(Multilingual) Knowledge representation for epistemological access - Antia, Mary-Jane (Department of Computer Science, 2022)
In South Africa, the inability of many students to acquire knowledge and to successfully demonstrate acquired knowledge in assessments has, in part, been attributed to their low levels of proficiency in the language of learning and teaching (which is also the language of textbooks). This dissertation investigates the possibility of using knowledge representation to enhance epistemological access for learners, specifically, enhancing understanding of school science by learners with limited proficiency in academic English. In the dissertation, sample texts from a life science textbook were modeled into entities and relations, using the conceptual graphs formalism. While the labels for the entities were in English, the links between the entities were provided in both English and in the variety of Afrikaans called Kaaps. A knowledge-based application, using Jupyter notebook and a graph database, was subsequently developed on the basis of the modeled texts. To test the impact of this graph-based resource, an experimental study was designed involving grade 10 learners in a Cape Town high school. One group was exposed to the graphically modeled content and another group was limited only to the text content. The null hypothesis formulated was as follows: there will be no difference in the performance scores of those learners who are exposed to the knowledge modeled in the application and scores of those learners exposed only to knowledge in text without the model. On six of the seven questions, the experimental group performed better than the control group. The performance of the experimental study was further verified using inferential statistics, which showed that the results were statistically significant. Given that the experimental group performed better than the control group, the null hypothesis was rejected. During interviews, participants' subjective experiences indicated that the graphically modeled knowledge allowed for a better understanding of the text. Although findings from larger studies are clearly required, the current study indicates that the implementation of graph-based knowledge systems is a promising means for intervening to enhance the understanding of English-language science textbooks by learners who may not be proficient in English.