Monthly Archives: April 2016

LDT Seminar – Master's Project – Week 5 – Update

Have been trying to focus on putting together an initial prototype for LXD.

Since the idea was to have a talking virtual character, I decided that it would be interesting for the instructor to talk back as well.

This sparked the notion that speach is a very effective way of ‘tangibilizing’ your thoughts in a spontaneous and maybe more authentic manner than writting down. Speaking is a way of exposing your internal schema, your knowledge, and your skillset. Hearing someone speak, instead of reading, adds nuances of tone, importance, cadence, and vigor that are challenging to replicate in writting.

With that I started looking at this particular interaction’s core loop:


Which evolved to this:

Core Loops.png

And this prototype – much work needed – first step towards tangibilizing the interface and focusing on the relevant functionality.

Internship – Week 4 – Check-in Assignment


Quick reflection:

What have you learned in terms of new skills and as well as insights through your internship work?  What questions has it raised?  

Do you have any concerns you would like help with or triumphs to share?


The internship at VPTL is going well even though I am doing mostly content revision with the occasional multimedia task of creating explanatory diagrams, adding explanatory elements of photos, and doing minor edits on videos. To be fair, I have started to write some content that will go into the course and have been updating the OpenEdX platform itself giving me some interesting insights. 

It has been very interesting to see the behind-the-scenes work and organization necessary to create an online course. I am satisfied to see that it was not only a personal perception that it is a daunting task – it really is an extremely labor intensive and meticulous job. 

Since the content of the course I am working on is about creating online courses, the content material is of extreme interest. I feel I am killing two birds with one stone. 

Engineering Education – Week 4.2 – Reading Notes

Screen Shot 2016-04-23 at 9.51.27 AM.png

LOFT Process Guides: Understand Phase.

Techniques: Identify Problems, Preparation

  • Identify problems
    • What problems should the learners be able to solve?
    • Subject matter expert develops list of challenging tasks
    • Steps:
      • Identify challenging tasks
        • Learning environment will help learner do something they couldn’t do before
      • Create problem typology
        • List all the problems learner must be able to tackle
        • Group problems into categories of similar knowledge and skills required
      • Describe the problem
        • Create problem statement
        • Describe how it sits in the typology
        • How is the problem solved
        • What skills does it require
        • Supporting materials

Presentation: Learning Module Design Understand Phase (benchmark tests and cognitive analysis)

  • Cognitive task analysis – what  specifically should be learned
  • Workflow
    • Identify experts
    • Identify cognitively challenging tasks
    • Gather data on how expert performs task
    • Analyze data
    • Represent it
  • Steps
    • What are the project deliverables?
      • Identify what the stakeholders need (including the student of course)
    • What is the task?
      • Create a focus statement
    • What aspects of expertise do you need to know about?
      • How to identify expert performance?
    • Documentation analysis (a.k.a. bootstrapping)
      • Come in with a schema
    • Go or no go?
      • If documents describe it all, no need to do full CTA
    • What situations will tell you the most about the issue?
    • Identify experts
    • Identify problems
    • Choose CTA method
      • Concept mapping
        • Expert + facilitator + mapper
        • Node and link diagram to map out concepts and relationships
      • Verbal Protocol Analysis (VPA) / Talk-aloud problem solving (TAPS)
        • Talk while solving a problem
        • Code expert’s behavior: “verbal protocol”
      • Guided Experiential Learning (GEL) CTA
        • Interview one expert then validate with 2 other experts
      • Critical Decision Method (CDM)
        • Facilitator + note taker
        • Interview in 4 sweeps
          • Identify good incident story
          • Chronology of good decisions
          • Goals, expectations and cues in each decision
          • Errors novices might make
      • Percursor, Action, Result, Interpretation (PARI)
        • Avionics training environments
        • Experts are interview in pairs
          • One tries to solve the problem
          • Other expert runs the simulation
      • Applied Cognitive Task Analysis (ACTA)
        • Expert describes problem in 4-6 steps
        • Describe what is difficult in each task
        • Present expert with simulation and ask about:
          • Actions
          • Assessments
          • Critical cues
          • Erros
    • Write your Preparation Report

Bike Stolen #3

Woke up to this:


This should’ve been there…

in some of the pictures the bike has no fenders… PLEASE keep an eye out for it… already filed a report with the police and am searching Craigslist and eBay for it… so sad…

Not the first time… this bike of mine was stolen in NYC:


And this attempted bike stealing episode! I was having lunch and saw the guy sneak into the garage, get my bike, mount it, and try to run away. Too bad I didn’t catch him.

