Sunday, March 27, 2011

tracker Yishun Junior College Singapore 24th March 2011

tracker scaling in Yishun Junior College Singapore 24th March 2011 Professional Development workshop, actual lessons are 28 March to 1 April 2011.
lesson by lookang and jimmy
author: doug brown video, lookang and jimmy model and worksheet 

Dear YJC Physics Students, Do complete the feedback (questionnaire) so that the teachers in YJC can decide whether to have another similar lesson to promote meaningful learning.

the results summary is here

an ordinary physics teacher (lookang) scaling effort on meaningful use of technology by ordinary mortals (zero dollar, just lots of passion by physics teachers in Yishun Junior College, thanks to Jimmy Goh HOD Sc) in a challenging educational system that is forwarding looking because of the people.
A ground-up project by lookang, and you can't find it on any moe website ( well maybe in forums u can) because it is complete personally motivated and initiated.
Also thanks to etd colleagues, seau yoon ,yew meng ,ms chan and dr cheah for giving space for me to harness technology, transforming learners, a vision for mp3, moehq initiative.

time for me to go back to school? hmmmmmm

tracker scaling in yishun junior College Singapore 24th March 2011

as a follow up action of my sharing at Singapore Science Teacher conference 2010 23-24th Nov,

Tracker is a free video analysis and modeling tool built on the Open Source Physics (OSP) Java framework. It is designed to be used in physics education.
Software:   Java 1.5   jre-6u20-windows-i586.exe (the latest is update 24)
QuickTime 7 ( as Xuggle may not read mov files, it is recommended to install to read mov files)
Any Video Converter (May not be necessary after Tracker 4.0 with Xuggle video reader )
License and Copyright:
Tracker is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License.

Analysis with Tracker, refresh with youtube video!

Modeling with Tracker! i doubt the workshop of 1.5 hours can do this modeling part, refer to video for tips!
from EOM
x = ux.t
from data analysis
x = 1.772t

from EOM
y = uy.t + 0.5.a.t^2
from data analysis
y = 2.436.t -5.202.t^2
y = 2.436.t - 0.5*10.404.t^2 

there appears to be an error of |(9.81-10.404)/9.81| = 0.06
i guess it is due to the ruler, perhaps i didn't choose 1 meter correctly. Reply if you know why.thx!

screenshot of the actual Tracker 4.0 using the Doug's video on projective motion
Jimmy giving tips on how to operate the Tracker 4.0 to other year 1 physics teachers video on projective motion
Simon Koh (left) and Patrick (right) the most helpful and capable Lab supervisor for physics lab in YJC also listening to the use of the tracker on the lesson next week for whole of JC1 on projective motion
surprise cake from jimmy and physics teachers in yjc
surprise cake from jimmy and physics teachers in yjc video taken by jimmy
surprise cake from jimmy and physics teachers in yjc photo taken by jimmy

So far, after 28 March Monday lesson i observe some area for improvement

1. some students are disengaged, 4 students:1 laptop is causing the 3rd or 4th to be disengaged, solution is to have 2 student:1 laptop ratio
2. worksheet has an error of dt = 0.05s, (the default is correct 0.033 s, don't not tell students to change it) corrected the error after students surface inconsistent value for g
3. modeling activity on the special video is problematic, student got vx =1.2  vy = 2.43  g = -9.81 but the model is faster ahead of the real video ball, the video need to change the frame rate to 30 frame/s to be accurate. anyway i suggest to do modeling on the existing video to build up the understanding of the analysis activities.
4. students cannot follow the logic of inferring EOM s = u.t + 0.5*g*t^2 to the parabola fit coefficient of y = a*t^2 + b*t +c, i suggest the future worksheet to have the hint of the EOM.
5. teacher for getting the students to be do task more quickly, should gather the students for a short 5-10 minutes briefing on the affordance of the tool, after which the students should be in self directed/ in control of the learning.

Students in action with tracker lesson designed by Jimmy Goh.

