Roy Bhakta’s research while affiliated with KWS UK Ltd and other places

This chapter presents research on the use of pedagogical agents as a tool to support the learning of skills related to the transposition of formulae. Participants from diverse backgrounds were recruited from those being taught on a compulsory mathematics course and allocated to one of three conditions. Each undertook a one-hour training session on mathematical transposition appropriate to their group allocation. The Approaches and Study Skills Inventory for Students (ASSIST) questionnaire and Technology Acceptance using a questionnaire based on the Technology Acceptance Model Framework (TAM) were administered. Interviews and focus groups were undertaken to explore their experiences. The pedagogical agent provided a positive learning experience that enabled learners to achieve the same levels of attainment as those who undertook human teaching. There is a need to improve techniques for designing and encoding the database of responses to natural language inputs and to make more use of automated strategies for acquiring and constructing databases. However, it is evident that this model of learning can be used to increase access to mathematics learning across sectors and devices. Such agents can be used with diverse learners, enabling them to personalise their learning and thereby improve the possibility for teaching in inclusive ways.

To date the research and practice of problem‐based learning (PBL) in digital spaces is both wide and varied. In particular, the use of PBL both online and in virtual worlds appears to prompt a re‐consideration of what counts as effective learning within the boundaries of current curricula structures, unsettling established spatial practices and educational norms. This chapter provides a review of the literature in this area and implications regarding some of the most effective ways of utilising PBL in digital spaces, which include the use of virtual worlds and virtual humans. The chapter also presents the findings of a recent study (Savin‐Baden & Bhakta, 2016) that explored the use of online PBL to examine whether students could detect a covert pedagogical agent in the group. The chapter concludes by making suggestions about how current practices might be developed and improved and further areas of research that are required.

The research on Virtual Humans has been increasingly adopted, adapted and tested in educational settings and the research indicates that they are of value as mentors and guides for students. It is evident from the literature that the term Virtual Humans tends to be used as an overarching term that include other terms such as Chatbots, Autonomous Agents and Pedagogical Agents. Virtual Humans are characters on the computer screen with embodied life-like behaviours such as speech, emotions, locomotion, gestures, and movements of the head, the eye, or other parts of the body. However, the research to date has not yet drawn clear distinctions between applications of Chatbots, Autonomous Agents and Pedagogical Agents across disciplines and in difficult and sensitive settings. This chapter reviews successful implementations of different types of Virtual Humans and discusses how this technology might be used in the future. It draws on recent studies undertaken to examine human interaction with a Pedagogical Agent and the passive and active detection of such agents within a synchronous, online environment. It also draws on a study that explored how the use of Pedagogical Agents might affect students' truthfulness and disclosure by asking them to respond to a lifestyle choices survey delivered by a web-based pedagogical agent. The implications of these studies are that truthfulness, personalisation and emotional engagement are all vital components in using Virtual Humans for online learning. It is argued that future studies on Virtual Humans should explore the differences in the relationships and interactions between learner and different types of Virtual Humans within authentic situations, such as virtual worlds.

It has been suggested that a covert Turing Test, possibly in a virtual world, provides a more level playing field for a chatbot, and hence an earlier opportunity to pass the Turing Test (or equivalent) in its overt, declared form. This paper looks at two recent covert Turing Tests in order to test this hypothesis. In one test (at Loyola Marymount) run as a covert-singleton test, of 50 subjects who talked to the chatbot avatar 39 (78 % deception) did not identify that the avatar was being driven by a chatbot. In a more recent experiment at the University of Worcester groups of students took part in a set of problem-based learning chat sessions, each group having an undeclared chatbot. Not one participant volunteered the fact that a chatbot was present (a 100 % deception rate). However the chatbot character was generally seen as being the least engaged participant—highlighting that a chatbot needs to concentrate on achieving legitimacy once it can successfully escape detection.