Lytics Seminar – Week 4 – Class Notes


Great talk today about how machine learning – the second of a series. We looked at collecting, cleaning, and coding data to create the training data set in a supervised learning model.


Emily SchneiderPhD candidate in Learning Sciences and Technology Design at Stanford University’s Graduate School of Education.


She is doing research on Lacuna Stories – a very cool document annotation tool that teachers can use to observe reading comprehension and critical interpretation. It was created by the Poetic Media Lab – yet another very interesting group here at Stanford that I didn’t know about… FoMO


Engineering Education – Week 4.1 – Reading Notes


Jesse, S. (2008). The Art of Game Design. A book of Lenses.
Chapter 11 – Game Mechanics Must be in Balance


This article furthers my awe of game development. It must be one of the hardest things to do well. I know from experience that the skills, time, and planning needed to program a game is leaps and bounds more complex than to program a mobile app or a web site. I also know that the graphics, which in most case have to be moving, are of extreme importance in a game. Again, it seems much harder to do art for games than to do art for a magazine, website, or mobile app. Then you have the storyline, the game mechanics, and all the factors mentioned in this article. This article is obviously assuming that you already have developed a game that can be balanced. I keep thinking of all the planning, design, development, and testing that goes on when creating a game. Obtaining balance is already hard in life; now try doing that in a game!


