## Saturday, November 29, 2014

### EJSS collision model by Dave Lommen

EJSS collision model by Dave Lommen, is an artifact of learning by a Physics Hwa Chong Institution  teacher who attended the EJS-OSP Singapore workshop.

 Add caption source: https://dl.dropboxusercontent.com/u/44365627/lookangEJSworkspace/export/ejss_src_ElasticCollision.zip run:https://dl.dropboxusercontent.com/u/44365627/lookangEJSworkspace/export/ejss_model_ElasticCollision/ElasticCollision_Simulation.xhtml author: Dave Lommen author of EJS: Francisco Esquembre (Paco)

http://weelookang.blogspot.sg/2013/09/one-dimension-collision-js-model.html

 One Dimension Collision JS Model author: lookang author EJS: Francisco Esquembre (Paco)

## Theory

The motion of a body of mass m and velocity v is described by a vector quantity known as momentum p where

$p = mv$

When objects collide, whether trains, cars, billiard balls, shopping carts, or your foot and the sidewalk, the results can be complicated. Yet even in the most chaotic of collisions, as long as there are no net external forces acting on the colliding objects, one principle always holds and provides an excellent tool for understanding the collision. That principle is called the conservation of linear momentum which states that

The total momentum of a system remains constant provided that no external resultant force acts on the system.

For two bodies colliding linearly, it is written mathematically as a vector equation

Total initial momentum = total final momentum

$m_{1}u_{1}+m_{2}u_{2} = m_{1}v_{1}+m_{2}v_{2}$

If external forces (such as friction) are ignored, the total momentum of two carts prior to a collision (left side of equation) is the same as the total momentum of the carts after the collision (right side of equation).

## Collisions can be generally classified into these categories:

perfectly inelastic, e= 0
inelastic, e is a value from 0 to 1
perfectly elastic, e=1

## There is also a concept of kinetic energy of a moving body is stated mathematically by the following equation:

$KE_{1} = \frac{1}{2} m_{1}v^{2}_{1}$

## Main Simulation View

The simulation has 2 collision carts on friction-less floor.
Sliders
Explore the sliders allows varying the variables .

mass of cart ONE, mass_1, $m_{1}$  in kg
initial velocity of cart ONE, $u_{1}$ in m/s
mass of cart TWO, mass_2, $m_{2}$  in kg
initial velocity of cart TWO, $u_{2}$  in m/s

### EJSS Vernier Caliper JS Model by Jiun Wei Chia, Fu Kwun Hwang, Loo Kang Wee, Wolfgang Christian.

Vernier Caliper JS Model recreated on JavaScript by Jiun Wei Chia. Original author is Fu Kwun Hwang, Loo Kang Wee, Wolfgang Christian.
another artifact of learning during the EJS-OSP workshop in Singapore.

 http://weelookang.blogspot.sg/2014/11/vernier-caliper-js-model-by-jiun-wei.html source: https://dl.dropboxusercontent.com/u/44365627/lookangEJSworkspace/export/ejss_src_VernierCaliper.zip model: https://dl.dropboxusercontent.com/u/44365627/lookangEJSworkspace/export/ejss_model_VernierCaliperV3/VernierCaliperV3_Simulation.xhtml offline: https://dl.dropboxusercontent.com/u/44365627/lookangEJSworkspace/export/ejss_model_VernierCaliperV3.zip author:  Jiun Wei Chia. Original author is Fu Kwun Hwang, Loo Kang Wee, Wolfgang Christian.

The Vernier Caliper JavaScript Model shows the principle of operation and the physical parts of a Vernier Caliper.

## The Vernier calipers model has

1. an object (Blue) for the internal jaws to measure width of an object with slider to control width of the object and simple drag action to control position of object.
2. an object (Green) for external jaws to measure internal diameter of a cylinder for example with slider to control dimensions of the cylinder.
3. checkbox for answer to show the meaning of reading on the main scale and the vernier scale with zero error calculations if any.
4. drop down menu of the various common vernier scales for sense making and additional testing out by learners their ideas of how vernier works.
5. fine <> control buttons for learners to manipulate the model with single incremental precision
6. slider control for fast changes in the vernier measurement
7. reset button to bring simulaton back to original (default)setting.

