Designing Tech Enhanced Learning Experiences

We are teaching in a modern world, and teaching in a modern world constitutes the necessity to design a Technology Enhanced Learning Experience (TELE) for use in our classrooms. The problem is, most teachers hop on to the “new is better” train and don’t think about why they incorporate the technology they do within their classrooms. Simply sticking an iPad into a student’s hand will not magically make their learning any more “transformative” than a worksheet. It’s how we use the technology and for what purpose that makes the difference.

Technology is a Tool to Solve Problems

I'm partial to Roblyer's description that (2012) describes technology as "technology is us -our tools, our methods, and our own creative attempts to solve problems in our environment." Technology is a tool that students use to solve problems they are faced with. This broad view could mean that interviews are a technology tool, as are books, apps, experimental manipulatives, etc. 

The broad viewpoint of a technology is appealing to me as it allows students to apply different tools to new situations, and to have a large "toolbox" of strategies that can be applied to new situations for high levels of flexibility within their learning.


Ideal Design: Collaboration focussed and Problem Based

The ideal design for a TELE in my opinion has students focused on solving a problem that they themselves are faced with in real life, through collaboration. I'm privy to Mitch Resnick's idea of the four P's, Projects are made about their [students] passion in collaboration with peers while discovering ideas through play. Students are more engaged in projects that matter to them, and collaboration has students focussing together to learn from one another, a 21C skill necessary in the real world. 



Resnick, M. (2018). Lifelong Kindergarten. October 2018. MIT Press. 

Roblyer, M. D., & Doering, A. H. (2012). Integrating Educational Technology into Teaching. (6th Edition ed.) Boston, MA: Allyn & Bacon.

Developing Computational Thinking Skills in Students

Can Man Survive on Mars?

Developing Computational Thinking Skills in Students in TransDisciplinary Units:

An Annotated Bibliography


As a K-5 technology teacher, a large portion of my curriculum (8 weeks, 7/28 total classes, or 25% of my year) focuses on developing the computational thinking (CT) skills of my students with respect to computer programming. CT has many proposed definitions, however I am privy to Riley and Hunt’s (2014) idea that CT is the way computer scientists think and reason, as well as Garcia-Penalvo et al.’s idea of using an algorithmic, step by step approach, to solve any kind of problems (2016). As an American International School in South Korea, our school uses a standards based assessment approach and in Technology, we use the International Society for Technology Education (ISTE) standards for assessment. A power standard for ISTE is, “Computational Thinker” which requires students to:

Develop and employ strategies for understanding and solving problems in ways that leverage the power of technological methods to develop and test solutions” (“ISTE Standards for Students,” 2016).

This power standard breaks up CT to encompass four realms that relate to a student’s ability to problem solve and make decisions:

a: Formulation of problems and defining technology-assisted solutions

b: Data collection, analyzation, and representation

c: Chunking of problems to extract key information, and developing models

d: Understand automation and algorithmic thinking to create and test automated solutions (“ISTE Standards for Students,” 2016).

As CT is one of the standards that I assess, it is relevant to my practice to answer this question: How do we develop CT skills in elementary, specifically K-5, students?

It is also important to situate this question into the context of my particular school’s pedagogical and curricular framework. My school teaches in a similar style to British Columbian schools in respect to cross-curricular units, however, we call them “TransDisciplinary Units” (TDU). Teachers from the various specialist areas collaborate together on thematic units with the outcome of having students solve an authentic problem. For example, Grade 5 students this unit sought to discover, “what skills and understanding would humans need to survive on mars?” It is clear to see how science, mathematics, language arts, and various other STEM specialties could relate learning to this driving question. The development of CT skills could have great carryover to learning in Science, Mathematics, and Design & Engineering classes as CT models have been shown to be effective for learning math and science concepts (Hambrusch, Hoffmann, Korb, Haugan, & Hosking, 2009).