 Good shot of the students in group of 3 to 4 using the projectile motion video to analyze the motion guided by the worksheet by Jimmy Goh
 Good shot of the students in group of 3 to 4 using another to be model projectile motion video to model the motion guided by teacher and me. The answer seems to be vx = 1.2, vy = 2.5, fy = -9.81 but the video chosen seems to have some problem with the increment dt.
to get the correct model, change frame rate to 30 frame/s instead of the default 20 f/s
 suggested to use the first video instead of building up of learning analysis to modeling.
the video can be found here;topic=1177.0;attach=4099 

my attempt at modeling this video, notice framework = 30f/s, vx = 1.22 m/s, vy = 2.39 m/s, ay = -9.81 m/s^2

Good shot of the students in group of 3 to 4 using the projectile motion video to analyze the motion guided by the worksheet by Jimmy Goh

Friday 01 April 2011 Com Lab 4
 Good shot of the teacher Hao Kai facilitating the projectile motion video, explaining the affordance of the tracker as well as linking to concepts of equation of motion sy = uy*t+1/2*ay*t^2 to the coefficients of parabola fit y = a*t^2 + b*t +c. by comparing a = 1/2*ay , b=uy, c = 0
 comfortable com lab 4 with air-con and fast laptops

 modeling the parabolic motion

teacher Hao Kai explaining step by step the learning intent and interpret the meaning of the inputs changes, ux = constant value and observe the model's path versus the real object

 student following the modeling approach to projectile motion

a possible solution model by students independent exploration

teacher eugene's lesson guiding the modeling approach to tracker in physics lab.

Alternative software for video analysis only
example video on the possible analysis on App Store Apple

Vernier Video Physics

Vernier Video Physics

By Vernier Software & Technology

letter of appreciation YJC 

Saturday, March 26, 2011

Ejs on Facebook

Ejs on Facebook

Ejs on Facebook

Easy Java Simulation (Official)
come join the community and support education through simulation that is easy to make!

Easy Java Simulation

Promote Your Page Too

Wednesday, March 23, 2011

Support Quality Physics Education by Renewing membership to AAPT

Support Quality physics Education by Renewing membership to AAPT.

this is the top reason why i continue to give to American Association of Physics Teachers

Your renewal has been received and processed. Your current AAPT membership includes the following:
BASIC_B-O_I - Dues with TPT and AJP Electron
Please note that your subscription(s) include the print and online versions of the journal(s).

Please retain this information for your records.
Thank you for your continued support of the Association and the physics education community.
Thank you for your support of physics education.
Purchase Information
Date of Purchase: Mar 22 2011 9:09PM
Purchase Number: 22455
Payment method: Credit card (If your total below is 0, there is no charge)
Code Type Description Quantity Unit Price
BASIC_B-O_I DUES Dues with TPT and AJP Electron 1 $92.00
Total: $92.00

Thursday, March 17, 2011

Excellence in Service Award Silver 2009 Gold 2010

I am spring cleaning my desk and knowing the certificates will get lost, i decided to archive them on blog-spot.
Excellent Service Award (EXSA) Silver 2009
Excellent Service Award (EXSA) Gold 2010

What is EXSA
This national award recognises individuals, in both the private and public sectors, who have delivered outstanding service. Launched in 1994, it seeks to develop service models within organisations for staff to emulate, create service champions and professionalise services.

The Industries Behind EXSA
EXSA is managed by SPRING Singapore and seven lead industry associations (the Association of Singapore Attractions, the Civil Aviation Authority of Singapore, the Land Transport Authority, the National Association of Travel Agents Singapore, the Singapore Hotel Association, the Singapore Retailers Association and the Restaurant Association of Singapore). In addition, the Consumers Association of Singapore, Food, Drinks & Allied Workers' Union, Singapore Manual & Mercantile Workers' Union, Service Quality Centre and Singapore Tourism Board serve as advisors and supporters for this award.

MOE & the EXSA
Subsequently in January 2006, the MOE PS 21 Quality Service Functional Committee (QSFC) introduced the EXSA as part of the Service Excellence Awards Landscape within MOE. It complements the existing MOE Service Excellence Award and civil service-wide Public Service Star Service Award, all of which recognise staff who deliver service excellence consistently.

EXSA aims to encourage all MOE staff—whether at MOE HQ or in schools—to acquire a service mindset and strive towards customer service excellence when serving both our internal and external customers. The progression of staff in achieving the various EXSA award levels will assist MOE Divisions and schools to continually strive for improvement in performance and internal practices to match industry standards.

Sunday, March 6, 2011

Wong, D., Sng, P. P., Ng, E. H., & Wee, L. K. (2011). Learning with multiple representations: an example of a revision lesson in mechanics. Physics Education, 46(2), 178.

Wong, D., Sng, P. P., Ng, E. H., & Wee, L. K. (2011). Learning with multiple representations: an example of a revision lesson in mechanics. Physics Education, 46(2), 178.