## Friday, November 28, 2014

### EJSS Distribution of sample means from a normal population model

ejss_model_RandomProbabilityFunction  by +Boon Leong Ng and Francisco Esquembre (Paco) is an artifact of learning by a Math teacher who attended the EJS-OSP Singapore workshop.

 http://weelookang.blogspot.sg/2014/11/distribution-of-sample-means-from.html https://dl.dropboxusercontent.com/u/44365627/lookangEJSworkspace/export/ejss_model_RandomProbabilityFunction/RandomProbabilityFunction_Simulation.xhtml source: https://dl.dropboxusercontent.com/u/44365627/lookangEJSworkspace/export/ejss_src_RandomProbabilityFunction.zip author: boonleong and paco

## Introduction

The sampling distribution of a statistic is the distribution of that statistic, considered as a random variable, when derived from a random sample of size n. It may be considered as the distribution of the statistic for all possible samples from the same population of a given size. The sampling distribution depends on the underlying distribution of the population, the statistic being considered, the sampling procedure employed, and the sample size used. There is often considerable interest in whether the sampling distribution can be approximated by an asymptotic distribution, which corresponds to the limiting case as n → ∞.

population: $N ( \mu , \sigma^{2} )$

For example, consider a normal population with mean μ and variance σ². Assume we repeatedly take samples of a given size from this population and calculate the arithmetic mean  x̄ for each sample — this statistic is called the sample mean. Each sample has its own average value, and the distribution of these averages is called the "sampling distribution of the sample mean". This distribution is normal

sample: $N ( \mu , \frac{\sigma^{2} }{n} )$

(n is the sample size) since the underlying population is normal, although sampling distributions may also often be close to normal even when the population distribution is not (see central limit theorem). An alternative to the sample mean is the sample median. When calculated from the same population, it has a different sampling distribution to that of the mean and is generally not normal (but it may be close for large sample sizes).

## Guidelines

At the tea session last week, the academy proposed that the various subject chapters celebrate the achievement and friendship forged in the core team over the years by creating a montage that captures some of our thoughts (about 40 – 50 words) with the following questions:

## How has your participation in this subject chapter impacted/ benefited you?

### Product -

benefited by harnessing the collective wisdom of the teachers in Singapore to create interactive resources for the benefit of all.

### Process -

Chapters are MOE endorsed disciplined (role- HOD etc, interest-Games etc) based Professional Learning Platform and has allowed more networking opportunities to share at various platforms like ExCeL Fest, Cluster Sharing, Beginning Teachers Workshop, Brown Bag etc.

### People -

Key to sustainable growth, being part of a shared identity group such as Physics Chapter

### 2 groups of contributors that i would like to thank are

#### Singapore Easy Java Simulations

 Officially in EJS as Shared Library http://iwant2study.org/lookangejss/indexEJSdl.php Browse the collection to view thumbnail images.Double-click on a video to open it in EJS 5.0 and later
1. Wee Loo Kang Lawrence, Educational Technology Division, Ministry of Education, Singapore
2. Lee Tat Leong, River Valley High, Educational Technology Division, Ministry of Education, Singapore
3. Lye Sze Yee, Educational Technology Division, National Junior College, Singapore
4. Kwek Eng Yeow, Victoria Junior College, Singapore
5. Yeu Chee Wee Thomas, Meridian Junior College, Singapore

#### Singapore Tracker Community such as:

 Officially in Tracker as Shared Library http://iwant2study.org/lookangejss/indexTRZdl.php
1. Wee Loo Kang Lawrence, Educational Technology Division, Ministry of Education, Singapore
2. Lim Jit Ning, Hwa Chong Institution, Singapore
3. Lee Tat Leong, River Valley High, Educational Technology Division, Ministry of Education, Singapore
4. Samuel Ooi, National Junior College, Singapore
5. Goh Giam Hwee Jimmy, Yishun Junior College, Singapore
6. Leong Tze Kwang, Raffles Girls Secondary, Singapore
7. Thio Cher Kuan, Raffles Girls Secondary, Singapore
8. Siow Seau Yan Sharon, Raffles Girls Secondary, Singapore
9. Ning Hwee Tiang, National Junior College, Singapore
10. Tan Kim Kia, Evergreen Secondary School, Singapore
11. Lim Ai Phing, River Valley High School, Singapore
12. Neiw Chun Hao Wilson, River Valley High School, Singapore

## What has supported your learning in the subject chapter?

the drive to inspire students and teachers to develop a deeper understanding of physics, encourage fellow educators to share their resources and make Physics learning more meaningful.

