Sharpen your English Language Teaching Skills with Computational Thinking

“If one plays a game, one needs rules; otherwise, there is no fun.” If these words of the British American poet W. H. Auden are interpreted in the context of language, they suggest that every language is governed by certain conventions and principles. Its linguistic rulebook must be understood and followed to develop the competence necessary for clear, accurate, and effective communication, whether in poetry or prose. In our part of the world, one of the most familiar books of the English language is undoubtedly Wren & Martin, which has guided generations of learners in understanding the structural framework of English grammar and composition.

Since 1935, Wren & Martin has, encouraged skills that closely resemble what we today have rechristened as Computational Thinking. In simple terms, it has trained learners to follow instructions, apply logical reasoning, recognise patterns, and solve linguistic problems systematically to understand the nuances of language.

Therefore, when Jeannette M. Wing, a professor of Computer Science, proposed in 2006 that Computational Thinking is a fundamental skill that should be learned by everyone, she drew attention to a way of thinking, rather knowledge sharing that could extend beyond the boundaries of computer science and enrich learning in many other disciplines. It is vitally important to invalidate the misconception that Computational Thinking in a language class amounts to coding or software development.

When the framework of Computational Thinking is applied to linguistics, it defines certain areas where language learning becomes systematised and easy to understand. The four main domains of Computational Thinking which find place in the canvas of language learning are as follows:

For ease of instruction and explanation, when any task is broken into manageable parts, that is decomposition. The variant word for this exercise is chunking which can be applied to breaking long prose, story, sentences or winding poems into smaller parts to facilitate understanding. It can be implemented in grammar lessons too; when teaching types of sentences, parsing - the process of breaking down a sentence into nouns, verbs, and phrases – can help students understand the structure of sentences. The aim is to simplify the topics into small components that would make the academic transaction uncomplicated. 

When Mark Twain said, “I know grammar by ear only, not by note, not by the rules.” He voiced the opinion of language purists who can identify the flaws in language by just listening to the spoken word. It can be the grammatical error of double past tense or redundancy error when the second form of verb is used with did or wrong use of reflexive pronouns. Pattern recognition is a bigger playfield for language teachers as they can identify mistakes in spellings, punctuation, capitalisation, jumps in tenses, incoherent sentences, wrong subject–verb agreement, misuse of words and more. In poetry this can help students follow the pattern of stanzas, rhyme schemes and the rhythmic pattern of stressed and unstressed syllables in verses.

As seen in inductive method of teaching, the focus is moved from specific to a general principle or finding. This forms the core of abstraction which in simple terms helps students turn a complicated idea into less complex scenario by sculpting away the unnecessary details and focusing on broader or relevant information. This can be seen in sessions when the task allotted to students is to figure out the central idea of a poem or interpreting the theme of a story concisely. The learner will develop the skill of juxtaposing literal meanings with symbolic representations. For instance, in “Keeping Quiet” when Pablo Neruda writes,

“…those who prepare green wars,
wars with gas, wars with fire,
victories with no survivors,
would put on clean clothes…”

Clean clothes signify a fresh peaceful beginning, not just washed, spotless clothes.

A simple application of algorithm thinking happens when the task involves listing out the logical order of events or tasks. It can be as simple as in the case of process writing when the assignment could be to write the recipe of how to bake a cake. The right sequencing of steps or clear orders to finish a task or make a flow chart forms the core of algorithmic thinking. It has vast application in a language classroom; be it writing a short story, where students are taught how to frame a story using the Freytag’s Pyramid by creating a sensible setting, conflict, climax, and resolution. The skill is also helpful in making students follow the systematic arrangement of paragraphs when writing reports, formal letters or articles, where organizing ideas coherently from introduction to the body and a conclusion is a requisite.

Thus, we see how the practical application of Computational Thinking in a language classroom provides a pedagogical advancement to teachers. This is one more path of reaching the goal of making teaching more effective and systematic.