Learning with multiple representations: an example of a revision lesson in mechanics

Darren Wong1, Sng Peng Poo2, Ng Eng Hock2 and Wee Loo Kang3
Natural Sciences and Science Education, National Institute of Education, Singapore Anderson Junior College, Singapore Educational Technology Division, Ministry of Education, Singapore 
Darren Wong et al 2011 Phys. Educ. 46 178

We describe an example of learning with multiple representations in an A-level revision lesson on mechanics. The context of the problem involved the motion of a ball thrown vertically upwards in air and studying how the associated physical quantities changed during its flight. Different groups of students were assigned to look at the ball's motion using various representations: motion diagrams, vector diagrams, free-body diagrams, verbal description, equations and graphs, drawn against time as well as against displacement. Overall, feedback from students about the lesson was positive. We further discuss the benefits of using computer simulation to support and extend student learning.
Issue 2 (March 2011)
Received 10 December 2010 , in final form 20 December 2010   the draft PDF is also available legally here at
Bouncing Ball with Drag Model with the multi representations such as scientific graphs versus time and displacement sy, world view and energy bars.

Bouncing Ball with Drag Model

A bouncing ball model here is simulated by both continuous dynamics, and  discrete transitions where the system dynamics can change and the state values can jump. The continuous dynamics of a bouncing ball is simulated using the evolution page given (simplified version) by dy/dt = vy dvy/dt = ay = g - (k/mass)*vy - (k2/mass)*vy*vy; // to simulate gravity constant g, drag forces models are Fdrag = k*vy and Fdrag2=k2*vy*vy the discrete transition is simulated by the event handler in Ejs by selecting Type = zero crossing Zero Condirtion codes are if (vy<0) return yground-(y); // bounced at the yground return 0; // time continues Action code is vy=-e*vy; //

Possible Exercise for Multiple Representation Revision Lesson:

Instructions: A ball is thrown vertically upwards with vy = 30 m/s and assuming ay = -10 m/s^2 at time t = 0s.  It is caught at the height of release on the way down at time t = 6s.  Do the following exercises, paying attention particular attention to the following moments: 1.     just after release from the hand (t = 0s); 2.     on its way up (t = 1s  &  t = 2s); 3.     at the highest point (t = 3s); 4.     on its way down (t = 4s  &  t = 5s); 5.     just before landing on hand (t = 6s). A         Vector Diagrams Draw vector diagrams to show the position of the ball at equal time intervals with its corresponding velocity vector (blue) and acceleration vector (black). Think about how you would describe the velocity and acceleration of the ball on its way up, at the top and on its way down. Use the simulation to assess your initial vector diagram by selecting the upmenubar of checkboxes, for velocity  vy, acceleration ay and so on.
Figure showing how the simulation display the instantaneous vy and ay at a particular time say = 1.25 s
B         Force Diagrams Draw free body diagrams showing momentum and all forces (use different colour for different forces, use red for net force) acting on the ball for the upward and downward motion. Think about how you would describe the change in momentum of the ball on its way up, at the top and on its way down.
Figure showing how the simulation display the force of gravity FG at a particular time say = 0.95 s
C         Graphs Draw graphs of displacement, velocity, acceleration with time/displacement to show the motion of the ball.
Figure showing how the simulation can draw the graphs of displacement vs t, velocity vs t and acceleration vs t from t = 0 to 6+ s
D         Energy graphs Draw the KE (red) and PE (blue) graphs wrt time and displacement for the motion of the ball. Think about how you would describe the transformation of energy of the ball in its flight.
Figure showing how the simulation can draw the graphs of energies vs t, and energies vs sy  from t = 0 to 6+ s
E         Equations Write down the equations of motion that describe the motion of the ball.
Figure showing how the simulation data tool allow students to analyze the data through a parabola curve fit arriving at the value of parameter a b and c to allow students to deduce the equation of motion as sy = a*t^2 + b*t + c
What is the average velocity of the ball?
Figure showing how the simulation data tool allow students to do a statistics mean of vy = -1.657E-1 = 0
What is the average acceleration of the ball?
Figure showing how the simulation data tool allow students to do a statistics mean of ay = -9.81
With air resistance, does it take longer to go up or come down?
Figure showing how the simulation different runs light blue( k=0) and blue( k = 0.3) can visually display the graphs of s vs t to reduce it takes longer to come down but also a comparison with the no air resistance case is possible too.
Advanced Learner: Please submit your remix model that model features that are not available in the existing virtual lab and share your model with the world through NTNUJAVA Virtual Physics Laboratory Impacting the world with your model now.