## Saturday, November 22, 2014

### EJSS Cube Block Cooling Model

EJSS Cube Block Cooling Model

 http://weelookang.blogspot.sg/2014/11/ejss-cube-block-cooling-model.html increasing surface area of copper cube increases rate of heat loss to surrounding model:https://dl.dropboxusercontent.com/u/44365627/lookangEJSworkspace/export/ejss_model_cooling/cooling_Simulation.xhtml zip model: https://dl.dropboxusercontent.com/u/44365627/lookangEJSworkspace/export/ejss_model_cooling.zip source: https://dl.dropboxusercontent.com/u/44365627/lookangEJSworkspace/export/ejss_src_cooling.zip author: lookang, Christian wolfgang
 http://weelookang.blogspot.sg/2014/11/ejss-cube-block-cooling-model.html dull copper lose heat slower than shiny copper model:https://dl.dropboxusercontent.com/u/44365627/lookangEJSworkspace/export/ejss_model_cooling/cooling_Simulation.xhtml zip model: https://dl.dropboxusercontent.com/u/44365627/lookangEJSworkspace/export/ejss_model_cooling.zip source: https://dl.dropboxusercontent.com/u/44365627/lookangEJSworkspace/export/ejss_src_cooling.zip author: lookang, Christian wolfgang

## Newton's Law of Cooling

The Newton's Law of Cooling model computes the temperature of an object of mass M as it is heated or cooled by the surrounding medium.

### Assumption:

The model assumes that the temperature T within the object is uniform.

### Validity:

This lumped system approximation is valid if the rate of thermal energy transfer within the object is faster than the rate of thermal energy transfer at the surface.

### Convection-cooling "Newton's law of cooling" Model:

Newton assumed that the rate of thermal energy transfer at the object's surface is proportional to the surface area and to the temperature difference between the object and the surrounding medium.

$\frac{\delta Q}{\delta t} = h A( T(t) - T_{background} )$

$Q$ is the thermal energy in joules
$h$ is the heat transfer coefficient (assumed independent of T here) ($\frac{W}{m^{2} K}$)
$A$ is the heat transfer surface area ($m^{2}$)
$T$ is the temperature of the object's surface and interior (since these are the same in this approximation)
$T_{background}$ is the temperature of the surrounding background environment; i.e. the temperature suitably far from the surface is the time-dependent thermal gradient between environment and object.

### Definition Specific Heat Capacity:

The specific heat capacity of a material on a per mass basis is

$Q = mc ( T_{final} - T_{initial} )$
$Q$ is heat energy
$m$  is the mass of the body
$c$ specific heat capacity of a material
$T_{final}$ is the $T_{background}$
$T_{initial}$ is the $T(t)$

combing the 2 equations

$\frac{mc ( T_{background}- T(t) ) }{\delta t} = h A( T(t) - T_{background} )$

assuming mc is constant'

$mc \frac{ \delta ( T_{background}- T(t) ) }{\delta t} = h A( T(t) - T_{background} )$

assuming $T_{background}$ is a infinite reservoir

$\frac{ ( T_{background}) }{\delta t} = 0$
therefore
$mc \frac{ ( \delta (- T(t)) ) }{\delta t} = h A( T(t) - T_{background} )$

negative sign can be taken out of the differential equation.

$mc \frac{ (\delta T(t) ) }{\delta t} = -h A( T(t) - T_{background} )$

$\frac{ ( T(t) ) }{\delta t} = -\frac{h A}{mc }( T(t) - T_{background} )$

let $\kappa = \frac{h A}{mc }$

$\frac{ ( T(t) ) }{\delta t} = -\kappa ( T(t) - T_{background} )$

$heating = \frac{\delta Q}{\delta t} = mc ( \frac{\delta T}{\delta t})$

the final ODE equation looks like

$\frac{ ( T(t) ) }{\delta t} = -\kappa ( T(t) - T_{background} ) + \frac{heating}{mc}$

