Designing a realistic peer-like embodied conversational agent for supporting children\textquotesingle s storytelling

Advances in artificial intelligence have facilitated the use of large language models (LLMs) and AI-generated synthetic media in education, which may inspire HCI researchers to develop technologies, in particular, embodied conversational agents (ECAs) to simulate the kind of scaffolding children might receive from a human partner. In this paper, we will propose a design prototype of a peer-like ECA named STARie that integrates multiple AI models - GPT-3, Speech Synthesis (Real-time Voice Cloning), VOCA (Voice Operated Character Animation), and FLAME (Faces Learned with an Articulated Model and Expressions) that aims to support narrative production in collaborative storytelling, specifically for children aged 4-8. However, designing a child-centered ECA raises concerns about age appropriateness, children\textquotesingle s privacy, gender choices of ECAs, and the uncanny valley effect. Thus, this paper will also discuss considerations and ethical concerns that must be taken into account when designing such an ECA. This proposal offers insights into the potential use of AI-generated synthetic media in child-centered AI design and how peer-like AI embodiment may support children\textquotesingle s storytelling.Comment: 6 pages with 2 figures. The paper has been peer-reviewed and presented at the "CHI 2023 Workshop on Child-centred AI Design: Definition, Operation and Considerations, April 23, 2023, Hamburg, German

DESIGNING CHATBOTS FOR HIGHER EDUCATION PRACTICE

In this research–in–progress paper, we employ design science research to articulate design knowledge for chatbots in higher education practice. We conducted a literature review to factor previous research into the design process. In addition, we performed a content analysis of student e-mails and forum posts from four instances of a basic Java programming course. Drawing from literature and data, we present a conceptual architecture for chatbots in higher education, discuss its rationale, and provide a proof-of-concept implementation. We conclude with a discussion including tentative design recommendations and a plan for continued research

The Virtual Tutor: Combining Conversational Agents with Learning Analytics to support Formative Assessment in Online Collaborative Learning

The objective of this design science research project is to combine Learning Analytics data with a conversational agent communication interface, the Virtual Tutor, which is able to support formative assessment for educators and learners in online collaborative learning (OCL) environments. The main benefit for educators is providing user-adaptable Learning Analytics data requests to fit the information needs for formative assessment. Learners receive semi-automated feedback on their platform activity in form of reports, which shall trigger self-reflection processes. By extracting requirements from the potential users and deriving design principles, a conversational agent is implemented and evaluated in an online collaborative learning course. The results indicate that the Virtual Tutor reduces the task load of educators, supports formative assessment and gives scaffolded guidance to the learners by reflecting their performance, thus triggering self-reflection processes. This research provides a first step towards data supported (semi-)automated feedback systems for formative assessment in OCL courses

Supportive technologies for group discussion in MOOCs

A key hurdle that prevents MOOCs from reaching their transformative potential in terms of making valuable learning experiences available to the masses is providing support for students to make use of the resources they can provide for each other. This paper lays the foundation for meeting this challenge by beginning with a case study and computational modeling of social interaction data. The analysis yields new knowledge that informs design and development of novel, real-time support for building healthy learning communities that foster a high level of engagement and learning. We conclude by suggesting specific areas for potential impact of new technology

Designing Automated Facilitation for Design Thinking: A Chatbot for Supporting Teams in the Empathy Map Method

The Empathy Map Method (EMM) in the Design Thinking approach is a powerful tool for user centered design but relies on the methodological skills and experience of rare facilitation experts to guide the team. In a collaboration engineering effort, we aim to make this expertise available to teams without constant access to a professional facilitator by packaging facilitation knowledge into structured process support and state-of-the art technology. Based on requirements from scientific and practitioners’ literature, we introduce the concept of a conversational agent in the form of a chatbot to take over the role of the facilitator of the EMM. We present an initial wizard of oz evaluation to derive insights and implications for improvements and the software implementation towards the ambitious goal of automated, non-human facilitation of EMM

Concepção, Implementação e Avaliação de um Agente Conversacional com Suporte à Aprendizagem Ubíqua

A ampla incorporação das tecnologias digitais na sociedade vem fazendo asferramentas instrucionais adquirirem novos recursos, com a finalidade de atender as reais necessidades de seus utilizadores. Essa premissa é refletida nos Ambientes Virtuais de Aprendizagem, que vêm recebendo constantes atualizações, em direção aos sistemas ubíquos. Nessa perspectiva, a presente pesquisa se insere com o intuito de apresentar a concepção, implementação e avaliação de um agente conversacional, integrado ao Moodle, que auxilia estudantes de Engenharia de Software. Para tanto, o agente, denominado Ubibot, adapta suas mensagens de auxílio, considerando o contexto do estudante, a fim de oferecer acesso propício à aprendizagem ubíqua

Interacting with educational chatbots: A systematic review

Chatbots hold the promise of revolutionizing education by engaging learners, personalizing learning activities, supporting educators, and developing deep insight into learners’ behavior. However, there is a lack of studies that analyze the recent evidence-based chatbot-learner interaction design techniques applied in education. This study presents a systematic review of 36 papers to understand, compare, and reflect on recent attempts to utilize chatbots in education using seven dimensions: educational field, platform, design principles, the role of chatbots, interaction styles, evidence, and limitations. The results show that the chatbots were mainly designed on a web platform to teach computer science, language, general education, and a few other fields such as engineering and mathematics. Further, more than half of the chatbots were used as teaching agents, while more than a third were peer agents. Most of the chatbots used a predetermined conversational path, and more than a quarter utilized a personalized learning approach that catered to students’ learning needs, while other chatbots used experiential and collaborative learning besides other design principles. Moreover, more than a third of the chatbots were evaluated with experiments, and the results primarily point to improved learning and subjective satisfaction. Challenges and limitations include inadequate or insufficient dataset training and a lack of reliance on usability heuristics. Future studies should explore the effect of chatbot personality and localization on subjective satisfaction and learning effectiveness