I started off my search examining “coding or programming AND computational thinking” (in the literature, coding, programming, and CT tend to go hand in hand), and refined my search keywords until I had less than fifty articles to sift through. I also wanted to focus on elementary students in my research, and required that the studies be empirical so as to know whether treatments were supportive of improving CT skills. In the end, these were my search parameters:

        Computational Thinking

AND Programming or Coding

AND Elementary or primary

AND students

NOT secondary

       Scholarly (Peer Reviewed) YES

       2003:2019 Publication Date

      Language: English & French


Introducing Computational Thinking to Young Learners: Practicing Computational Perspectives Through Embodiment in Mathematics Education

Woonhee Sung • Junghyun Ahn • John B. Black (2017)

The purpose of the authors’ study was to identify key factors in the design of elementary lessons that allow for the integration of CT skills into non-computing domains. Using a Pre-post mathematics test, the authors examined two K-1 classrooms that consisted of 66 underrepresented minority students. Using a randomly assigned, 2x2 factorial experiment (4 experimental groups), the authors designed a coding program using the iPad App, “Scratch Jr.”, to examine two factors:

Factor one: they embraced a constructionist, “embodied approach”, and looked at whether full body movement (embodied), role play, and hands on approaches were more powerful for learning abstract STEM subjects versus low-embody styles (hand gestures);

Factor two: they examined the importance of “computational perspective taking” (CPP), thinking like a computer scientist. High CPP had students programming a surrogate (machine or character) to solve the problem, while low CPP had students simply walk through the code themselves.

The authors found that the level of embodiment used had a statistically significant positive impact on student mathematics scores, as did high CPP. The Full embodied with CPP significantly outperformed the low-embody and no CPP group as well. The authors also found that high CPP instruction increased the accuracy of student programming skills.

The authors took significant rigor in randomly assigning their control, as with their experimental design. However, they introduced a major confounding variable in the fact that they themselves taught the four different lessons, and may have been influenced to be more enthusiastic about the high embodied/high CPP group than when they taught the low-embodied/low-CPP group, resulting in lower student achievement. If they had trained other teachers to teach the curriculum without knowing the goal of the study, the reliability of their findings could have been improved.

As the authors showed, CT skills and programming are important to the mathematics and science classrooms as programming also teaches planning abilities and the problem-solving process (Wing, 2006). This is evident by the statistically significant increases in the various groups, though as mentioned above, this should be viewed hesitantly as instructor bias was almost certainly present to influence the data.

Computational Thinking Equity in Elementary Classrooms: What Third-Grade Students Know and Can Do

Yune Tran (2019)

Tran’s study was concerned with two research questions (2019, p. 4):

What changes, if any, are evident in third-grade students learning of foundational CS concepts and CT over 10 weeks of coding lessons?

How can 10 weeks of coding lessons influence third-grade students’ CT in and out of school?

To answer these questions, Tran exposed over 200 elementary students to a 10-week, puzzle based coding curriculum and examined a pre-post test assessment on CT and computer science (CS) skills. There was no control group as this was the first intervention of its kind in Oregon, USA, and the 13 third grade classrooms were located in suburban and rural areas. was an affiliate of this study and was present in the decision making process of classrooms chosen, a conflict of interest in this study as the curriculum used was’s.

Tran examined the students using Kolb’s constructivist style experiential framework of Feeling > Watching > Thinking > Doing (1984,1999).

Tran found that after her intervention, there was a significant improvement in CT skills based on her self-created pre-post test of CT and CS skills. Student motivation and positive outlook on coding was also significantly improved post test, as is evident from the interview findings; Lastly, students noted in interviews that their teamwork, cooperation, and resiliency skills improved from the partner coding challenges.

A large limitation of Tran’s study is the measurement of CT. Tran, in collaboration with her university, used a self created model for measuring pre-post test scores with an internal reliability of .63 and .61 on pre-post tests respectively (and she notes this is a problem). With low internal reliability, the findings should be viewed hesitantly.

As well, since CT has not been solididly defined in the literature with many competing opinions, measuring CT tends to be done on a program by program basis, and the aptitude a student possesses within this program. As such, having an in-depth review of CT skills is difficult with changing definitions from scholar to scholar. This muddied waters means that the improvements in CT skills should be taken with caution.

That being said, the improvements to positive attitudes towards CT programs, problem-solving skills, and interest in STEM fields seems well supported based on interview responses. Whether this increase will survive in the future for these students is uncertain.

As noted by Tran, CT development initiatives have been largely in secondary schools with little emphasis on elementary CT skill development, in the USA at least. However, we know that earlier engagement with STEM concepts increases student motivation and initiative to learn STEM skills (Tran Y., 2019). The importance of early CT skills development is likely to further CT further down a student’s educational journey.