### Definition Equation Used:

$V = \frac{m}{\rho}$

$V$ is volume of object
$\rho$ is density of object

$A = 6 (\frac{m}{\rho})^{\frac{2}{3}}$

$A$ surface area of object

assumption of increased surface are

$A_{increased surface area due to fins} = (2)(6) (\frac{m}{\rho})^{\frac{2}{3}}$

copper shiny $c_{Cu}$ = 385  $\frac{J}{kg K}$
$\rho_{Cu}$ = 8933  $\frac{kg}{m^{3}}$
heat transfer coefficient  $h_{Cu}$ = 400 $\frac{W}{(K m^{2})}$

copper dull $c_{Cu}$ = 385  $\frac{J}{kg K}$
$\rho_{Cu}$ = 8933  $\frac{kg}{m^{3}}$
heat transfer coefficient  $h_{Cu}$ = 200 $\frac{W}{(K m^{2})}$

aluminium shiny $c_{Al}$ = 903  $\frac{J}{kg K}$
$\rho_{Al}$ = 2702  $\frac{kg}{m^{3}}$
heat transfer coefficient  $h_{Al}$ = 400 $\frac{W}{(K m^{2})}$

aluminium dull $c_{Al}$ =  903  $\frac{J}{kg K}$
$\rho_{Al}$ = 2702  $\frac{kg}{m^{3}}$
heat transfer coefficient  $h_{Al}$ = 200 $\frac{W}{(K m^{2})}$

iron shiny $c_{Al}$ = 447  $\frac{J}{kg K}$
$\rho_{Al}$ = 7870  $\frac{kg}{m^{3}}$
heat transfer coefficient  $h_{Al}$ = 400 $\frac{W}{(K m^{2})}$

iron dull $c_{Al}$ =  447  $\frac{J}{kg K}$
$\rho_{Al}$ = 7870  $\frac{kg}{m^{3}}$
heat transfer coefficient  $h_{Al}$ = 200 $\frac{W}{(K m^{2})}$

Users can select the mass of the object and the material and the model computes the surface area assuming a cubic shape. The model plots the object's temperature as a function of time as the user heats and cools the object. A data-tool button on the temperature graph allows users fit the data to analytic functions.

Note: A typical (rough) heat transfer coefficient h for still air and iron is 6 W/(K m^2) and 400 W/(K m^2) . The Newton's Law of Cooling model assumes h=400 for all shiny and h=200 for dull materials. The actual value of h depends on many parameters including the material, the fluid velocity, the fluid viscosity and the condition of the object's surface.

## References:

1. "Measuring the Specific Heat of Metals by Cooling," William Dittrich, The Physics Teacher, (in press).

## Credits:

1. The Newton's Law of Cooling model was created by Wolfgang Christian using the Easy Java Simulations (EJS) version 4.2 authoring and modeling tool.
2. EJSS Cube Block Cooling Model was created by Wolfgang Christian and recreated by lookang using the Easy Java Simulations (EJS) version 5.1 authoring and modeling tool

## Thursday, November 20, 2014

### What is NRF2011-EDU001-EL001 ?

NRF2011-EDU001-EL001 = Java Simulation for Teaching and Learning
there are 2 writeup about it.

## general

http://www.nie.edu.sg/edulab-funding-programme

eduLab is an MOE-NIE initiative designed to surface and spread ground-up IDM-enriched pedagogical innovations. A key programme under the third Masterplan for ICT in Education (mp3), eduLab partners teachers in developing theoretically-informed IDM-enriched pedagogical innovations while ensuring that these innovations can potentially be adopted by different schools across the system.

## specific

http://edulab.moe.edu.sg/edulab-programmes/existing-projects

## Principal Investigator

Ms. Lim Ai Phing, Senior Physics Teacher, River Valley High (2013-current)
Mr. Xu Weiming, Physics Teacher, River Valley High (2012)

## Project Information

This project aims to increase student’s appreciation and efficacy in handling multi-variable phenomena and concepts, with a view of improving students’ understanding of challenging concepts in physics, through customized computer models. Applying the guided inquiry approach to learning, these computer models are used to bridge the gap between theory and reality, providing students with visual and relevant representations of physics concepts.

