1. The Sub-forum of the 9th Annual Education Innovation Conference
The "AI + Metaverse + Digital Game-Based Learning" sub-forum will take you into the fantastic world of future education. Here, you will witness how artificial intelligence perfectly integrates with the metaverse to create an immersive digital game-based learning environment. The teacher exhibition area will showcase the latest AI teaching tools that allow students to easily master knowledge through games; the student exhibition area will demonstrate students' creativity and talent in digital game-based learning; and the corporate exhibition area will bring cutting-edge technological solutions to support the transformation and upgrading of the education industry. In addition, the roundtable discussion will invite industry experts to explore the directions and challenges of educational change. This is not only a feast of knowledge but also a collision of ideas and inspiration.
Event Time: May 17th, 2024 (Friday), 2:00 PM - 4:00 PM (Beijing Time)
Event Venue: 12th Floor of the International Research Building, South Campus, Xi'an Jiaotong-Liverpool University
For more details, please check: https://connect.xjtlu.edu.cn/group/aied/the-sub-forum-of-the-9th-annual-education-innovation-conference
2. AI and Education Special Session at the 10th International Conference on Smart Computing and Communication (ICSCC 2024)
The intersection of AI and Education presents a vast landscape of opportunities and challenges. As AI technologies continue to evolve, their potential to transform teaching, learning, and the overall educational experience becomes more apparent. This special session aims to delve into the latest advancements and research in this field, exploring how AI can enhance various aspects of education.
We invite experts, researchers, and practitioners to share their insights and experiences through papers and presentations.
Proposal submission: 30th April 2024
Acceptance: Rolling basis
Submission Link: https://edas.info/N31700
Event Time: July, 2024
For more details please check: https://icscc.undiknas.ac.id/special-sessions/
Website: https://icscc.undiknas.ac.id/
The previous proceedings can be seen at the following links:
- 9th ICSCC 2023 papers have been published at IEEExplore: https://ieeexplore.ieee.org/xpl/conhome/10334953/proceeding
- 8th ICSCC 2021 papers have been published at IEEExplore: https://ieeexplore.ieee.org/xpl/conhome/9528077/proceeding
- 7th ICSCC 2019 papers have been published at IEEExplore: https://ieeexplore.ieee.org/xpl/conhome/8826063/proceeding
3. AI and Education Special Session at the International Conference on Higher Education Learning and Teaching 2024
Full paper submission: 2nd July 2024
Submission Link: http://curtin.edu.my/event/ichelt-2024/
For more details, please check: https://connect.xjtlu.edu.cn/group/aied/ichelt
About (click to expand)
Mission:
We aim to revolutionize the education industry by integrating cutting-edge Artificial Intelligence technologies. We strive to enhance learning experiences, empower educators, and inspire the next generation of innovative thinkers.
Vission:
Our vision is to create a future where education is personalized, accessible, and tailored to individual needs through the seamless integration of Artificial Intelligence. We envision a world where every learner can reach their full potential.
Conceptual Framework:
We have identified three levels of AI models (Figure 1) to achieve these goals: L0, L1, and L2. L0 level contains general AI models in which numerous companies have released their products. L1 level is the specified AI model for the education industry, and no organization has announced a mature model yet. The L2 level applies the L1 model in the specific educational context. Currently, there are some applications developed at this level. Without the support of L1, connections from just L0 to L2 cannot impact the whole education system. Our centre's first essential task is collaborating with external partners to develop the L1 model and, simultaneously, developing some contextual applications at the L2 layer. The other essential task is to promote this model to other education institutions to transform their education system and practice.
Figure 1. Conceptual Framework of Research Centre for AI and Education
(The Research Centre for AI and Education was launched on December 22, 2023. The Academy of Future Education within Xi'an Jiaotong-Liverpool University (XJTLU) will provide the start-up fund. The website content will be constantly updated as we expand, with new members and ideas coming in.)
Click this link to see the launch event slides.
English Introduction of the Research Centre for AI and Education
1. AI-Driven Model Development for Educational Advancement (click to see more)
Project Leader: Liu, Jingxin (School of AI and Advanced Computing, Entrepreneur College (Taicang), XJTLU)
The project aims to develop specialized AI models for the education industry, with a focus on advancing teaching, learning, and administrative processes. Through collaborative efforts with experts and partners, we harness the power of AI technologies to optimize educational outcomes and create transformative tools. Our primary objective is to drive positive change in education by providing personalized learning experiences and streamlining administrative tasks.
