Research Study Summary: Computational Thinking

Introduction   

      Computational Thinking (CT) is a problem-solving process that can involve technology, but technology is not necessary for CT to occur.  Its roots are in computing (using computers) and people often use the terms interchangeably, creating a giant misconception about what CT actually is.  Although we are in an information-based society and people are becoming more tech-savvy (and gadget-savvy), CT goes much deeper than the smart devices that have become necessary appendages.    

     The general consensus in the literature defines CT as “the thought processes involved in formulating problems and their solutions so that the solutions are represented in a form that can  be effectively carried out by an information processing agent…these agents can be computers or humans, or a combination of both” (Yadav, Mayfield, Zhou, Hambrusch, & Korb, 2014).  Even though this definition is accepted and agreed upon, the bulk of the literature revolves around computing and CT.  CT is a problem-solving process and problems are solved across the curriculum, beyond what occurs in the computer lab within the computer sciences curriculum.  “…computational-thinking concepts have been used in other disciplines via problem solving techniques, and that the ability to think computationally is essential to every discipline” (2014).

     Problem-solving is a key area of focus in content standards across curriculums.  When unpacking the components of what problem-solving is, CT is present.  When observing the major tenets of CT, problem-solving is present.  One does not exist without the other.  No one disagrees that CT skills are important in K-12 education.  In fact, there is a push to familiarize students with CT as early as possible.  “To reading, writing, and arithmetic, we should add computational thinking to every child’s analytical ability” (Yadav, Mayfield, Zhou, Hambrusch, & Korb, 2014).”  This will require a teacher professional development on CT and an overall shift in the current understanding of CT. 

Statement of the Problem

     Currently, few studies exist on embedding CT across the curriculum.  “…in order to maximize the…benefits of computational thinking and get students interested in computing, we need to integrate CT in core content areas at the K-12 level” (Yadav, Mayfield, Zhou, Hambrusch, & Korb, 2014).  To meet this challenge at its apex, the study aimed to prepare preservice teachers to “present CT ideas in explicit ways” to their future K-12 students.  Prior research indicated that “introducing teachers to computational thinking can change their attitudes towards computing as well as raise their understanding of CT as an approach to solving problems…these efforts, however, need to involve content-area teachers and not just computer science teachers” (2014).
Significance of the Problem

     The misconception that CT solely deals with the use and understanding of computers deters teachers from understanding its importance and implementing it in their classrooms.  Many teachers are unfamiliar with CT, solely because they think it belongs in the computer sciences curriculum.  It is important to redirect CT misconceptions into tangible classroom experiences that facilitate the strengthening of students’ CT skills.  “…the goal of teaching computational thinking is to teach [students] how to think like an economist, a physicist, an artist, and to understand how to use computation to solve their problems, to create, and to discover new questions that can fruitfully be explored and not for everyone to think like a computer scientist” (Yadav, Mayfield, Zhou, Hambrusch, & Korb, 2014).
Conceptual Framework

     The authors behind this study did not discuss a particular theory or concept that guided their research, but Problem-based Learning Theory (PBL) supports CT.  In PBL, the teacher facilitates student work through an authentic problem that is relevant to them. 

Basic PBL Model

1.      Identify, clarify, and describe the problem.

2.      Identify what is already known about the problem.

3.      Identify what is unknown at this point in the process.

4.      Identify possible solutions with the information that has been generated thus far.  Examine these solutions to determine if the answers seem correct.

5.      Identify the solution that is the best answer for the problem presented.  If there is not one, continue to search and develop possible solutions.

6.      Identify the solution to be presented and assess this solution (Fredrickson, McMahan, & Dunlap, 2013).  

     CT is present in the steps of a basic PBL model.  In the 2014 Horizon Report, key skills of CT are identified.  These skills include:

·         “Logical analysis and organization of data;

·         modeling, abstractions, and simulations;

·         identifying, testing, and implementing possible solutions; and

·         making complex ideas understandable with data visualization, imagery, succinct narrative, and other communication techniques” (Johnson, Adams Becker, Estrada, & Freeman, 2014).

Research Questions

1.       What is the influence of computational-thinking modules on preservice teachers’ understanding of computational thinking?