A Study of Primary School Students' Interest, Collaboration Attitude, and Programming Empowerment in Computational Thinking Education

Siu-Cheung Konga • Ming Ming Chiub • Ming Lai (2018)

Building upon Seymour Papert’s conception of CT and its proposed ability to empower students, the authors of this study sought to define and measure “programming empowerment” to fill the gap in measurement of CT skills. Operationally, they define CT similar to the initial proposed definition in this paper, and they defined programming empowerment to compose of four components: meaningfulness, impact, creative self-efficacy, and programming self-efficacy (p. 1). Though part of a larger, unpublished as of this writing, study on the promotion of CT skills in elementary schools, this specific portion of the study sought to answer if greater interest in computers, and more positive outlooks on collaboration, led to greater programming empowerment in students.

The 30m likert-scale survey was completed online with 287 Gr 4-6 students. The survey was satisfactory in its rigorous analysis, as well as found to be reliable to measure the constructs designed to measure.

Researchers found that their data supported their initial hypothesis that a student with greater interest in programming also viewed programming as more meaningful, impactful, and had greater creative self-efficacy and programming self-efficacy. However, more positive attitudes towards collaboration suggested higher creative self-efficacy, but not greater programming self-efficacy. The data also supported the hypothesis that interest was critical to programming empowerment, and that older students viewed programming training as less meaningful, and that boys showed more interest in programming that girls did.

The minor flaw in this study is that the instrument used is only mentioned to be validated by experts, but what this means or what rigour was used in the study of the reliability of this tool was not discussed. The authors did include the full measurement tool for examination.


Perhaps the most frustrating issue with discovering how to develop CT skills in students is that there is no clear, well defined definition of CT in the literature that has been agreed upon. The studies examined in this annotation seem to be privy to the 3 systems approach of CT that defined CT as both algorithmic thinking skills, using technology and automation to solve problems, and perceiving a situation like a computer scientist would; so it is good to see a resemblance of scholarly consistency when defining CT. Having a more consistent running definition of CT, or at least having the river of scholars beginning to flow in the same direction, will certainly help to aide future research.

There also needs to be a more reliable and valid measurement tool for measuring CT skills, rather than the current method of needing to extrapolate CT skill development outside of programming performance within a specific coding program. However, this may also be a limitation of the CT concept itself in that CT requires a computer programming software in order to fully understand the notion of CT in the first place. This will need to be further discovered.

Lastly, it is useful to see that CT skills can be developed outside of the computing environment like the Tran study suggested, and that CT skills can support further mathematics and science learning through generalized problem-solving skills. Having scientific data to support the divergent capabilities of programming knowledge will provide further support for the inclusion of programming courses within elementary curricula.


D.D Riley, K.A. Hunt, (2014). Computational thinking for the modern problem solver. CRC Press, Boca Raton, FL, USA (2014)

F.J. García-Peñalvo, D. Reimann, M. Tuul, A. Rees, I. Jormanainen. “An overview of the most relevant literature on coding and computational thinking with emphasis on the relevant issues for teachers”. Belgium TACCLE 3 Consortium (2016)

García-Peñalvo, F. J., & Mendes, A. J. (2018). Exploring the computational thinking effects in pre-university education. Computers in Human Behavior, 80, 407–411.

ISTE Standards for Students. (2016). Retrieved from:

Kolb, D. (1984). Experiential learning: Experience as the source of learning and development. Englewood Cliffs, NJ: Prentice Hall.

Kolb, D. (1999). The Kolb Learning Style Inventory, Version 3. Boston, MA: Hay Group.

Kong, S.-C. sckong@eduhk. h., Chiu, M. M. mingchiu@eduhk. h., & Lai, M. mlai@eduhk. h. (2018). A study of primary school students’ interest, collaboration attitude, and programming empowerment in computational thinking education. Computers & Education, 127, 178–189.

Tran, Y. ytran@georgefox. ed. (2019). Computational Thinking Equity in Elementary Classrooms: What Third-Grade Students Know and Can Do. Journal of Educational Computing Research, 57(1), 3–31.

