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

Chatbots for learning: A review of educational chatbots for the Facebook Messenger

With the exponential growth in the mobile device market over the last decade, chatbots are becoming an increasingly popular option to interact with users, and their popularity and adoption are rapidly spreading. These mobile devices change the way we communicate and allow ever-present learning in various environments. This study examined educational chatbots for Facebook Messenger to support learning. The independent web directory was screened to assess chatbots for this study resulting in the identification of 89 unique chatbots. Each chatbot was classified by language, subject matter and developer's platform. Finally, we evaluated 47 educational chatbots using the Facebook Messenger platform based on the analytic hierarchy process against the quality attributes of teaching, humanity, affect, and accessibility. We found that educational chatbots on the Facebook Messenger platform vary from the basic level of sending personalized messages to recommending learning content. Results show that chatbots which are part of the instant messaging application are still in its early stages to become artificial intelligence teaching assistants. The findings provide tips for teachers to integrate chatbots into classroom practice and advice what types of chatbots they can try out.Web of Science151art. no. 10386

No Grice: Computers that Lie, Deceive and Conceal

In the future our daily life interactions with other people, with computers, robots and smart environments will be recorded and interpreted by computers or embedded intelligence in environments, furniture, robots, displays, and wearables. These sensors record our activities, our behavior, and our interactions. Fusion of such information and reasoning about such information makes it possible, using computational models of human behavior and activities, to provide context- and person-aware interpretations of human behavior and activities, including determination of attitudes, moods, and emotions. Sensors include cameras, microphones, eye trackers, position and proximity sensors, tactile or smell sensors, et cetera. Sensors can be embedded in an environment, but they can also move around, for example, if they are part of a mobile social robot or if they are part of devices we carry around or are embedded in our clothes or body. \ud \ud Our daily life behavior and daily life interactions are recorded and interpreted. How can we use such environments and how can such environments use us? Do we always want to cooperate with these environments; do these environments always want to cooperate with us? In this paper we argue that there are many reasons that users or rather human partners of these environments do want to keep information about their intentions and their emotions hidden from these smart environments. On the other hand, their artificial interaction partner may have similar reasons to not give away all information they have or to treat their human partner as an opponent rather than someone that has to be supported by smart technology.\ud \ud This will be elaborated in this paper. We will survey examples of human-computer interactions where there is not necessarily a goal to be explicit about intentions and feelings. In subsequent sections we will look at (1) the computer as a conversational partner, (2) the computer as a butler or diary companion, (3) the computer as a teacher or a trainer, acting in a virtual training environment (a serious game), (4) sports applications (that are not necessarily different from serious game or education environments), and games and entertainment applications

Multi-agent systems for power engineering applications - part 2 : Technologies, standards and tools for building multi-agent systems

This is the second part of a 2-part paper that has arisen from the work of the IEEE Power Engineering Society's Multi-Agent Systems (MAS) Working Group. Part 1 of the paper examined the potential value of MAS technology to the power industry, described fundamental concepts and approaches within the field of multi-agent systems that are appropriate to power engineering applications, and presented a comprehensive review of the power engineering applications for which MAS are being investigated. It also defined the technical issues which must be addressed in order to accelerate and facilitate the uptake of the technology within the power and energy sector. Part 2 of the paper explores the decisions inherent in engineering multi-agent systems for applications in the power and energy sector and offers guidance and recommendations on how MAS can be designed and implemented. Given the significant and growing interest in this field, it is imperative that the power engineering community considers the standards, tools, supporting technologies and design methodologies available to those wishing to implement a MAS solution for a power engineering problem. The paper describes the various options available and makes recommendations on best practice. It also describes the problem of interoperability between different multi-agent systems and proposes how this may be tackled

Agents for educational games and simulations

This book consists mainly of revised papers that were presented at the Agents for Educational Games and Simulation (AEGS) workshop held on May 2, 2011, as part of the Autonomous Agents and MultiAgent Systems (AAMAS) conference in Taipei, Taiwan. The 12 full papers presented were carefully reviewed and selected from various submissions. The papers are organized topical sections on middleware applications, dialogues and learning, adaption and convergence, and agent applications

Profiling the educational value of computer games

There are currently a number of suggestions for educators to include computer games in formal teaching and learning contexts. Educational value is based on claims that games promote the development of complex learning. Very little research, however, has explored what features should be present in a computer game to make it valuable or conducive to learning. We present a list of required features for an educational game to be of value, informed by two studies, which integrated theories of Learning Environments and Learning Styles. A user survey showed that some requirements were typical of games in a particular genre, while other features were present across all genres. The paper concludes with a proposed framework of games and features within and across genres to assist in the design and selection of games for a given educational scenari

OFMTutor: An operator function model intelligent tutoring system

The design, implementation, and evaluation of an Operator Function Model intelligent tutoring system (OFMTutor) is presented. OFMTutor is intended to provide intelligent tutoring in the context of complex dynamic systems for which an operator function model (OFM) can be constructed. The human operator's role in such complex, dynamic, and highly automated systems is that of a supervisory controller whose primary responsibilities are routine monitoring and fine-tuning of system parameters and occasional compensation for system abnormalities. The automated systems must support the human operator. One potentially useful form of support is the use of intelligent tutoring systems to teach the operator about the system and how to function within that system. Previous research on intelligent tutoring systems (ITS) is considered. The proposed design for OFMTutor is presented, and an experimental evaluation is described

Intelligent and adaptive tutoring for active learning and training environments

Active learning facilitated through interactive and adaptive learning environments differs substantially from traditional instructor-oriented, classroom-based teaching. We present a Web-based e-learning environment that integrates knowledge learning and skills training. How these tools are used most effectively is still an open question. We propose knowledge-level interaction and adaptive feedback and guidance as central features. We discuss these features and evaluate the effectiveness of this Web-based environment, focusing on different aspects of learning behaviour and tool usage. Motivation, acceptance of the approach, learning organisation and actual tool usage are aspects of behaviour that require different evaluation techniques to be used

Innovating Pedagogy 2015: Open University Innovation Report 4

This series of reports explores new forms of teaching, learning and assessment for an interactive world, to guide teachers and policy makers in productive innovation. This fourth report proposes ten innovations that are already in currency but have not yet had a profound influence on education. To produce it, a group of academics at the Institute of Educational Technology in The Open University collaborated with researchers from the Center for Technology in Learning at SRI International. We proposed a long list of new educational terms, theories, and practices. We then pared these down to ten that have the potential to provoke major shifts in educational practice, particularly in post-school education. Lastly, we drew on published and unpublished writings to compile the ten sketches of new pedagogies that might transform education. These are summarised below in an approximate order of immediacy and timescale to widespread implementation