordable price point.