Your Turn Greg Niemeyer Associate Professor for New Media University of California at Berkeley

Berkeley CoopID/WBAN,Station Name,State,Year,Month,MMXT,MMNT,MNTM,DPNT,HTDD,CLDD,EMXT,High Date,EMNT,Low Date,DT90,DX32,DT32,DT00,TPCP,DPNP,EMXP,Greatest Observed Date,TSNW,MXSD,Max Date,DP01,DP05,DP /99999,BERKELEY,California,2005,1,54.5,41.4,48.0,-2.0,522,0,60,31,38,23,0,0,0,0,4.33,-0.80,0.90,2,0.0,0,,10,4, /99999,BERKELEY,California,2005,2,60.5,48.3,54.4,1.7,293,0,69,2,42,6,0,0,0,0,4.39,-0.36,1.14,15,0.0,0,,9,3, /99999,BERKELEY,California,2005,3,65.1,48.5,56.8,2.6,253,6,84,12,41,30,0,0,0,0,4.79,0.71,1.25,22,0.0,0,,10,3, /99999,BERKELEY,California,2005,4,66.8,47.0,56.9,0.6,236,0,74,23,41,13,0,0,0,0,2.17,0.54,0.64,8,0.0,0,,5,2, /99999,BERKELEY,California,2005,5,69.7,51.9,60.8,1.8,124,3,81,25,46,10,0,0,0,0,1.84,1.23,0.61,8,0.0,0,,5,1, /99999,BERKELEY,California,2005,6,73.4,52.8,63.1,1.5,64,15,85,14,46,7,0,0,0,0,1.06,0.92,0.44,8,0.0,0,,3,0, /99999,BERKELEY,California,2005,7,75.5,54.1,64.8,2.0,29,30,92,24,52,26,1,0,0,0,0.00,-0.07,0.00,31,0.0,0,,0,0, /99999,BERKELEY,California,2005,8,73.2,52.9,63.1,-0.1,67,14,88,31,50,28,0,0,0,0,0.00,-0.10,0.00,31,0.0,0,,0,0, /99999,BERKELEY,California,2005,9,72.4,52.1,62.3,-1.5,98,21,88,1,48,25,0,0,0,0,0.00T,-0.36,0.00,30,0.0,0,,0,0, /99999,BERKELEY,California,2005,10,70.6,50.4,60.5,-1.3,142,10,86,1,45,30,0,0,0,0,0.45,-0.92,0.16,26,0.0,0,,2,0, /99999,BERKELEY,California,2005,11,66.1,48.4,57.3,2.2,224,0,76,19,38,27,0,0,0,0,2.32,-1.30,0.84,7,0.0,0,,6,2, /99999,BERKELEY,California,2005,12,M,M,M,M,M,M,60,20,39,16,0,0,0,0,13.49,9.95,2.84,18,0.0,0,,12,8, /99999,BERKELEY,California,2005,Annual,M,M,M,M,M,M,92,Jul,38,Nov,1,0,0,0,34.84,9.44,2.84,Dec,0.0,0,,62,23, /99999,BERKELEY,California,2006,1,57.8X,43.4X,50.6X,0.6,438B,0B,66,5,38,15,0,0,0,0,4.03,-1.10,0.69,14,0.0X,0,,10,3, /99999,BERKELEY,California,2006,2,61.2,44.5,52.9,0.2,330,0,73,10,35,20,0,0,0,0,3.23,-1.52,1.67,27,0.0,0,,6,2, /99999,BERKELEY,California,2006,3,57.9,43.3,50.6,-3.6,439,0,66,24,35,11,0,0,0,0,9.42,5.34,1.25,5,0.0,0,,20,7, /99999,BERKELEY,California,2006,4,62.9,48.1,55.5,-0.8,278,0,74,28,40,17,0,0,0,0,5.32,3.69,0.90,11,0.0,0,,11,4, /99999,BERKELEY,California,2006,5,71.8,50.4,61.1,2.1,126,13,90,15,47,29,1,0,0,0,0.52,-0.09,0.26,21,0.0,0,,2,0, /99999,BERKELEY,California,2006,6,75.7,53.9,64.8,3.2,44,46,93,22,50,19,2,0,0,0,0.00,-0.14,0.00,30,0.0,0,,0,0, /99999,BERKELEY,California,2006,7,78.0,54.6,66.3,3.5,29,79,99,23,49,7,2,0,0,0,0.00,-0.07,0.00,31,0.0,0,,0,0, /99999,BERKELEY,California,2006,8,73.0,53.3,63.2,0.0,64,16,92,10,50,22,1,0,0,0,0.00,-0.10,0.00,31,0.0,0,,0,0, /99999,BERKELEY,California,2006,9,74.6,51.0,62.8,-1.0,91,29,89,26,46,15,0,0,0,0,0.00,-0.36,0.00,30,0.0,0,,0,0, /99999,BERKELEY,California,2006,10,72.5,49.9,61.2,-0.6,121,11,85,22,45,25,0,0,0,0,0.61,-0.76,0.52,5,0.0,0,,1,1, /99999,BERKELEY,California,2006,11,64.4,46.3,55.4,0.3,283,0,76,7,37,28,0,0,0,0,2.05,-1.57,0.93,14,0.0,0,,4,1, /99999,BERKELEY,California,2006,12,59.7,41.7,50.7,0.5,436,0,70,6,33,19,0,0,0,0,4.53,0.99,1.46,12,0.0,0,,7,5, /99999,BERKELEY,California,2006,Annual,67.5X,48.4X,57.9X,0.4,2679,194,99,Jul,33,Dec,6,0,0,0,29.71,4.31,1.67,Feb,0.0X,0,,61,23, /99999,BERKELEY,California,2007,1,58.9,38.9,48.9,-1.1,490,0,68,10,29,13,0,0,3,0,1.00,-4.13,0.31,4,0.0,0,,4,0, /99999,BERKELEY,California,2007,2,61.1,43.5,52.3,-0.4,348,0,77,18,34,28,0,0,0,0,5.79,1.04,1.41,10,0.0,0,,10,5, /99999,BERKELEY,California,2007,3,67.5,45.0,56.3,2.1,268,3,82,13,37,1,0,0,0,0,0.64,-3.44,0.39,20,0.0,0,,2,0, /99999,BERKELEY,California,2007,4,67.5,44.9,56.2,-0.1,259,1,81,28,38,18,0,0,0,0,1.56,-0.07,0.42,14,0.0,0,,5,0, /99999,BERKELEY,California,2007,5,70.6,48.1,59.4,0.4,193,25,91,8,43,12,1,0,0,0,0.59,-0.02,0.31,2,0.0,0,,2,0,0