In 2012, more than 2000 students from 5 schools, with the aid of 39 teachers, benefited from the 6 lesson packages featuring 9 computer models. Both students and teachers gave positive feedback. For instance, teachers shared that they were able to more effectively transmit difficult physics concepts to their students as the computer models could be customized to fit their specific purposes. On the other hand, students enjoyed the increased engagement and interaction that stemmed from such a learning approach.

## Project Artifact

1. 6th IPSG instructional program support group A level physics scaling page (2014)
2. ExCEL Fest scaling page (2013)

## Journal Papers

1. Wee, L. K., & Goh, G. H. (2013). A geostationary Earth orbit satellite model using Easy Java Simulation. Physics Education, 48(1), 72. doi: 10.1088/0031-9120/48/1/72 arXiv:1212.3863 [pdf] [1212.3863iopgeostationary.pdf]
2. Wee, L. K. (2012). One-dimensional collision carts computer model and its design ideas for productive experiential learning. Physics Education, 47(3): 301. arXiv:1204.4964 [pdf] [1204.4964iopejscollision.pdf]

## MOE publication

1. Wee L.K. (2013) Open Source Physics, i in Practice 1(1), p. 58-63, Ministry of Education.[PDF] [iinpracticeOpen Source Physics_PG58-63_lr.pdf]

## Conference Papers and Presentations

1. Wee L.K., Lim A.P., Goh G.S., Lye S.Y., Lee T.L., Xu W.M., Goh G.H., Ong C.W., Ng S.K., Lim E.P., Lim C.L., Yeo W.L., Ong Matthew, Lim Kenneth (2012, 01-06 July, 1300-1430) Computer Models Design for Teaching and Learning using Easy Java Simulation PS 02.09 | Parallel Session 02.09 | Room 09 | 02.07.2012 Monday | 13:00 - 14:30 | 2012 World Conference on Physics Education Bahçeşehir Üniversitesi, Istanbul, Turkey arXiv:1210.3410 [pdf][7-WCPE2012(413-438).pdf]

## Awards

1. Innergy Award 2014 HQ (Interactive Learning Resources) commendation
2. Innergy Award 2012 HQ (Gravity-Physics by Inquiry) Gold Award
3. Best Suggestion 2013 Nov of the Month (Ripple Tank Model) River Valley High School

## Itinerary

Venue: Edulab@AST 2 Malan Road Block J level 4.
Date: 25 Nov 0900-1300 Workshop beginner, 1430-1700 small group consultations
26 Nov 0900-1300 Workshop intermediate.
27Nov 0900-1300 Workshop advance, 1430-1700 small group consultations
28 Nov 0900-1300 Workshop expert and group presentation, 1430-1700 Public Lecture @NIE5-01-LT12
Cost: Free
Intended Participants: Physics Educators, Mathematical Modeling, Chemistry Molecular Modeling

## Pre Workshop Flipped Day 0

### Software EJS:

3. video tutorials: http://weelookang.blogspot.sg/2011/02/easy-java-simulation-tutorial.html
4. Activity: chapter 2 worksheet by wolfgang and paco http://www.opensourcephysics.org/items/detail.cfm?ID=7306

## Software Tracker:

1. download and install and click on Tracker from the Windows Start Menu to Launch https://www.cabrillo.edu/~dbrown/tracker/. We recommend Tracker 4.87 installer FULL installation, do not select upgrade option, Windows  Mac OS X
2. video tutorials playlist watch 12 analysis and 13 modeling: https://www.youtube.com/watch?v=cuYJsnhWXOw&list=PLYIwRBA8ZhdM3jqtpxj3SSxE4z5dWzrnx&index=12
3. worksheet for students http://www.opensourcephysics.org/items/detail.cfm?ID=11705

## 25 Nov (Tue) Day 1

– provide 30 pax beginners’ workshop (model simple physical systems such as spring mass with damping using EjSS) in eduLab@AST
09h00 - 09h30: Introduction to the workshop
09h30 - 11h00 Exploration of the OSP-EJS-ComPADRE Platform
• How do OSP, EjsS, and ComPADRE work together?
• Search, find, and run existing programs
• ComPADRE filing cabinets and community tools
• EjsS workspace fundamentals
• Tracker Video Analysis Tool
• How to package and distribute simulations