2. AI and Game-based Learning (click to see more)
Project Leader: Liang, Hai-Ning (Founding Head of Department (2019-2023), Deputy Director of the Suzhou Municipal Key Lab for Intelligent Virtual Engineering, the Suzhou Key Lab for Virtual Reality Technologies, and the XJTLU Virtual Engineering Center)
Digital games are very popular because they are fun to play. There is clear evidence that games have strong motivational properties, and when they are designed to support learning activities, students can learn while playing, that is, having fun and learning at the same time. Recent computing advances have enabled the rapid development and integration of AI into many activities that were previously not possible. In doing so, AI has empowered people to accomplish tasks more efficiently and effectively. This project explores how we can make games more supportive and engaging via AI-enhanced features. In short, we want to understand how to design and deploy AI-supported games to make them more fun and tailored to the needs of individual learners.
3. AI and Language Learning (click to see more)
Project Leader: Zou, Bin(Department of Applied Linguistics, XJTLU)
AI and language learning project aims to explore using AI, including Generative AI, to enhance learning languages such as English, Chinese, Japanese, Spanish, etc. We welcome teachers, researchers, institutions, schools, companies and investors to join us to develop and share AI resources, practice and research.
4. AI and Organizational Learning (click to see more)
Project Leader: Wang, Qian(Research Director, Academy of Future Education, XJTLU)
AI and Organizational Learning is a project aimed at leveraging artificial intelligence to optimize knowledge sharing and skill development within knowledge organizations, ultimately enhancing overall performance and adaptability. Through interacting with advanced AI and personalized learning, we seek to create a dynamic and responsive learning environment that fosters continuous growth and innovation.
5. AI as a Design Partner for Learning (click to see more)
Project Leader: Dall’Asta, Juan Carlos(Department of Architecture, Design School, XJTLU)
The project seeks to explore the integration of AI Machine Learning in design education with the aim of enhancing creativity and design inspiration. The design process relies on a foundation of technical knowledge, accumulated experience, and an intuitive 'creative' component that often reflects the unique talent of the designer. Artificial Intelligence serves as a valuable collaborator in the creative phase by offering suggestions and ideas to designers.
The question arises, 'What do you think about this idea?' AI actively engages with designers during specific stages of their work. From this perspective, AI emerges as a valuable support system, capable of generating ideas and insights during the crucial conceptualisation phase, one of the most critical stages in the design process.
6. AI and Learner Emotion (click to see more)
Project Leader: Craig, Paul(School of Advanced Technology, XJTLU)
The goal of this project is to investigate how Artificial Intelligence (AI) can be used to improve our understanding of learner emotion in order to improve the student learning experience and learning outcomes. Emotions and learning are closely related with learner emotion having the potential for either a positive or negative effect, depending on the type of emotion and the context in which it is experienced. For example, positive emotions such as joy, excitement, and curiosity can enhance learning by increasing motivation, engagement, and attention. Negative emotions such as anxiety, frustration, and boredom can hinder learning by reducing motivation, engagement, and attention. Being able to recognise and respond to learner emotion is key to fostering a supporting and engaging learning environment. This project aims to investigate how AI technology can improve the process for this type of emotionally empathetic learning support, particularly to improve our use of educational technologies where the normal channels for face-to-face recognition of human emotion may not be feasible.
7. AI and Learning Analytics (click to see more)
Project Leader: Purwanto, Erick(Department of Computing, School of Advanced Technology, XJTLU)
Learning analytics systems leverage various types of data to gain insights into students' learning processes. They play a crucial role in identifying at-risk students and facilitating early, individualized intervention strategies. Traditional systems rely on Learning Management Systems and engagement data. This project aims to incorporate AI to additionally consider emotional states through multimodal data such as chat text, facial expressions, biometric sensor data, and voice recognition.
8. AI and Teaching Materials (click to see more)
Project Leader: Georgiev, Svetoslav(School of Intelligent Finance and Business, XJTLU); Tinsley, Joseph
(Educational Development Unit, XJTLU)
This project aims to explore students’ perceptions of teachers’ usage of generative AI (GAI) assisted teaching materials. Teaching materials created with the assistance of GAI have the potential to increase teacher efficiency and create value for students. Whilst the effectiveness of AI-assisted teaching materials has been demonstrated, there is a need for studies which examine students’ perceptions and acceptance of AI-assisted teaching materials. Students who have a positive perception of their learning environment, including teaching materials, are more likely to take a deeper approach to learning.
