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Meaning Making in Computer Education

02 Sep

One of the difficulties in looking at the knowledge practices of teachers of middle and high school computing is the diverse nature of educational practices around the world. In some contexts the curriculum resembles Computer Science at a tertiary level, with an emphasis on computer programming and the theory of hardware, software and networking. In other contexts, however, the emphasis is on computing applications. In South Africa, for example, students can take Information Technology as a matriculation subject, in which programming is studied, or Computer Applications Technology, with an emphasis on Office applications. At middle school levels the emphasis is often on basic computer literacy. Coding and robotics are, however, often taught alongside basic computer literacy and information literacy.

Waite, et al (2019) have argued that Legitimation Code Theory (LCT), in particular the idea that effective knowledge building practices involve the formation of semantic waves, provides a framework for assessing the effectiveness of practices in the teaching of computing by providing a common language for describing diverse practices. I have described Semantic Wave Theory before in this blog, But here is a brief summary.

Karl Maton (2014) has described semantic waves as how teachers try to bridge the gap between high stakes reading  and high stakes writing where ideas are highly abstract and context independent (Weak Semantic Gravity) and highly complex and condensed (Strong Semantic Density). In the classroom these highly abstract and complex ideas are introduced in the form of texts. Students are expected to reproduce these ideas in their own words in the form of essays and examination answers. In order to do this teachers need to help students by giving concepts greater context (Strong Semantic Gravity) and make them simpler (Weak Semantic Density). They do this by using examples, metaphors and personal experience. If you map the changes in semantic gravity and density over time you can describe waves. The ability to make links between abstraction and the concrete, between theory and practice, complex and simple ideas is what makes for effective teaching and learning.

Waite, et al (2019) show how a semantic analysis of an unplugged computer programming task describes just such semantic waves and makes for a successful lesson plan. They also suggest that using semantic waves to analyse lesson plans, and actual lessons, is a way of assessing the effectiveness of lessons teaching computer programming of different kinds. Many teachers use online coding platforms, like Codecademy or Code Combat. In this article I would like to look at a semantic wave analysis of a code combat course on web development to see what it reveals about its strengths and weaknesses as a pedagogical platform. Code Combat uses as its basic structure a series of courses covering a computer science syllabus teaching JavaScript or Python programming and some HTML and CSS. Each course is divided into a series of levels, and each level introduces key concepts such as loops, conditional statements and so on, using quests and tasks performed by an avatar. Students enter the code in a command line interface and can run to test success.The platform provides hints and text completion prompts to help scaffold activities.

Students generally enjoy the platform, and take pleasure in grappling with problems and succeeding at each task. I use it in my grade 8 & 9 computer skills classes. In this analysis I looked at the 13 levels that make up the Web Development 1 course, introducing HTML tags and CSS properties. I looked at Semantic Gravity alone. SG- (Weak Semantic Gravity) representing highly abstract ideas and SG+ (Strong Semantic Gravity) representing highly concrete ideas. I used three levels of degree to indicate strength and weakness (SG— to SG +++)

I used the following translation device for rough coding the level of semantic gravity, and looked at the instructions in each level. The purpose of a translation device is to help translate the theory into what it looks like in practice. What does Weak Semantic Gravity look like when using HTML, what does Strong Semantic Gravity look like?

SG – – – Over-arching concepts Tags used to mark-up text
SG – – Coding Concepts Tags do different things eg <h1> regulates size of a heading
SG – Properties of concepts Tags have properties eg <img> has source, alignment, width
SG + Examples of concepts students must decide which tag to enter
SG + + Examples of properties Student must edit a property eg <img src=”” align=”left”> change to right align
SG + + + Data entry Typing in text

The coding of the thirteen levels was done using only the text used in the platform. I did not look at the graphics. I would argue that the graphics display tends to scaffold all activities by strengthening semantic gravity and helping students visualise what they are coding. The semantic waves formed over time looked as follows:

What we can see is a non-continuous wave which loosely describes the movement between abstract and concrete. Each unit followed a pattern of introducing a particular concept and giving students a chance to practice enacting it. The next level would then introduce a new concept and so on. In some levels students are able to partially practice their developing understanding of the concepts by making choices of which tags to use rather than merely practising enacting the one explained. The movement between weak and strong semantic gravity has been described as a down escalator, and is common in teaching practice. Teachers are generally good at explaining concepts so that students understand them, less common in classroom practice and less common here is the full movement of the wave in such a way that students take concrete examples and are able to express the underlying concepts and display their own understanding effectively. In programming terms this would translate into being able to use concepts learned in novel situations to develop unique solutions, in other words move from a concrete problem to be solved to a conceptual enactment of that by designing an algorithm or coding.

What the semantic wave analysis seems to indicate is that the units in this course are doing a good job in explaining the programming concepts, but not good enough a job in giving students a chance to explore and display their understanding in new contexts. As a teacher, I have to say that this is what struck me immediately. The platform could do some things better than I could. It could allow students to work at their own pace and gave instant feedback, and was certainly more engaging with graphics and its game-like interface, but was not able to set more open-ended tasks, or give students a chance to explain their own understanding of the concepts. The course ends with a “design your own poster” exercise which potentially does this, but each level lacks a degree of this full movement through the semantic wave.

This weakness appears to be hard-coded in, and would require teachers using the platform to mediate as a way of creating fuller semantic waves. Given that students are working at their own pace, my own solution was to use mentors in every class. It was the job of the mentor, anyone who had already completed the course, to help peers who were struggling to complete levels by explaining what needed doing. The mentors at least were then consolidating their knowledge and understanding by explaining it to others, and mentees were benefiting from having the problem re-phrased or re-contextualized.

I would argue that semantic wave analyses like this one would help inform better instructional design decisions. It might appear as if I am being critical of Code Combat, but I believe that other platforms of a similar kind suffer the same weaknesses. This platform, in fact is better than most in using Constructivist learning principles by asking students to design their own solutions, but more could clearly be done to create full semantic waving.

Bibliography

Maton, Karl. (2014). A TALL order?: Legitimation Code Theory for academic language and learning. Journal of Academic Language and Learning. 8. 34-48.

Waite, J., Maton, K., Curzon, P., & Tuttiett, L. (2019). Unplugged Computing and Semantic Waves: Analysing Crazy Characters. Proceedings of UKICER2019 Conference (United Kingdom and Ireland Computing Education Research).

 

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