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

Knowledge Cartography: Software tools and mapping techniques

Knowledge Cartography is the discipline of mapping intellectual landscapes.The focus of this book is on the process by which manually crafting interactive, hypertextual maps clarifies one’s own understanding, as well as communicating it.The authors see mapping software as a set of visual tools for reading and writing in a networked age. In an information ocean, the primary challenge is to find meaningful patterns around which we can weave plausible narratives. Maps of concepts, discussions and arguments make the connections between ideas tangible and disputable. With 17 chapters from the leading researchers and practitioners, the reader will find the current state–of-the-art in the field. Part 1 focuses on educational applications in schools and universities, before Part 2 turns to applications in professional communitie

Say Hello to Your New Automated Tutor – A Structured Literature Review on Pedagogical Conversational Agents

In this paper, we present the current state of the art of using conversational agents for educational purposes. These so-called pedagogical conversational agents are a specialized type of e-learning and intelligent tutoring systems. The main difference to traditional e-learning and intelligent tutoring systems is that they interact with learners using natural language dialogs, e.g. in the form of chatbots. For the sake of our research project, we analyzed current trends in the research stream as well as research gaps. Our results show for instance that (1) there is a trend towards using mobile conversational agents in education, (2) a proper generalization of existing research results (e.g. design knowledge) is missing, and (3) there is a need for comprehensive in-depth evaluation studies and corresponding process models. Based on our results, we outline a research agenda for future research studies

A model for providing emotion awareness and feedback using fuzzy logic in online learning

Monitoring users’ emotive states and using that information for providing feedback and scaffolding is crucial. In the learning context, emotions can be used to increase students’ attention as well as to improve memory and reasoning. In this context, tutors should be prepared to create affective learning situations and encourage collaborative knowledge construction as well as identify those students’ feelings which hinder learning process. In this paper, we propose a novel approach to label affective behavior in educational discourse based on fuzzy logic, which enables a human or virtual tutor to capture students’ emotions, make students aware of their own emotions, assess these emotions and provide appropriate affective feedback. To that end, we propose a fuzzy classifier that provides a priori qualitative assessment and fuzzy qualifiers bound to the amounts such as few, regular and many assigned by an affective dictionary to every word. The advantage of the statistical approach is to reduce the classical pollution problem of training and analyzing the scenario using the same dataset. Our approach has been tested in a real online learning environment and proved to have a very positive influence on students’ learning performance.Peer ReviewedPostprint (author's final draft

Conversational Agents in Education – A Systematic Literature Review

Conversational Agents (CAs) are widely spread in a variety of domains, such as health and customer service. There is a recent trend of increasing publications and implementations of CAs in education. We conduct a systematic literature review to identify common methodologies, pedagogical CA roles, addressed target groups, the technologies and theories behind, as well as human-like design aspects. The initially found 3329 records were systematically reduced to 252 fully coded articles. Based on the analysis of the codings, we derive further research streams. Our results reveal a research gap for long-term studies on the use of CAs in education, and there is insufficient holistic design knowledge for pedagogical CAs. Moreover, target groups other than academic students are rarely considered. We condense our findings in a morphological box and conclude that pedagogical CAs have not yet reached their full potential of long-term practical application in education

The Virtual Tutor: Tasks for conversational agents in Online Collaborative Learning Environments

Online collaborative learning environments are becoming increasingly popular in higher education. E-tutors need to supervise, guide students and look out for conflicts within the online environment to ensure a successful learning experience. Web-based platforms allow for interactive elements such as conversational agents to disencumber the e-tutor. Repeatable tasks, which do not require a human response, can be automatized by these systems. The aim of this study is to identify and synthesize the tasks an e-tutor has and to investigate the automatisation potential with conversational agents. Using a design science research approach a literature review is conducted, identifying 13 tasks. Subsequently, a matrix is established, contrasting the tasks with requirements for the use of conversational agents. Furthermore, a virtual tutor framework is developed, clarifying the agent type selection, the technical structure and components for a prototype development in an online collaborative learning environment

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

Intelligent Pedagogical Agents in Immersive Virtual Learning Environments: A Review

The concept of Intelligent Pedagogical Agents (IPA) has been an important research topic for a long time. IPA is supported by multi-agent systems research derived from AI. IPA provides personalized instruction, increase learner motivation, and act pedagogically on behalf or with the learner. On the other hand, virtual environments add value to the education process by giving new educational possibilities and computational-richness support. Combining both IPA and Virtual environments can make a promising approach for effective computer-aided learning. This paper provides a review on IPA and related topics focusing on a general overview of the topic, gives a detailed review in the application domain of virtual learning environments, and outlines a proposal for a flexible conceptual approach for the flexible application in different learning settings

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

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