Showing papers presented at "Artificial Intelligence in Education in 2016"

Letting Artificial Intelligence in Education Out of the Box: Educational Cobots and Smart Classrooms

Abstract: This paper proposes that the field of AIED is now mature enough to break away from being delivered mainly through computers and pads so that it can engage with students in new ways and help teachers to teach more effectively. Mostly, the intelligent systems that AIED has delivered so far have used computers and other devices that were essentially designed for businesses or personal use, and not specifically for education. The future holds the promise of creating technologies designed specifically for learning and teaching by combining the power of AIED with advances in the field of robotics and in the increasing use of sensor devices to monitor our surroundings and actions. The paper assumes that “schools” (i.e., a place where children will gather to learn) will still exist in some shape or form in 25 years and that teachers will continue to oversee and promote learning among the students. It proposes that there will be educational cobots assisting teachers in the classrooms of tomorrow and provides examples from current work in robotics. It also envisions smart classrooms that make use of sensors to support learning and illustrates how they might be used in new ways if AIED applications are embedded into them.

Modelling Human Teaching Tactics and Strategies for Tutoring Systems: 14 Years On

Abstract: One of the promises of ITSs and ILEs is that they will teach and assist learning in an intelligent manner. Historically this has tended to mean concentrating on the interface, on the representation of the domain and on the representation of the student’s knowledge. So systems have attempted to provide students with reifications both of what is to be learned and of the learning process, as well as optimally sequencing and adjusting activities, problems and feedback to best help them learn that domain. We now have embodied (and disembodied) teaching agents and computer-based peers, and the field demonstrates a much greater interest in metacognition and in collaborative activities and tools to support that collaboration. Nevertheless the issue of the teaching competence of ITSs and ILEs is still important, as well as the more specific question as to whether systems can and should mimic human teachers. Indeed increasing interest in embodied agents has thrown the spotlight back on how such agents should behave with respect to learners. In the mid 1980s Ohlsson and others offered critiques of ITSs and ILEs in terms of the limited range and adaptability of their teaching actions as compared to the wealth of tactics and strategies employed by human expert teachers. So are we in any better position in modelling teaching than we were in the 80s? Are these criticisms still as valid today as they were then? This paper reviews progress in understanding certain aspects of human expert teaching and in developing tutoring systems that implement those human teaching strategies and tactics. It concentrates particularly on how systems have dealt with student answers and how they have dealt with motivational issues, referring particularly to work carried out at Sussex: for example, on responding effectively to the student’s motivational state, on contingent and Vygotskian inspired teaching strategies and on the plausibility problem. This latter is concerned with whether tactics that are effectively applied by human teachers can be as effective when embodied in machine teachers.

AI as a Methodology for Supporting Educational Praxis and Teacher Metacognition.

Abstract: Evidence-based practice (EBP) is of critical importance in education where emphasis is placed on the need to equip educators with an ability to independently generate and reflect on evidence of their practices in situ – a process also known as praxis. This paper examines existing research related to teachers’ metacognitive skills and, using two exemplar projects, it discusses the utility and relevance of AI methods of knowledge representation and knowledge elicitation as methodologies for supporting EBP. Research related to technology-enhanced communities of practice as a means for teachers to share and compare their knowledge with others is also examined. Suggestions for the key considerations in supporting teachers’ metacognition in praxis are made based on the review of literature and discussion of the specific projects, with the aim to highlight potential future research directions for AIEd. A proposal is made that a crucial part of AIEd’s future resides in its curating the role of AI as a methodology for supporting teacher training and continuous professional development, especially as relates to their developing metacognitive skills in relation to their practices.

Preface to the IJAIED 25th Anniversary Issue

Abstract: It is our great pleasure, as guest editors, to present an issue with invited articles by authors of high-impact articles from the journal’s past. By the end of 2015, the International Journal of Artificial Intelligence in Education completed its 25th volume and its 25th year of operation. This milestone called for a celebration of a scholarly kind. The current issue is part of that celebration. Although several landmark publications in the field appeared long before the journal’s first year of publication (1989), the journal’s early years coincided with the coalescing of the research community in Artificial Intelligence and Education (AIED). The same period saw the start of two relevant conferences, the International Conference on AI in Education (first held in 1987) and Intelligent Tutoring Systems (first held in 1988), although there had been two AI and Education conferences in the UK prior to Int J Artif Intell Educ (2016) 26:1–3 DOI 10.1007/s40593-015-0092-6

Preface to Special Issue on User Modelling to Support Personalization in Enhanced Educational Settings

Abstract: Personalization approaches in learning environments aim to foster effective, active, efficient, and satisfactory learning. Suitable user modelling techniques are crucial to support these approaches in dealing with learners’ needs within realistic learning environments, which are currently cropping up in a varied range of situations. Bearing this in mind, this paper provides an overview of relevant research over the last five years in both user modelling and education, which shows an increasing interest among researchers and practitioners who are concerned with modelling users’ needs in the new and evolving educational settings that are widening the diversity of learning contexts and issues to be considered. In particular, we have identified three main areas of research: i) modelling of learners and their performance to provide engaging learning experiences, ii) designing adaptive support, and iii) building standards-based models to cope with interoperability and portability.

Reflections on the Ecolab and the Zone of Proximal Development

Abstract: In 1999 we reported a study that explored the way that Vygotsky’s Zone of Proximal Development could be used to inform the design of an Interactive Learning Environment called the Ecolab. Two aspects of this work have subsequently been used for further research. Firstly, there is the interpretation of the ZPD and its associated theory that was used to operationalize the ZPD so that it could be implemented in software. This interpretation has informed further research about how one can model context and its impact on learning, which has produced a design framework that has been successfully applied across a range of educational settings. Secondly, there is the Ecolab software itself. The software has been adapted into a variety of versions that have supported explorations into how to scaffold learners’ metacognition, how to scaffold learners’ motivation and the implications of a learner’s goal orientation upon their use of the software. The findings from these studies have informed our understanding of learner scaffolding and have produced consistent results to demonstrate the importance of providing learners with appropriately challenging tasks and flexible support. Vygotsky’s work is as relevant now as it was in 1999: it still has an important role to play in the development of educational software.

Exploiting Listener Gaze to Improve Situated Communication in Dynamic Virtual Environments

Abstract: Beyond the observation that both speakers and listeners rapidly inspect the visual targets of referring expressions, it has been argued that such gaze may constitute part of the communicative signal. In this study, we investigate whether a speaker may, in principle, exploit listener gaze to improve communicative success. In the context of a virtual environment where listeners follow computer-generated instructions, we provide two kinds of support for this claim. First, we show that listener gaze provides a reliable real-time index of understanding even in dynamic and complex environments, and on a per-utterance basis. Second, we show that a language generation system that uses listener gaze to provide rapid feedback improves overall task performance in comparison with two systems that do not use gaze. Aside from demonstrating the utility of listener gaze in situated communication, our findings open the door to new methods for developing and evaluating multi-modal models of situated interaction.