Toward Personalized Scaffolding and Fading of Motivational Support in L2 Learner–Dialogue Agent Interactions: An Exploratory Study

Abstract

This study proposes a computer-based approach to effectively enhance second language learners' willingness to communicate in the target language. To do so, we implemented a conversational agent embedding a dialogue management model based on two conversational strategies (i.e., communication strategies and affective backchannels), serving as scaffolds for enhancing learners' willingness to communicate in the target language. Here, we report on differences observed among second language learners' preferences for both conversational strategies according to their initial level of willingness to communicate and on variations of their willingness with respect to such differences. Although we found that most students generally preferred a combination of both strategies, learners' preferences and the effects of the support provided by these strategies varied according to their level of willingness to communicate. Learners with lower willingness to communicate tended to prefer affective backchannels whereas those with higher willingness to communicate seemed to favor communication strategies. These results were consistent with posttest results, which showed that learners' expected willingness to communicate tended to be higher after interacting with systems embedding their preferred strategies. In sum, these results are preliminary evidence of the meaningfulness of accounting for such learners' preferences in adaptively using and fading the strategies employed by conversational agents to motivate second language learners to communicate in the target language.

Empathic pedagogical conversational agents: A systematic literature review

“…Ayedoun et al. (2020) find that Communication Strategies (CS) and Affective Backchannel (AB) have a positive impact on student perceptions. The authors observed that learners with a lower willingness to communicate tend to prefer AB over CS, while their counterparts with higher willingness to communicate tend to favour CS over AB.…”

“…On the other hand, affective feedback involves fostering a creative environment, giving students confidence and motivating students to think that the lesson goals are achievable and to become more involved in the learning activities. Ayedoun et al (2020) find that Communication Strategies (CS) and Affective Backchannel (AB) have a positive impact on student perceptions. The authors observed that learners with a lower willingness to communicate tend to prefer AB over CS, while their counterparts with higher willingness to communicate tend to favour CS over AB.…”

A systematic review on cross-culture, humor and empathy dimensions in conversational chatbots: the case of second language acquisition

“…(2015) Multimodal response generator To foster L2 learners' willingness to communicate in L2 N/A The approach decreases students' nervousness while increasing their self-confidence Ayedoun et al. (2019) Conversation agent, Jack To foster learners' readiness toward communication in a second language 40 Japanese university students Enhancing L2 learners' participation in contact and communication Ayedoun et al. (2020) An embodied conversational agent, Peter To encourage students to converse in the target language.…”

“… Approaches Authors and Year Name of the Chatbot Empathy Dimensions Affective Approaches Wu et al. (2022) An innovative affective mobile language tutoring system (AMLTS) The stress relief module The emotion recognition module Ayedoun et al. (2020) An embodied conversational agent, Peter Backchannels emotion-sensitive support Xie et al.…”

The implementation of chatbot-mediated immediacy for synchronous communication in an online chemistry course

“…Out of these, metacognitive scaffolding is the most appropriate to promote higher order thinking, helping students reflect on what they have learned, and assisting individual learning management (Reingold et al, 2008 ; Teo & Chai, 2009 ). One instance of this, although not a chatbot, would be Ayedoun et al’s ( 2020 ) computer-based approach to teach students with different levels of willingness using varied scaffolding and fading strategies. In moving towards a more adaptive educational chatbot, our system can benefit by incorporating more scaffolding theory and working examples.…”