The project’s implications are two-fold. First, on the scientific front, we expect to enrich the literatures on student engagement, as well as on student perceptions of GAI usage in HE classroom environments. Second, on the industry front, we expect to aid companies developing AI tools for educational purposes to better understand students’ needs and perceptions of visual teaching materials, which would enable them to redesign and/ or readapt their software so that it can reflect the current needs of both students and teaching instructors.
9. AI and Childcare Quality Evaluation (click to see more)
Project Leader: Lu, Jinjin(Academy of Future Education, XJTLU)
The development of Childcare quality framework (3-6 years) is important for both EC teachers and parents. With the development of AI technology, we aim to provide a holistic method to evaluate the Childcare quality in the EC context. This powerful AI tool will be used as the first innovative tool in China.
We are recruiting PhDs who have experience in early childhood education, AI, computer science, and graph design, and user experience. Also, we are seeking for marketing and business partners in China and oversea.
10. AI and Assessment (click to see more)
Project Leader: Fan, Pengfei(Department of Intelligent Science, School of Advanced Technology, XJTLU)
The project aims to investigate AI's transformative role in educational assessment. This project seeks to explore the potential benefits, challenges, and implications of integrating AI technologies into various aspects of assessment, including automated grading, customised feedback, and testing methodologies.
11. AI and Multimodal Learning (click to see more)
Project Leader: Varga-Atkins, Tünde(Centre for Innovation in Education, University of Liverpool, UK)
This project’s aim is therefore to explore and evaluate the opportunities brought by the use of GenAI tools within education to support disciplinary knowledge creation in the form of multimodal learning and the development of digital capabilities by students and staff.
Our interest in multimodality follows Kress’ (2010) social semiotic approach, which explores the ways in which different semiotic modes (text, speech, sound, image, moving image, touch, gesture etc.) are present and combined within one communication to produce a multimodal artefact. For instance, an infographic combines text and image in ways that produce extra meaning. Multimodal learning is concerned with designing learning utilising multimodal texts across media, forms and formats appropriately to the given context (van Leeuwen, 2017). Other examples of multimodal texts include posters, video, dance or virtual simulation. Multimodal learning also involves the use of ‘semiotic technologies’ such as collaborative tools, visualisation apps, online quizzes to support teaching practice. The ascent of GenAI offers further expansion to eductors’ repertoire of semiotic technologies.
GenAI is a form of technology that uses deep learning techniques to access a huge swathe of data and produce artefacts based on the prompt(s) provided to it by a human user, is increasingly capable of producing multimodal content, including (but not limited to) text, speech, audio, image, video and even three-dimensional models (Fui-Hoon Nah et al., 2023). Multimodal GenAI can be, and is being, used to create, manipulate, and adapt content and combine different semiotic forms together, to produce multimodal artefacts.
In this project, we focus on three strands:
- Teaching: teachers can potentially use GenAI to represent subject knowledge multimodally.
- Learning: students may be able to encounter, explore, evaluate and express ideas via multimodal GenAI, where technology can help manipulate, change, adapt or create artefacts that incorporate multiple semiotics forms.
- Assessment: students could use GenAI to create multimodal artefacts, or critique/reflect on existing ones for assessment.
Project Leader: Reis, Charlie (Director of Educational Development Unit, XJTLU); Sun, Yiqun
(Educational Development Unit, XJTLU)
In order to gain insights into the impact of AI on higher education and explore innovative applications for enhancing learning and teaching, it is proposed to establish an experimental research fund and project for student-staff exploration of generative artificial intelligence in higher education. Students, key stakeholders in the learning and teaching process, will collaborate with faculty members to create a “creative sandpit” that enables a comprehensive understanding of AI's impact on learning and teaching and an exploration of creative possibilities to harness the power of AI to enhance the educational experience.
13. AI and Project Fair Allocation (click to see more)
Project Leader: Song, Pengfei(Department of Mechatronics and Robotics, School of Advanced Technology, XJTLU)
The aim of this project is to develop a personalized, and AI-assisted project recommendation system based on the Moodle fair allocation plugin to promote the effectiveness and satisfaction of students' Final Year Project learning experiences.