The Twelve Most Common Types of Game Balance

  1. Fairness
    1. Symmetrical Games
      1. All players have equal powers.
      2. Random assignment resolves small potential asymmetries
    2. Asymmetrical Games
      1. Simulate real-world situations: it’s not symmetric
      2. Ways to explore the game-space: customize characters and strategies
      3. Personalization: shape game to suit their skill level
      4. Level playing field: opponent car’s must go slower at first
      5. Interesting situations: provocations, stimulate curiosity
    3. Example: Biplane Battle
      1. Choose from 3 planes with speed, maneuverability, and firepower
      2. Can balance on numbers alone but must play-test them to really feel it
      3. Takes around 6 months to balance your game properly
    4. Example: Rock Paper Scissors
      1. None of the elements are supreme
    5. Lens of Fairness
      1. Should my game be symmetrical? Why?
      2. Should my game be asymmetrical? Why?
      3. Which is more important: that my game is a reliable measure of who has the most skill, or that it provide an interesting challenge to all players?
      4. If I want players of different skill levels to play together, what means will I use to make the game interesting and challenging for everyone?
  2. Challenge vs. Success
    1. Strategies
      1. Increase difficulty with each success
      2. Let player get through the easy parts first
      3. Create “layer of challenge”
      4. Let players choose the difficulty level
      5. Play-test with a variety of players
    2. Don’t make it impossible to win
    3. Lens of Challenge
      1. What are the challenges in my game?
      2. Are they too easy, too hard, or just right?
      3. Can my challenges accommodate a wide variety of skill levels?
      4. How does the level of challenge increase as the player succeeds?
      5. Is there enough variety in the challenges?
      6. What is the maximum level of challenge in my game?
  3. Meaningful Choices
    1. Bad choices
      1. 50 equal vehicles to choose from = no choice at all
      2. A choice no-one wants
    2. Dominant strategy
      1. One option might win over all others – not good – need to adjust balance
      2. If Choices > Desires, then the player is overwhelmed.
      3. If Choices < Desires, the player is frustrated.
      4. If Choices = Desires, the player has a feeling of freedom and fulfillment.
    3. Lens of Choices
      1. What choices am I asking the player to make?
      2. Are they meaningful? How?
      3. Am I giving the player the right number of choices? Would more make them feel more powerful? Would less make the game clearer?
      4. Are there any dominant strategies in my game?
    4. Triangularity
      1. Choices
        1. Play it safe -> small reward
        2. Big risk -> big reward
      2. “Balanced asymmetric risk”
      3. Lens
        1. Do I have triangularity now? If not, how can I get it?
        2. Is my attempt at triangularity balanced? That is, are the rewards commensurate with the risks?
  4. Skill vs. Chance
    1. Lens of Skill vs. Chance
      1. Are my players here to be judged (skill), or to take risks (chance)?
      2. Skill tends to be more serious than chance: Is my game serious or casual?
      3. Are parts of my game tedious? If so, will adding elements of chance enliven them?
      4. Do parts of my game feel too random? If so, will replacing elements of chance with elements of skill or strategy make the players feel more in control?
  5. Head vs. Hands
    1. Hard to balance and some games have both
    2. Lens
      1. Are my players looking for mindless action, or an intellectual challenge?
      2. Would adding more places that involve puzzle-solving in my game make it more interesting?
      3. Are there places where the player can relax their brain, and just play the game without thinking?
      4. Can I give the player a choice — either succeed by exercising a high level of dexterity, or by finding a clever strategy that works with a minimum of physical skill?
      5. If “1” means all physical, and “10” means all mental, what number would my game get?
      6. This lens works particularly well when used in conjunction with Lens #16: Lens of the Player.
  6. Competition vs. Cooperation
    1. Animal urges
    2. Most games are competitive in nature
    3. Collaborate to compete against machine
    4. Collaborate to compete against another team
    5. Lens of Competition
      1. Does my game give a fair measurement of player skill?
      2. Do people want to win my game? Why?
      3. Is winning this game something people can be proud of? Why?
      4. Can novices meaningfully compete at my game?
      5. Can experts meaningfully compete at my game?
      6. Can experts generally be sure they will defeat novices?
    6. Lens of Cooperation
      1. Cooperation requires communication. Do my players have enough opportunity to communicate? How could communication be enhanced?
      2. Are my players friends already, or are they strangers? If they are strangers, can I help them break the ice?
      3. Is there synergy (2 + 2 = 5) or antergy (2 + 2 = 3) when the players work together? Why?
      4. Do all the players have the same role, or do they have special jobs?
      5. Cooperation is greatly enhanced when there is no way an individual can do a task alone. Does my game have tasks like that?
      6. Tasks that force communication inspire cooperation. Do any of my tasks force communication?
    7. Lens of Competition vs. Cooperation
      1. If “1” is Competition and “10” is Cooperation, what number should my game get?
      2. Can I give players a choice whether to play cooperatively or competitively?
      3. Does my audience prefer competition, cooperation, or a mix?
      4. Is team competition something that makes sense for my game? Is my game more fun with team competition, or with solo competition?
  7. Short vs. Long
    1. Determined by win or loose conditions
    2. Timing is everything
    3. Lens
      1. What is it that determines the length of my gameplay activities?
      2. Are my players frustrated because the game ends too early? How can I change that?
      3. Are my players bored because the game goes on for too long? How can I change that?
      4. Setting a time limit can make gameplay more exciting. Is it a good idea for my game?
