Gaming the Educational System

Games in School?

Games in school are, more often than not, a taboo topic.  The conversation has shifted, for sure, due to recent research and gradual changes in educator opinions, but games as learning vehicles in the classroom are generally still not taken seriously.  Isolated educator success has definitely raised interest but also proven difficult to duplicate.  A lot this is due to the chicken and egg scenario of established approaches, research, and, most importantly, administrative support for game-based learning and gamification in the classroom.  As with most things in modern education, a good place to start is the standards.  As far as game-based learning and gamification are concerned, the ISTE standards provide an excellent cornerstone to build upon.

International Society for Technology in Education (ISTE) Educator Standard 5

Designer: Educators design authentic, learner-driven activities and environments that recognize and accommodate learner variability. Educators:

  • 5a. Use technology to create, adapt and personalize learning experiences that foster independent learning and accommodate learner differences and needs.
  • 5b. Design authentic learning activities that align with content area standards and use digital tools and resources to maximize active, deep learning.
  • 5c. Explore and apply instructional design principles to create innovative digital learning environments that engage and support learning.

ISTE Educator Standard 5, Designer, provides good guidance for educators in terms of focusing on designing authentic, learner-driven experiences..  By focusing on supporting student learning and learner engagement and then matching that with something like game-based learning and gamification, educators can create digital learning environments that explore and apply instructional design principles in truly innovative ways.  This type of unique approach can both increase intrinsic motivation and overall student learning at the same time.

Essential Question

How can educators explore and apply innovative instructional design approaches to create new unique digital learning environments that increase student engagement and learning? 

Game-based Learning vs. Gamification

In any general conversation regarding game-based learning and gamification, it’s important to clarify similarities and differences.  Game-based learning utilizes games as the primary vehicle for the learning itself.  So students are learning directly through a game.  Gamification is when something other than a game is taken and game-like qualities are added on.  Examples include a traditional lesson or homework where points are added and classroom management strategies where positive behavior choices lead to earning points.  There are countless examples of each and many ways to approach both game-based learning and gamification.  It is a little bit of a spectrum too where sometimes there can be a some blurring of the lines between the two classifications.  Ultimately, while helpful, understanding the distinction between game-based learning and gamification is less important at the outset then focusing on the intended result of increasing student engagement, content retention, and overall learning.

Innovating in Schools with Games

Innovation, by definition, means doing something new, unique, and different in order to more effectively and or efficiently accomplish a task, goal, and/or objective.  In this case, improving upon the traditional educational experience in such a way that students are more engaged, remember more content, and learn more standards-based material overall.  If they have fun along the way then all the better!  Piaget is often quoted as saying that “Play is the work of childhood” so if we can tap into this in the classroom then we can create a naturally more effective means for learning in the classroom.  Game-based learning and gamification tap into play and utilize this as a means to facilitate learning, thereby tapping into how children are naturally wired to learn.  Even simple multiplication games are start toward helping increase engagement and any number of game-focused approaches can help make all content areas more interesting for students.  Even gamification of classroom management can help make the generic class experience more fun for students.  All of these approaches can be analog or digital in terms of the game-based approach.  Digital, or video, games do provide some additional opportunities that weren’t readily available even just a few years ago.

MakeCode Makes Video Games Easy

One platform for engaging students with a focus on game-based learning via video games is Microsoft’s MakeCode platform.  MakeCode Arcade, especially, provides a readily available approach for leveraging this area in the classroom.  MakeCode’s coding environment is very intuitive and user friendly.  I was able to get on, explore, teach myself, and program my first video game via MakeCode in approximately 15 minutes.  The first lesson is a basic environment where a character can be moved around to eat a food item for points with the more items eaten before time lapses then the higher the score (you can play my first MakeCode video game pictured above by clicking here).  There are so many possibilities in terms of utilizing this as a means to encourage students to practice content standards.  Students could easily design a similar game where the main character needed to “eat” the correct answer to a math problem in order to earn points.  Or, students could write a story to go along with the video game adventure and utilize the experience as motivation for a writing prompt.  In social studies, this simple mechanism could illustrate an experience around finding appropriate food sources on the Oregon Trail.  The list goes on and that’s just via a very simple introductory video game.  Very quickly more complex approaches and concepts become possible where students can program to demonstrate their own learning, program games to teach concepts to classmates, program solutions to project-based problems, and much more.  Very quickly, students can make the transition from learning to code to coding to learn.