14. AI and Collaborative Learning (click to see more)
Project Leader: Kim, Jinhee (Old Dominion University, US)
The aim of this project is to systematically investigate the process and outcome of SAI in classroom debate contexts and to introduce a conceptual framework guided by both self-regulated theory and AI methods used to advance research in human and AI collaboration in Education.
Project Leader: Amini, Mansour (School of Languages, Literacies, and Translation, Universiti Sains Malaysia )
The proposed study aims to investigate Chinese postgraduate students' perspectives on the ethical considerations, challenges, and benefits associated with the use of artificial intelligence (AI) in their academic pursuits within the Malaysian higher education landscape. This study could hold significant relevance in understanding the nuances of AI adoption among Chinese students studying in Malaysia, and the insights garnered can contribute to informed decision-making in educational policies and practices related to AI integration. The research questions are structured to address key aspects: a) Ethical considerations perceived by Chinese postgraduate students in Malaysia regarding AI usage in academic studies. b) Challenges Chinese postgraduate students face when integrating AI technologies into research and coursework. c) Perceptions of the functions and benefits of AI in enhancing academic performance and research outcomes among Chinese postgraduate students in Malaysian universities.
Project Leader: Koroleva, Diana (Institute of Education, HSE University); Li, Na
(Academy of Future Education, XJTLU)
This study aims to explore the impact of Hofstede's national cultural dimensions on the adoption of AI tools by university teachers and students, comparing AI adoption patterns between the Higher School of Economics (HSE) and Xi'an Jiaotong-Liverpool University (XJTLU). This study can identify common challenges and opportunities in AI integration within the academic setting, and propose recommendations for enhancing AI adoption in higher education.
Project Leader: LeCorre, JeanYves (Educational Development Unit, XJTLU)
This project evaluates alternative strategies for incorporating AI-driven tools into the classroom-as-organisation instructional design. AI can substantially elevate immersive learning environments. The project builds on an existing learning prototype supported by a learning management system (Moodle) and an immersive virtual reality (VR) platform. Along with developing the AI-enhanced prototype, a methodology roadmap will be proposed to assist educators in designing and implementing AI-enhanced immersive learning experiences based on classroom-as-organisation learning design in online or blended settings. The prototype features a course in management accounting, and the methodology roadmap could serve to design immersive learning experiences in other subject areas or disciplines. The project has applied for funding from XJTLU Summer Undergraduate Research Fellowship.
18. A quasi-experimental scenario-based study of the effect of using AI tools on self-regulation of learning (scenario-based experiments) (click to see more)
Project Leader: LeCorre, JeanYves (Educational Development Unit, XJTLU)
The literature suggests that learners demonstrate various behavioural intentions in response to socio-cognitive conflicts when interacting in groups to develop new knowledge. However, socio-cognitive conflicts benefit learning because they are regulated through specific mechanisms to ensure that the conditions under which confronting diverging ideas results in positive cognitive and relational outcomes are met. This project investigates the effects of incorporating AI-driven tools and learning activities on learning self-regulation. A causality model is examined through a series of scenario -based quasi-experiments to determine the antecedents of collaborative behaviours that affect behavioural intentions towards resolving socio-cognitive conflicts.The study uses an immersive learning prototype supported by a VR immersive learning platform and a learning management system in lab settings to support the research design. The project has applied for funding from the ‘German Academic Exchange Service’ to use the behavioural lab facilities of Lakelab at Universitat Konstanz (Germany)
Note: The projects are listed chronologically with the most recent appearing last.
Roles and Responsibilities (click to expand)
Director or co-director: The director or co-director will oversee the centre's overall direction, management, and coordination. They will be responsible for setting clear goals, milestones, and timelines and ensuring the projects remain on track. They will also serve as the primary point of contact for external stakeholders and provide updates and progress reports regularly.
Board of Advisors: They are the most experienced and knowledgeable individuals in the centre. They possess a wealth of information and resources that they can provide to the centre to support its success. As senior-level members, they provide guidance and leadership to the project teams. They serve as a sounding board for ideas and provide valuable feedback to help steer the projects in the right direction. By leveraging their expertise and resources, they help ensure that the centre has the necessary support to achieve its goals.
Project leaders: The project leader plays a critical role in managing and coordinating AI and education projects within the research center. Responsible for allocating resources, setting milestones, collaborating with the director/co-director, and overseeing project progress, the project leader ensures the smooth implementation of projects and their alignment with the centre's overall objectives.
