Technology and gaming in education

Beaumie Kim

Associate Professor and Chair of Learning Sciences

Pratim Sengupta

Associate Professor and Research Chair of STEM Education

Werklund School of Education

Welcome

Webinar series by University of Calgary scholars

Information presented is a summary of the scholars’ research

Beaumie Kim

Associate Professor & the Chair of Learning Sciences, Werklund School of Education

PhD & MEd, University of Georgia (USA), BA Hanyang University (Korea)

Research focused on empowering learners as designers of their own and others’ learning (using games)

Twitter: @beaumiekim

Pratim Sengupta

Associate Professor of Learning Sciences and Research Chair of STEM Education, Werklund School of Education

Designs open-source programming languages and computer modeling tools

Researches how such tools can be part of a cultural transformation in K-12 classrooms and public spaces around innovation and scientific literacy

Twitter: @Pratim

Game play & design as learning

Engagement in schools vs. in games

Playful learning

Game design & learning

Examples of game design practices for learning

Supporting playful learning

Engagement

Wilians, Friesen & Milton, 2009), CEA (Canadian Education Association)

Game/play &

productive failure

Playful learning

Creative & improvised

Emotional – sense of who they are

Social – interaction, magic circle

Cognitive – making sense, creating meanings

Identity negotiation –diversity, curiosity, creativity

Game design & learning

Games are models of systems - systemic & rule-structured while dynamic when played (Gee, 2008; Zimmerman, 2013)

In creating games, learners need to understand and create a complex set of meanings (Kim & Bastani, 2016)

Playing and designing games:

• Construct new relationships with knowledge through the process of creating sharable artifacts (Kafai, 2006)

• Encourage learners' storytelling and identity expression (Ke, 2014)

• Promote critical thinking, systems thinking, problem-solving skills (Gee, 2008; Peppler et al., 2010)

Creating games

Problem-solving, decision-making, & evaluating designs

Developing systems thinking (game components, rules, feedback & balance)

Mixing of game genres & Improvising rule changes

Trivia to complex role-playing & strategy games

Kim & Bastani (2016)

Tentative systems in learners’ games

Race of Renaissance• Da Vinci, Galileo,

Gutenberg, Kepler as playable characters

Renaissance: Rebirth• Spread/impact of

knowledge

Kim & Bastani (2016; 2017)

Conceptualizing & recreating experiences

Re-conceptualize the Meso-American Ball game in Minecraftand incorporate cultural practices of the Aztecs• Game theme: Recreate the dark

experience of the actual Aztec game

Contextual wrapping of Aztec game theme through game design (Space and rituals)

Gupta & Kim (2016)

Algorithms & game design

Dungeoneering

Laser Escape

Marasco, Gatti Jr., Kim, Behjat, & Eggermont (2017)

"Once this idea was established, the project was explored in more detail with the problem definition. General game design aspects were outlined here, such as scoring, difficulty, levels, hints, audience, etc. As well as the fact that this game would be based off a routing algorithm to calculate the optimal path through the maze/doors."

Developing relationships with disciplines

Aggression game play & redesign for early math learners

Kim & Takeuchi (2018)

Playful coding through games

Sengupta, Kim & Shanahan (2017)

Supporting playful learning with games

Simple games are okay

Redesigning, adopting or modding games • Investigating & creating a complex set of meanings• Challenging systems and rules through game play and

design• Intended game goals vs. emergent player goals

Distributing the design responsibilities • Opportunities for deep learning (critical thinking,

problem-solving, systems thinking)• Opportunities for diverse expressions• Creating new relationships with knowledge

Opening up S,T,E,M

Modeling Engineering Design

Coding Designing for Use

STEM

Science as modeling

Maxwell’s model of field lines

Einstein’s Equation

Model of DNA

Modeling involves computation

… and computational thinking

Punchline: Programming becomes modeling in science

Some important mandates

Computational thinking

Integrated STEM

A complex image of learning

ViMAP + Sensors: One sensor controls the “turn”, other controls the “speed” of the Turtle

Learning Math = Modeling + Engineering Design + Coding

Engineering design

mathematical explanations. Their explanations made explicit the mathematical rela-

tionships between algorithmic elements (e.g., number of loops in their ViMAP pro-

gram) and the actions of the Turtle in every step (e.g., right turn), which in turn was

directly effected by the users’ actions (e.g., sensor reading generated by the user). We

consider this as evidence of the reflexivity between user-centered engineering design

and mathematical learning.

Figure 5: Jacinda and Tom’s user guides in User Testing 1 (Figure 5A, left) and User Testing 2

(Figure 5B, right). We annotated their user guides using the schematic shown in Figure 6.

Figure 6: A schematic for mechanistic explanations used by all groups in User Testing 2

Figure 7: Final version of Jacinda & Tom’s machine used during UT2

Making mathematics for others

mathematical explanations. Their explanations made explicit the mathematical rela-

tionships between algorithmic elements (e.g., number of loops in their ViMAP pro-

gram) and the actions of the Turtle in every step (e.g., right turn), which in turn was

directly effected by the users’ actions (e.g., sensor reading generated by the user). We

consider this as evidence of the reflexivity between user-centered engineering design

and mathematical learning.

Figure 5: Jacinda and Tom’s user guides in User Testing 1 (Figure 5A, left) and User Testing 2

(Figure 5B, right). We annotated their user guides using the schematic shown in Figure 6.

Figure 6: A schematic for mechanistic explanations used by all groups in User Testing 2

Figure 7: Final version of Jacinda & Tom’s machine used during UT2

Splitting (Confrey, 1994)

Modeling with gestures

The SQUARE Is a mathematical PHENOMENON that can be EXPERIENCED

Modeling with code

Modeling complexity in Public Spaces

Modeling with “real” code

Minnows are triangles, and triangles are squished rectangles

Coding Science @ Spark (opens Jan 22)

Open Source, Open Science @ UCalgary

Learn WITH your children; Play the long game

Don’t underestimate what children can accomplish with little help

The big three

Complex is easy • (playful coding and building + learning X) is easier than

learning X• coding in science = Modeling• innovation = renewal + disruption

Play the long game• learning NOT EQUAL TO assessment• Interest develops over the long term• teaching = learning with

Encourage thinking with objects• virtual and Physical• don’t dilute problems for children• make room for uncertainty

Thank you

Usable goodies

www.vimapk12.net: Website for downloading ViMAP programming language and activities. Designed for your STEM classroom

www.M3lab.org: Website for my research lab, papers, videos, etc.

Twitter: www.twitter.com/pratim, @pratim

Public education, Private code

New mandates on “coding” in public education

Thank you

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