On-Going Research Projects

Building upon AI technology, an avantgarde Self-diagnostic English Language Assessment System (SELA System), which supports adaptive learning, is needed to specifically cater for Hong Kong sub-degree and degree students in the self-financed institutions, for their disparate English backgrounds and self-learning needs. SELA, an all-rounded self-access online system, evaluates multiple aspects of learners’ English, including pronunciation, grammar, vocabulary, reading and listening. It aims to address the shortcomings of existing online English tests in which questions are not generated in an adaptive mode and oral skills are seldom assessed. Another major advantage of SELA is the provision of objective and comprehensive reports with statistical analysis that informs the stakeholders of students’ specific learning needs. Overall, the launch of the SELA System is expected to significantly contribute to students’ academic success and cultivate self-learning motivation for their future career prospects.

Students in higher education consistently rely on teacher feedback to excel in academic writing. Organizing teacher-student conferences is crucial to improving feedback literacy and enhancing their writing skills effectively. Given the rise of online and blended learning, this pioneering project aims to develop a technology-mediated multimodal platform through a teacher-student collaborative approach to address the limitations of existing one-size-fit-all platforms like Zoom, Blackboard, and Google Meet. The project involves modifying the existing subscribed Microsoft Teams and creating a mobile application with progress-tracking portfolios, supporting various feedback modes. The team will assess L2 student engagement with multimodal feedback, its impact on feedback literacy development, evaluate effectiveness of the platform, and identify usage factors. Anticipated findings will advance feedback literacy, enhance student engagement and learning outcomes, and contribute to curriculum design and teaching methodologies.

Lantau Island was an important military strategic location for China during the Ming and Qing Dynasties. Coastal defense facilities such as Diversion Fort, Tung Chung Walled City and Fort are important carriers for understanding this period of history. Activities under this project include on-site photography and sketching inspections, augmented reality for specific scenes, sound stories at checkpoints, and board games, etc., to increase the public’s understanding of the site selection, design, construction and operation of Lantau coastal defense facilities, and its important role in modern China.

Embedding Hong Kong into the development of the country is one of the key goals of the 20^th National Congress meeting, and Hong Kong’s 2022 Policy Address places a strong emphasis on supporting innovative technologies and entrepreneurship. It is believed that considerable efforts on entrepreneurial development should be put forward at the college level to create long-term success in the Greater Bay Area and contribute to the country. In alignment with this future plan, this 3-year project aims to support and develop innovation, entrepreneurship, and cross-region employability in the two metropolises on the south and north of Hong Kong and the GBA. The key project deliverables are considered based on: (1) Education; (2) Exposure; (3) Experience; and (4) Entrepreneurship. As a result, the project will provide students with meaningful opportunities and activities that incorporate education, exposure, experience, and entrepreneurship by creating platforms to leverage their potential and explore their own entrepreneurial ideas and career paths in the region. Also, the project will help foster students’ entrepreneurial mindsets, skills, and competencies and provide internship experiences and opportunities to develop new ideas.

The project plans to develop an artificial intelligence (AI) prediction model using a deep artificial neural network (ANN) approach. The prediction model is aimed at identifying the group of students who are at-risk of failure, dropping out or withdrawing from their studies in an early stage. Then necessary support can be provided to assist them in successfully completing their studies. Our objective is to evaluate the effectiveness of early support to at-risk students, in terms of minimizing the failure rate, drop-out rate and withdrawal rate. Unlike most research works that focus on the prediction in a specific course, our design would consider a more generic view of at-risk students in tertiary education. By doing so, our prediction model can be applied to a wide range of courses and is suitable for students of different backgrounds.

This 24-month project examines the meaning-making practices of handwritten annotation by collecting and analysing live lecture recordings in a tertiary institution through Multimodal Discourse Analysis informed by Systemic Functional Linguistics. The project also investigates the learners’ perceptions and experience of using learning materials with dynamic on-screen handwritten annotations and the observed instructors’ practices of dynamic on-screen handwritten annotations in live lectures through class observations, surveys and interviews.

The objectives of this project are as follows:

• To enable the teachers to appreciate the benefits of using chatbots to complement classroom and/or online teaching.
• To enable the teachers to develop a chatbot for their courses to complement classroom and/or online teaching.
• To improve the student learning experience by providing instant 24-hour feedback.
• To enable teachers to share the knowledge and experience pertaining to chatbot usage to enhance effective achievement of subject intended learning outcomes.
• To promote chatbot usage to teachers from our institution and other self-financing tertiary education institutions by enhancing understanding of the rationale, benefits, and methods of using chatbots.

The above objectives will be achieved through a series of seminars, workshops, a website and synchronous online learning sessions. Teachers from other self-financing tertiary education institutions will be invited to join these activities so that more teachers can improve their pedagogy and practice to benefit students.

PolyU SPEED aims to support students’ English literacy development through cross-disciplinary cooperation. The proposed AI-Assisted Academic Writing platform aims to provide all-round supervisory support that is unconstrained by time and location for students to improve their disciplinary academic writing performance. One of the most useful features of the proposed platform is the incorporation of AI text analytics technology. The platform will feature diversified functions to support self-directed learning and feedback communication.