10h30 - 10h45: Break and Networking
11h15 - 13h00: Exploration of EjsS
• Load, inspect, and run a JavaScript simulation from within EjsS
• Step-by-step EJS tutorial
• Modify a simulation (assistance will be given to help with the modifications)
• Explore ComPADRE and create a personal filing cabinet
Lunch: 12:30-14:00
followed by consultation (evaluate and recommend improvements to teachers worksheets , research design and instruments)
Day 1 Afternoon
14h30 - 17h30: Independent work and consultations on curriculum design referencing some of the teachers of eduLab NRF2011-EDU001-EL001 Java Simulations for Teaching and Learning (http://weelookang.blogspot.sg/2013/10/6th-ipsg-level-physics.html)
15h30 - 16h00: Break and Networking

## 26 Nov (Wed) Day 2

– provide 30 pax intermediate workshop (model simple physical systems such as free fall with collision detection using EjSS) in eduLab@AST
09h00 - 11h00: Creating models with EJS I (good if we can situate this on some sample models available on something the teachers agree to work on? Less theory, more on stuff they want to remix?)
• Structure of a model in EJS
• Variables and their types.
• Initialization, fixed relations, and custom functions
• Introduction to the ODE editor and the Prelim code page
• Binding model variables to view elements and controls
10h30 - 11h00 break and Networking

11h30 - 13h00 Enhancing the View
• Elements and Properties
• 2D Field Elements
• 3D Elements
• Tables and arrays
Lunch: 12:30-14:00
Day 2 Afternoon
14h30 - 16h30: Up Close Discussions on topics such as Blended-Face to Face&Online Learning, Massive Online Open courses, Open educational Resources, teacher Learning communities, Learning analytics, Technology scans etc.
1. Brown Professor Wolfgang Christian, Founder of Open Source Physics (OSP) Projecthttp://www.compadre.org/osp/ and Elected Secretary for the National American Association of Physics Teachers (AAPT).
2. Professor Francisco Esquembre (Paco), Founder of Easy Java Simulation and President of Multimedia in Physics Teaching and Learning (MPTL) research group. http://www.um.es/fem/EjsWiki/pmwiki.php
3. Sng Chern Wei, Director of Curriculum Planning and Development Division (CPDD)
4. Sin Kim Ho, Deputy Director, CPDD, Sciences Branch
5. Kwan Yew Meng, Assistant Director, Educational Technology Division (ETD), Edulab
6. Goh Sao Ee, Academy of Singapore Teacher, (AST)
7. Kwek Leong Chuan, PI Centre for Quantum Technologies, NUS
8. Lye Sze Yee (ETD)
9. Lee Tat Leong  (ETD)
10. Darren Tan (CPDD)
11. Lawrence Wee Loo Kang  (ETD)
15h30 - 16h00: Break and Networking

## 27 Nov (Thurs) Day 3:

– provide 30 pax (from the eariler workshops) advance (model advance physical systems such as gravitational binary planets), workshop in eduLab@AST followed by consultation (evaluate and recommend improvements to teachers worksheets, research design and instruments) to project teachers or dialogue MOEHQ with CPDD-ETD-AST senior-lead-master teacher network

09h00 - 11h00 Lecture: Creating models with EJS II (good if we can situate this on some sample models available on something the teachers agree to work on? Less theory approach and, more on stuff they want to remix?)
• Arrays and Element Sets
• N-dimensional ODEs
• The ODE editor revisited (advanced parameters, error control, events, DDEs)
• Model Elements
• External Libraries
10h30 - 11h00 break and Networking

Lunch: 12:30-14:00
Day 3 Afternoon
14h30 - 17h30: Independent work, consultations, and breakout sessions based on interest as well as referencing some of the teachers of eduLab NRF2011-EDU001-EL001 Java Simulations for Teaching and Learning (http://weelookang.blogspot.sg/2013/10/6th-ipsg-level-physics.html)

15h30 - 16h00: Break and Networking

## 28 Nov (Fri) Day 4:

– provide 30 pax (from advance and beginners) expert (model family array of physical systems such as multiple masses using array in resonance systems) workshop eduLab@AST, PM Open Public Lecture @NIE in LT12 seating capacity of 300

09h00 - 11h00 Lecture: Curriculum Development and Distribution
• Multi-model files and ePubs
• Translating a simulation
• A personal EJS Digital Library using PHP
• Contributing to the OSP Collection
10h30 - 11h00 Break and Networking

