Agentic Engagement with a Programmable Dialog System
Agentic Engagement with a Programmable Dialog System
复制标题
通过可编程对话系统进行代理参与
DOI：
10.1145/3446871.3469782
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发表时间：
2021
期刊：
影响因子：
--
通讯作者：
Walker, Erin
中科院分区：
文献类型：
--
作者：
Buddemeyer, Amanda;Hatley, Leshell;Stewart, Angela;Solyst, Jaemarie;Ogan, Amy;Walker, Erin
与社交教学机器人或代理对话是孩子学习[1，5]的有力途径，但可能会限制与技术形成代理关系[9]。会话代理的一个主要目的是允许用户进行自然的交互，从而减少学习人工约定的需要[6]，但对话系统在故障恢复、词汇多样性、记住对话历史和其他措施方面做得不够[2，3]。进一步说，Hill et.艾尔[4]发现人们调整他们的交流模式以匹配聊天机器人的交流模式，就像他们对孩子或非母语人士所做的那样。因此，与教学代理交谈的用户被隐含地培训为塑造他们的行为以适应技术，而不是塑造技术。对于年轻的学习者来说，特别是在历史上被排除在技术领域之外的人群中，这限制了代理，并加强了边缘化的权力结构[9]。这个项目将对话代理与代理参与的想法结合起来，帮助中学生学习计算思维。代理参与被定义为学生对教学流程的建设性贡献，包括表达兴趣、偏好和意见等行为。它与学习成绩和动机呈正相关[7，8]。与文化响应课程(CRC)相结合，代理参与可能有助于培养与技术的代理关系。我们的系统鼓励学习者通过使用编程构造来改变代理的词汇表，识别用户话语(调用)背后的意图，并定义代理将采取的操作来响应调用，从而鼓励学习者进行代理参与。学生使用计算思维概念，如模式识别、抽象和分解，将想法转换为对话系统的命令，并了解他们的哪些想法不能用所提供的技术编程。他们学习今天个性化的系统，并将代理视为他们可以在未来塑造的技术-社会结构。编程可以使用谷歌的块可视化编程工具(https://developers.google.com/blockly))，也可以通过与代理本身的对话来完成。代理被体现为机器人角色，因此代理的动作可以是口头的、身体的或两者兼而有之。通过与代理的社交对话，学习者反思计算思维是如何与他们自己和他们的社区相关的，作为CRC的一部分，建立在Stewart et的工作基础上。艾尔[10]。例如，学习者可能会被要求反思问候行为和身份之间的关系。在设计了问候语交互后，学员可以编写对话系统来实现问候语。在开发对话系统和课程的同时，我们还将把里夫的代理参与工具[7]改编成适用于CRC的对话系统。我们的贡献将包括这个工具，对代理参与和与技术的代理关系之间的关系的见解，以及对可编程对话系统如何影响代理参与和学习计算思维的见解。
Dialog with a social pedagogical robot or agent is a powerful way for kids to learn [1, 5] but may limit the formation of an agentic relationship with the technology [9]. One main purpose of conversational agents is to allow the user to have a natural interaction that reduces the need to learn artificial conventions [6], but dialog systems fall short with respect to failure recovery, vocabulary diversity, remembering conversational history, and other measures [2, 3]. Further, Hill et. al. [4] found that people adapt their model of communication to match a chatbot’s in the same way they do with a child or non-native speaker. Thus, users conversing with a pedagogical agent are implicitly trained to shape their behavior to suit the technology rather than shaping the technology. For young learners, particularly among populations that have been historically excluded from technology fields, this limits agency and reinforces marginalizing power structures [9].This project combines a conversational agent with ideas of agentic engagement to help middle-school-aged children learn computational thinking. Agentic engagement is defined as students’ constructive contribution into the flow of instruction and includes behaviors such as expressing interests, preferences, and opinions. It has been positively correlated to learning performance and motivation [7, 8]. Combined with a culturally responsive curriculum (CRC), agentic engagement may help to foster an agentic relationship with technology. Our system encourages learners to engage agentically by using programming constructs to change the agent’s vocabulary, recognizing the intent behind a user utterance (an invocation), and defining the action the agent will take to respond to an invocation. Students use computational thinking concepts such as pattern recognition, abstraction, and decomposition to convert ideas into commands for the dialog system and to understand which of their ideas can’t be programmed with the technology as presented. They learn both to personalize the system today and to see the agent as a technosocial construct that they can shape in the future.Programming can be accomplished either using Google’s Blockly visual programming tool (https://developers.google.com/blockly) or through conversation with the agent itself. The agent is embodied as a robot character, so agent actions can be verbal, physical, or both. Through social dialog with the agent, learners reflect on how computational thinking is relevant to themselves and their communities as part of a CRC, building on the work of Stewart et. al. [10]. For example, learners may be asked to reflect on the relationship between greeting behaviors and identity. After designing a greeting interaction, learners program the dialog system to achieve the greeting. Then learners may be asked to imagine how they might hypothetically enhance the dialog system to make it even more capable of implementing their preferences.In parallel to the development of the dialog system and curriculum, we will also adapt Reeve’s agentic engagement instrument [7] for CRC. Our contributions will include this instrument, insights into the relationship between agentic engagement and an agentic relationship with technology, and insights into how a programmable dialog system impacts agentic engagement and learning computational thinking.
对机器人的舒适度会影响与社交、可教导的机器人的融洽关系
DOI：
10.1007/978-3-030-23204-7
发表时间：
2019
期刊：
International Conference on Artificial Intelligence in Education
影响因子：
--
作者：
Lubold, Nichola;Walker, Erin;Pon-Barry, Heather;Ogan, Amy
通讯作者：
Ogan, Amy
解释参与度：虚拟编程营中的学习者行为
DOI：
10.1007/978-3-030-78270-2_60
发表时间：
2021
期刊：
International Conference on Artificial Intelligence in Education
影响因子：
--
作者：
Stewart, Angela EB;Solyst, J.;Buddemeyer, A;Hatley, L.;Henderson-Singer, S.;Scott, K.;Walker, E.;Ogan, A.
通讯作者：
Ogan, A.
DOI：
10.1080/10447318.2020.1841438
发表时间：
2020-11-09
影响因子：
4.7
作者：
Chaves, Ana Paula;Gerosa, Marco Aurelio
通讯作者：
Gerosa, Marco Aurelio