Learning Taxonomy in SQL Teaching and Learning

Shneiderman [7] highlighted five tasks that one can apply to provide a query to retrieve information for the database. The following are the five tasks:

1. Learning the syntax and semantics of the function specification. He argues that a typical goal at this stage is to reduce the time of learning.

2. Composition of the syntax required to perform the required function. Composition includes writing a query or formulating a natural language query.

3. Comprehension of function syntax composed by someone else. It is often necessary to read syntax composed by others for learning or other

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purposes. Easily composed syntax may not be easy to comprehend. Comprehension is often a component of others.

4. Debugging of syntax or semantics written by others or by the users. The main purpose of the debugging is to correct errors. Shneiderman [7] said that debugging requires comprehension and composition ability but includes other complex cognitive skills. He suggested that query language debugging will require novel debugging strategies. The central problem will be to provide users with feedback to help them determine whether the semantics of the function they invoke correspond with their intentions.

5. Modification of a query written by oneself or others. Existing database queries will often be the basis of new queries. This task requires composition and comprehension skills as well.

Shneiderman’s [7] focus was on the human factors aspects of database interactions and how to facilitate the use of query language. However, in this research, the focus is on how to facilitate the learning of SQL. Looking at the five tasks mentioned, it was possible to relate them to learning theory and organize them into a level of learning taxonomy (see Figure 2.4 a. and Figure 2.4 b).

Figure 2.4a: Bloom Taxonomy Figure 2.4 b: Shneiderman five tasks Figure ‎2.4: Shneiderman Five Tasks and The Related Task in Learning Taxonomy

Renaud et al. [53], on the other hand, examined theories of learning such as those of Bloom and Gorman and noted that the reason students sometimes have

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difficulty applying database skills, such as SQL, is that they do not master the required knowledge, or understand the basic concepts correctly. The authors argue that it is thus very important to convey core knowledge first so that students can construct skills (such as SQL) up on top of that core knowledge [53]. They proposed a pedagogical pattern called “Teaching SQL based on Gorman’s Taxonomy”.

Renaud’s [53] approach might be criticized in one aspect, that the suggested waterfall approach in delivering the course material might incorporate possibility of feeling bored by a lengthy period of learning concepts before the application of these concepts. In addition, they need to practice the learnt concepts within the skills-oriented teaching.

Figure 2.5 a: Bloom Taxonomy as a Spiral Taxonomy [54] (left),

Figure 2.5 b: Learning Through Knowledge Construction (right)

Figure ‎2.5: Spiral Model for Learning through Construction

Pollock et al. [55] describe an approach based on cognitive principles that teaches students information in isolated portions when teaching all concepts together would make it too complex to understand in its entirety. This approach

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is often used for material, which is complex, and they argue that one can reduce the complexity and cognitive load by teaching concepts in an isolated fashion with maximum interactivity. This approach appears to be particularly suitable for SQL teaching since students need to have internalised a number of inter- related concepts in order to embark on and master SQL skills.

One can argue that, it is possible to enhance the proposed approach by Renaud

et al.[53] through changing it to a spiral taxonomy as suggested by Fuller et al.

[54] arguing that learning is knowledge construction. Hence, learning should not only go directly from bottom to top (what to why), but by seeing each round as thoroughly learning some new pieces of information, which is then used as a basis for the next round topic (see Figure 2.5, right). For example, teaching part of SQL knowledge, then examining the learner‘s understanding of the taught concepts, the student learns how to apply it for different concepts. Later on, learner’s knowledge can be evaluated through involvement in a bigger scenario where many concepts need to be applied.

This research aims to provide a comprehensive emphasis on the practical part of learning taxonomy that is done through problem solving. From the personal observation, students consume a lot of unnecessary time and effort solving each query problem depending on its complexity or occasionally not solving it at all. Thus, it is crucial to understand why students are consuming unnecessarily more time and effort, and why they sometimes give up or end up solving it incorrectly. Are there any deficiencies in transferring the knowledge or skills in one of these levels in the taxonomy, or is it a lack in the problem solving strategy knowledge? These questions might be answered by relating them to cognitive psychology literature. The next section discusses the cognitive aspects in SQL teaching and learning. It presents the different research and models in cognitive activities in solving SQL queries.

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2.3 How Students Learn: A Cognitive Theory in Learning