Where Educational Games meet Pedagogy

Okay, this is great and all, you may even have gotten excited about trying out some sort of game-based learning or gamification in your classroom, but where to begin?  I recommend thinking about your current teaching context.  Are there any other teachers in your building that have experimented with either?  If so then ask them what’s worked in their case.  How does your administrator feel about this?  Is it better to ask in advance in case s/he walks in or is it better to ask forgiveness?  Is there anything in your existing curriculum that resembles game-based learning or gamification?  Or, can you start with something as simple as classroom Jeopardy?  Your teaching context and experience is incredibly relevant when considering your starting point.  Teaching basic coding before attempting to teach any sort of computer game programming is also important.  By starting with activities that are clearly standards based and connected to existing curriculum, an educator can build a track record of gradual transition and implementation into more in-depth game-based learning and gamification where the learning involved will be more obvious to all that observe the educational progression.

References

  1. International Society for Technology in Education. (2019). ISTE Standards For Educators. ISTE. Retrieved from https://www.iste.org/standards/for-educators
  2. Microsoft (2020). MakeCode Arcade. Retrieved from https://arcade.makecode.com/#reload 
  3. Farber, M. (2020, January 22nd). How to Find Games for Classroom Learning. Edutopia (George Lucas Foundation). Retrieved from edutopia.org/article/how-find-games-classroom-learning
  4. Farber, M. (2014, October 9th). Games in Education: Teacher Takeaways. Edutopia (George Lucas Foundation). Retrieved from edutopia.org/blog/games-in-education-teacher-takeaways-Matthew-farber
  5. Gee, J.P. (2012, March 19th). James Paul Gee on Learning With Video Games. Edutopia (George Lucas Foundation). Retrieved from edutopia.org/video/James-Paul-gee-learning-video-games
  6. Samueli Foundation. (2020). North America Scholastic Esports Federation. Retrieved from NASEF.org
  7. Nazerian, T. (2019, January 31st). Can Designing Video Games Help Kids Gain Hard and Soft Skills? Edsurge. Retrieved from https://www.edsurge.com/news/2019-01-31-can-designing-video-games-help-kids-gain-hard-and-soft-skills
  8. Nazerian, T. (2019, January 22nd). Educators Share How Video Games Can Help Kids Build SEL Skills. Edsurge. Retrieved from https://www.edsurge.com/news/2019-01-22-educators-share-how-video-games-can-help-kids-build-sel-skills
  9. Noonoo, S.  (2019, February 12th). Playing Games Can Build 21st-Century Skills. Research Explains How. Edsurge. Retrieved from https://www.edsurge.com/news/2019-02-12-playing-games-can-build-21st-century-skills-research-explains-how

Encoding Creative Communication

Creating Creative Communicators

Communication, Collaboration, Critical Thinking, and Creativity are often referred to as the 4 C’s of 21st Century Learning.  These so-called “soft skills” are different from the “hard skills” of math and science” but essential for success in applying math, science, engineering, and technology in our modern society and, arguably, harder to teach. The Battelle Foundation’s Partnership for 21st Century Learning highlights these 4 C’s throughout its “Framework for 21st Century Learning Definitions”.  Another organization in this space, the International Society for Technology in Education (ISTE), provides us with multiple references to these modern “soft” skills throughout the ISTE standards. One example is ISTE standard 6, Creative Communicator, which addresses all of these in one standard for students.

International Society for Technology in Education (ISTE) Standard 6

ISTE Standard 6, Creative Communicator, students communicate clearly and express themselves creatively for a variety of purposes using the platforms, tools, styles, formats and digital media appropriate to their goals. Students:

  1. Choose the appropriate platforms and tools for meeting the desired objectives of their creation or communication.
  2. Create original works or responsibly repurpose or remix digital resources into new creations.
  3. Communicate complex ideas clearly and effectively by creating or using a variety of digital objects such as visualizations, models or simulations.
  4. Publish or present content that customizes the message and medium for their intended audiences.

