AI and Teaching Materials

Project Name

AI and Teaching Materials

Project Description

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.

Project Members

Project Leader: Georgiev, Svetoslav  direction-sign.png (School of Intelligent Finance and Business, XJTLU); Tinsley, Joseph direction-sign.png (Educational Development Unit, XJTLU)

Project Members: To be announced at the end of August.

Project Updates and Output

Highlights:

  • February 29, 2024, In line with a special edition on ‘Moving Artificial Intelligence Scholarship’ in the African Journal of Inter/Multidisciplinary Studies (AJIMS), the project leaders submitted an abstract in early February 2024 that was recently accepted by the editorial team. Currently, the project members are working on the manuscript, which needs to be completed by mid-June 2024.
  • May 29, 2024.  One of the Project Leaders – Dr. Svetoslav Georgiev – presented some of the research project’s interim findings at the XJTLU Annual Learning and Teaching Colloquium 2024. 
  • June 14, 2024.  The project leaders submitted a manuscript for the special edition on "Moving Artificial Intelligence Scholarship" in the African Journal of Inter/Multidisciplinary Studies.
  • October 4, 2024. Mr. Joseph Tinsley presented at the International Conference on Higher Education Learning and Teaching 2024 (ICHELT2024). The presentation focused on exploring HE student perceptions of AI-assisted PowerPoint creation.
  • December 13, 2024. A manuscript titled “Exploring Student Acceptance and Perceptions of AI-Assisted PowerPoint Creation” was officially published in the African Journal of Inter/Multidisciplinary Studies. For more information and full access to the article, click on the following link: https://journals.dut.ac.za/index.php/ajims/article/view/1521

Funding Awarded: Budget project No. is EFP10120240052. The budget unit is the Academy of Future Education. Budget Amount: 10,000 RMB.

Workshop: December 10, 2024. "Using GenAI to Enhance Teaching & Learning". Dr. Svetoslav Georgiev (IFB) and Mr. Joseph Tinsley (EDU) presented on using GenAI to enhance teaching materials.

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Journal Articles: Georgiev, S. and Tinsley, J. (2024) “Exploring Student Acceptance and Perceptions of AI-Assisted PowerPoint Creation”, African Journal of Inter/Multidisciplinary Studies, 6(1), pp. 1–13. doi: 10.51415/ajims.v6i1.1521. 

Conference Presentations: Tinsley, J. and Georgiev, S., Acceptance of AI-generated Visual Materials among Undergraduate Students: The Case of the School of Intelligent Finance and Business, XJTLU, International Conference on Higher Education Learning and Teaching (ICHELT), Kuala Lampur, Malaysia, Oct 3-4, 2024.

Project Outcome

Recruitment

RA Job Opening
We are seeking a motivated and detail-oriented individual to join our project as a research assistant (RA) from September 2024. Responsibilities include conducting literature reviews, data collection and analysis, and providing administrative support to the research team. Candidates should have strong organizational skills, proficiency in research methods, and the ability to work independently and as part of a team. Experience with qualitative data analysis, particularly using NVivo, is preferred. This is a great opportunity for someone looking to gain valuable research experience in a dynamic and collaborative research environment. If you are interested in contributing to our research project and are eager to learn and grow in a research setting, please get in touch. This is a paid part-time role. XJTLU’s policy on part-time positions shall be strictly followed. 

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