Multiple Agent Designs in Conversational Intelligent Tutoring Systems

Lippert, Anne; Shubeck, Keith T.; Morgan, Brent; Hampton, Andrew; Graesser, Arthur C.

doi:10.1007/s10758-019-09431-8

Cited by 21 publications

(18 citation statements)

References 75 publications

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“…The PAs in this literature review were software-based, embedded in digital learning environments. Agents typically use pattern matching and string processing, but more advanced technologies enable agents to use complex knowledge-based models (Hussain et al, 2019), and emerging technologies will enable multiple agents with different strategies and communication styles at the same time (Lippert, Shubeck, Morgan, Hampton, & Graesser, 2019). Despite the advancements, effective, scalable, and robust dialog management techniques are still a challenge, but, for example, explainable AI could make a dialog management system more human-like as users can understand the rationale behind it (Brabra et al, 2021).…”

Section: Discussionmentioning

confidence: 99%

How pedagogical agents communicate with students: A two-phase systematic review

Sikström

Valentini

Kärkkäinen

et al. 2022

Computers & Education

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Section: Discussionmentioning

confidence: 99%

How pedagogical agents communicate with students: A two-phase systematic review

Sikström

Valentini

Kärkkäinen

et al. 2022

Computers & Education

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“…ACM Q2 [23], [24], [25], [26] IEEE Q1 [27], [28], [29], [30], [31], [32], [33] Science Direct Q1 [34], [35], [36], [13], [33], [37], [38] Springer Q1 [39], [40], [41], [42], [43], [44], [45], [46], [47], [48], [49], [50], [51], [52], [53], [54], [18], [55], [56], [57], [58] Others Q1 [59], [60] Q2 [61], [62], [63], [64],…”

Section: Publisher Quartile Papermentioning

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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“…The specific interaction between culture, structure and technology is an environment that can be modeled with agent-based modeling. Agents interact with each other, imitate, communicate, exchange and can also compete with each other [12,13]. Based on the heterogeneous interaction modalities, various socialites can produce information including communication, identity, economy and culture.…”

Section: Figure 1 General Model Of Sustainable Developmentmentioning

confidence: 99%

Serious Game Relationship Between Socio-Economic and Territorial Condition

Retnani¹,

Bukhori²

2021

MMEP

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This research models a sustainable development through a serious game. The sustainable development system is influenced by internal factors and external factors. Internal factors consist of three sub-systems, namely: Culture, structure and technology. External factors consist of three sub-systems, namely: environment, economic actors and socio-cultural actors. The model in this research is agent-based involving three types of agents (firm, worker, and policy), internal variables, and external variables using a dynamic system. The behavior of each variable is observed using a dynamic system model. By providing initial values in internal factor variables and external factor variables, agent movement can provide information about the firm-size condition, the income of workers and the effect of policy on the development of companies and workers. Determination of initial data from internal factor variables and external factor variables aims to achieve a balance between supply and demand. In a certain phase, it will produce an optimal value, shown by supply and demand are at the same point. This condition needs to be maintained by adjusting all input variables so that supply and demand are in an optimal position.

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Multiple Agent Designs in Conversational Intelligent Tutoring Systems

Cited by 21 publications

References 75 publications

How pedagogical agents communicate with students: A two-phase systematic review

How pedagogical agents communicate with students: A two-phase systematic review

Emotion-Related Pedagogical Agent: A Systematic Literature Review

Serious Game Relationship Between Socio-Economic and Territorial Condition

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