An exploratory study on how children interact with pedagogic conversational agents

Marín, Diana Pérez; Pascual-Nieto, Ismael

doi:10.1080/0144929x.2012.687774

Cited by 22 publications

(11 citation statements)

References 10 publications

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“…It is expected that it increases the motivation of children and adolescents to learn with their agents [62]. In the future, students could even develop social friendship relationships with their agents [63][64][65][66][67]. Regarding the type of character, 8 out of the 12 reviewed agents have a human shape, usually for older students.…”

Section: Comparisonmentioning

confidence: 99%

A Review of the Practical Applications of Pedagogic Conversational Agents to Be Used in School and University Classrooms

Marín

2021

Digital

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Pedagogic Conversational Agents (PCAs) can be defined as autonomous characters that cohabit learning environments with students to create rich learning interactions. Currently, there are many agents reported in the literature of this fast-evolving field. In this paper, several designs of PCAs used as instructors, students, or companions are reviewed using a taxonomy to analyze the possibilities that PCAs can bring into the classrooms. Finally, a discussion as to whether this technology could become the future of education depending on the design trends identified is open for any educational technology practitioner, researcher, teacher, or manager involved in 21st century education.

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Section: Comparisonmentioning

confidence: 99%

A Review of the Practical Applications of Pedagogic Conversational Agents to Be Used in School and University Classrooms

Marín

2021

Digital

Self Cite

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“…A finding by Pérez-Marín [42] also revealed that the 'mood' of the chatbot might also decrease users' desire to leave the chatbot's room. Further research by Jin and Youn found out that the expressive chatbot may get different responses from people with social phobia and those who do not [43].…”

Section: User's Acceptance and Motivationmentioning

confidence: 95%

“…One of the vital features to sustain motivation is providing sufficient empathy for student's emotions. Compassion for the feelings of pupils seems to boost their desire to learn [42].…”

Section: User's Acceptance and Motivationmentioning

confidence: 99%

Gamification on Chatbot-Based Learning Media: a Review and Challenges

Hidayatulloh

Pambudi

Surjono

et al. 2021

ELINVO

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The mobile learning sector has exploded, implying that the e-Learning trend is shifting to mobile platforms. As a result, chatbots have become increasingly popular alternatives for online learning and examinations on mobile platforms. However, it did not provide enough motivation for the student. On the other hand, gamification in a typical e-Learning platform is a widely used technique for increasing students' learning motivation. Therefore, combining gamification with chatbot-based learning and examinations possibly offer benefits, including increase student learning motivation. This study explored the possibilities and future challenges of the development of gamification within chatbot-based learning media. We discussed four aspects: architecture's reliability, security and privacy issue, user’s acceptance and motivation, and gamification feature challenges.

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“…Therefore, there is reason to assume that a conversational application considering the notions of content packaging by means of the relation between thematicity and prosody will benefit from the same advantages as in natural conversation environments. Most of all, conversational avatars in applications for children in educational settings [16], applications for those with special needs [1] as well as for elderly [2] and, in particular, for those with cognitive impairments [17], would greatly benefit from such a communicatively-oriented improvement.…”

Section: Motivation and Backgroundmentioning

confidence: 99%

Towards expressive prosody generation in TTS for reading aloud applications

Domínguez¹,

Burga²,

Farrús³

et al. 2018

IberSPEECH 2018

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Conversational interfaces involving text-to-speech (TTS) applications have improved expressiveness and overall naturalness to a reasonable extent in the last decades. Conversational features, such as speech acts, affective states and information structure have been instrumental to derive more expressive prosodic contours. However, synthetic speech is still perceived as monotonous, when a text that lacks those conversational features is read aloud in the interface, i.e. it is fed directly to the TTS application. In this paper, we propose a methodology for pre-processing raw texts before they arrive to the TTS application. The aim is to analyze syntactic and information (or communicative) structure, and then use the high-level linguistic features derived from the analysis to generate more expressive prosody in the synthesized speech. The proposed methodology encompasses a pipeline of four modules: (1) a tokenizer, (2) a syntactic parser, (3) a communicative parser, and (3) an SSML prosody tag converter. The implementation has been tested in an experimental setting for German, using web-retrieved articles.

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An exploratory study on how children interact with pedagogic conversational agents

Cited by 22 publications

References 10 publications

A Review of the Practical Applications of Pedagogic Conversational Agents to Be Used in School and University Classrooms

A Review of the Practical Applications of Pedagogic Conversational Agents to Be Used in School and University Classrooms

Gamification on Chatbot-Based Learning Media: a Review and Challenges

Towards expressive prosody generation in TTS for reading aloud applications

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