11h00 - 12h30 Presentations by teachers and group discussion
Lunch: 12:30-14:00
Day 4 Afternoon

14h30 - 17h30: Public Lecture @NIE LT12

15h30 - 15h45: Break and Networking

I would like to publicise and arrange for dialogue-talk(2 hours) or Easy Java Simulation-Open Source Physics workshop (4 hours) with 2 professors that are our collaborators, invited to Singapore during our visit to MPTL18 conference Madrid Spain, co-funded by edulab project NRF2011-EDU001-EL001 Java simulations for teaching and learning and AST professional development fund.

Date: 25 to 28 November 2014
Venue: Edulab@AST 2 Malan Road Block J level 4.
Time: 0900-1300 or 1300-1700
1. Brown Professor Wolfgang Christian, Founder of Open Source Physics (OSP) Project http://www.compadre.org/osp/ and Elected Secretary for the National American Association of Physics Teachers (AAPT).
2. Professor Francisco Esquembre (Paco), Founder of Easy Java Simulation and President of Multimedia in Physics Teaching and Learning (MPTL) research group. http://www.um.es/fem/EjsWiki/pmwiki.php

Their CV are below:

## Wolfgang Christian

Brown Professor of Physics
Davidson College, Box 6926
Davidson, NC 28035

## Education

• Ph.D.: 1976, North Carolina State University at Raleigh, Dissertation: The Determination of Particle Size Distributions By Small Angle Forward Scattering. Mentor: Dr. Edward Manring
• B.S. with Honors: 1970, North Carolina State University at Raleigh (Major: Physics; Minor: Mathematics)

## Davidson College Appointment History

• Physics Dept. Chair 2010 to Present
• Brown Professor of Physics 2002 to Present
• Professor 1993 to 2002
• Davidson Physics Computation Center Director 1991 to Present
• Associate Professor 1986 to 1993
• Assistant Professor 1983 to 1986

## Service/Honors/Awards

• Elected Secretary for the national American Association of Physics Teachers, 2012. Term of service 2013-15.
• Elected NC Section American Association of Physics Teachers, Vice-President, President-Elect, President, and Past-President 2009-2015.
• American Association for the Advancement of Science SPORE Award, 2011.
• Pegram Award for Excellence in the Teaching of Physics in the Southeast by the Southeastern Section of the American Physical Society, 2009.
• Computation and Computer-Based Instruction Gordon Research Conference vice-chair and chair, 2004-08
• UCES Undergraduate Computational Engineering and Science Award, 2007.
• Fellow, American Physical Society, 2006. Citation: “For his years of dedication and significant contributions to the use of computers in undergraduate physics education, especially for his creation, design and effective use of interactive curricular materials.”
• APS Forum on Education Vice-Chair, Chair-Elect. Chair, and Past-Chair. 2001-2004

### Tracker 4.87 released fixes Macosx yosemite

I have tested on my own Yosemite machine but I still need more testing. Could I ask the OSX users among you to download and run the installer from www.cabrillo.edu/~dbrown/tracker/installers/Tracker-4.87-osx-installer.zip and let me or the whole group know how the new version works for you?

Message by Doug brown, creator of tracker an awesome tool for physics modeling pedagogy.

## Thursday, November 6, 2014

i recommend upgrading to Java 8 to resolve the problem of compiling EJSS models that are complex resulting in errors compiling using Java 7
 Windows x86 Offline 28.35 MB jre-8u25-windows-i586.exe

after installing to Java 8 seems to have solve the problem i have in the Windows XP

enjoy!

## Wednesday, November 5, 2014

### Tracker Solar Spectrum by Lee Tat Leong

Tracker Solar Spectrum by Lee Tat Leong
 http://weelookang.blogspot.sg/2014/11/tracker-solar-spectrum-by-lee-tat-leong.html Tracker Solar Spectrum by Lee Tat Leong https://dl.dropboxusercontent.com/u/44365627/lookangEJSworkspace/lookangejss/04waves_13light/trz/solarspectrum01.trz https://dl.dropboxusercontent.com/u/44365627/lookangEJSworkspace/lookangejss/04waves_13light/trz/solarspectrum21Na.trz https://dl.dropboxusercontent.com/u/44365627/lookangEJSworkspace/lookangejss/04waves_13light/trz/solarspectrum22he.trz https://dl.dropboxusercontent.com/u/44365627/lookangEJSworkspace/lookangejss/04waves_13light/trz/solarspectrum23H.trz

https://www.dropbox.com/s/3jesfv10e5xrne0/recanprovidedoctrzpptresourcestoyourstudentsscie.zip?dl=0

Attached are the zipped files for using tracker for spectral lines that we conduct for the entire Y6 (JC2) cohort.