2.       What is the influence of computational-thinking modules on preservice teachers’ attitudes towards computing?

Methodological Approach

     Three hundred and fifty-seven preservice teachers from a Midwestern university participated in this study.  The control group had a total of 200 students enrolled in the introductory educational psychology course during Fall 2011, while the treatment group had 157 students enrolled in the introductory educational psychology course during Spring 2012.  A one-week module on CT was introduced in the course for the treatment group.  The module was developed jointly by faculty and graduate students from education and computer science.  Participants completed the Computational-Thinking Quiz, which was composed of three open-ended questions to assess students’ understanding of computational thinking.  Participants also completed the Computing Attitude Questionnaire in order to examine their attitudes towards computing.  The survey consisted of 21 Likert-type scale questions on the following scale: Strongly Agree, Agree, Disagree, and Strongly Disagree.  “The control group received the content typical for the course, which included lectures on higher-level cognitive processes, such as problem solving, transfer, critical thinking, and creativity. The treatment group…received the computational-thinking module.  Both groups completed the same quiz and computing attitude survey during the class one week later” (Yadav, Mayfield, Zhou, Hambrusch, & Korb, 2014).

Findings

     Aligned with the common misconception that CT and computing are interchangeable, control group participants “tended to include the use of computers as a necessary component in computational thinking” (Yadav, Mayfield, Zhou, Hambrusch, & Korb, 2014).  In contrast, the treatment group demonstrated an understanding of CT as a “cognitive tool that involved using computing concepts to solve complex problems with or without the use of computers” (2014).  On integrating CT into their future classrooms, the control group generally focused more on the technology-aspects of CT, while the treatment group focused on “critical thinking skills and how to use algorithms and heuristics” (2014).  The treatment group was more likely to answer “yes” as compared to the control group when asked if CT relates to other content areas, aside from computer science.  Although the findings highlighted the misconceptions of CT, it also showed that “there were no statistically significant differences between the control and the [treatment] groups with regards to their comfort and interest in computing” (2014).  Technology is already such an integral part of the lives of the preservice teachers who participated in the study, which consisted of mostly sophomores and juniors.

Conclusions and Implications  

     CT is a core 21^st century skill and it is important to go beyond the push to expose students in the K-12 realm as early as possible.  It is critical to foster intentional, explicit experiences with CT to give students the necessary time to understand CT and develop all of the skills it encompasses.  For this to happen, teachers need to go through this process.  “It is important that we develop teachers’ understanding of computational thinking in the context of the subject matter they teach. Unless their knowledge is developed in that context, teachers may only gain an abstract understanding of CT. As a result, their knowledge will remain inert and they will be unable incorporate it into their teaching” (Yadav, Mayfield, Zhou, Hambrusch, & Korb, 2014). 

     The authors of this study recommend that future work be collaborative between educators and computer scientists.  Concrete examples in literacy, mathematics, the sciences and the arts need to be developed.  Time must be invested in the development of CT pedagogy as well.  For CT to become an integral part of the K-12 realm, all stakeholders (policymakers, educators, and computer scientists) must be involved.  Because the study did not focus on the actual implementation of CT and there is a gap in the current literature, it is recommended that “future research should examine how teachers from a variety of disciplines incorporate [CT] practices in their own teaching” (2014). 

Resources

Fredrickson, R., McMahan, S., & Dunlap, K. (2013). Problem-based learning theory in the handbook of educational theories (pp.211-217). Charlotte, NC: Information Age Pub.

Johnson, L., Adams Becker, S., Estrada, V., & Freeman, A. (2014). NMC Horizon Report > 2014 K-12 Edition. Retrieved February 26, 2017, from http://www.nmc.org/publication/nmc-horizon-report-2014-k-12-edition/

Yadav, A., Mayfield, C., Zhou, N., Hambrusch, S., & Korb, J. (2014). Computational thinking in elementary and secondary teacher education. Acm Transactions On Computing Education, 14(1).

Gamification

Describe gamification and the two distinct ways it has been used in the classroom.

