SBIR Phase I: Intelligent Language Learning Environment

SBIR第一阶段：智能语言学习环境

• 批准号: 2112088
• 负责人: William Jordan-Cooley
• 金额: $ 25.6万
• 依托单位: PANGEA CHAT LLC
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-03-01 至 2023-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2112088&HistoricalAwards=false
• 关键词: SBIR; Phase; Intelligent; Language; Learning

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will improve the current US deficiency in foreign language skills and bring critical innovations to the $13 billion global online language learning market. Current language learning methods focus on rote memorization and not nearly enough on using the language. Experiential learning opportunities in which students have free-flowing conversations driven by interests are often not introduced until the third or fourth semester of language study. The result is that American students graduate with little ability or motivation to actually use a foreign language and maintain any degree of language fluency. Using novel machine learning technologies and game design, this project will let students learn a language while texting with their friends and help teachers facilitate conversation-based learning in their classrooms. The project will offer opportunities for students in classes located in the US to interact with students in other countries around the globe, turning textbook abstractions into real people, culture, and language. Ultimately, these machine learning solutions enable a platform that the 1.2 billion individuals learning language worldwide can use to supplement textbook instruction with experiential learning for greater long-term fluency.This Small Business Innovation Research (SBIR) Phase I project will develop a state-of-the-art machine learning solution to address critical challenges in the implementation ofconversation-based language learning. Learning languages through conversation has been shown by previous research to be engaging and effective. However, beginners are oftenuncomfortable in the early days because they aren’t confident in expressing themselves. Educators can provide the needed support, but it is difficult for them to give every studentpersonalized tutelage. This project will jumpstart these initial conversations with the help of in-chat translation, dictionaries, and grammar checking. To cement learning, the project will generate practice activities directly from chats and deliver the activities in the context of those authentic text conversations. This project will analyze the text chats and form hypotheses about student strengths and weaknesses. The system will then test these hypotheses with assessments automatically generated from the same text chats. The Phase I technical objectives are to 1) automatically identify examples of learning objectives in student text 2) align system-generated and human-authored assessment activities and 3) predict student scores on practice activities with increasing accuracy. Over time, the system will understand student needs to maximize learning and engagement.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该小企业创新研究 (SBIR) 第一阶段项目的更广泛影响/商业潜力将改善美国当前外语技能的缺陷，并为价值 130 亿美元的全球在线语言学习市场带来关键创新。当前的语言学习方法侧重于死记硬背。学生在兴趣驱动下进行自由对话的体验式学习机会往往要到语言学习的第三或第四学期才引入，其结果是美国学生毕业时几乎没有能力或动力。实际上使用外语使用新颖的机器学习技术和游戏设计，该项目将让学生在与朋友发短信的同时学习语言，并帮助教师在课堂上促进基于对话的学习。位于美国的课程与全球其他国家的学生互动，将教科书的抽象内容转化为真实的人物、文化和语言，最终，这些机器学习解决方案为全球 12 亿学习语言的人提供了一个可以用来补充教科书的平台。通过体验式学习进行指导，以获得更长期的效果该小型企业创新研究（SBIR）第一阶段项目将开发一种最先进的机器学习解决方案，以解决实施基于对话的语言学习中的关键挑战。然而，初学者在早期往往会感到不舒服，因为他们没有信心表达自己，但他们很难为每个学生提供个性化的指导。这些最初的谈话在聊天翻译、词典和语法检查的帮助下，该项目将直接从聊天中生成练习活动，并在这些真实的文本对话的背景下进行活动。该项目将分析文本聊天和表单。然后，系统将通过相同文本聊天自动生成的评估来测试这些假设。第一阶段的技术目标是 1) 自动识别学生文本中的学习目标示例 2) 使系统生成的学习目标与人类的学习目标保持一致。 -授权的评估活动和3)随着时间的推移，系统将越来越准确地预测学生在实践活动中的得分。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。 。