Los Angeles

Gears of War, Epic Games, 2006

Lights On Text Sunset Gas Conversation Corkscrew Dishes

Lights On Text Sunset Gas Conversation Corkscrew Dishes Action Participation Transformation

Imagination “One interesting line of research that exemplifies these points is Glenberg et al. This study describes an experiment in which young children read a passage and manipulate plastic figures so that they can portray the actions and relationships in the passage. By manipulating the figures, the children get a structured, embodied experience with a clear goal (portray the action in the text). After some practice doing this, the children were asked to simply imagine manipulating the figures. This is a request to engage in simulation in their heads. As a posttest, the children read a final passage without any prompting. Children who completed the sequence of embodied experience then simulation were better at remembering and drawing inferences about the new passage, as compared to children who received no training. They were better as well, compared to children who were instructed to only imagine the passage. And, most interestingly, they were better compared to children who manipulated the figures without the intermediate instructions to imagine manipulating. Encouraging simulation through the initial use of physical enactment helped the children learn a new reading comprehension strategy, namely a strategy whereby they called on their experiences in the world to build simulations for understanding a text in specific ways. “ Gee, James Paul. “Learning and Games." The Ecology of Games: Connecting Youth, Games, and Learning. Edited by Katie Salen. The John D. and Catherine T. MacArthur Foundation Series on Digital Media and Learning. Cambridge, MA: The MIT Press, –40. doi: /dmal

4 Game Elements Game Assets: Interface, Characters, Drama Players: Present, Past (Hi-Scores) Rules: Implicit, Explicit Game Engine: Turns, AI

5 Game Conditions Free Separated by Magic Circle Rule-based Non-productive Abstract Limited in time and space Mixed After Caillois, Roger. Man, Play and Games. University of Illinois Press, 1961

5 Game Parameters Learning: How easy to start? Mastery: How significant is success Replay: How many play again? Spread: How many show others? Modding: Other ways to play? After Caillois, Roger. Man, Play and Games. University of Illinois Press, 1961

5 Game Dynamics Gameplay: models of large and small dramatic processes with objectives Interaction: Game and Player change each other Feedback: High rate of outcomes Competition: Sportsmanship, Gamesmanship Imagination: Identification with game machine, game and role

What I could never figure out, even with help What I could figure out with some help What I already know

Activity Activity Action Media SubjectObject CommunityRulesLabor

Embodiment Bodies are time-sensitive Information is time-sensitive Action is time-sensitive How long does it take the body to acquire information and how long does it take the body to then take informed action?

Game-Based Learning Games are models of reality Models train prediction To know is to predict Learning is training prediction Games equal learning

Lights On Text Sunset Gas Conversation Corkscrew Dishes Action Participation Transformation Prediction: Your Turn

Game Design To create a model of the process you wish students to learn predict To include in that model dramatic motivations so students want to predict outcomes To include adaptive elements, choices