Successfully addressing ISTE Standard 6, Creative Communicator, requires aspects of all four C’s from the core set of 21st Century Skills.  Creativity is obviously required in order to be a creative communicator, as are communication and collaboration essential skills for creatively communicating with others.  Lastly, and perhaps less obvious, is the need for critical thinking as creative communicators (i.e. students) evaluate tools, mediums, and resources to use effectively in order to accomplish their goals as supported by this standard.  This last part comes out through the third component of the standard to “communicate complex ideas clearly and effectively…” and forms the basis for my essential question and the focus of this blog post.

Essential Question

How do teachers empower students to communicate complex ideas in creative ways so that they use a variety of digital objects such as visualizations, models, and simulations?

Computer Science for the Non-Computer-Science Teacher

Encoding is a means of transforming information into a format that is easily transferred or communicated.  Encoding creative communication is one way to think about transforming student abilities so as to transfer information in more unique and creative ways such as visualizations, models, or simulations.  What better way to do this than computer science and programming? Not a coder? Not a problem. We need to move beyond the traditional definition of the computer science teacher and expand the communication medium to all classrooms and thus create computer science opportunities for the non-computer-science teacher.  Block based coding is an equalizer in this area and empowers everyone to approach and learn to write computer programs in an easily understood and transferable environment. This opens all sorts of doors for everyone to explore creative communication and to communicate complex ideas creatively via a variety of digital objects because those objects can be programmed by students as young as 1st grade and in some cases even kindergarten.

MIT, Scratch, & the Rise of Block-Based Programming in Education

MIT’s Scratch Website: The Logo computer programming language, otherwise known as the “turtle programming language” is what essentially launched accessible programming but MIT’s Scratch is what truly made block-based programming mainstream (it’s worth noting that Logo led to Lego Logo which was a precursor to Scratch).  Scratch is an accessible block-based language that is especially user friendly when it comes to animating a character, otherwise known as “sprite”, and assigning dialogue or interactions via code. This becomes extremely useful for integration opportunities across Language Arts, English language learning, and art among other areas.  Scratch is compatible with a wide-range of products and browser-based so it’s easily accessible (like most modern block-based programming languages).

BootUp: Scratch’s curriculum for educators has not historically been one of the more user-friendly resources. The newest iteration appears to be a definite improvement although still a little text heavy at times.  Those looking for something a little different may want to check out BootUp’s freely available Scratch curriculum which utilizes a variety of short student-friendly video vignettes to support instruction.  BootUp bills themselves as “what’s next” after initially jumping into computer coding via Code.org or some other introductory platform.

Google CS: This is arguably the newest block-based coding curriculum for mainstream k-12 computer science.  Google has created a series of introductory lessons that utilize Scratch as a means to teach basic computer coding strategies.  Google CS’s selection at this point in time is somewhat limited compared to other resources because it’s newer but new lessons and resources are being added on a regular basis.  Google CS’s choice of Scratch is an interesting one given that the block-based programming language, Blockly, is also created by and a project of Google.

Block-Based Coding with Blockly & Code.org as the Gold Standard

Code.org: “Hour of Code” was popularized by Code.org which essentially launched somewhat of a k-12 computer science revolution in a relatively short amount of time.  Code.org uses Blockly and is the current gold standard of providing student friendly lessons for all grade levels. Once students have progressed through the highly formulaic, structured, and scaffolded lessons then they can apply the basic computer science skills they’ve learned in couple of different settings such as Code.org’s Play Lab.  This is a fun environment for students to try out their newfound skills but slightly more limited than the more open forum provided by Scratch. To date, Code.org remains arguably the most user-friendly introduction to programming.

MakeCode as the New Kid on the Block & Physical Computing

MakeCode: Microsoft’s entry into the foray of block-based programming is only a couple of years old but has some powerful partnerships.  MakeCode’s main strength is through these partnerships and both the virtual and physical computing that this allows. Current partners include micro:bit, Circuit Playground Express, Minecraft, LEGO Mindstorms Education EV3, Wonder Workshop Cue, Arcade, and Chibi Chip.  The micro:bit partnership in particular is powerful because students can program a microbit: simulator on a computer web browser and take turns testing their programs on the relatively inexpensive physical micro:bits themselves (a basic microcontroller). The same is true of the Circuit Playground Express simulator as well as the LEGO Mindstorms EV3 simulator which provides a rough but workable simulated example.  Long story short, students can write programs for physical devices but test them virtually which increases accessibility and stretches limited physical resources further. With the notable exception of the Wonder Workshop Cue, the remaining options can all be programmed via any browser and have a series of accessible tutorials provided below the programming environment. The micro:bit in particular has a robust set of curriculum available as well as a significant number of accessories.

