Workshop on VTL Inter-institutional Collaborative Activities (IICA) Projects Part II
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Introduction by Dr Kam-Tim WOO (HKUST)
Dr. LEUNG Chung Man Alvin (CityU)- Developing an Assurance of Learning System for Online Learning Course Assessmen
Dr LAI Po-Yan, Pauli (PolyU) – AI-assisted virtual presentation skills training
Professor KONG Siu-Cheung (EdUHK) – Using Learning Analytics of Course Learners in the Moodle Learning Management System for Informed Decisions of Teachers
Panel Discussion facilitated by Dr Kam-Tim WOO (HKUST)
Speakers (In order by sharing rundown)
Developing an Assurance of Learning System for Online Learning Course Assessment
Category: Governance frameworks, assessment methods, quality assurance systems and professional best practices of VTL
Led by CityU in collaboration with HKU and CUHK
Dr LEUNG Chung-man Alvin (PI)
Associate Head (IS)
Department of Information Systems
City University of Hong Kong
This project aims to develop a new governance framework based on CityU College of Business (CB)’s Assurance of Learning (AoL) model to evaluate students’ learning performance on online platforms administered by UGC-funded universities. CB AoL was recognized as the best practice for sharing at the 2020 AACSB Global Accreditation Conference. Evaluating students from three broad perspectives—3As—namely, Attitude, Ability, and Accomplishment, derived from CityU Discovery-Enriched Curriculum (DEC), the framework can serve as a new governance model to evaluate and enhance online teaching effectiveness, and provide insights to course instructors to identify areas to improve online learning environment of students. With the help of trace analytics, an intelligent system can be developed to evaluate overall learning effectiveness on online platforms. The system can also generate assessment reports to senior management and external accreditation agents for objective evaluation of teaching quality.
AI-assisted virtual presentation skills training
Category: Integration of VTL into scenarios such as practicum and on-site training
Led by PolyU in collaboration with HKBU and CityU
Dr LAI Po-yan, Pauli (PI)
Department of Electronic and Information Engineering
The Hong Kong Polytechnic University
- Dr Julia CHEN, Director of Educational Development, Educational Development Centre, The Hong Kong Polytechnic University,
- Ms Vicky MAN, Senior Lecturer, Language Centre Hong Kong Baptist University,
- Mr Chi-Ho CHAN, Project Associate, Department of Electronic and Information Engineering Department, The Hong Kong Polytechnic University
Oral presentation is a common type of assessment in undergraduate degree programmes. However, the delivery of presentations and their grading pose considerable challenges to students and faculty. With UGC VTL-IICA funding, our project team has begun to develop an AI-assisted presentation platform to offer students frequent opportunities for presentation training and assist teachers’ grading with the aid of AI. In our trialling of the platform, students submitted their pre-recorded video presentations to the platform twice for assessment. After submitting the first attempt, students received AI scores and feedback as a reference for improvement. Students were also advised to improve their presentation skills by referring to the learning units that the project team had designed and uploaded on the platform. Students then submitted an improved version for the second attempt. Teachers reviewed the videos manually and gave final grades. It is found that AI tools can help the rater gauge the English presentation performance of the students in certain aspects, such as vocal variety and vocal fillers. However, some AI tools on other aspects, such as facial expression, require fine-tuning. Further work on enhancing the AI tools to help students improve their English presentations and aid human markers in scoring is planned for the next few months.
Using Learning Analytics of Course Learners in the Moodle Learning Management System for Informed Decisions of Teachers
Led by EdUHK in collaboration with HKBU
Professor KONG Siu-cheung (PI)
Research Chair Professor of E-Learning and Digital Competency;
Director, Centre for Learning, Teaching and Technology
The Education University of Hong Kong
Learning analytics tools in Learning Management Systems are widely used to assist teachers in better understanding and interpreting students’ learning behaviour and progression, thus facilitating data-driven decision-making for pedagogical adjustments, and encouraging student engagement. In this sharing, four learning analytics tools will be introduced. First, Behavior Analytics reveals the students’ overall engagement with materials at the course and clusters students with similar learning patterns into groups, allowing teachers to decide how and when to help students lagging behind. Second, BookRoll captures students’ reading activity, like reading frequency, speed, and notes, enabling teachers to monitor the students’ reading progress and identify common questions students have in reading. Third, Discussion Forum Participation presents the number of activities and contribution of each student, group, and the entire class in the forum over time so that teachers can examine students’ activeness and performances in the forum. Fourth, text-mining provides teachers and students hierarchical visualization of how often important keywords appears in students’ reflective writing. Teachers can thus check what students have acquired before and after the course. With the use of learning analytics tools, not only can the students’ learning process be improved, but also can the self-directed learning among students be promoted.
Dr Kam-Tim WOO
Associate Professor of Engineering Education, Department of Electronic and Computer Engineering
Academic Director of Undergraduate Core Education
The Hong Kong University of Science and Technology
This event is organized by HKTEA.