Maiga Chang

2023-2025 Distinguished Visitor
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Dr. Maiga Chang is a Full Professor in the School of Computing and Information Systems at Athabasca University, Canada. He has recently received Distinguished Researcher Award from Asia Pacific Society on Computers in Education (APSCE) this year. Dr. Chang has given more than 135 talks and lectures in different events. He also has (co-)authored more than 240 book chapters, journal and international conference papers. He is an IEEE member since 1996.  Dr. Chang is currently the chair of the IEEE (Institute of Electrical and Electronics Engineers) Technical Community of Learning Technology (TCLT) as well as the editor-in-chief of Educational Technology and Society, which is indexed by Web of Science’s Social Science Citation Index (SSCI). In addition, He is also the editor-in-chief of the International Journal of Distance Education Technologies (IJDET) and the Bulletin of Technical Committee on Learning Technology – both are open access publication indexed by Web of Science Emerging Sources Citation Index (ESCI).  Dr. Chang is now Vice President (2022~) of International Association of Smart Learning Environments (IASLE); Executive Committee member of Asia-Pacific Society for Computers in Education (APSCE, 2017~2024), IEEE Computer Society Technical & Conference Activities Board (2022), Global Chinese Society for Computing in Education (GCSCE, 2016~2025), IEEE Computer Society Special Technical Communities (2021~); and Chair (2021~) of Educational Activities Committee, IEEE Northern Canada Section. Dr. Chang is also a Steering Committee member (2020~) for International Conference on Intelligent Tutoring Systems (ITS).  In the last two decades, Dr. Chang’s research directions are Data Analytics Service and Game-based Learning. His Data Analytics research focus on the design of algorithms and methodologies for item generation (for quizzes and exams), learning activity generation, behaviour pattern extraction from sequential data and preference prediction and recommendation service. The Personalized Study Guide is research aiming to enable an open-source learning management system (i.e., Moodle) to provide students with a personalized study guide for their online learning by via the use of graph structures to analyze the learning objects in an online course and compare the learning behaviours, strategies, and preferences of individual students studying online. Three open-source Moodle plugins have been developed, reviewed, approved, and included in Moodle plugins directory.  On the Game-based Learning direction, his research continuously designs games for teaching, learning, rewards, and assessment. For instances, different games (including 3D, mobile and role-playing games) have been designed and developed to help students learning various topics, including botany, culture and history, finance, programming, management information systems, and meta-cognitive skills. His Trading Card Game (TCG) and the use of In-game Card as Educational Reward (ICER) research also inspired Trinity Primary School in the United Kingdom to develop “Character Clash!” to encourage children to read more. The Multiplayer Educational Game for All (MEGA World) is a web-based massively multiplayer educational game platform which supports any languages and is capable of access any existing external resources (e.g., multimedia, materials, online meetings, etc.). Teachers can create their virtual worlds as well as create learning and assessment activities (i.e., quests in the game) for students. Students can learn specific knowledge and reach the learning goal by taking and solving those quests while playing.

DVP term expires December 2025


Summary Generation for Users’ Coronavirus Questions

 In this COVID-19 pandemic, many people have doubts and questions regarding coronavirus. What they can do is googling the answers or waiting until someone asks in the News or asks for the top doctors. Allen Institute for AI works with Chan Zuckerberg Initiative, Georgetown University’s Center for Security and Emerging Technology, Microsoft Research, IBM, and the National Library of Medicine – National Institutes of Health to create COVID-19 Open Research Dataset (CORD-19, via the contributions of publishers. CORD-19 is an open data set that currently (as of June 2, 2022) contains more than 717,000 scholarly articles in full text (with the size of 58.92 GB), about COVID-19, SARS-CoV-2, and related coronaviruses. The dataset’s growth rate is about having new 1,032 full-text articles daily.   In this talk, I will introduce the method that allows computers read and process the COVID-19 Open Research Dataset (i.e., CORD-19 dataset) to obtain information that is required for making summary for users’ questions. My research group has designed and developed a service that is capable of identifying the keys from a question entered by a user and then summarize the content associated to the question and provide the summary to the user as the answer of the question. At the end, I will reveal the evaluation results of a comparison between our research and AWS’ Natural Language Processing service Comprehend on the virtual machines of three different Amazon EC2 Instance Types (i.e., general purpose, compute optimized, and memory optimized).

Chatbot in Education

Online learning and teaching do not mean that putting course materials online and asking students to learn by themselves. It is important to provide students supports when they encounter questions about course content or materials. When students ask their question on a discussion forum in an online learning environment, sometimes there may have no one available at that time to help them due to time differences or study behaviors and needs – for instances some students may have family/children/baby and day job and they might not be able to do their study until late night or weekends. This leads to an obvious conclusion that if a system was in place to provide an automated summary, this could facilitate learning. Having an easily accessible system, which can quickly provide responses, allows students to get information that may have otherwise been difficult to find.  In this talk, I will explain how chatbots can be developed and discuss three potential chatbot in education applications: (1) the Ask4Summary Moodle plugin ( acts like an online tutor can automatically answers a student’s question with a summary assembled via matching and retrieving from the stored information; (2) a block-based, visual editing environment to alleviate the burden of knowledge imposed on users wishing to implement chatbots in their use of training and/or as an automated first-level of support; and (3) guardians living in MEGA World (, who provide individual students a way to get their questions explained and the information asked.

Challenges in Natural Language Processing Applications

My research group uses Natural Language Processing techniques include n-grams and part-of-speech tags to analyze large datasets like CORD-19, DBpedia, and Google Books to build an online summary generation system  ( and Moodle plugin Ask4Summary ( that are capable of reading articles regarding Coronavirus and course content and provide summary for users’ questions. This talk will explain to audience what and how we have done step-by-step to reach the goal; how the fundamental service like the valid n-grams identifier service ( that can help developers and researchers; what are the challenges we have encountered; and what are the plans and potentional ways for investigating and overcoming those challenges.


  • Summary Generation for Users’ Coronavirus Questions
  • Chatbot in Education
  • Challenges in Natural Language Processing Applications