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Call for Papers - AI in smart learning for sustainable education

Guest Editors:

Stephen J.H. Yang: National Central University, Taiwan
Hiroaki Ogata: Kyoto University, Japan
Tzu-Chi Yang: National Yang Ming Chiao Tung University, Taiwan
Owen H.T. Lu: National Chengchi University, Taiwan

Submission Status: Closed   |   Submission Deadline: 30 september 2023


Smart Learning Environments Journal is calling for submissions to our Collection on AI in smart learning for sustainable education. This collection intends to advocate an in-depth dialogue between researchers with a diversity of thoughts, genders, ethnicity, and cultures, as well as across disciplines, leading to a better understanding of AI in smart learning for sustainable education.

About the collection

Sustainable education is a quality education considering humanity. As we strive to develop smart learning environments, we also need to reflect appropriately on the impact of social change on education. How to provide fair and explainable analysis results to gain learners’ and teachers’ trust? How to guide them to meet challenges from both technical and organizational aspects? How to consider technological development with social value and human factors? 

The challenge for smart learning environments is incorporating educational and social changes into the design from the outset, including educating all stakeholders and providing the appropriate training. To develop the most helpful strategies for stakeholders from different perspectives, such as the content, methods, tools, systems, and training platforms. From the viewpoints of fairness, equality, diversity, inclusion, explainable, trustworthiness, and resilience, we work toward sustainable education.

Topics of interest for this special issue include, but are not limited to the following:

• Explainable AI in smart learning
• Trustworthy and responsible AI in smart learning
• Generative AI in smart learning
• Intelligent tutoring systems in smart learning
• Conversational robots in smart learning
• Differentiation and individualization in smart learning
• Intelligent assessment and evaluation in smart learning
• Data science for supporting AI in sustainable education
• Ethics of AI in sustainable education
• Fairness and equality of AI in sustainable education 
• Diversity and inclusion of AI in sustainable education
• Accountability and governance of AI in sustainable education
• The future smart learning environment in the Digital Age

  1. In the age of artificial intelligence (AI), trust in AI systems is becoming more important. Explainable recommenders, which explain why an item is recommended, have recently been proposed in the field of learn...

    Authors: Kyosuke Takami, Brendan Flanagan, Yiling Dai and Hiroaki Ogata
    Citation: Smart Learning Environments 2023 10:65
    Content type: Research Published on:

  4. Information avoidance has been studied in medicine, economics, and psychology, and has recently been discussed in educational technology. In this study, the authors developed a grouping method to reduce studen...

    Authors: Juan Zhou, Siqi Wang, Ling Xu and Chengjiu Yin
    Citation: Smart Learning Environments 2023 10:62
    Content type: Research Published on:

  6. In recent years, initiatives and the resulting application of precision education have been applied with increasing frequency in Taiwan; the accompanying discourse has focused on identifying potential applicat...

    Authors: Yi-Tzone Shiao, Cheng-Huan Chen, Ke-Fei Wu, Bae-Ling Chen, Yu-Hui Chou and Trong-Neng Wu
    Citation: Smart Learning Environments 2023 10:55
    Content type: Research Published on:

  7. The pretrained large language models have been widely tested for their performance on some challenging tasks including arithmetic, commonsense, and symbolic reasoning. Recently how to combine LLMs with prompti...

    Authors: Yicong Liang, Di Zou, Haoran Xie and Fu Lee Wang
    Citation: Smart Learning Environments 2023 10:52
    Content type: Research Published on:

  8. In recent years, smart learning environments have become central to modern education and support students and instructors through tools based on prediction and recommendation models. These methods often use le...

    Authors: Taisei Yamauchi, Brendan Flanagan, Ryosuke Nakamoto, Yiling Dai, Kyosuke Takami and Hiroaki Ogata
    Citation: Smart Learning Environments 2023 10:51
    Content type: Research Published on:

Submission Guidelines

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This Collection welcomes submission of Research Articles. Before submitting your manuscript, please ensure you have read our submission guidelines. Articles for this Collection should be submitted via our submission system. 

Articles will undergo the journal’s standard peer-review process and are subject to all of the journal’s standard policies. Articles will be added to the Collection as they are published.

The Guest Editors have no competing interests with the submissions which they handle through the peer review process. The peer review of any submissions for which the Guest Editors have competing interests is handled by another Editorial Board Member who has no competing interests.