Workshop on Incorporation of Computational Thinking into Physics Curriculum by Prof Duncan CarlSmith

17 May (Thurs) 1:30 – 5:00 pm
Self Introduction on using computational thinking.
http://iwant2study.org/lookangejss/00workshop/2015HCIstudentLookang/ejss_model_PanRuoxiBall/PanRuoxiBall_Simulation.xhtml by Pan Ruoxi Hwa Chong 2015 student.

http://iwant2study.org/lookangejss/00workshop/2015HCIstudentLookang/ejss_model_blockslidingmodelcheehsinyee/blockslidingmodelcheehsinyee_Simulation.xhtml by Chee SinYee Hwa Chong 2015 student.

Part 1: Why and how to include computation in a physics curriculum

https://www.compadre.org/jtupp/docs/J-Tupp_Report.pdf
Recommended learning goals for undergraduate physics programs Upon completing an undergraduate physics program, ideally a graduate should be able to
A. Physics-Specific Knowledge
A.1. Demonstrate the ability to apply fundamental, crosscutting themes in physics, including conservation laws, symmetry, systems, models and their limitations, the particulate nature of matter, waves, interactions, and fields.
A.2. Demonstrate competency in applying basic laws of physics in classical and quantum mechanics, electricity and magnetism, thermodynamics and statistical mechanics and special relativity, and the applications of these laws in areas such as optics, condensed matter physics, and properties of materials.
A.3. Represent basic physics concepts in multiple ways, including mathematically (including through estimations), conceptually, verbally, pictorially, computationally, by simulation, and experimentally.
A.4. Solve problems that involve multiple areas of physics.
A.5. Solve multidisciplinary problems that link physics with other disciplines.
A.6. Demonstrate knowledge of how basic physics concepts are applied in modern technology and apply this knowledge to the solution of applied problems.

B. Scientific and Technical Skills
B.1. Solve complex, ambiguous problems in real-world contexts.
B.1.a. Define and formulate the question or problem, i.e., ask the right question.
B.1.b. Perform literature studies (print and online) to determine what is known about the problem and its context by locating, reading, analyzing, evaluating, interpreting, and citing technical articles; manage scientific and engineering information so that it is actionable.
B.1.c. Perform trade studies [52] to identify the optimum technical solutions among a set of proposed viable solutions, based on applied experience.
B.1.d. Identify appropriate approaches to the question or problem, such as performing an experiment, performing a simulation,
developing an analytical model, and making rough estimates based on specific strategies.
B.1.e. Develop one or more strategies to solve the problem and iteratively refine the approach.
B.1.f. Design an appropriate experiment or simulation to address the problem, taking into account precision, repeatability, and signal-to-noise ratio.
B.1.g. Engage in appropriate statistical analysis of results.
B.1.h. Identify resource needs for solving the problem and make decisions or recommendations for beginning or continuing a project based on the balance between opportunity cost and progress made.
B.2. Show how results obtained relate to the original problem, determine follow-on investigations, and place the results in a larger perspective.
B.3. Demonstrate instrumentation competency: competency in basic experimental technologies, including vacuum, electronics, optics, sensors, and data acquisition equipment. This includes basic experimental instrumentation abilities, such as knowing equipment limitations; understanding and using manuals and specifications; building, assembling, integrating, operating, troubleshooting, and repairing equipment; establishing interfaces between apparatus and computers; and calibrating laboratory instrumentation and equipment.
B.3.a. Use basic hand tools.
B.3.b. Interface apparatus to computers using tools such as LabVIEW, MatLab interface modules, and GBIP.
B.3.c. Use laboratory tools such as oscilloscopes, sensors, electronics, optics, vacuum systems, materials fabrication tools, signal digitizers, and signal analyzers.
B.3.d Make effective use of advanced analytical or process tools.
B.4. Demonstrate software competency: competency in learning and using industry-standard computational, design, analysis, and simulation software, and documenting the results obtained for a computation or design. Examples include:
B.4.a. General-purpose computational tools: Excel, MatLab, Mathematica, Maple
B.4.b. Optical computational tools: OpticStudio, CODE V, OSLO, TFCalc
B.4.c. Electrical computational tools: SPICE, PSPICE B.4.d. Mechanical computational tools: SOLIDWORKS, Pro/ENGINEER
B.4.e. Physics computational tools: COMSOL Multiphysics
B.4.f. Educational simulation tools: Physlets, Open Source Physics/Easy JavaScript Simulation, PhET Simulations 
B.5. Demonstrate coding competency: competency in writing and executing software programs using a current software language to explore, simulate, or model physical phenomena.
B.6. Demonstrate data analytics competency: competency in analyzing data, including with statistical and uncertainty analysis; distinguishing between models; and presenting those results with appropriate tables and charts.
C. Communication Skills
D. Professional/Workplace Skills

Softwares suggested
https://www.python.org/
http://jupyter.org/
http://www.wolfram.com/mathematica/online/
https://www.maplesoft.com/
https://www.maplesoft.com/products/Mobius/
https://www.mathworks.com/products/matlab.html
https://www.gnu.org/software/octave/

https://www.compadre.org/
https://www.compadre.org/PICUP/exercises/Exercise.cfm?A=fallsph&S=6 lots of cool source codes in different format after login

https://www.audacityteam.org/

Part 2: Low cost mobile phone labs for introductory physics and beyond

18 May (Fri) 9:00 am to 12:00 pm 

Computation in introductory accelerated physics courses using software such as Matlab
http://www.physics.usyd.edu.au/teach_res/mp/mphome.htm
https://www.mathworks.com/products/matlab/plot-gallery.html#standardplots
https://www.youtube.com/watch?v=9k7zywli4Vg

https://www.overleaf.com/

18 May (Fri) 1:30 am to 5:00 pm 

Part 1: Garage Physics

Part 2: Cell Phone Microscopes

21 May (Mon) 9:00 am to 12:00 pm 

Computation in Advanced Courses and labs

Short Biography

Duncan Carlsmith is Professor of Physics at University of Wisconsin - Madison. He received a B.S. degree in Physics and in Mathematics from Yale University and a Ph.D. in Physics from University of Chicago. His research in fundamental physics has included studies of TeV-scale proton-antiproton collisions with the Collider Detector Facility (CDF) at Fermilab and of proton-proton collisions with

the Compact Muon Solenoid (CMS) detector at the CERN Large Hadron Collider (LHC). Presently he is engaged in a direct search for weakly interacting massive particle (WIMP) dark matter with the LUX-Zeplin (LZ) collaboration. Carlsmith is author of a graduate-level text in particle physics. His activities in advancing undergraduate education in physics include video production for introductory,

intermediate, and advanced educational labs, social bookmarking and journal research, cloud-based LaTeX, electronic rubric-based assessment, small-group organization and peer-review, blended learning, audience response systems and active learning strategies, low-cost mobile-phone-based labs, and computation for modeling and big data analysis. Carlsmith also directs Garage Physics, a lab devoted to multidisciplinary project-based learning, innovation, and entrepreneurship.

Please click on the link below for registration.

Registration will ends on 16 MAY 2018

https://wis.ntu.edu.sg/pls/webexe/REGISTER_NTU.REGISTER?EVENT_ID=OA18050710364678

If you have any queries, please email Dr Ho Shen Yong at hosy@ntu.edu.sg