Disciplinary Experts: Disciplinary experts in Education (theory and technology) will contribute their deep knowledge and expertise in their respective fields to inform the development of the L1 model. They will analyse educational theories, frameworks, and best practices and help to integrate them into the AI model. Disciplinary experts in AI techniques will be responsible for bringing their technical expertise to bear on the center's projects. They will help design, develop, and implement AI models and evaluate their effectiveness. They will also provide insights to refine and improve these models.
AI Educators: AI educators will provide their insights and expertise on applying AI technology in education. They will be responsible for understanding educational institutions' and students' needs and challenges and helping to develop AI models that address these challenges effectively.
Research Assistants: Research Assistants will be integral to the operations of the research centre. They will assist the project leaders and disciplinary experts in carrying out research activities, data collection and analysis. They will also support in the preparation of reports and presentations, as well as in organizing meetings and workshops.
Industrial Experts: Industrial experts from leading AI companies will bring their practical knowledge and experience to the project. They will advise on AI technology trends, market opportunities, and potential applications of the L1 model in real-world settings.
User Representatives: User representatives will provide feedback and input on integrating the L1 model into educational institutions' practices. They will represent the voices and needs of students, educators, and other stakeholders and ensure their input is considered in the development process.
Note: In the member list, the icons for each role will be displayed beside member's name to indicate everyone's role.
Member List
Full member list (by alphabet):
A: Albano, Silvia (Department of Architecture, Design School, XJTLU); Amini, Mansour
(School of Languages, Literacies, and Translation, Universiti Sains Malaysia ); Andreeva Anastasia
(Institute of Education, HSE University)
B: Beech, Helen (Dean, School of Languages, XJTLU); Bi, Xin
(Chief Officer of Data; Director, Centre for Knowledge and Information; Director, Learning Mall; Director, University Marketing and Communications; University Librarian, XJTLU); Bu, Hongyuan (student)
C: Chen, Qi (School of AI and Advanced Computing, XJTLU); Chen, Jianjun
(Department of Computing, School of Advanced Technology, XJTLU); Chen, Jiehui
(Principal of Science and Technology Center, Aisa Liwan School, Guangzhou); Chen, Lei
(Management Information Technology and System Office, XJTLU); Chen, Xinyi
(School of Language, XJTLU); Craig, Paul
(School of Advanced Technology, XJTLU); Cross, Adam
(Associate Vice President of Education, Director of the Graduate School, XJTLU); Cui, Wei
(Learning Mall, XJTLU)
D: Dall’Asta, Juan Carlos (Department of Architecture, Design School, XJTLU); Drumm, Louise
(Department of Learning and Teaching Enhancement, Edinburgh Napier University)
E:
F: Fan, Pengfei(Department of Intelligent Science, School of Advanced Technology, XJTLU); Fan, Li
(Principal of Suzhou Ren 'ai School); Fan, Liangjie
(student); Fu, Jiaqi
(Department of Educational Studies, Academy of Future Education, XJTLU)
G: Gan, Hongseng (School of AI and Advanced Computing, Entrepreneur College (Taicang), XJTLU); Georgiev, Svetoslav
(School of Intelligent Finance and Business, XJTLU); Gu, Yubin
(Management Information Technology and System Office, XJTLU)
H: Han, Wei (School of Language, XJTLU); He, Huimin
(School of Language, XJTLU); Hu, Zhengdong
(founder (CEO) of “Kookaburra Education); Hua, Weiwei
(Learning Mall, XJTLU); Huang, Lulu
(School of Language, XJTLU); Huang, Yanhao
(student); Huijser, Henk
(Learning and Teaching Unit, Queensland University of Technology, Australia); Hou, Xianxu
