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(Multilingual) Knowledge representation for epistemological access

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 dissertatio...

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Main Author: Antia, Mary-Jane
Other Authors: Meyer, Thomas
Format: Thesis
Language:English
Published: Department of Computer Science 2022
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access_status_str Open Access
author Antia, Mary-Jane
author2 Meyer, Thomas
author_browse Antia, Mary-Jane
Meyer, Thomas
author_facet Meyer, Thomas
Antia, Mary-Jane
author_sort Antia, Mary-Jane
collection Thesis
description 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.
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institution University of Cape Town (South Africa)
language eng
license_str Not specified — see source repository
provenance_str_mv Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository
publishDate 2022
publishDateRange 2022
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spelling oai:open.uct.ac.za:11427/36412 (Multilingual) Knowledge representation for epistemological access Antia, Mary-Jane Meyer, Thomas Computer Science 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. 2022-05-04T07:56:27Z 2022-05-04T07:56:27Z 2018 2022-05-03T07:55:30Z Master Thesis Masters MSc http://hdl.handle.net/11427/36412 eng application/pdf Department of Computer Science Faculty of Science
spellingShingle Computer Science
Antia, Mary-Jane
(Multilingual) Knowledge representation for epistemological access
thesis_degree_str Master's
title (Multilingual) Knowledge representation for epistemological access
title_full (Multilingual) Knowledge representation for epistemological access
title_fullStr (Multilingual) Knowledge representation for epistemological access
title_full_unstemmed (Multilingual) Knowledge representation for epistemological access
title_short (Multilingual) Knowledge representation for epistemological access
title_sort multilingual knowledge representation for epistemological access
topic Computer Science
url http://hdl.handle.net/11427/36412
work_keys_str_mv AT antiamaryjane multilingualknowledgerepresentationforepistemologicalaccess