Smart Learning Partner: An Interactive Robot for Education

Lu, Yu; Chen, Chen; Chen, Penghe; Chen, Xiyang; Zhuang, Zijun

doi:10.1007/978-3-319-93846-2_84

Cited by 15 publications

(8 citation statements)

References 6 publications

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“…Sungkur & Maharaj (2022) advocate the use of SMART Learning Environments capable of taking into account learners' individualities and providing personalized learning. Lu et al (2018) present a new robot, called a Smart Learning Companion (SLP), which adopts self-determination theory (SDT) as a design principle to provide a more enjoyable learning experience and better motivate learners during their interaction with the robot. Elhoseny et al (2018) uses new smart learning technology to build a learning analytics framework that dissects measures of learner ability, meta-ability, and certainty in a smart learning environment.…”

Section: Data Mining: Prediction Of School Dropout Rates Using the De...mentioning

confidence: 99%

Review of Genetic Algorithm to improve Students Academic Performance by applying Smart Learning

Ortiz-Suarez,

Reyes-Hernández,

Ramírez-Hernández

et al. 2023

Int. Journal of COP and Infor.

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This paper reviews the use of genetic algorithms for enhancing academic performance through Smart learning. The study reveals that the application of technology in teaching can improve students' grades. It also analyzes the implementation of cognitive training and the benefits obtained for a better comprehension of the information received by individuals. A literature review is provided to give an overview of how these issues have impacted various parts of the world. The importance of integrating novel approaches to Smart learning, such as genetic algorithms and cognitive training, to enrich pedagogical strategies is highlighted.

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Section: Data Mining: Prediction Of School Dropout Rates Using the De...mentioning

confidence: 99%

Review of Genetic Algorithm to improve Students Academic Performance by applying Smart Learning

Ortiz-Suarez,

Reyes-Hernández,

Ramírez-Hernández

et al. 2023

Int. Journal of COP and Infor.

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“…There are few researched and commercially available examples of this. One example is the Open Tutor (OT, formerly known as the Smart Learning Partner), developed by researchers at Beijing Normal University (Lu et al, 2018). If a student has not understood something in their classroom, they can open the OT app on their mobile phone, type in what they want to know, and the app connects them with a list of human tutors who can help, all rated by other students (much like a dating app).…”

Section: Learning Network Orchestratorsmentioning

confidence: 99%

State of the art and practice in AI in education

Holmes

Tuomi

2022

Euro J of Education

145

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Recent developments in Artificial Intelligence (AI) have generated great expectations for the future impact of AI in education and learning (AIED). Often these expectations have been based on misunderstanding current technical possibilities, lack of knowledge about state‐of‐the‐art AI in education, and exceedingly narrow views on the functions of education in society. In this article, we provide a review of existing AI systems in education and their pedagogic and educational assumptions. We develop a typology of AIED systems and describe different ways of using AI in education and learning, show how these are grounded in different interpretations of what AI and education is or could be, and discuss some potential roadblocks on the AIED highway.

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“…Educational scenarios to which social robots have been deployed have been primarily formal settings with child learners [1,5,8,9,14,18,27]. Our focus is on a different setting: informal, conversational lifelong learning.…”

Section: Related Workmentioning

confidence: 99%

“…Robotic companions have been examined in many educational settings, acting as learning partners [14], intelligent tutors [5,8,12,26], teachable agents [9,18,27], and feedback providers [1]. A common goal among most robots filling these roles to date has been the furtherance of specific learning objectives.…”

Section: Introductionmentioning

confidence: 99%

AI Meets Austen: Towards Human-Robot Discussions of Literary Metaphor

Parde

Nielsen

2019

Lecture Notes in Computer Science

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Artificial intelligence is revolutionizing formal education, fueled by innovations in learning assessment, content generation, and instructional delivery. Informal, lifelong learning settings have been the subject of less attention. We provide a proof-of-concept for an embodied book discussion companion, designed to stimulate conversations with readers about particularly creative metaphors in fiction literature. We collect ratings from 26 participants, each of whom discuss Jane Austen's Pride and Prejudice with the robot across one or more sessions, and find that participants rate their interactions highly. This suggests that companion robots could be an interesting entryway for the promotion of lifelong learning and cognitive exercise in future applications.

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Smart Learning Partner: An Interactive Robot for Education

Cited by 15 publications

References 6 publications

Review of Genetic Algorithm to improve Students Academic Performance by applying Smart Learning

Review of Genetic Algorithm to improve Students Academic Performance by applying Smart Learning

State of the art and practice in AI in education

AI Meets Austen: Towards Human-Robot Discussions of Literary Metaphor

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