The Bouncing Ball with Drag Model was created by Loo Kang WEE with contributions of open source codes from Francisco Esquembre & Fu-Kwun Hwang,  using the Easy Java Simulations (EJS) version 4.2 authoring and modeling tool.  An applet version of this model is available on the NTNU website < >. You can examine and modify this compiled EJS model if you run the model (double click on the model's jar file), right-click within a plot, and select "Open EJS Model" from the pop-up menu.  You must, of course, have EJS installed on your computer.  Information about EJS is available at: <> and in the OSP comPADRE collection <>.

Wednesday, March 2, 2011

Language use in Findings a personal analysis on an excellent research paper by Phet

Discipline / Subject Area 
Legitmizing Computer Simulations to support Context for Doing / Physics Education
Authors: N.D. Finkelstein, W. K. Adams, C. J. Keller, P. B. Kohl, K. K Perkins, N. S. Podolefsky, S. Reid, R. LeMaster 
Title of Article: When learning about the real world is better done virtually: a study of substituting computer simulations for laboratory equipment


Language use in Findings

This wiki assembles observations on the kind of language (grammar, words) used to perform typical moves in the Findings section/chapter. Grammar includes: tense switches - when and for what purpose writers switch tense, use of modal expressions (may, probably, appear to) if any, sentence structure (passive construction - when and for what purpose, subordinate clauses and their function), language for expressing author comment if any, etc.

Active voice is generally used in the findings, with instances where it transform to passive voice, serves to switch the grammatical role between subject and direct object. For example in page 4, active "we (subject) find an increase in the statistical significance of the difference (direct object) between average times for CCK and TRAD conditions to a p 0.01 level" switches to "Considered in this manner, the statistical differences in mean times (direct object)between the No Lab condition and either the CCK or TRAD condition are even more significant.(subject is perceived by the W)"

Modal expressions is used "can" and "may" each twice in findings but not for "appears to" and "probably".
For example"This play can lead to the organization of students’ knowledge and its alignment with scientific models." allows qualifiers over its possibility instead of certainty. 

Subordinate clauses such as  foregrounding and backgrounding is a grammar tool for W to construct central information with satellite information. This can be observed through not often. For example in page 4, "The researcher team came to consensus on the grading metric, grading not only for overall correctness, but also for use of particular concepts and mathematics." Here, foreground information is that researcher team agree on the assessment rubrics while the background information is thatthere are some understanding on when to give credits (use particular concepts or mathematics) and discredit (correct answer but incorrect logical).

Language for expressing W's comment can appear in the naming complex ideas through nominalization (summarizes situation and give it a name) can be observed appropriately though not often. In page 5, W gives prominence to the term "messing about" to illustrate scientific play with 2 citations to indicate W's scholarly mastery on the relevance of this idea. This aims to support learning in simulations allows for more productive concept learning than real equipment, if the simulation is well design, in appriopriate context and well used. 

Language for expressing W's comment can appear through how W is shaping R's perception by looking at how the W craft the 3 parts of the findings, by having sentence after sentence that direct R to W's main goal. For example, in page 4, W's sentence about the data of the timings for the 3 different groups (CCK, TRAD and No Lab) and use connectors like "If we consider" to arrive at a particular evidence based hypothesis. And use "However, if we include...." to lead the R into the chain of thought to consider a different "conditional zoom lens" to examine the data to arrive at a more conclusive hypothesis that advances W's claim.

Language for expressing W's comment through coherency and cohesion in language used is observed at paragraph level where evidence findings through all 3 measurement of data methods ( 1 timing, 2 evaluation of student writeup and 3 final examinations), it is always painting the same goal of the paper, in a scholarly and careful manner. There are also instances where complex information (not to paint a overly simplistic nature of the data findings) is reported but it serves to add creditability and realism into the W's research finding.

Language for expressing W's comment through qualifying claim is a discourse tool to limit the area it covers and limit the extent of validity. For example in page 5, W claim "While not an exhaustive case study of these laboratories, drawing from the field notes and observations we find particular themes arise that help delineate the differences and similarities of the two laboratory conditions".  W understands that the B Themes from observation cannot stand most R's research vigor and cross examinations, but W continues to put fore some evidences and findings because it helps to paint a richer understanding of W's smaller claims.