S. Hambrusch, C. Hoffmann, J.T. Korb, M. Haugan, A.L.Hosking. “A multidisciplinary approach towards computational thinking for science majors”. Proceedings of the 40th ACM technical symposium on computer science education, SIGCSE '09, March 4-7, 2009, Chattanooga, TN USA, ACM, New York, NY, USA (2009), pp. 183-187

Sung, W. W. columbia. ed., Ahn, J. J. columbia. ed., & Black, J. B. columbia. ed. (2017). Introducing Computational Thinking to Young Learners: Practicing Computational Perspectives Through Embodiment in Mathematics Education. Technology, Knowledge & Learning, 22(3), 443–463.

Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33–35. doi:10.1145/ 1118178.1118215.

ETEC 533: Interview with a Mathematics Teacher Veteran

Below are several excerpts from an interview that I had with a colleague, “M.”. Our conversation concerns the benefits and drawbacks of technology inside of a Middle School mathematics classroom. Below, M’s words are italicized while my own are in regular font. M.’s name has been written as a changed initial for privacy reasons.

About M.

M. has been a teacher for 12 years and previously worked as an engineer in a municipal role, designing builds for bridges and roads. He has a passion for teaching students applied mathematics, and has taught in Kuwait and South Korea during his teaching career. Presently, he is a Middle School Mathematics teacher, as well as an instructional coach for teachers K-12 in our school.

Real World Applicability of Mathematics

“For math and using tech, the simplest tech is the best and im trying to get my students to be ready for the real world; because my background is in engineering. To your question specifically... most applicable technology is excel. Just getting them to use the program...getting the students to be comfortable to be using excel in a practical application.

Working in an engineering firm, the type of program that we basically excel or a spreadsheet on i try to get student comfortable with area and volume...and make the worksheet look like a form... and get them to use excel in real life because that's the one that they;ll use the most often as engineers.

This was surprising to me, that M. believed the best technology that he has used in his classroom was simply using an excel program. However, the above transcript points out a few important things.

Many teachers often have not had real world experience in their field before they go in and teach the content. M., having been a city engineer before, has knowledge of what content he can include in his classes that will have the most carry-over to the real world. This means that he can look past much of the glamour of new technologies and design lessons that would transfer well to the real world of engineering for his students.

I realize that it is not possible for all teachers to be able to have had real world experience in their field, and in this case, having a course on real world applicability of technology in various careers, watching recorded interviews, or speaking with employees from a variety of careers would help teachers assess what technologies would be more applicable for use in the classroom.  

With technology, there is a growing notion that “newer is better” as the technology is the newest, most flashy piece of information on the market and this gets kids engaged, and teachers, as it looks cool. However, teachers need to take a step back and think pedagogically why we include the technology that we do in a classroom from the basis of an entire curricula. Excel, working off real world experience, seems to be an incredibly robust tool to use in a math classroom as it is a piece of software that students, should they decide to become engineers, will use every day in their lives. Not only do teachers need to stay up to date with technology, they must also wrestle with what technology is most applicable as well as fits in with the rest of their curriculum as well.

The Four Uses of Technology in Classrooms

One of the more interesting offshoots of our conversation was M’s notions of various uses of technology in the Classroom, and how he categorized the use of technology in his Math classroom.

1.Student interacting with technology

This is the Direct Application use of technology.

The most obvious category is students interacting with digital technology in the classroom, using applications to solve problems, and working with digital technology throughout various projects.


2. Formal & Informal assessments

“Here you can use [technology] as an exit ticket, informal assessment, formative assessment; You know, let’s check in and see [how you are doing]... let’s practice what we just talked about it.”

Using technology as a “quick and dirty” exit slip to check in on understanding of a concept for the lesson, was a low pressure way for students to engage and get involved in the content. Rather than using it as a formal assessment, it allows a quick check in with students to see if they understood the lesson content. As most digital forms can mark automatically, it can serve as a quick and efficient formative assessment option for teachers.

Using tech as a formal assessment method has been difficult for M. so as to not let students open another program in order to cheat on the exam. NWEA Lockdown browser may be a good tool for his formal assessments with technology as it locks students into an application and a single website/tab for the completion of a formalized test.



