Abstract:
Data science has become an emerging subject that can be widely applied across various fields of study, such as business, engineering, medicine, science, and social science. In the 21st century, data can be constantly collected due to technology advancement, and a data-driven approach has become an essential part of decision making. Statistical techniques are always important tools in a data-driven approach for data exploration. However, not many undergraduate and even graduate students are fully equipped with statistical thinking skills to analyze data and to make decisions based on data. It is because all the statistical tools are built upon probability distributions and many students have insufficient fundamental knowledge of probability. As a result, many students wrongly use statistical tools to analyze data. The results could draw a wrong conclusion, leading to a wrong decision. In this regard, innovative digital learning objects will be developed with a powerful statistical tool, R, and an appropriate curriculum will be designed in this project, to facilitate teaching and learning of probability distributions. In addition, the deliveries can be placed on e-learning platforms and students can access the deliveries anytime and anywhere when they are connected to internet, to facilitate blending learning and flipped classrooms.
Code:
T0214
Principal Project Supervisors:
Keywords provided by authors:
Start Date:
01 Aug 2018
End Date:
31 Jul 2019
Status:
Completed
Result:
One shiny app, 8 video clips, and 30 practice problems for exercises were produced. Those developed teaching objects were shared with 76 students in learning discrete probability distributions. From the results of the questionnaire, more than 70% of the respondents were satisfied with the developed teaching objects, and 60% of them will recommend this app to their friends. From the focus group interviews, students appreciated that the app could demonstrate the distributions with images and resolve some limitations in textbooks. In addition, the videos with the app make it easier to understand the theorem and various scenarios with the bar charts let them understand better. They are willing to use the app for flipped classrooms when they are teaching.
Impact:
A series of videos and exercises about the discrete probability distributions were produced to enhance students' learning. Those developed teaching objects will also be uploaded on the MIT departmental learning platform/ Moodle for e-learning/ blended learning in introductory courses of probability and statistics. Our students can access the developed objects through their own devices and learn probability distributions on their paces. This learning approach could meet the need of students with diverse backgrounds. Besides, the syllabus of Mathematics Extended Part (Calculus and Statistics) M1 in HKDSE covers several discrete probability distributions, such as binomial distribution, geometric distribution, and Poisson distribution. The developed app can gain a solid understanding of those probability distributions so that our students can become more professional in teaching probability and statistics. Secondary school teachers could improve their teaching efficacy in teaching these discrete probability distributions. We do think that the success of this project will also benefit the mathematics teachers as well as their students studying in M1 in secondary schools.
Deliverables:
Seminars/Presentations/Sharing Sessions
凌萬豪(2019年6月)：一種促進概率分佈學習的交互式應用程序。「兩岸四地數學教育改革研討會：素養導向的數學教育改革」發表之論文，香港教育大學。(參加人數：10) Ling, M. H. A. (2019, June). An interactive shiny app for enhancing learning probability distributions. Workshop conducted at the Cross-Strait Four Regions Conference on Mathematics Education: Competency-based Mathematics Education Reforms, The Education University of Hong Kong, Hong Kong, China. (https://repository.eduhk.hk/en/publications/an-interactive-shiny-app-for...)
Teaching and Learning Resources/ Materials (including online resources)
Teaching resources (videos, and exercises) on use of Shiny apps on the following topics: (https://repository.eduhk.hk/en/publications/teaching-resources-on-use-of...)
Preliminary knowledge
Bernoulli distributions
Binomial distributions
Negative Binomial distributions
Poisson distributions
Review
Financial Year:
2018-19
Type:
TDG