Influence of Selected Factors on a Counselor\u27s Attention Level to and Counseling Performance with a Virtual Human in a Virtual Counseling Session

Virtual humans serve as role-players in social skills training environments simulating situational face-to-face conversations. Previous research indicates that virtual humans in instructional roles can increase a learner\u27s engagement and motivation towards the training. Left unaddressed is if the learner is looking at the virtual human as one would in a human-to-human, face-to-face interaction. Using a modified version of the Emergent Leader Immersive Training Environment (ELITE-Lite), this study tracks visual attention and other behavior of 120 counselor trainees counseling a virtual human role-playing counselee. Specific study elements include: (1) the counselor\u27s level of visual attention toward the virtual counselee; (2) how changes to the counselor\u27s viewpoint may influence the counselor\u27s visual focus; and (3) how levels of the virtual human\u27s behavior may influence the counselor\u27s visual focus. Secondary considerations include aspects of learner performance, acceptance of the virtual human, and impacts of age and rank. Result highlights indicate that counselor visual attentional behavior could be separated into two phases: when the virtual human was speaking and when not speaking. When the virtual human is speaking, the counselor\u27s primary visual attention is on the counselee, but is also split toward pre-scripted responses required for the training session. During the non-speaking phase, the counselor\u27s visual focus was on pre-scripted responses required for training. Some of the other findings included that participants did not consider this to be like a conversation with a human, but they indicated acceptance of the virtual human as a partner with the training environment and they considered the simulation to be a useful experience. Additionally, the research indicates behavior may differ due to age or rank. Future study and design considerations for enhancements to social skills training environments are provided

Collaborative trails in e-learning environments

This deliverable focuses on collaboration within groups of learners, and hence collaborative trails. We begin by reviewing the theoretical background to collaborative learning and looking at the kinds of support that computers can give to groups of learners working collaboratively, and then look more deeply at some of the issues in designing environments to support collaborative learning trails and at tools and techniques, including collaborative filtering, that can be used for analysing collaborative trails. We then review the state-of-the-art in supporting collaborative learning in three different areas – experimental academic systems, systems using mobile technology (which are also generally academic), and commercially available systems. The final part of the deliverable presents three scenarios that show where technology that supports groups working collaboratively and producing collaborative trails may be heading in the near future

Design and Evaluation of a Cross-Cultural Training System

Cross-cultural competency, and the underlying communication and affective skills required to develop such expertise, is becoming increasingly important for a wide variety of domains. To address this need, we developed a blended learning platform which combines virtual role-play with tutorials, assessment and feedback. A Middle-Eastern Curriculum (MEC) exemplar for cross-cultural training U.S. military personnel was developed to guide the refinement of an existing game-based training platform. To complement this curriculum, we developed scenario authoring tools to enable end-users to define training objectives, link performance measures and feedback/remediation to these objectives, and deploy experiential scenarios within a game-based virtual environment (VE). Lessons learned from the design and development of this exemplar cross-cultural competency curriculum, as well as formative evaluation results, are discussed. Initial findings suggest that the underlying training technology promotes deep levels of semantic processing of the key information of relevant cultural and communication skills

Can You Hear What I See? Nonverbal Communication and the Changing Face of TML

Business training and education are changing. Organizations have experienced dramatic changes in their structure, competitive environment, and the demographics and demands of their employees. As a result, organizations are seeking new and innovative ways to train employees. At the same time the evolution of technology mediated learning tools (TML) has resulted in flexible, interactive, engaging, learning technology tools that promote experiential learning, analytical thinking and problem solving. Simulation based technology mediated learning (SimTML) tools are gaining popularity in practice. SimTML facilitates lifelike environments that utilize animated pedagogical agents (APAs) which employ nonverbal communication traits in their interaction with the user. The effect is a lifelike, face-to-face interaction, between the user and the APA. The result is a flexible, interactive, engaging, TML tool that promotes experiential learning, analytical thinking and problem solving. This paper explores current SimTML technology, how we interact with learning technology, and provides selection and evaluation principles for organizations to use when evaluating SimTML tools for their own training programs

A comparative study of the effect of collaborative problem solving in a massively multiplayer online game (MMOG) on individual achievement

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The design and evaluation of distributed virtual environment to support learning in global operations management

The primary goal of this research is to design and develop an education technology to support learning in global operations management. The research implements a series of studies to determine the right balance among user requirements, learning methods and applied technologies, on a view of student-centred learning. This research is multidisciplinary by nature, involving topics from various disciplines such as global operations management, curriculum and contemporary learning theory, and computer aided learning. Innovative learning models that emphasise on technological implementation are employed and discussed throughout this research

Building Artificially Intelligent Learning Games

The idea of digital game-based learning (DGBL) is gaining acceptance among researchers, game designers, educators, parents, and students alike. Building new educational games that meet educational goals without sacrificing what makes games engaging remains largely unrealized, however. If we are to build the next generation of learning games, we must recognize that while digital games might be new, the theory and technologies we need to create DGBL has been evolving in multiple disciplines for the last 30 years. This chapter will describe an approach, based on theories and technologies in education, instructional design, artificial intelligence, and cognitive psychology, that will help us build intelligent learning games (ILGs)

Instructional Designers' Observations about Identity, Communities of Practice and Change Agency

We presume that models and theory in instructional design inform professional practice, but theory has not been consistently built from the professional experiences of instructional designers. This study draws on the observations of five instructional designers who discuss their professional identities, their communities of practice and their roles as agents of social and institutional change. This study is embedded in two theoretical positions: instructional design as a social construct that is expressed in professional communities of practice, and critical pedagogy, in which designers act as agents of social change

Conversational Agent: Developing a Model for Intelligent Agents with Transient Emotional States

The inclusion of human characteristics (i.e., emotions, personality) within an intelligent agent can often increase the effectiveness of information delivery and retrieval. Chat-bots offer a plethora of benefits within an eclectic range of disciplines (e.g., education, medicine, clinical and mental health). Hence, chatbots offer an effective way to observe, assess, and evaluate human communication patterns. Current research aims to develop a computational model for conversational agents with an emotional component to be applied to the army leadership training program that will allow for the examination of interpersonal skills in future research. Overall, the current research explores the application of the deep learning algorithm to the development of a generalized framework that will be based upon modeling empathetic conversation between an intelligent conversational agent (chatbot) and a human user in order to allow for higher level observation of interpersonal communication skills. Preliminary results demonstrate the promising potential of the seq2seq technique (e.g., through the use of Dialog Flow Chatbot platform) when applied to emotion-oriented conversational tasks. Both the classification and generative conversational modeling tasks demonstrate the promising potential of the current research for representing human to agent dialogue. However, this implementation may be extended by utilizing, a larger more high-quality dataset