     Gamification is a way to turn work into an enjoyable, memorable, and rewarding experience.  Whatever the work is, gamification should make it feel less like work.  “The idea is to integrate game-like elements and mechanics, including quests, experience points, leader boards, milestones, and badging, among others, into non-game environments” (Johnson, Adams Becker, Estrada, & Freeman, 2014).  My days are spent with teens in the math classroom.  Anytime I can make the work feel less like work, I do it.  I spend a lot of time researching gamification and implementing it with a colleague, who I will refer to as Mr. Gates.  Mr. Gates doesn’t just dabble in gamifying his class—it IS a game.  There is a huge guild board with each guild’s shield, along with the student-designed avatars and handles that belong to each guild.  A big part of gamification is letting students create an alter ego.  The students work on this task during the first few weeks of school, maintaining these identities throughout the school year.  The students are addressed by their handles, as well.  Students in Mr. Gates’ classes don’t have quizzes and tests—they have ‘boss mobs’ along with adventures and tasks to gain XP (experience points) and ‘level up’.  There are leaderboards that are used for students to track their own progress in ‘the game’, not as a means of student-to-student competition.

Explain at least two advantages and two drawbacks of gamification in education settings.

     The biggest advantage is the freedom to fail.  Failure creates a culture of math-phobic people who turn into math-phobic parents who don’t know how to help their kids.  These are the parents who tell their kids they were bad in math so no biggie if problems exist.  Ugh!  Freedom to fail allows students to try without judgment on their results.  Another advantage, which I spoke about previously, is the freedom to assume different identities.  Middle school kids often don’t like who they are and they feel awkward.  A new identity is a great escape for them.  It also fosters creativity and provides another means for the teacher (and peers) to get to know who they are.

     As you can tell, I am a fan of gamification.  There are a few drawbacks to a gamified classroom.  Not all students ‘get it’.  I love the idea of earning XP and leveling up, collecting more badges and tackling boss mobs.  There are some kids who just aren’t into all of that.  Sure, they will adapt and play by the rules, but it won’t have the same effect as it does on the other kids and everything will still feel like work.  They will do what they need to do to pass the class without a build-up of intrinsic motivation.  Another drawback is guild work, also known as group work.  Cooperative learning is a necessary experience that teachers must facilitate.  Even in the best situations, tension can build within a group and negate the purpose of the task.  I wouldn’t label this as solely a gamification drawback, but I will say that gamification doesn’t solve this common classroom problem.

Describe two best practices of gamification.

     One important best practice is to have mixed skill-level groups.  I already mentioned that Mr. Gates has his classes form guilds.  Depending on the size of the class, a guild will consist of three to four students.  Students get to choose who is in their guild, and this will be the guild for the year.  Recognizing when it is appropriate to let students choose groups is just as important as knowing when to create them.  Mr. Gates solves this problem by creating groups that change, depending on the task.  He will assign these groups as new tasks become available.  When students come in the room, all he has to say is ‘go to groups’ or ‘go to guilds’ and students know what to do.

     Another best practice is establishing flow.  Flow is “a state of total focus on the task at hand” (Oxford Analytica, 2016).  To facilitate flow, there must be a clear goal, clear and immediate feedback, and a perfect balance between challenge and skill.  In Mr. Gates class, all of the conditions are continually met.  Students meet the tasks with focus and persevere until it is completed.  This is one of the reasons I believe in the power of gamifying a classroom.  I see it.

Describe the three elements of gamification and give an example of each.

     The three elements of gamification with relevance to education are Mechanical Elements, Personal Elements, and Emotional Elements.  Mechanical Elements are a means to address incremental progression and provide instant feedback.  A great example of this is badging.   Badges are a way to acknowledge student accomplishments while providing a tangible reward that highlights an achieved skill or completed task.  Badges also allow teachers to quickly identify students’ strengths, weaknesses, and gaps in content.  Many students are motivated by the ability to attain badges.

     Personal Elements deal with student status and visibility, including leaderboards and rankings.  An example of this is the creation of guilds, avatars, and personal handles in Mr. Gates’ classes.  All of these provide the opportunity for students to create new identities, making the game personal to each student.  Guilds provide a sense of collective responsibility within the class while allowing students to collaborate with each other.

     Emotional Elements of gamification deal with the psychological state of flow, which I briefly addressed as a best practice.  When the challenge-level is high and the skill-level is low, flow will be hindered by feelings of anxiety and worry.  When the skill-level is higher and the challenge-level is appropriate to the student, the task-at-hand can be approached with relaxation and control.  When the perfect balance of challenge-level and skill-level are achieved, students will enter the state of flow.

Describe two factors that hinder gamification.

