In this paper, we argue for the importance of conducting replication studies over various schools and countries when addressing topics about learning and instruction and propose educational technology to be a tool for this endeavor. We present an example of a cross-cultural replication study that makes use of educational technology in the form of a digital game-based automated feedback system. The study addresses feedback related behavior in 11-15-year-old students in US and Swedish classrooms, investigating students' choices to seek confirmatory (i.e., positive) or critical (i.e., negative) feedback, as well as their subsequent choices to revise their work based on this feedback. Comparisons of the data collected at several schools in the US and Sweden showed similar patterns of relationships among students' feedback-seeking behavior, their tendency to revise their work, and their learning outcomes in and outside the assessment environment. Overall, the findings revealed that this assessment approach seems to be generalizable from a North American to a European population. However, the findings showed both a significant difference between Sweden and the US regarding the preference for critical feedback and between different schools within each country. Thus, it is possible that the difference between countries reflects school differences rather than cultural differences.

In this paper we explore gender, perceived humanlikeness, animacy, intelligence and likeability of a female and male Furhat robot, and test for uncanny valley effects. We found no gender differences for neither user nor Furhats in perceived humanlikness or likeability, but female users rated the Furhats higher on animacy and intelligence. The study showed a tendency to an uncanny valley effect, but somewhat surprisingly the Furhat robots were overall not perceived as humanlike.

The field of Intelligent Virtual Agents (IVAs) has evolved immensely with respect to design and development of agents over the years. This has brought the following questions: What processes and methods are used to design virtual agents, and in particular, to what extent and how are users involved in the design process of virtual agents? In this paper, we review papers from the conference “Intelligent Virtual Agents” for the last five years (2015 - 2019) to shed light on these questions. The review included 308 short and long papers, with a focus on the interactive aspects of design. The review showed that only 14% of 308 papers explicitly mentioned/referred to user participation during the design of an IVA. User involvement is classified into two categories: one-time and iterative. The few studies that mention design only report on the use of standard Human-Computer Interaction (HCI) design methods to a rather limited degree.

This study examines the effects of teachable agents’ expressed self-efficacy on students. A total of 166 students, 10- to 11-years-old, used a teachable agent-based math game focusing on the base-ten number system. By means of data logging and questionnaires, the study compared the effects of high vs. low agent self-efficacy on the students’ in-game performance, their own math self-efficacy, and their attitude towards their agent. The study further explored the effects of matching vs. mismatching between student and agent with respect to self-efficacy. Overall, students who interacted with an agent with low self-efficacy performed better than students interacting with an agent with high self-efficacy. This was especially apparent for students who had reported low self-efficacy themselves, who performed on par with students with high self-efficacy when interacting with a digital tutee with low self-efficacy. Furthermore, students with low self-efficacy significantly increased their self-efficacy in the matched condition, i.e. when instructing a teachable agent with low self-efficacy. They also increased their self-efficacy when instructing a teachable agent with high self-efficacy, but to a smaller extent and not significantly. For students with high self-efficacy, a potential corresponding effect on a self-efficacy change due to matching may be hidden behind a ceiling effect. As a preliminary conclusion, on the basis of the results of this study, we propose that teachable agents should preferably be designed to have low self-efficacy.

The reported study investigated three gender-related effects on the rated persuasiveness of a speech given by a humanoid robot: (1) the female or male gendered voice and visual appearance of the robot, (2) the female or male gender of the participant, and (3) the interaction between robot gender and participant gender. The study employed a measure of persuasiveness based on the Aristotelian modes of persuasion: ethos, pathos and logos. In contrast to previous studies on gender bias toward intelligent virtual agents and robots, the gender of the robot did not influence the rated persuasiveness of the speech, and female participants rated the speech as more persuasive than men overall.

In a study with 108 10- to 12-year-olds who used a digital educational game targeting history, we addressed the phenomenon of perseverance, that is, the tendency to stick with a task even when it is challenging. The educational game was designed to make all students encounter tasks they did not succeed to solve, at which point they were offered a set of choices corresponding to perseverance and non-perseverance. Methods used were behavioral log data, post-questionnaires, and an in-game questionnaire conducted by a game character, who asked the students about the reason for their choice. Overall, we found no differences between high and low-perseverance students as to their experiences of effort, difficulty, and learning, and neither in their self-reported motives for persevering – when doing so. With respect to performance, however, high-persevering students solved significantly more tasks at higher difficulty levels. Comparing high-perseverance students who tended to take a break directly after a failed test – before they continued with the same task – with those who did not take a break, we found no significant differences, indicating that taking a break is not detrimental to learning and perseverance.

The present study used a questionnaire-based method for investigating people's interpretations of behavior exhibited by a person and a humanoid robot, respectively. Participants were given images and verbal descriptions of different behaviors and were asked to judge the plausibility of seven causal explanation types. Results indicate that human and robot behavior are explained similarly, but with some significant differences, and with less agreement in the robot case.

The current study investigated if and how students’ behaviour when using a teachable agent-based educational software were related to their working memory capacity. Thirty Swedish students aged 11–12, participated in the study. Results showed that differences in behaviour such as time spent on an off-task activity, time spent on interactive dialogues, and the number of tests that students let their TA take, were associated with differences in working memory capacity. 

This paper explores how users ascribe gender to a visually androgynous teachable agent, and if and how the ascribed gender can influence the perceived personality characteristics of the agent. Previous studies have shown positive effects of using agents with more neutral or androgynous appearances, for instance, a more gender neutral agent evoked more positive attitudes on females than did a more stereotypical female agent [1] and androgynous agents were less abused than female agents [2]. Another study showed that even though an agent was visually androgynous, the user typically ascribed a gender to it [3].

This paper explores the potentials of a new type of pedagogical agent – a Challenger Teachable Agent. The aim of such a pedagogical agent is to increase engagement and motivation, and challenge students into deeper learning and metacognitive reasoning. It is based on the successful implementation of the Learning by Teaching approach in Teachable Agents, and in addition it draws on previous work that has shown the potential of resistance or challenge as means to improve learning. In this paper we discuss how these two bases can be combined and realized through new types of behaviours in a Teachable Agent