Instructing a Teachable Agent with Low or High Self-Efficacy – Does Similarity Attract?

Abstract

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 selfefficacy. Furthermore, students with low self-efficacy significantly increased their selfefficacy in the matched condition, i.e. when instructing a teachable agent with low selfefficacy. 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 Int J Artif Intell Educ (2019) 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.

Applications of data science to game learning analytics data: A systematic literature review

“… Data to be collected: before applying GLA, and as part of the game design, it is highly recommended to specify and determine the game traces that will be collected (Tlili et al 2016;Serrano-Laguna et al 2018).  Teachable agents: in educational games, teachable agents can help achieve deeper levels of learning that transfer outside the game (Pareto 2014) and have a significant impact on in-game performance, preferably when designed to have low self-efficacy (Tärning et al 2018).…”

Time to Plan : How to support everyday planning in adolescents with intellectual disability

“…The research shows a promising learning outcome for the paradigm (Fiorella & Mayer, 2016). Another positive effect of the learning-by-teaching paradigm is that it supports the student's self-efficacy, that is a person's belief in his or her ability to carry out a certain task successfully, which in turn protects the tutee from blaming themselves for mistakes (Tärning et al, 2019). The paradigm has also been investigated in computer-based pedagogical agents with successful results (e.g.…”

“I Didn’t Understand, I´m Really Not Very Smart”—How Design of a Digital Tutee’s Self-Efficacy Affects Conversation and Student Behavior in a Digital Math Game

“…The analysis in [37] showed that interacting with a digital tutee with low self-efficacy was beneficial for students' performance. This was especially apparent for students who themselves had had reported low self-efficacy, they significantly increased their performance and performed as well as students with high self-efficacy when interacting with a digital tutee with low self-efficacy, see Figure 1 (left side).…”

“…In contrast, the characteristic of self-efficacy is possible to design and manipulate in a digital tutee and this is what we have done. In [37], we studied whether the manipulation of self-efficacy in a digital tutee-in terms of low versus high self-efficacy-would affect any of the following for the (real) students who acted as teachers for the digital tutee: (i) their self-efficacy (ii) their in-game performance, (iii) their attitude towards the digital tutee. The study made use of an educational game targeting mathematics and the base ten concept [38], further described in Section 2.1.…”

“…In order to make these results into guidelines on how to design pedagogical agents with low (or possibly high) self-efficacy and know the benefits and possible disadvantages of doing so, we need to know more about the possible causes of these effects, but also look more carefully after differences Together, these results indicate that interacting with a teachable agent with low self-efficacy was beneficial for students overall and in particular for students with low self-efficacy. In [37] we speculated that this can be due to the protégé effect, in that students make a greater effort for an agent lacking in self-efficacy that seems more in need of help than an agent with high self-efficacy. The ego-protective buffer can also be in play, in that students with low self-efficacy, that also tend to be low performing, do not perceive the feedback as negatively since it is recursive and aimed at the agent rather than them.…”