Author voice in Findings a personal analysis on an excellent research paper by Phet

For Topic 6. Writing the results section
Organisation of moves and graphic representation of evidence in Findings
This wiki records observations on how the Findings or Results section of published research papers is organised in different disciplines, what moves are made, how they the moves are typically arranged, and how graphics for communicating findings are presented. Please state the discipline/subject area in which the observations were made 

Discipline / Subject Area 
Legitmizing Computer Simulations to support Context for Doing / Physics Education
Authors: N.D. Finkelstein, W. K. Adams, C. J. Keller, P. B. Kohl, K. K Perkins, N. S. Podolefsky, S. Reid, R. LeMaster 
Title of Article: When learning about the real world is better done virtually: a study of substituting computer simulations for laboratory equipment 

Author voice in Findings

This wiki reports observations on whether and how author voice is present in the Findings report - whether author comments are made, why they are or are not made, and if they are made, whether author comments serve the function of argument. (Author comment refers to what is said that is not a report of the results of data collection and analysis, for example the underlined word in The use of the first person pronoun is interestingly different across the three sets of master’s theses.)

Example of Author's voice in Findings: B Themes from observations
1. Students messing about
Researchers in education and in physics have described the benefits of “messing about.”29,30 This idea of scientific play is the methodical investigation of the constraints and opportunities of a system. This play can lead to the organization of students’ knowledge and its alignment with scientific models. Depending upon how these tools ( in our case, simulation or real equipment ) are used, messing about may or may not be productive. With the simulation, theobservers note that the messing about was more generally restricted to building circuits an activity that is considered generally on task, or supportive of the goals of the laboratory.

(Start the paragraph by citing other research findings on benefits of "messing about". Highlight how in W research, the use of simulation can allows for more productive messing about than real equipment thus, learners are "considered generally" more "on task" and achieving "the goals" of the experiential lab. Not include above but W later continue to use the voices of students and teaching assistants to illustrate very vividly and expertly, examples of what "messing about" is in both simulation and real life case and bring out the benefits of "messing about" as a productive exploring in simulation learning) 

2. Design of the equipment
In both the cases of the simulation and the real equipment, the tools are designed with specific constraints. These constraints can either be productive or not. For the real equipment, both the wire color and observation of a dim bulb in a bright room cause problems for students.
Meanwhile, the simulation is designed to make explicit both bulb brightness and an underpinning model of electron flow.
No instances were reported in which students failed to recognize a bulb as lit in the virtual case, whereas this difficulty frequently arose with the real equipment. There were instances where TAs reported difficulty with the simulation, though these instances were rare.31

(To show that constraints exist in both simulation and real equipment. Use a real equipment example close to many physics teachers' heart; the confusion caused by the color of wires {RED color insulated wire confused as to connect to positive ends of battery and BLACK color insulated wire to negative ends} to voice about the poor design of real equipment. Meanwhile design of simulations make understanding of circuit more explicit with a visible electron model {not available in real equipment} but there are rare reported difficulties nevertheless. This serves to paint an balance and scholarly picture about using simulations, but yet serves W's goal) 

3. Use of instructor time 
How the TAs spent time in class varied. In the case of the simulation, the students had been asked to conduct the prelaboratory online, and were familiar with the simulation upon arrival at the laboratory. Meanwhile, the TA in the laboratory using real equipment was frequently fetching bulbs, or troubleshooting unexpected circumstances e.g., dim bulbs that had been misinterpreted as unlit .

Of course, there are failure modes for the simulations as well. For instance, as described below, one section suffered from repeated computer failure, which demonstrates both the increased demands on the TA and the limitations of equipment when a simulation fails to operate as designed.

(To show that instructor time are possibly more productively spent on supporting learners questions due to a pre-lab exposure in simulations lab while real equipment is generally more chaotic as students have lots of questions {lack prior knowledge}, and equipment such as bulb could need replacement fairly frequently if use incorrectly [short-circuited] )

29 D. Hawkins, The Informed Vision: Essays on Learning and Human Nature Agathon Press, New York, 1974 .
30 D. Hammer, Am. J. Phys. 68, S52 2000 .
31For instance, one instructor reported difficulties with the virtual voltmeter, because unlike its physical counterpart, the virtual meter did not act as a multimeter and could not be set to read resistance. Until the instructor recognized this, he attempted to use the voltmeter to measure resistance.