     To appropriately gamify a classroom, an understanding of what gamification is must exist.  Teachers need the proper knowledge and willingness to invest the time and work necessary to implement gamification.  It’s not a quick fix to make content fun, nor is it simply turning content into games.  Somewhere, I read that chocolate covered broccoli is still broccoli and students will sniff it out!

     Another factor that hinders gamification is the lack of technology.  In Mr. Gates’ classroom, most of the gamification that happens is not on a computer—it is in the environment of his classroom.  However, technology has been a major support in the facilitation of all of the elements of gamification.  With technology, students design their guild shields and avatars.  With technology, students keep track of XP and leaderboards.  With technology, Mr. Gates provides more immersive, relevant tasks for students to tackle.  Could Mr. Gates do all of this without technology?  Of course, but technology makes all of the work more manageable and helps Mr. Gates to be efficient.  Gamifying a classroom is a huge commitment and requires much work, something that could be easily pushed and replaced with a focus on the Ohio Teacher Evaluation System (OTES) and Ohio State Test (OST) preparation. 

Describe one gamification platform and its different features used to gamify a classroom.

     I know I’ve spent a lot of time talking about Mr. Gates and his classroom, but now I’m going to talk about Ms. Campbell.  She has been using ClassDojo for three years and I have been privileged to witness the before-and-after in her classroom.  ClassDojo is a classroom management app that encourages students to work to potential, participate, be respectful, and whatever else a teacher wants to give points for.  Teachers can also take points away without saying a word.  In Ms. Campbell’s classes, students will hear a different tone when points are being subtracted versus when they are being added.  She doesn’t need to say who is gaining or losing points.  Students hear either tone and get on track.  Why?  Because parents have access to their child’s ClassDojo account.  They can see what points are earned or deducted for and the time of each occurrence.  Additionally, parents and teachers can communicate with each other through ClassDojo.  Students create their own avatars in ClassDojo, where all of their accomplishments (or problems) are highlighted.  Students can customize their portfolios by highlighting learning accomplishments with photos and videos.  Better yet? Parents can access ClassDojo through the app on their smartphones.  It’s an easy way to get parents involved in their child's behavior at school.      

Describe the relationship between motivation, engagement and gamification.

     Middle school students aren’t the most motivated individuals.  In fact, Ms. Campbell and I have been struggling with her eighth graders all year.  She is doing everything recommended in the research on motivation, but nothing seems to spark this group of kids.  Even the principal has told her that this cohort of students is a tough group and that she shouldn’t waste any more time trying to figure out how to motivate them.  Recently, I had the opportunity to provide time for Ms. Campbell to visit Mr. Gates’ classroom.  His eighth graders are the only students I work with who are truly motivated and engaged.  It is no coincidence that his classroom is completely gamified.  Why does it work?  “Gamification is the introduction of an extrinsic reward system (based on game mechanics) to non-game content (such as learning content) in order to engage and motivate learners to participate and complete the activity.  Its use is intended to compensate the lack of intrinsic motivation towards a learning activity” (Boulet, 2016).  Ms. Campbell was inspired by what she saw in Mr. Gates’ classroom, and I am supporting her in implementing gamification in the fall.

Resources

Boulet, G. (2016, July 19). Gamification and motivation: it's the content that matters, not the container. Retrieved March 22, 2017, from https://elearningindustry.com/gamification-and-motivation-content-matters

Johnson, L., Adams Becker, S., Estrada, V., and Freeman, A. (2014). NMC Horizon Report: 2014 K-12 Edition. Austin, Texas: The New Media Consortium.

Johnson, L., Adams Becker, S., Estrada, V., and Freeman, A. (2015). NMC Horizon Report: 2015 K-12 Edition. Austin, Texas: The New Media Consortium.

L. (2016, April 26). Gamification when it comes to education. Retrieved March 22, 2017, from https://www.joytunes.com/blog/music-fun/playing-learn-gamification-comes-education-infographic/

Lee, J. J., & Hammer, J. (2011). Gamification in education: what, how, why bother? Academic Exchange Quarterly, 15(2), 1-5. Retrieved March 22, 2017.

Oxford Analytica. (2016). Gamification and the future of education. Retrieved March 22, 2017, from https://worldgovernmentsummit.org/annual-gathering/reports

Computational Thinking

Check out my first piece of *artwork* at code.org...