      5. Would a hierarchy of time structures help my game? That is, several short rounds that together comprise a larger round?
  8. Rewards
    1. Types
      1. Praise: good job
      2. Points: the more the merrier
      3. Prolonged play: keep going
      4. Gateway: access to a new level
      5. Spectacle: usually paired with other types of reward
      6. Expression: change clothes, decorate… fun
      7. Powers: more
      8. Resources: more
      9. Completion: I did it
    2. Rules of thumb
      1. People get acclimated to rewards
      2. Variable rewards
    3. Lens
      1. What rewards is my game giving out now? Can it give out others as well?
      2. Are players excited when they get rewards in my game, or are they bored by them? Why?
      3. Getting a reward you don’t understand is like getting no reward at all. Do my players understand the rewards they are getting?
      4. Are the rewards my game gives out too regular? Can they be given out in a more variable way?
      5. How are my rewards related to one another? Is there a way that they could be better connected?
      6. How are my rewards building? Too fast, too slow, or just right?
  9. Punishment
    1. Reasons to punish
      1. Creates endogenous value: resources are more valuable if they can be taken away
      2. Taking risks is exciting
      3. Increases challenge
    2. Types
      1. Shaming: “you loose”
      2. Loss of points: very painful
      3. Shortened play: loose a life
      4. Terminated play: game over
      5. Setback: go to last checkpoint
      6. Removal of Powers: slow down
      7. Resource depletion: loss of goods
    3. Better to reward than punish
    4. Punishments need to be understood and preventable – risk of being “unfair”
    5. Lens
      1. What are the punishments in my game?
      2. Why am I punishing the players? What do I hope to achieve by it?
      3. Do my punishments seem fair to the players? Why or why not?
      4. Is there a way to turn these punishments into rewards and get the same, or a better effect?
      5. Are my strong punishments balanced against commensurately strong rewards?
  10. Freedom vs. Controlled Experience
    1. Game isn’t a simulation of real life, rather more interesting
    2. Too much freedom becomes cumbersome
    3. Take control over experience when necessary – no problem
  11. Simple vs. Complex
    1. Kinds of complexity
      1. Innate complexity: too many rules or “exception cases” – hard to learn
      2. Emergent complexity: simple rules with complex situations – hard to achieve in the design of the game
    2. Lens of Complexity
      1. What elements of innate complexity do I have in my game?
      2. Is there a way this innate complexity could be turned into emergent complexity?
      3. Do elements of emergent complexity arise from my game? If not, why not?
      4. Are there elements of my game that are too simple?
    3. Neutral vs. Artificial Balancing
      1. Careful when adding innate complexity to balance game
    4. Elegance
      1. Game is simple to learn and understand, but full of emergent complexity
      2. Pac Man: short- and long-term goals for player, slow down when eating, points measure success
      3. Lens of Elegance
        1. What are the elements of my game?
        2. What are the purposes of each element? Count these up to give the element an “elegance rating.”
        3. For elements with only one or two purposes, can some of these be combined into each other, or removed altogether?
        4. For elements with several purposes, is it possible for them to take on even more?
    5. Character
      1. Having a personality is a good thing (Tower of Pisa)
      2. Lens of Character
        1. Is there anything strange in my game that players talk about excitedly?
        2. Does my game have funny qualities that make it unique?
        3. Does my game have flaws that players like?
  12. Detail vs. Imagination
    1. “The game is not the experience — games are simply structures that engender mental models in the mind of the player.” (Jesse, 2008)
    2. How to do it well
      1. Only detail what you can do well
        1. Let the imagination do the heavy lifting
        2. Subtitles for example
      2. Give details the imagination can use
        1. Help imagination grasp the functionality of the game, making it more accessible
      3. Familiar words do not need much detail
      4. Use the binocular effect
        1. Show the details first to situate the user
      5. Give details that inspire imagination
    3. Lens of Imagination
      1. What must the player understand to play my game?
      2. Can some element of imagination help them understand that better?
      3. What high-quality, realistic details can we provide in this game?
      4. What details would be low quality if we provided them? Can imagination fill the gap instead?
      5. Can I give details that the imagination will be able to reuse again and again?
      6. What details I provide inspire imagination?
      7. What details I provide stifle imagination?

Game Balancing Methodologies

  • Use the Lens of the Problem Statement.
  • Doubling and halving.
    • “You never know what is enough unless you know what is more than enough.” – William Blake, Proverbs of Hell
    • Double or half values to see the effects
  • Train your intuition by guessing exactly
  • Document your model
  • Tune your model as you tune your game
  • Plan to balance
  • Let the players do it

Balancing Game Economies

  • Defined by:
    • How will I earn money?
    • How will I spend money I have earned?
  • Balancing act:
    • Fairness
    • Challenge
    • Choices
    • Chance
    • Cooperation
    • Time
    • Rewards
    • Punishment
    • Freedom
  • Lens of Economy
    • How can my players earn money? Should there be other ways?
    • What can my players buy? Why?
    • Is money too easy to get? Too hard? How can I change this?
    • Are choices about earning and spending meaningful ones?
    • Is a universal currency a good idea in my game, or should there be specialized currencies?

Dynamic Game Balancing

  • Adjust difficulty level on the fly
    • It spoils the reality of the world
    • It is exploitable
    • Players improve with practice

The Big Picture

  • Lens of Balance
    • Does my game feel right? Why or why not?