What motivates parents to choose a particular school?

To answer this question, 22 parents from Melbourne and regional Victoria, Australia, were interviewed. These parents came from a broad range of middle socio-economic backgrounds.  Parents were sourced through school newsletters or advertisements in local community newspapers. The diversity of this group of parents is provided in the table below.

Demographics

Table 1.Demographics of parents interviewed.

Parents where asked open questions at the beginning of each interview about their children’s education and the school which they attend. A set of specific questions were then asked about when they started to decide on a school, what they thought were positive and negative characteristics of a school, the importance of teaching and academic performance, the culture of the school, and proximity of the school.  Questions were also asked to understand how the parents arrived at a joint decision, whether their children participated in the decision making, and how they went about collecting information in order to choose or evaluate a school.

One part of the interview analysis involved tabulating a list of preferences parents indicated as reasons for choosing, or not choosing, a particular school.  Each interview was then evaluated to generate a list of preferences that were salient for each parent in their school choice decision.

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Word cloud of school choice interviews of regionally (non-metro) based parents

Out of curiosity, below is a word cloud of the 4 school choice interviews of parents from regional Victoria, Australia.

Regional_Lemmed

It will be interesting to see how word cloud visualizations compare to more sophisticated linguistic analysis techniques.

Latent Semantic Analysis

An everyday application of Latent Semantic Analysis (LSA) is the Google search engine where words that are semantically/contextually similar are also returned in the search query.  Type in “run” and the search will also pick up “ran”, “runs” and “running”. LSA allows natural language processing of vast collections of data, such as web pages, to provide information about how similar words are related to each other in (semantic) context by converting words into vectors (vectorial semantics) and applying singular value decomposition to the matrix.  In this way, the data itself is used to create a ‘latent semantic dictionary/thesaurus’ which reflects the context of the documents being analysed.

LSA captures the contextual relationships between text documents and word meanings.  Taking into account the context in which words are used is important for linguistic analysis.  The contextual meaning of words change over time and across social groups.  An example of the importance of context is how the meaning of ‘terrific’ changes over time.  Latent semantic analysis of documents from the second half of the 19th century would show ‘terrific’ as similar to ‘horror’. While documents from the second half of the 20th century would show ‘horror’ as now being the opposite of ‘terrific’.

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