...or reminisce on past Christmases with my completed Holiday Tree from Trinket!



Define computational thinking and describe at least five skills included in computational thinking.

     Computational Thinking (CT) is at the core of my life’s work.  In fact, it’s the basis of the Common Core State Standards of Mathematics (CCSS-M), specifically the Standards for Mathematical Practice.  “…Computational Thinking refers to thought processes that are involved when solving complex problems and generalizing and transferring this problem solving process to a wide variety of problems” (Voogt, Fisser, Good, Mishra, & Yadav, 2015).  My job as a math coach involves giving teachers and students research-based strategies for attacking problems.  We take problems apart, analyze them, discuss what’s happening and create a solution strategy.  This is CT.

     There are four major facets of CT. 

1.      Decomposition: breaking down a problem or task into smaller pieces.

2.      Pattern Recognition: finding similarities and differences to make predictions.

3.      Abstraction: generalizing patterns.

4.      Algorithm Design: developing step-by-step instructions (2015).

     A host of skills are embedded within these four facets, including logical analysis and organization of data; modeling, abstractions, and simulations; identifying, testing, and implementing possible solutions; and making complex ideas understandable with data visualization, imagery, succinct narrative, and communication (Johnson, Adams Becker, Estrada, & Freeman, 2014).  

Describe an activity that can promote each of the five skills of computational thinking.

     There is much debate on the actual definition of CT.  Because of this, not everyone agrees on five specific skills.  The International Society for Technology in Education (ISTE), along with The Computer Science Teachers Association (CSTA), published Computational Thinking Teacher Resources as a set of “materials to help educators understand, value, and implement computational thinking in K–12 education” (ISTE, 2014).  The materials include a section that defines CT in K-12 education, a CT progressions chart, a collection of CT lesson plans, and a narrative scenario.  The progression chart is organized by skill, providing a sample activity for each grade band to help develop each particular skill.  The progression includes nine specific skills.  Below are five that I focus on most frequently, along with an appropriate middle-school-level activity.

ISTE-identified Skill	ISTE Definition	ISTE Sample Activity for Grades 6-8
Data Analysis	Making sense of data, finding patterns, and drawing conclusions.	Produce and evaluate charts from data generated by a digital probe and describe trends, patterns, variations, and/or outliers represented in the charts.
Data Representation	Depicting and organizing data in appropriate graphs, charts, words, or images.	Plot data using different charting formats and select the most effective visual representation strategy.
Problem Decomposition	Breaking down tasks into smaller, manageable parts.	In planning the publication of a monthly newsletter, identify roles, responsibilities, timelines and resources needed to complete the project.
Abstraction	Reducing complexity to define the main idea.	After studying a period in history, identify symbols, themes, events, key people, and values that are most representative of the time period.
Algorithms and Procedures	A series of ordered steps.	Program a robot to find its way out of a maze such that any given maze, the robot could exit successfully within a specified time period.

Explain a rationale for integrating computational thinking in the classroom.

     Computational Thinking empowers students because it honors their own ideas and the knowledge they bring to a problem-solving situation.  When examining the tenets of CT, it becomes apparent that what it looks like is unique to each field; unique to each individual.  Students need time to identify their CT strengths and weaknesses.  They also need opportunities to experiment and grow.  These opportunities exceed math and computer classrooms.  “[Computational Thinking] is an important competency and influences nearly all disciplines” (Voogt, Fisser, Good, Mishra, & Yadav, 2015). 

Describe some of the pedagogical concerns of integrating computational thinking in different disciplines.

     Assumptions made about Computational Thinking prevent it from being developed in classrooms in content-areas beyond math and computer science.  The initial assumption is that it is only applicable to experiences involving computers.  This is largely due to the ignorance of the definition of CT.  Another assumption?  Some think CT is too abstract, prior to Grade 8.  This shows a clear misunderstanding of what CT is, while displaying a need for teacher professional development (PD).  A solid body of grounded, research-based knowledge about how aspects of CT map to brain development doesn’t exist (National Research Council, 2011).  Because of this, it might be difficult to get districts to invest in professional development on CT.  The push for PD will need to originate from the teachers, and this will not happen until they have a true understanding of what CT is and what it looks like in their content-area.  Once they understand that CT is unpacking problems and laying them out into manageable pieces, it will take a higher priority in the classroom.


