Effects of an Adaptive Robot Encouraging Teamwork on Students’ Learning

Ravari, Parastoo Baghaei; Lee, Ken Jen; Law, Edith; Kulić, Dana

doi:10.1109/ro-man50785.2021.9515354

Cited by 10 publications

(9 citation statements)

References 31 publications

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“…Since robotic facilitation did not result in generating more or fewer ideas, the authors concluded that a robot facilitator can be effectively applied to support brainstorming activities, especially in cases when a human facilitator is unavailable or undesirable [21]. The study by [22] used the NAO robot as a teachable, adaptive robot in higher education settings and investigated whether robotic encouragement of group discussions can enhance social engagement and improve learning. The NAO robot was applied as a novice learner and an active member of a team.…”

Section: Related Workmentioning

confidence: 99%

“…In a study with 68 participants, pairs of learners were encouraged to take on the teaching role. The study showed that the robot's adaptive encouragement resulted in more dialogues between pairs of learners and increased both task and social engagement in the group [22].…”

Section: Related Workmentioning

confidence: 99%

“…Next, students reveal the card value to other players by turning the card face up; the robot encourages students to discuss and justify their choices with the aim of reaching a consensus. Following the approach proposed by [22], the robot is programmed to provide students with encouraging utterances to enhance group discussions and reach a consensus. For example, "Ok, so now justify your estimation and discuss which number you will assign to this task" is used as an encouraging utterance by the NAO robot.…”

Section: Planning Poker With Naomentioning

confidence: 99%

“…In addition to the shortened learning experience scale, which focuses on the overall learning experience of planning poker in a small group of students, the online evaluation survey included further items and questions, which were designed to capture the interaction experience of students with the NAO robot as the facilitator of planning poker. Eight items (21)(22)(23)(24)(25)(26)(27)(28) were designed and rated by study participants on a Likert-type scale from 1 = "strongly disagree" to 5 = "strongly agree" (Table 2). In addition to these eight items, an open question was asked at the end of the survey: "What are your recommendations for improving the planning poker in a team with a robot facilitator like NAO?…”

Section: Interaction Experience With Naomentioning

confidence: 99%

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Scaling-Up Social Learning in Small Groups with Robot Supported Collaborative Learning (RSCL): Effects of Learners’ Prior Experience in the Case Study of Planning Poker with the Robot NAO

Buchem

2023

Applied Sciences

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The COVID-19 pandemic accelerated the shift to online learning in higher education, making the need to rethink pedagogical approaches to on-campus education stronger than ever before. While online learning offers a wide range of benefits for both teachers and students, social, face-to-face interaction provides a strong rationale for in-person education. This paper proposes a novel approach to enhancing in-person social learning experiences through robot-supported collaborative learning facilitated by a social robot NAO in the case study “Planning poker with NAO”, which is a collaborative game-based activity facilitated by the robot. The case study was designed to provide a scalable social learning experience in small groups of students. The evaluation results from a study with 46 university students who played Planning poker with NAO explore different quality aspects of the learning experience. The results indicate that students valued both the social learning experience and the robotic facilitator. The analysis revealed some significant differences among students with and without prior experience in interacting with NAO, suggesting directions for future research related to novelty and familiarisation effects as well as to scaling up of social learning in small groups by applying social robots.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Planning Poker With Naomentioning

confidence: 99%

Section: Interaction Experience With Naomentioning

confidence: 99%

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Scaling-Up Social Learning in Small Groups with Robot Supported Collaborative Learning (RSCL): Effects of Learners’ Prior Experience in the Case Study of Planning Poker with the Robot NAO

Buchem

2023

Applied Sciences

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“…The Curiosity Notebook is a highly configurable, learning by teaching web application, where students teach an agent about different classification tasks. It supports flexible agent embodiment-for example a virtual agent [26], or a physical robot [27]-the configuration of agent characteristics-for example its style of humour [28]-and also facilitates group based teaching [29]. In the current implementation, natural language input is only supported for short, defined inputs, such as what topic to teach or responses to well-defined questions that are easy to parse (e.g.…”

Section: Curiosity Notebookmentioning

confidence: 99%

Natural Language Communication with a Teachable Agent

Love¹,

Law²,

Cohen³

et al. 2022

Preprint

Self Cite

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Conversational teachable agents offer a promising platform to support learning, both in the classroom and in remote settings. In this context, the agent takes the role of the novice, while the student takes on the role of teacher. This framing is significant for its ability to elicit the Protégé effect in the student-teacher, a pedagogical phenomenon known to increase engagement in the teaching task, and also improve cognitive outcomes. In prior work, teachable agents often take a passive role in the learning interaction, and there are few studies in which the agent and student engage in natural language dialogue during the teaching task. This work investigates the effect of teaching modality when interacting with a virtual agent, via the webbased teaching platform, the Curiosity Notebook. A method of teaching the agent by selecting sentences from source material is compared to a method paraphrasing the source material and typing text input to teach. A user study has been conducted to measure the effect teaching modality on the learning outcomes and engagement of the participants. The results indicate that teaching via paraphrasing and text input has a positive effect on learning outcomes for the material covered, and also on aspects of affective engagement. Furthermore, increased paraphrasing effort, as measured by the similarity between the source material and the material the teacher conveyed to the robot, improves learning outcomes for participants.

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