(School of AI and Advanced Computing, Entrepreneur College (Taicang), XJTLU); He, Hao
(CEO of Hong Kong Hang Fun International Corporation Limited); Huang, Long
(School of Intelligent Manufacturing Ecosystems, XJTLU); Huang, Zhiying
(Department of Accounting, International Business School Suzhou, XJTLU)
I:
J: Ji, Qiong (School of Intelligent Finance and Business, XJTLU); Jiang, Yue
(Department of Economics, XJTLU); Jiang, Yirui
(Wenzhou-Kean University); Jogezai, Nazir
(Institute of Education, HSE University); Juwono, Filbert
(Department of Electrical and Electronic Engineering, XJTLU);
K: Kim, Jinhee (Old Dominion University, US); Koroleva, Diana
(Institute of Education, HSE University)
L: LeCorre, JeanYves (Educational Development Unit, XJTLU); Leach, Mark
(Deputy Dean, School of Advance Technology); Lei, Yanhui
(Department of Urban Planning and Design, XJTLU); Li, Bowen
(student); Li, Jingquan
(CUHK); Li, Huakang
(School of Artificial Intelligence and Advanced Computing, XJTLU); Li, Qingjie
(General Manager, MathWorks China Education Division); Li, Na
(Department of Educational Studies, Academy of Future Education, XJTLU); Li, Sheng
(Principal of International Department of Shijiazhuang Foreign Language Education Group); Li, Wang
(Education BU General manager, Ximmerse Inc); Li, Yanle
(student); Li, Yihan
(student); Li, Yuanzhi
(student); Li, Yue
(Department of Computing, School of Advanced Technology, XJTLU); Liang, Hai-Ning
(Founding Head of Department (2019-2023), Deputy Director of the Suzhou Municipal Key Lab for Intelligent Virtual Engineering, the Suzhou Key Lab for Virtual Reality Technologies, and the XJTLU Virtual Engineering Center); Liang, Jiapei (student); Liang, Yuan
(Learning Mall, XJTLU); Liao, Ruizhi
(Chinese University of Hong Kong, Shenzhen); Lin, Xi
(East Carolina University); Lindsay, Rob
(Centre For Innovation In Education, University of Liverpool); Liu, Hengyan
(School of AI and Advanced Computing, XJTLU); Liu, Tanjun
(Department of Applied Linguistics, XJTLU);Liu Suying
(student); Lim, Eng Gee
(Dean, School of Advanced Technology, XJTLU); Limniou, Maria
(Department of Psychology, University of Liverpool, UK); Liu, Bohan
(student); Liu, Jingxin
(School of AI and Advanced Computing, Entrepreneur College (Taicang), XJTLU); Lu, Jinjin
(Academy of Future Education, XJTLU); Luo, Lan
(student); Luo, Rong
(English Language Centre, XJTLU); Luo, Yujuan
(Department of Educational Studies, Academy of Future Education, XJTLU).
M: Ma, Fei (Associate Vice President of Research and Impact, XJTLU); Ma, Teng
(Department of Computing, School of Advanced Technology, XJTLU);
N: Nahar, Nurun (Institute of Management, University of Bolton); Ni, Yi
(student); Ning, Xujia
(student)
O:
P: Purwanto, Erick (Department of Computing, School of Advanced Technology, XJTLU); Pan, Yushan
(Department of Computing, School of Advanced Technology, XJTLU)
Q: Qin, Ke (student); Quadir, Benazir
(Learning Institute for Future Excellence)
R: Reis, Charlie (Director of Educational Development Unit, XJTLU)
S: Saunders, Samuel (Generative Artificial Intelligence Network, Centre for Innovation in Education, University of Liverpool, UK); Selig, Thomas
(Department of Computing, School of Advanced Technology, XJTLU); Shao, Ying
(English Language Centre, XJTLU); Shen Nan
(Student); Shen, Xuanying
(School of Language, XJTLU); Song, Pengfei
(Department of Mechatronics and Robotics, School of Advanced Technology, XJTLU); Stefanidis, Angelos
(founding Dean of School of AI and Advanced Computing and the School of Internet of Things at XJTLU Entrepreneur College (Taicang)); Sun, Yiqun
(Educational Development Unit, XJTLU); Sun, Qingyang
(Department of Applied Linguistics, XJTLU); Sun Zehui
(student)
T: Tang Rui (student); Tang, Wenjia (student); Tedjosaputro, Mia
(Department of Architecture, XJTLU); Tinsley, Joseph
(Educational Development Unit, XJTLU).