Describe the computational skills you used while creating the two programs in Code Studio and Trinket and describe the kinds of challenges you faced while learning to code in the different platforms.

 I can provide evidence of each stage of Computational Thinking throughout my experiences in Code Studio and Trinket.  Each stage happened multiple times throughout the course of my time in each coding platform.  New problems presented themselves as my work became more in-depth, leading me through the process in a continuous manner.

Decomposition

Code Studio led me to realize I didn’t know what Blockly was, so that was my first foray into unpacking a coding problem.  Once I learned that Blockly was a nice way to create Javascript, I had a basic understanding of how Blockly functions.  Next, I had to consider how each block fit together and what that meant for the task I was trying to accomplish.  Every time I was introduced to a new block, I had to repeat the same process.  My coding adventures in Trinket revolved around Python.  I had to acclimate myself to the language of Python before I could work through any task.  When working through Holiday Tree, I wasn’t sure if I needed to start each line with ‘turtle’.  Once I had the problems unpacked (Decomposition), I began to rely on patterns.   

Pattern Recognition, Abstraction, and Algorithms

Pattern Recognition allowed me to become a more efficient coder.  In both Code Studio and Trinket, I very quickly realized I could copy-and-paste code.  This was helpful because I noticed much of the code was repetitive.  Abstraction is generalizing a pattern.  In Holiday Tree, I was able to copy-and-paste the code for one dot twenty times.  Then, I would adjust the coordinates and the color.  This is an example of an algorithm.  Algorithms are user-created steps to solve a problem.  Dr. Lambert required a minimum of 15 dots on the tree.  The steps for moving the turtle and creating the dot were the same, regardless of color, size, or location.  The cycle of Pattern Recognition, Abstraction, and Algorithm-development are interlocking and continuous, no matter the problem being solved.

Challenges

Oh, the challenges!  Once I figured out how block coding worked, I was fairly successful in Code Studio.  However, I never figured out how the function block worked.  I had to bypass it, altogether.  I was afraid my code wouldn’t work with a huge, empty function block in the work space.  I tried to drag the block over to the trash can to delete it but it wouldn’t work.  I decided to shrug my shoulders and move on with life.  Once I began working in Trinket, my true frustrations surfaced.  As an Algebra Coach, my days are spent in the coordinate plane.  I used mathematical reasoning to determine the distance between coordinates Trinket gave me for the left vertex of the triangle and the right vertex, as well as the points-of-intersection for the base of the triangle and the sides of the square.  This allowed me to find the mid-point of the triangle.  Why was this important?  I wanted my dot at the top of the tree to be centered.  All of this logic was (almost) a waste.  The coordinate plane that Trinket operates on doesn’t mirror a true coordinate plane.  This became apparent as I began to mathematically space my dots on the triangle.  The coordinates that should have worked, based on the mathematics of the base of the triangle, didn’t.  I began a series of trial-and-error coordinate entry, observing the change in the location between points as I ran the code again.  This felt inefficient, and I wished there was an option to overlay the coordinate plane so I could see it.  Again, I realized I wasn’t in control of the situation and worked with what I had.  If I could have move past trial-and-error coordinate entry, I would have felt more satisfied with the process.  

 

Resources

G. (2015, June 18). What is computational thinking? Retrieved February 26, 2017, from https://www.youtube.com/watch?time_continue=337&v=sxUJKn6TJOI

ISTE. (2014). Computational thinking: teacher resources. Retrieved February 26, 2017, from http://www.iste.org/docs/ct-documents/ct-teacher-resources_2ed-pdf.pdf?sfvrsn=2

Johnson, L., Adams Becker, S., Estrada, V., & Freeman, A. (2014). NMC horizon report > 2014 k-12 edition. Retrieved February 26, 2017, from http://www.nmc.org/publication/nmc-horizon-report-2014-k-12-edition/

National Research Council. (2011). Report of a workshop of pedagogical aspects of computational thinking. Washington, D.C.: National Academies Press. doi: https://doi.org/10.17226/13170

Voogt, J., Fisser, P., Good, J., Mishra, P., & Yadav, A. (2015). Computational thinking in compulsory education: towards an agenda for research and practice. Education and Information Technologies, 20(4), 715-728. doi:10.1007/s10639-015-9412-6