“Not student[s] engaged [with technology], but presentation style. Using an ipad for drawing a picture and projecting that up on the board... there are a lot of different ways to present material [with technology]”

When designing curriculum, a teacher needs to decide what concepts should receive priority, and with this, what concepts can be taught in a more inquiry fashion versus a “typical” lecture style format. Depending on whatever structure chosen for the lesson content, technology can assist with the presentation of information. Obviously, apps like powerpoint, keynote, videos, and even video interviews come to mind when thinking about various presentation styles. However, technology can also assist with showing off one’s learning on an individualized basis, such as 3D printed models, laser cut objects, or even an interactive digital textbook.


4.Backend Assessment & Grading

“[This is] the backend students don't see. Putting together ways that we can directly input in grades and calculate grades using spreadsheets.”

The last use of technology in classrooms was on the backend where teachers can more efficiently calculate grades (or standards tracking if grades are not used). Spreadsheet programs allow for instant calculation, as well as visual representations of data that would take far longer to complete by hand. This gives a teacher more time to be able to focus on other tasks at hand in their teaching profession, than needing to spend time calculating marks.

ETEC 524: Course Goals & "Flight Path"

Below is a course goal outline for which I hoped to achieve during the ETEC 524 course.

This is my 5th-7th course in the MET program. Recently, I’ve become the iPad program coordinator for our 1:1 device classrooms in grades 3-5. Simultaneously, I’m also the elementary technology teacher for grades K-5, and a quasi tech coach for my colleagues in the elementary school. There’s a lot happening in my life professionally, especially in terms of oversight with technology adoption in multiple classrooms, so this is the perfect time to take ETEC 524.

I started the MET program wanting to both grow professionally with my long term goal of tech administration, and also to better incorporate technology in my classrooms (and cross-curricularly between classes) at my school. After becoming the iPad coordinator, I have since tacked on even more questions to research and discover;

  • How can I best support teachers in a 1:1 device classroom to use their devices effectively? I’ll need to learn best practices for implementing 1:1 technology, best theories, and get a better understanding of my own personal conceptions of learning.

  • What makes a 1:1 device classroom more powerful to student learning than simply having a device but not revamping the current curriculum? Building off of SAMR theory, how do we get to Modification and Redefinition, and get teachers on board with these ideas as well?

  • What does connectivism have to do with cross-curricular units and inquiry (Roblyer, M.D., Doering, A., 2016)? (Our school is heavily based on cross-curricular units like those in BC, however we call them TDU’s). Is this part of my school’s pedagogy, and how can we blend the two together?

Weeks in ETEC 524 that I see being most beneficial for learning to create these outcomes:

  • This past week’s reading into SAMR has reminded me of the theory I have come across more, but this time introduced me to its author in person (very cool!) (Puentedura, R, 2010).

  • Week 3’s first 2 readings, looking into where we teach has implications for helping my colleagues discover ways to connect learning between classrooms and different classroom teachers for creating TDU’s

  • Week 4’s readings, specifically Ciampa’s, on mobile technology will hopefully give me a better understanding of increasing student motivation for learning (something I had not considered to this point).

  • While week 7 is not fully applicable to my goals, having a better understanding of theory in learning online should benefit my own practice in researching online.

  • The culminating project, creating a unit of learning, will allow me to continue to practice developing one of my TDU’s with another grade level team. There were some projects last year that were stand alone islands that I can already start to see some new connections from my readings already in order to better align them with other classes’ projects for better connecting student learning.


Anderson, T. (2008a). Teaching in an online learning context. In Anderson, T. & Elloumi, F. Theory and practice of online learning (pp. 343-365). Athabasca University. Retrieved from Theory_and_Practice_of_Online_Learning.pdf

Anderson, T. (2008b). Towards a theory of online learning. In T. Anderson & F. Elloumi (Eds.), Theory and practice of online learning (pp. 45-74). Edmonton AB: Athabasca University. Retrieved from

Burnett, C. (2016) Being together in classrooms at the interface of the physical and virtual: Implications for collaboration in on/off-screen sites. Learning, Media and Technology, 41(4), 566-589. [LOCR]

Benade, L. (2017). Is the classroom obsolete in the twenty-first century? Educational Philosophy and Theory, 49(8), 796-807. [LOCR]

Puentedura, R. (2010). The journey through the SAMR model. IPad Educators: Sharing Best Practice in the use of Mobile Technology. Retrieved from

Roblyer, M.D. & Doering, A. (2016; 2012). Integrating educational technology into teaching, (6th or 7thEd.). Upper Saddle River, New Jersey: Prentice Hall.