Application of data mining techniques to identify significant patterns in the Grade 12 results of the Free State Department of Education

[摘要] ENGLISH SUMMARY : The Free State Department of Education (FSDoE) has a mandate to ensure that examinations and assessment processes are conducted according to the set out legislations and that they produce expected results. It has become common for Grade 12 results to be challenged by interested parties within and outside the government on their credibility. It is, therefore, the responsibility of the Free State Department of Education to ensure that the input data which represent raw marks obtained by the learners give a true reflection of what individual learners have achieved during a particular assessment period.This study seeks to explore the role that data mining (DM) can play in establishing credibility of the Grade 12 data in the FSDoE. The study makes use of open-source data mining software called WEKA. The software is applied on the 2010-2013 Grade 12 data results in the Free State. For this study, two algorithms, j48, and simpleKMeans algorithms, have been selected for classification and clustering respectively. In line with the universally accepted Cross Industry Standard Process for Data Mining (CRISP-DM) methodology, the selected data has been modified and saved in WEKA software-compliant csv format.The prepared data represent four selected subjects which are English Home Language (EHL), English First Additional Language (EFAL), Mathematics and Mathematical Literacy. Four Different models were iteratively generated and analysed and valuable insights were drawn from them to highlight how their possible influence on future decision making in the FSDoE. The analysis focuses on performance of learners within the performance categories (levels 1 to 7) and compares them Free State's Grade 12s average performance during the selected 2010 to 2013 period. The English Languages (EHL and EFAL) models and the Mathematics (Mathematics and Mathematical Literacy) models are analysed and interpreted according to the identified patterns as observed over the four year period (2010-2013).In addition, the study makes sense of the models generated from WEKA by interpreting them using theories from Bloom's Mastery Learning and Argyris' Learning Organisations. Furthermore, the study delves into the 2011 census data and make sense of the results obtained from the application of WEKA in the selected 2010-2013- Grade 12 results in the FSDoE.The study concludes by giving recommendations which the Free State Department of Education may use as they plan not only for future Grade 12 results but across all grades. It is through the application of DM tools that credibility, as seen with Grade 12 data in the FSDoE, can be established through sense making which can assist during decision making.

[发布机构] Stellenbosch University