Coding in Mathematics with Polyup

Polyup.com: Polyup is a drag and drop website that allows the user to program via math and what is essentially a math-based functional programming language.  The platform gets around the challenge of doing this with order of operations by utilizing Reverse Polish Notation. Students can then use math to write basic programs, solve unique problems, and even code motion into objects.  All of this is done via Polyup’s gamified computational thinking and mathematical coding online platform. There is also a real-world model for this approach to programming with math via the Wolfram Alpha search engine which uses a similar computing language and algorithm approach to Polyup.  All of this bridges math, computer science, and a broader fundamental approach to applied computational thinking in a problem-based learning setting.

How Then Does The Average Classroom Teacher Apply This?

Again, think computer science for the non-computer science teacher.  A classroom teacher interested in incorporating computer science should consider his/her objectives and what s/he is hoping to accomplish with students in the classroom setting.  Is the focus on teaching basic programming itself? Problem solving? Content integration? Physical computing? Some combination thereof or something else all together? Additionally, gauging individual comfort level and available resources is important.  Code.org empowers the average teacher without any programming background, knowledge, or support to sign up students and get them started together on mostly self-paced programming lessons as well as detailed offline computing lesson plans. The more comfortable or advanced the teacher’s ability then the more robust the example they might try such as programming stories in Scratch from scratch, designing video games in Arcade, writing programs for micro:bit microcontrollers in MakeCode, or even exploring entirely new avenues like programming 3-dimensional shapes in Minecraft for virtual interaction or Tinkercad for physical printing via their respective coding environments.  The hardest part is starting but the journey of a thousand programming steps begins with that very first coded “Hello World” program. From there, the possibilities are infinite and students will no doubt exceed any expectations.

References

  1. MIT. (2020). Scratch. Retrieved from https://scratch.mit.edu/
  2. BootUp. (2020). BootUp Professional Development Curriculum Overview. Retrieved from https://bootuppd.org/curriculum/
  3. Code.org. (2020). Hour of Code Full course catalog. Retrieved from https://studio.code.org/courses
  4. Google for Education. (2020). Google CS. Google. Retrieved from https://csfirst.withgoogle.com/
  5. Microsoft. (2020). MakeCode. Retrieved from https://www.microsoft.com/en-us/makecode
  6. Polyup. (2020). Poly Challenge. Retrieved from https://www.polyup.com/
  7. Wolfram Alpha. (2020). Reverse Polish Notation. Retrieved from https://mathworld.wolfram.com/ReversePolishNotation.html
  8. Battelle for Kids. (2019). Partnership for 21st Century Learning Frameworks & Resources.  Retreived from https://www.battelleforkids.org/networks/p21/frameworks-resources
  9. International Society for Technology in Education. (2016). ISTE Standards For Students. ISTE. Retrieved from https://www.iste.org/standards/for-students 
  10. Computer Science Teachers Association. (2019). Computer Science Standards. Retrieved from https://www.csteachers.org/page/standards
  11. Microsoft (2020). Minecraft. Retrieved from https://www.minecraft.net/en-us/
  12. Autodesk. (2019). Tinkercad. Retrieved from https://www.tinkercad.com/

Computational Thinking Across the Content Areas

Photo by Jan Zhukov on Unsplash

“Computational thinking is the thought process involved in formulating a problem and expressing its solution(s) in such a way that a computer—human or machine—can effectively carry out.” 

Wing, Jeannette (2014). “Computational Thinking Benefits Society.” 40th Anniversary Blog of Social Issues in Computing.

Computational Thinking

Jeannette Wing, a computational thinking researcher, describes computational thinking as a specific thought process for formulating a problem so that it can be effectively solved by someone or something that computes (human or machine).  This makes computational thinking an especially effective approach for developing computer science and programming approaches via physical computers and for those that program and utilize those computers.  But what about for other content areas beyond computer science? A good place to start with this in mind is a slightly closer look at computational thinking. There are four primary components of computational thinking that are commonly recognized as its pillars and they are as follows:

  • Decomposition: Breaking down data, processes, or problems into smaller, manageable parts.
  • Pattern Recognition: Observing patterns, trends, and regularities in data.
  • Abstraction: Identifying the general principles that generate these patterns.
  • Algorithm Design: Developing the step-by-step instructions for solving this and similar problems.

