As a learner, participation in NGL was useful to me


As a learner, participation in NGL was useful to me in that previous learning behaviours were made more explicit and I was encouraged to trial new learning behaviours. My learning goal was to learn how to teach my nephews aged two and five to code in the near future. As Van Jones (# Yes We Code, 2015) mentioned the technology sector (in the US) will have 1 million jobs available in eight years. As such I felt that introducing them to coding skills at a young age would be beneficial, especially as parents today regard coding as the “new literacy” (American Library Association, 2016).

In practice my plan for my networked learning journey, expanded to include the Seek Sense Share framework (Jones, 2017a) and Socol’s (2009) Toolbelt Theory, in addition to the CLEM model (Jones, 2017b). I sought information by using the CLEM model to scope environments and literature that dealt with teaching kids to code. Through Google, I found the community included people who ran blog sites, Facebook groups, the Khan Academy and Scratch, and those who answered questions on Reddit and uploaded YouTube infomercials. I also evaluated those within my knowledge network and identified Lauren, as a potential node. For my learning purposes the best communities were found on Facebook, Reddit and Scratch – not EDU8117. This was because I suspected that questions posted to the former communities would be responded to more quickly by people who shared my same interest. This can be explained by Muther (2013) and Thompson (2015) who claim that highly connected people have high expectations for instant information gratification. I noticed for example that responses to forum posts among EDU 8117 cohorts took up to a week to answer. However, responses to questions posted from people in Scratch gained multiple views and answers within a day (please see Figure 1). Consequently as a result of this evaluation, these people and websites became a part of my tool belt as did knowledge gained from commencing a few Code Academy classes.


Figure 1: Help with Scripts (Gained from Scratch, 2017)

In starting to learn about my topic I also evaluated the content found in websites, and settled on four websites, the Educational AppStore, Hour of Code, Hour of Code – Disney and the Scratch websites. However, further exploration made me conclude that constructivist learning was required to supplement the TPACK model I originally settled on where regarding my nephews. I also concluded that even my oldest nephew was still too young to learn coding. For small children, programming content needs to be scaffolded on other basic skills, as advocated for by teachers (Sentance & Csizmadia, 2017). A quick analysis showed that basic instruction in coding, even if non computer based, required an attention span of 10 minutes, the ability to carry out sequential instructions and the maturity to understand concepts such as loops in order to be effective. In the UK, lessons in coding are started at the age of five. In Australia, this begins at eight (Vivian, Falkner, & Szabo, 2014). Further, analysis showed that young children who are able to use iPads, need to have also mastered basic reading skills to manipulate drag and drop coding programs. This is confirmed by many teachers who state a lack of literacy “is a stumbling block when trying to introduce variables and functions etc” (Sentance & Csizmadia, 2017, p. 482).

Also, an analysis of EDU8117 student behaviours during this course bears mentioning. Only one student asked for help with their learning task. Futher only one other student, myself, offered solutions to her question. As a result, this behaviour could reflect the fact that our individual learning tasks were not meaningful enough for us to participate in (McLoughlin and Lee). This is understandable considering that the practice of NGL in a class situation was probably limited by the normal demands of reading course material (Willging & Johnson, 2009) and having to attend to family and work commitments. However, the situation changed when discussing NGL. A number of posts were placed on blog sites with futher comments offered, thus indicating that meaningful student centred learning was occuring (Curtin University of Technology, 2017). Thus, it appears that students began to demonstrate mature learning behaviours as seen by their willingness to focus on interesting aspects of the course, think and independently further their learning (Vivian et. al, 2014).

So as a result of these experiences, even though I have not learned to code yet, NGL has formalised my information gathering processes which are ultimately required for problem solving. NGL’s reliance on seeking, defining and accessing knowledge networks results in connectivist learning. This formalisation lead to stepping out of comfort zones to seek and evaluate new products. As a person who is learning a task on behalf of someone else however, I find that the knowledge gained needs to be fused with pedagogical frameworks in order for success to occur. I further understand that effective networks can only exist when the content being addressed is meaningful to all concerned.


# Yes We Code. (2015). Van Jones on teaching 100,000 low-income kids to code. Retrieved from

(2016, December 8). Libraries ready to code. [Video file]. Retrieved from

Curtin University of Technology. (2017). Student centred learning.  Retrieved September 5, 2017 from

Jones, D. (2017a). Week 2 – Conceptions of network learning. Retrieved  from

Jones, D. (2017b). Week 4 – CLEM and community. Retrieved from

Muther, C. (2013, February 2). Instant gratification is making us perpetually impatient. Boston Globe. Retrieved from

Scratch. (2017). Help with Scripts. Retrieved September 14, 2017 from

Sentance, S., & Csizmadia, A. (2017). Computing in the curriculum: Challenges and strategies from a teacher’s perspective. Education and Information Technologies, 22(2), 469. doi: 10.1007/s10639-016-9482-0.

Socol, I. D. (July 20 2017). The toolbelt [Powerpoint presentation]. Michigan State University, Retrieved July 23, 2017 from

Thompson, P. (2015). How digital native learners describe themselves. Education and Information Technologies, 20(3), 467-484. doi: 10.1007/s10639-013-9295-3.

Vivian, R., Falkner, K., & Szabo, C. (2014). Can everybody learn to code? Computer science community perceptions about learning the fundamentals of programming. In Proceedings of the 14th Koli Calling International Conference on computing education research, Koli, Finland. Retrieved from

Willging, P. A., & Johnson, S. D. (2009). Factors that influence students’ decision to dropout of online courses. Journal of Asynchronous Learning Networks, 13(3), 115. Retrieved from



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