Pendulum Experiment



This is an AI for Curriculum activity where Data Science concepts and skills are integrated into Physics Practicals - The Pendulum Experiment. This mini course is related to the measurement and analysis of the period of a simple pendulum, in relation to its length.  A simple pendulum is an idealised model of a point mass suspended from a weightless thread.  

Course License: CC BY-NC-SA 4.0

Learning Objectives 

  • To investigate the relationship between the period and the length of a simple pendulum

Physics Lab Experiment:

  • Explain that every measurement is associated with an error
  • Identify independent and dependent variables in an experiment

Analyzing Results in Python:

  • Input and represent data 
  • Use a scatter plot to visualise relationships 
  • Fit a Least Square Regression Model

Structure Overview and Typical Completion Time

The total estimated course learning time is 2 hours (for option 2 - no coding) and 4 hours (for option 1 - coding).
There will be no e-certificate/badge upon completion of this micro-course.

Authors Biography

1) Tan Bee Hoon

Senior Customer Success Manager / Presale Consultant, Allego Inc (Sales Enablement software)

Bee Hoon has more than 20 years of data-related experience in Data Analytics, Data Mining, and Campaign Management. She has also previously taken on roles including AI Engineer, Data Analytics Senior Manager, Project Manager, Consultant, Presale Consultant, and Business Analyst, with companies including AI Singapore, PHD Media/ Omnicom Media, Apple Inc (Asia Pacific), Unica Corporation, and SAS Institute Inc.

2) Tan Jing Long

Physics Educator, National Institute of Education Alumni Association

Jing Long is a Physics educator and teaches secondary school physics. His interests lie in AI education, inculcating computational thinking and data literacy in Physics education, the digitisation of Physics Practicals and using AI to model students' conceptual understanding. Prior to joining the teaching service, he was the inaugural chairperson of the AI in Education Chapter, National Institute of Education (NIE) Singapore where he organised professional development workshops for pre-service teachers. Previously, Jing Long read a M.S. in Applied Mathematics and Computational Science at the King Abdullah University for Science and Technology, Saudi Arabia. His undergraduate training in Physics was at the University of Oxford, UK.

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