- Spectra Analysis.zip - Include the worksheet, picture files only
- Analysing Solar Spectrum.zip - Include worksheet, suggested answers, picture files, tracker files on teacher's analysis of pictures (I have upgraded my mac to OS X Yosemite which broke my tracker so I can't check which pictures the tracker files is reference to, so zipped all the possible files).

Instructional video on how to use tracker for spectral analysis is here.

Thank you.

Lee Tat Leong

## 1. Pedagogical Design & Practice

### Is there going to be further revision on the DP?

- If ‘yes’, why, and how do you intend to go about it? How many iterations of lesson enactment will there be?
living document, 2015 iterations with all 4 schools.

- if ‘no’, what is the focus in year 2? (e.g., practise the DP in regular lessons) Will there be further lesson observation by LDs?

### How many schools, teachers and classes are involved? Is there any increase from 2014?

schools RGS, RVHS, NJC ES
teachers 1,       2,          1,    1
no increase, likely decrease

### - If ‘yes’, what is the plan to initiate, develop and mentor teachers who are new to the project?

school based customised workshops for teachers in each school.
plus edulab@ast sharing.

## 2. Research/ Study

### What is the plan for research on learning gains, or impact study?

support each schools different needs, mentoring teachers while using/revising design principles to better assist others schools to adopt adapt the practices.

same.

## 3. Communication /Reporting

modeling

modeling

### Is there plan to present the project (design. Findings etc) at any other platforms (e.g., international conference, zonal seminar..)

yes.
1. GIREP/MPTL19 Palermo Italy
2. AAPTWM2015 San Diego, California, USA
3. 7thIPSG2015 NYJC

## 4. Scaling

### Is the project ready for scaling in year 2?

#### - If ‘yes’, how would you go about it? How many schools are you aiming for?

yes, based on request by school teachers.

## 5. Lesson Packages

### Please work with the PI and co-PIs to submit at least one lesson package per project to the ICT Connection, and put yourself as one of the co-submitters.

1
 Learning Physics of Free Fall through Video Analysis& Modeling (Tracker) In this lesson you will learn the fundamentals of free fall motion by video analysis (study various kinematics qualities such...  Subjects : Physics School : Evergreen Sec Sch
Tan Kim Kia
(0)
55 / 261-Apr-2014 (Tue)26-Mar-2014 (Wed)1-Apr-2014 (Tue)
2
 Learning Physics of Kinematics through Video Analysis & Modeling (Tracker) In this lesson you will learn the fundamentals of energy changes when a ball bounces by video analysis (study various...  Subjects : Physics School : National Junior College
Goh YingLun Allan
(0)
3 / 029-Jul-2014 (Tue)26-Mar-2014 (Wed)29-Jul-2014 (Tue)

2 more coming

## 6. Year-end Reports

Besides the Project Progress Report/Final Report to be completed by PIs and submitted to eduLab PMO, LDs are to report on their respective projects based on a template to be provided.

## 7. Networking session

### · Objective: To scale the practices to more schools

· Date, time, venue (tentative): AST, 11 Mar 2015 PM
· Target audience: Representatives from potential adopting schools, Friends of eduLab, HOD ICT, etc
· Format (tentative): Each project will be provided with a pull-up banner (content to be provided by project team), and a space furnished with a few tables and chairs for sharing and discussion.
· Presenters: PIs and co-PIs of all eduLab projects (including completed ones)
More details will be communicated in due course.

## 8. Presentation at Evaluation Committee meeting

For projects that have not been reported at EC meeting before, the presentation will take place in mid-May 2015. Please guide the PIs in preparing for the 10-minute presentation. Get them to

focus on showcasing learning gains from the practices, using artefacts as far as possible.