This paper presents a study that was undertaken to examine human interaction with a pedagogical agent and the passive and active detection of such agents within a synchronous, online environment. A pedagogical agent is a software application which can provide a human like interaction using a natural language interface. These may be familiar from the smartphone interfaces such as ‘Siri' or ‘Cortana', or the virtual online assistants found on some websites, such as ‘Anna' on the Ikea website. Pedagogical agents are characters on the computer screen with embodied life-like behaviours such as speech, emotions, locomotion, gestures, and movements of the head, the eye, or other parts of the body. The passive detection test is where participants are not primed to the potential presence of a pedagogical agent within the online environment. The active detection test is where participants are primed to the potential presence of a pedagogical agent. The purpose of the study was to examine how people passively detected pedagogical agents that were presenting themselves as humans in an online environment. In order to locate the pedagogical agent in a realistic higher education online environment, problem-based learning online was used. Problem-based learning online provides a focus for discussions and participation, without creating too much artificiality. The findings indicated that the ways in which students positioned the agent tended to influence the interaction between them. One of the key findings was that since the agent was focussed mainly on the pedagogical task this may have hampered interaction with the students, however some of its non-task dialogue did improve students' perceptions of the autonomous agents' ability to interact with them. It is suggested that future studies explore the differences between the relationships and interactions of learner and pedagogical agent within authentic situations, in order to understand if students' interactions are different between real and virtual mentors in an online setting.

Chatbots, known as pedagogical agents in educational settings, have a long history of use, beginning with Alan Turing's work. Since then online chatbots have become embedded into the fabric of technology. Yet understandings of these technologies are inchoate and often untheorised. Integration of chatbots into educational settings over the past five years suggests an increase in interest in the ways in which chatbots might be adopted and adapted for teaching and learning. This article draws on historical literature and theories that to date have largely been ignored in order to (re)contextualise two studies that used responsive evaluation to examine the use of pedagogical agents in education. Findings suggest that emotional interactions with pedagogical agents are intrinsic to a user's sense of trust, and that truthfulness, personalisation and emotional engagement are vital when using pedagogical agents to enhance online learning. Such findings need to be considered in the light of ways in which notions of learning are being redefined in the academy and the extent to which new literacies and new technologies are being pedalled as pedagogies in ways that undermine what higher education is, is for, and what learning means.

It would seem that emerging communication technologies are disrupting and changing societal norms and conventions. The literature suggests central to making sense of the unique qualities of cyberspace are understandings of such social networks, veracity and the differences between online and offline behaviour. We propose that as pedagogical agents are seen to help support and even improve the level of interactive learning on a programme or course, it is essential that these societal norms and behaviours are considered within pedagogical agent learning situations. Pedagogical agents are characters on the computer screen with embodied life-like behaviours such as speech, emotions, locomotion, gestures, and movements of the head, the eye, or other parts of the body. This paper presents findings of a pilot study that used pedagogical agents to examine disclosure in educational settings. The study used responsive evaluation to explore how the use of pedagogical agents might affect students’ truthfulness and disclosure by asking them to respond to a lifestyle choices survey delivered by a web-based pedagogical agent. The findings of this study suggest that 3 key issues are important; firstly the pedagogical appearance of the agent, secondly, the issue of choice and finally that of disclosure. Data also suggested that body language is critical to the learning effectiveness of pedagogical agents. The appearance of the pedagogical agent and the images it invoked, determined partially by students’ ability to choose their own pedagogical agent, were found to play a role in students’ willingness to disclose information. Qualitative findings from users also suggested that they may feel comfortable disclosing more sensitive information to pedagogical agents than to the interviewer. Our findings support the growing body of literature which suggests that the social environment of cyberspace is characterised by more open, straightforward and candid interpersonal communication, and that a pedagogical agent can support this. Findings indicate that emotional connection with pedagogical agents were intrinsic to the user’s sense of trust and therefore likely to affect levels of truthfulness and engagement. The implications of this study are that truthfulness, personalisation and emotional engagement are all vital components in using pedagogical agents to enhance online learning.