These four pillars are also explained well in a video for educators created by Google.  With these four pillars in mind, we can look at how the ISTE Indicators of Computational Thinking quantify computational thinking into a single applicable statement: “Students break problems into component parts, extract key information, and develop descriptive models to understand complex systems or facilitate problem-solving,” ISTE Indicators of Computational Thinking.  Essentially, computational thinking is a process for quantifying, breaking down, and solving problems into small solvable pieces.  Problem solving can be done in any content area. By looking more closely at the ISTE Computational Thinking standard, we can get an idea for how computational thinking might be applied more generically across content areas as a way to approach problem solving in different subjects.

International Society for Technology in Education (ISTE) Standard 5

ISTE Standard 5, Computational Thinker, students develop and employ strategies for understanding and solving problems in ways that leverage the power of technological methods to develop and test solutions. Students:

  1. Formulate problem definitions suited for technology-assisted methods such as data analysis, abstract models and algorithmic thinking in exploring and finding solutions.
  2. Collect data or identify relevant data sets, use digital tools to analyze them, and represent data in various ways to facilitate problem-solving and decision-making.
  3. Break problems into component parts, extract key information, and develop descriptive models to understand complex systems or facilitate problem-solving.
  4. Understand how automation works and use algorithmic thinking to develop a sequence of steps to create and test automated solutions.

The ISTE Computational Thinker standard emphasizes the leveraging of technology in problem solving via computational thinking.  The focus is on formulating problems, collecting data, breaking down problems into quantifiable parts, and understanding automation via algorithmic thinking.  The ISTE standards aren’t the only standards that address computational thinking, though. We can also look to the Next Generation Science Standards (NGSS) Science and Engineering Practices and Common Core State Standards (CCSS) Mathematical Practices for direct and indirect references to computational thinking.  The NGSS directly references computational thinking via the fifth Science and Engineering Practice, “Using mathematics and computational thinking,” and references aspects of computational thinking through other practices such as “Analyzing and interpreting data.” The CCSS Mathematical Practices do not explicitly state computational thinking but the components are definitely present in practices such as “Look for and express regularity in repeated reasoning” and “Reason abstractly and quantitatively.”  With all of these references across a variety of standards, it makes sense to start thinking about applying computational thinking in as many relevant places as possible across the curriculum.

Essential Question

How do teachers effectively integrate computational thinking across academic disciplines in such a way that it becomes an effective tool for areas of instruction beyond computer science and math, such as engineering, science, reading, writing, history, and art?

Starting with Familiar Computational Thinking Problems

As we think about applying computational thinking beyond computer science and math, it’s probably best to reflect on how computational thinking is more traditionally applied in computer science and mathematics.  This will provide a starting point when thinking about applying computational thinking elsewhere.

  • Decomposition in Computer Science: in programming this means looking at how to approach a problem in small and simple enough ways that it can be written as parts of a computer program that utilizes primarily binary logic.
  • Pattern Recognition in Computer Science: by looking for patterns across any problem or problems then programmers can start to identify similarities and differences necessary for solving various aspects of a problem or problems.
  • Abstraction in Computer Science: once patterns are identified then computer programmers can begin to piece the various small pieces of a problem together into something that might become a larger solution as it’s applicable across problems of a certain problem type whether known or as yet unknown.
  • Algorithmic Design in Computer Science: the creation of a set of steps to solve a certain problem type can be described as an algorithm because it applies to both known and unknown problems.

These various steps when applied via computer science should start to sound familiar for mathematics.  We basically teach students to memorize a variety of algorithms starting with those that are most simple and building up toward the more complex.  Along the way, we also try to teach deeper mathematical thinking, concepts, and terminology but the algorithms tend to be at the center of instruction.  Teaching computational thinking in mathematics means taking instruction to a deeper level, though, because we need to show students how to identify, break down, quantify, and design algorithmic thinking itself.  This deeper approach to mathematics via computational thinking would go a long way toward helping students understand the “why” behind what they are doing.

