Evaluation of anthropomorphic feedback for an online auction and affordances

This paper describes an experiment investigating the effectiveness and user satisfaction of using anthropomorphic feedback at the user interface. The context chosen was online bidding due to this kind of activity being very much used in current times by general users. The main results of the experiment were that there was a statistically significant effect observed for the time taken to place a bid in the anthropomorphic text condition. However there were no other significant effects for effectiveness issues and user satisfaction indicators. The results were also analysed in terms of the affordances and the main findings were that each of the four conditions tested in the experiment were probably equivalent in terms of their facilitating the affordances. Overall it may be more important to facilitate the affordances rather than a type of feedback being anthropomorphic in nature or not

Evaluation of an anthropomorphic user interface in a travel reservation context and affordances

This paper describes an experiment and its results concerning research that has been going on for a number ofyears in the area of anthropomorphic user interface feedback. The main aims of the research have been to examine theeffectiveness and user satisfaction of anthropomorphic feedback in various domains. The results are of use to all interactivesystems designers, particularly when dealing with issues of user interface feedback design. There is currently somedisagreement amongst computer scientists concerning the suitability of such types of feedback. This research is working toresolve this disagreement. The experiment detailed, concerns the specific software domain of Online Factual Delivery in thespecific context of online hotel bookings. Anthropomorphic feedback was compared against an equivalent non-anthropomorphicfeedback. Statistically significant results were obtained suggesting that the non-anthropomorphic feedback was more effective.The results for user satisfaction were however less clear. The results obtained are compared with previous research. Thissuggests that the observed results could be due to the issue of differing domains yielding different results. However the resultsmay also be due to the affordances at the interface being more facilitated in the non-anthropomorphic feedback

Explicit Feedback Within Game-based Training: Examining The Influence Of Source Modality Effects On Interaction

This research aims to enhance Simulation-Based Training (SBT) applications to support training events in the absence of live instruction. The overarching purpose is to explore available tools for integrating intelligent tutoring communications in game-based learning platforms and to examine theory-based techniques for delivering explicit feedback in such environments. The primary tool influencing the design of this research was the Generalized Intelligent Framework for Tutoring (GIFT), a modular domain-independent architecture that provides the tools and methods to author, deliver, and evaluate intelligent tutoring technologies within any training platform. Influenced by research surrounding Social Cognitive Theory and Cognitive Load Theory, the resulting experiment tested varying approaches for utilizing an Embodied Pedagogical Agent (EPA) to function as a tutor during interaction in a game-based environment. Conditions were authored to assess the tradeoffs between embedding an EPA directly in a game, embedding an EPA in GIFT’s browser-based Tutor-User Interface (TUI), or using audio prompts alone with no social grounding. The resulting data supports the application of using an EPA embedded in GIFT’s TUI to provide explicit feedback during a game-based learning event. Analyses revealed conditions with an EPA situated in the TUI to be as effective as embedding the agent directly in the game environment. This inference is based on evidence showing reliable differences across conditions on the metrics of performance and self-reported mental demand and feedback usefulness items. This research provides source modality tradeoffs linked to tactics for relaying training relevant explicit information to a user based on real-time performance in a game

Orientações de design para Agentes Pedagógicos Animados

A área de agentes animados pedagógicos está relacionada ao desenvolvimento de aplicações que visam melhorar o processo de interação humano-computador (por humanos queremos dizer estudantes e professores) utilizando software de agentes representados por caracte- res ou figuras humanas. A fim de ajudar os pesquisado- res a projetar agentes pedagógicos que possam melhorar a usabilidade do agente humano, este trabalho vai discutir as diretrizes básicas para o design de Agentes Animados Pedagógicos, com base nos conceitos fornecidos pela In- formática na Educação, Inteligência Artificial e Interação Humano-Computador

Interactive narration with a child: impact of prosody and facial expressions

International audienceIntelligent Virtual Agents are suitable means for interactive sto-rytelling for children. The engagement level of child interaction with virtual agents is a challenging issue in this area. However, the characteristics of child-agent interaction received moderate to little attention in scientific studies whereas such knowledge may be crucial to design specific applications. This article proposes a Wizard of Oz platform for interactive narration. An experimental study in the context of interactive story-telling exploiting this platform is presented to evaluate the impact of agent prosody and facial expressions on child participation during storytelling. The results show that the use of the virtual agent with prosody and facial expression modalities improves the engagement of children in interaction during the narrative sessions

"Teach AI How to Code": Using Large Language Models as Teachable Agents for Programming Education

This work investigates large language models (LLMs) as teachable agents for learning by teaching (LBT). LBT with teachable agents helps learners identify their knowledge gaps and discover new knowledge. However, teachable agents require expensive programming of subject-specific knowledge. While LLMs as teachable agents can reduce the cost, LLMs' over-competence as tutees discourages learners from teaching. We propose a prompting pipeline that restrains LLMs' competence and makes them initiate "why" and "how" questions for effective knowledge-building. We combined these techniques into TeachYou, an LBT environment for algorithm learning, and AlgoBo, an LLM-based tutee chatbot that can simulate misconceptions and unawareness prescribed in its knowledge state. Our technical evaluation confirmed that our prompting pipeline can effectively configure AlgoBo's problem-solving performance. Through a between-subject study with 40 algorithm novices, we also observed that AlgoBo's questions led to knowledge-dense conversations (effect size=0.73). Lastly, we discuss design implications, cost-efficiency, and personalization of LLM-based teachable agents

The use of animated agents in e‐learning environments: an exploratory, interpretive case study

There is increasing interest in the use of animated agents in e‐learning environments. However, empirical investigations of their use in online education are limited. Our aim is to provide an empirically based framework for the development and evaluation of animated agents in e‐learning environments. Findings suggest a number of challenges, including the multiple dialogue models that animated agents will need to accommodate, the diverse range of roles that pedagogical animated agents can usefully support, the dichotomous relationship that emerges between these roles and that of the lecturer, and student perception of the degree of autonomy that can be afforded to animated agents