Exploring Persona Characteristics in Learning: A Review Study of Pedagogical Agents

Tao, Yayi; Zhang, Guangli; Zhang, Di; Wang, Fang; Zhou, Yun; Xu, Tao

doi:10.1016/j.procs.2022.03.014

Cited by 16 publications

(8 citation statements)

References 41 publications

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“…Currently, studies on the effects of user acceptance and emotions on character design used in video game displays [10,11], animation [13], and real human-sized holographic tutors are being conducted [9]. There is still very little research on the effect of emotions in student learning on character design in the use of 3D Hologram Talking-head.…”

Section: Students' Emotion and Uncanny Valleymentioning

confidence: 99%

“…Typically, the primary display for these hologram educators is a real human character [5,[7][8][9]. According to research on the use of character design in video games [10,11] and pedagogical agents [12,13], the use of different levels of realistic character design can influence different levels of user comfort and emotions. For instance, although using too Manuscript received September 2, 2022; revised October 14, 2022; accepted November 2, 2022.…”

Section: Introductionmentioning

confidence: 99%

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A Conceptual Framework for 3D Hologram Talking-Head Character Design

Ramlie¹,

Ali²,

Aziz³

et al. 2023

IJIET

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In a previous study, we made some new discoveries regarding the use of holograms, particularly as a substitute for classroom instructors. The appropriate hologram tutor character is an important topic to study, considering that the character design as a hologram can significantly influence student learning emotions. In addition, the character design of the hologram tutor is believed to influence the student’s learning experience (LX). Since hologram tutors can have a positive impact on learning sessions, their use should be maintained. However, one of the issues that will hamper the use of hologram tutors in the future is the size of the platform, which is big and challenging to handle. In fact, hologram technology can also utilize the Talking-Head application. This 3D Hologram Talking-head is more manageable due to its smaller size. However, since the 3D Hologram Talking-head only displays the character’s head, the effect of using it on students’ learning emotions remained unclear. Therefore, in the context of this study, we will determine the emotional responses of students to the use of 3D Hologram Talking-Heads with different levels of realism of various characters.

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Section: Students' Emotion and Uncanny Valleymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Conceptual Framework for 3D Hologram Talking-Head Character Design

Ramlie¹,

Ali²,

Aziz³

et al. 2023

IJIET

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“…Numerous studies have been conducted to develop pedagogical agents, including literature reviews. Most of the literature studies that have been made discuss the role, design, and representation of pedagogical agents such as facial expressions, movements, sounds, and gender and how the roles of pedagogical agents [10], [11], [16], [17]. More in-depth research is needed to investigate how a series of enigmatic factors influence the efficacy of pedagogical agents [18].…”

Section: Introductionmentioning

confidence: 99%

Emotion-Related Pedagogical Agent: A Systematic Literature Review

Septiana,

Mutijarsa,

Putro

et al. 2024

IEEE Access

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The purpose of this systematic literature review (SLR) is to examine more deeply the various learning interventions provided by pedagogical agents and their relation to emotional aspects. A pedagogical agent is a software agent that provides guidance, feedback, or intervention to learners in digital environments. Pedagogical agents have the potential to address issues in computer-based learning, particularly online learning, which often neglects affective aspects, such as the emotions of its users. Most research on pedagogical agents has focused on their visual design, types of feedback, and other empirical aspects. However, this research has not examined what underlies these agents' ability to provide interventions personalized to learner's emotions. This paper explores the extent to which pedagogical agents have addressed learners' emotional needs. It also identifies opportunities and challenges for further research on interventions by pedagogical agents personalized to learners' emotional states. The study's research questions include: 1) To what extent does research exist on models, frameworks, or architectures for pedagogical agents, especially those related to emotions? 2) How are pedagogical agents represented, what types of interventions do they use, and how do these interventions affect learners' emotions? 3) What kinds of inputs are used to activate the pedagogical agent's functions? This SLR applied the Kitchenham method to select reference sources from 2013 to 2023 and was indexed by Scopus in the Q1 to Q4 range. Our review revealed the absence of a specific model for mapping out interventions tailored to the learner's emotional needs. Most existing pedagogical agents provide learning interventions that are less adaptive and personalized based on the learner's emotional state and are applied to asynchronous learning systems such as e-learning. There are still very few pedagogical agents that use real-time input technology by utilizing artificial intelligence to recognize the emotional state of learners so that they can trigger an adaptive and personalized intervention.

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“…To satisfy the individual needs of learners, the network learning platform needs to provide learning resources according to the characteristics and needs of different learners. This requires an in-depth analysis of the learners' online learning behaviors [6]. Efficient mining of these behavior data will help learners fully understand their learning behaviors, advantages, and disadvantages in the learning process.…”

Section: Introductionmentioning

confidence: 99%

Research on the construction of learner personas

Peng

Shang

et al. 2023

Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022)

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In the big data environment, the key is the precise recommendation of learning resources to learners. The core is the indeep mining of learners' personalized demands. This study solves this problem by constructing learner personas. Primarily, collect web learning data of learners to cluster them. Then analyze the characteristics of learners to predict their learning intentions and knowledge blind spots. Based on it, generate a clear personalized learning path subsequently. Precise positioning, quickly finding out the learner's ability and quality shortcomings. And completing the accurate recommendation to learners. It will help learners establish a reasonable learning path, and provide more accurate service support. This study will provide a theoretical basis for carrying out big data precision services and meeting the personalized learning needs of learners.

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Exploring Persona Characteristics in Learning: A Review Study of Pedagogical Agents

Cited by 16 publications

References 41 publications

A Conceptual Framework for 3D Hologram Talking-Head Character Design

A Conceptual Framework for 3D Hologram Talking-Head Character Design

Emotion-Related Pedagogical Agent: A Systematic Literature Review

Research on the construction of learner personas

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