Applying Computational Thinking Problems to Other Areas

Now comes the more challenging task of applying computational thinking to those content areas that we don’t normally think of as applicable.  By focusing on the four pillars of computational thinking, we can start to think about what this might look like. At its core is probably pattern identification.  So we need to start thinking about everything in terms of patterns. Computer science is patterns of binary logic and mathematics is patterns of numbers. Beyond these two, art is patterns of lines, reading is patterns of letters, writing is patterns of words, science is patterns of ideas, engineering is patterns of science applied to or with technology, history is patterns of events, music is patterns of notes, etc.  This list is probably an oversimplification but you get the idea that we can look at everything as being composed of patterns, and if we can do this then we can use a problem solving approach like computational thinking that relies on patterns to solve problems across all of these content areas.

  • Decomposition in Art: breaking down the components of a particular type of picture (e.g. landscape or portrait) into different smaller parts.
  • Pattern Recognition in Art: identifying patterns that a particular type of picture or pictures has.
  • Abstraction in Art: by synthesizing from the patterns of similarities and differences across a particular type of picture(s) then a more general idea or set of ideas can be described.
  • Algorithmic Design: a set of repeatable steps for recognizing and possibly creating more pictures of a certain type allows for this type of art problem of recognition or creation to be repeatable and reproducible.
  • Decomposition in History: breaking down the components that lead up to collapse of a civilization in history can lead the student to understand the smaller details that may lead up to such a large scale event.
  • Pattern Recognition in History: recognizing that a certain pattern of events probably leads up to a collapse of a civilization and means the more similarities and differences that can be quantified then the more likely patterns can be identified.
  • Abstraction in History: by building a bigger picture of the patterns that occur leading up to the collapse of a civilization then a synthesized coherent and detailed description of this overall type of event can begin to emerge.
  • Algorithmic Design in History: a step-by-step description of the characteristics of events leading up to the collapse of a civilization and how these can generally be codified as repeatedly observable steps in a process means that students could be tasked with designing an algorithm for analyzing the typical civilization collapse and search throughout history for similar scenarios.

These are two fairly generic examples of applying computational thinking to content areas beyond computer science and mathematics.  Art and history are not traditionally associated with computational thinking and yet there is tremendous potential for applying this problem solving approach to problems that might exist in either subject area.  With practice, components of computational thinking can be identified in all subject areas and then applied to relevant problems by students with proper support through thoughtfully designed lessons.

How Then Does The Average Classroom Teacher Apply This?

Start simple and start small.  This fun video from the website “Hello Ruby” explains computational thinking in the context of everyday life.  The “Hello Ruby” website also has a selection of fun and unique lesson approaches that include topics such as computational thinking.  This Edutopia website article shared by one of my Digital Educational Leadership colleagues at Seattle Pacific University provides a variety of specific content area lesson examples where computational thinking can be applied in a classroom setting.  Looking at examples helps identify approaches to directly copy or inspire various ways that variations can be created and adapted for a different curriculum. There are a variety of online resources out there and more popping up every day with support from organizations such as the Computational Thinking Alliance.  Again, overall, the key is to start simple and start small while growing your classroom approaches from there over time.

References

  1. Liukas, L. (2020, February 29th). Hello Ruby. Hello Ruby Website. Retrieved from http://www.helloruby.com/
  2. Google School. (2016, October 26th). What is Computational Thinking.  YouTube.  Retreived from https://www.youtube.com/watch?v=GJKzkVZcozc&feature=youtu.be
  3. Sheldon, E. (2017, March 30th). Computational Thinking Across the Curriculum.  Edutopia.  Retrieved from https://www.edutopia.org/blog/computational-thinking-across-the-curriculum-eli-sheldon 
  4. International Society for Technology in Education. (2016). ISTE Standards For Students. ISTE. Retrieved from https://www.iste.org/standards/for-students
  5. The Next Generation Science Standards for States by States. (2013). Home Page. Next Generation Science Standards. Retrieved from https://www.nextgenscience.org/ 
  6. Common Core State Standards Initiative. (2020). Home Page. Common Core State Standards. Retrieved from http://www.corestandards.org/
  7. Computational Thinking Alliance (2020, February 29th). Home Page.  Computational Thinking Alliance. Retrieved from https://www.computationalthinking.net