Designing Virtual Agents for Simulation-Based Learning in Virtual Reality

Designing Virtual Agents for Simulation-Based Learning in Virtual Reality

Fengfeng Ke (Florida State University, USA), Zhaihuan Dai (Florida State University, USA), Chih-Pu Dai (Florida State University, USA), Mariya Pachman (Florida State University, USA), Ram Sharan Chaulagain (Florida State University, USA) and Xin Yuan (Florida State University, USA)
DOI: 10.4018/978-1-7998-3250-8.ch008

Abstract

In this chapter, the authors review and explore propositions, approaches, and core elements of designing virtual agents that contextualize and scaffold simulation-based learning. They start the chapter by reviewing the literature and prior research on the nature, role, design claims, and evidence of virtual agents in digital and multimedia learning environments. They then analyze the educational affordances of virtual reality (VR) for agent-supported, simulation-based learning as well as the design challenges for creating interactive virtual agents. Through an empirical design case, they describe a conceptual and design framework of creating and using virtual agents for VR simulation-based teaching training. Specifically, they provide an analytical and contextualized synthesis of core design elements, including specific design problems associated with virtual agents, the design solutions, and the patterns of transferring or scaling these design solutions to other cases of virtual agent development.
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Introduction

Defined by their core functions, virtual agents in a multimedia or virtual learning environment are typically: (a) pedagogical agents—graphical characters presented on a computer screen to support or guide student learning of the presented material (Heidig & Clarebout, 2011; Makransky, Wismer, & Mayer, 2019; Wang, Li, Mayer, & Liu, 2018); (b) embodied conversational agents—human-like characters that are specifically conversational (both verbal and non-verbal) in their behaviors and present the similar properties as humans in face-to-face conversations (Cassell, Sullivan, Churchill, & Prevost, 2000); and (c) interactive simulators that simulate not only physical behaviors but also cognitive functions (e.g., reasoning, decision-making, and learning) of a subject or person that is interacted with, such as a virtual patient- or a student-simulator (Kleinert et al., 2015; Matsuda, Cohen, & Koedinger, 2015).

Motivation of using and designing virtual agents, sometimes called virtual humans, in a digital learning environment is to present an active, cost-efficient, and personalized teaching/learning experience. Specifically, virtual agents have been used to (a) motivate and scaffold the processing, retention, and application of the presented information, (b) enable computer-assisted personalized learning, (c) simulate the behaviors of a system in reaction to user inputs to frame a situated learning experience or to elicit and foster targeted cognitive functions, and (d) facilitate the authoring or assessment of a competency model. Prior research examining the effects and conditions of using virtual agents indicated a great variety of agents used and hence inconclusive findings about their effectiveness, even though recent meta-analyses started to show a small but significant effect of using a pedagogical agent on learning (Heidig & Clarebout, 2011; Schroeder, Adesope, & Gilbert, 2013; Wang et al., 2018). Rather, the previous studies and reviews of virtual agents argue that it is more meaningful to question the design and targeted function of virtual agents in relation to the properties or characteristics of learning, learner, and implementation contexts or conditions.

In this chapter, we aims to review and explore propositions, approaches, and core facets of designing virtual agents that contextualize and scaffold simulation-based active learning. Virtual agents can be considered as a major pedagogical design element in the virtual learning environment. They can be used to improve learning interactivity and engagement by providing adaptive learning feedback and other personalized learning services (e.g., mentoring and guidance). Virtual agents can be the middle point between the learner and the virtual environment for achieving personalization, by providing personalized learning services based on a stored learner or user profile. They are also considered effective to improve the sense of presence in the immersive virtual learning environments and improve motivation. They are the key to creating a continuous virtual presence for users within a virtual world. Prior research indicated that the feeling of co-presence fostered by virtual agents can complement user-controlled avatars to achieve an ever-present virtual presence (Gerhard, Moore, & Hobbs, 2001).

Despite the increasing interest and existing studies on the usage and design of virtual agents, open questions remain governing the dynamic interaction and convergence among the targeted agent-based learning, learner characteristics, affordances of the technological platform, and the implementation contexts. Conceptual or design research outlining the heuristics of embodied and potentially intelligent agents in the virtual environment is still lacking. The constraints and opportunities presented by the current virtual environments for agent-based learning, such as virtual reality and game-based learning, warrant a critical and contextualized review and discussion.

Key Terms in this Chapter

Persona: The personification of the virtual agent, or the design of the agent’s appearance and physical behaviors that are indicative of the simulated character or role profile.

Embodied Conversational Agents: Human-like characters that are specifically conversational (both verbal and non-verbal) in their behaviors and present the similar properties as humans in face-to-face conversations.

Interactivity: The degree to which a virtual agent acts like the real-world character in reacting to the user actions or inputs.

Virtual Reality: A computer-generated 3D representation of real-life environment that enables immersion, interaction, and imagination.

Virtual Agents: Computerize agents that can interact with the virtual environment and other avatars and agents to fulfill predefined operations or tasks.

Agent Simulators: Simulators that simulate not only physical behaviors but also cognitive functions of a subject or person that is interacted with.

Pedagogical Agents: Graphical characters presented on a computer screen to support or guide student learning of the presented material.

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