U:
V: Varga-Atkins, Tünde (Centre for Innovation in Education, University of Liverpool, UK)
W: Wang, Airong (School of Language, XJTLU); Wang, Luchang
(Department of Applied Linguistics, XJTLU); Wang, Hua
(Hebei Institute of Environmental Engineering); Wang, Qian
(Research Director, Academy of Future Education, XJTLU); Wang, Jialin
(student); Wang, Jing
(Deputy Head, Learning Mall, XJTLU); Wang, Peiyao
(student); Wang, Ping
(Head of Higher Education Division, ILEAD, Academy of Future Education, XJTLU); Wang, Yicheng
(School of Intelligent Finance and Business, XJTLU); Wang, Yizhi
(student); Wang, Yu
(Educational Development Unit, XJTLU); Wang, Ziyang
(student); Wei, Chenlong
(student); Wei, Dawei
(Department of Applied Linguistics, XJTLU); Wen, Run
(Department of Educational Studies, the Academy of Future Education, XJTLU) Wu, Guanjun
(Dean, School of Politics and International Relations, East China Normal University); Wu, Yao
(School of Language, XJTLU); Wu, Yun
(Salisbury University); Wu, Zhaobin
(Longhua District Education Bureau, Education Science Research Institute of information and technology minister and Shenzhen Youth Artificial Intelligence Education Association Executive Vice president).
X: Xi, Youmin (Executive President of Xi'an Jiaotong-Liverpool University, Pro-Vice-Chancellor of University of Liverpool, Prof. of Management of Xi’an Jiaotong University); Xia, Ling
(School of Languages, XJTLU); Xie, Jun
(National Open University); Xiong, Lin
(School of Intelligent Finance and Business, XJTLU); Xu Lei
(student)Xu, Liwei
(student); Xu, Wenqi
(student); Xu, Youlong
(student); Xu, Zongzhen
(Dalian Jiaotong University); Xue, Xinrong
(Learning Mall, XJTLU); Xun, Jiyao
(EEH Academic, Entrepreneur College (Taicang), XJTLU)
Y: Yang, Guang (student); Yang, Rui
(Department of Intelligent Science, School of Advanced Technology, XJTLU); Yang, Zhiqin
(Learning Mall, XJTLU); Yang, Xinyi
(student); Yao, Xue
(School of Language, XJTLU); Ye, Tiantian
(student); Yin, Hui
(Department of Applied Linguistics, XJTLU); Yu, Lingyun
(Department of Computing, School of Advanced Technology, XJTLU); Yue, Yong
(Director, Virtual Engineering Centre, Department of Computing, School of Advanced Technology, XJTLU)
Z: Zeng, Yiwei (Deputy Head, Management Information Technology and System Office, XJTLU); Zhang, Di
(School of AI and Advanced Computing, Entrepreneur College (Taicang), XJTLU); Zhang, Qing
(Department of Educational Studies, Academy of Future Education, XJTLU); Zhang, Jianlan
(Head of ILEAD, Academy of Future Education, XJTLU); Zhang, Linjia
(Department of Economics, XJTLU); Zhang, Xiaojun
(Chief Officer of Education; Leader of Entrepreneur College (Taicang) Leadership Team; Executive Dean, Academy of Future Education; Acting Dean, Entrepreneurship and Enterprise Hub, XJTLU); Zhang, Ziye
(student); Zhang Yiwen
(student); Zhang Yujin
(student); Zhao, Yiran
(Academy of Future Education, XJTLU); Zhao, Yuxuan
(School of AI and Advanced Computing, Entrepreneur College (Taicang), XJTLU); Zhou, Qianqian
(Department of Applied Linguistics, XJTLU); Zhu, Chenyue
(School of Language, XJTLU); Zhu, Zhefei
(Learning Mall, XJTLU);Zou, Bin (Department of Applied Linguistics, XJTLU).
Special Acknowledgement (by alphabet):
Bi, Xin (Chief Officer of Data; Director, Centre for Knowledge and Information; Director, Learning Mall; Director, University Marketing and Communications; University Librarian, XJTLU); Cross, Adam (Associate Vice President of Education, Director of the Graduate School, XJTLU); Ma, Fei (Associate Vice President of Research and Impact, XJTLU); Zhang, Xiaojun (Chief Officer of Education; Leader of Entrepreneur College (Taicang) Leadership Team; Executive Dean, Academy of Future Education; Acting Dean, Entrepreneurship and Enterprise Hub, XJTLU); Xi, Youmin (Executive President of Xi'an Jiaotong-Liverpool University, Pro-Vice-Chancellor of University of Liverpool, Prof. of Management of Xi’an Jiaotong University).
Contact
If you are interested in joining us, or have any questions please feel free to contact us by na.li@xjtlu.edu.cn or Guang.Yang2202@student.xjtlu.edu.cn or Lan.Luo2202@student.xjtlu.edu.cn.
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