https://www.um.edu.mt/library/oar/handle/123456789/80390 Thu, 23 Apr 2026 04:26:06 GMT 2026-04-23T04:26:06Z https://www.um.edu.mt/library/oar/handle/123456789/94783 Title: Linguistic profiles of students diagnosed with SpLD : an investigation of Maltese and English essay writing in national examinations Abstract: This research analyses a sample of 1,861 English and Maltese essays written by students during two national examination sessions 2015 and 2016 in Malta at the end of secondary school. Different qualities of writing produced by Access Arrangements (AA) students with SpLd/dyslexia and those without AAs (the Rest) were analysed and compared through mixed method research within the framework of the explanatory sequential design. The results from the quantitative analysis highlighted areas of interest that were subsequently analysed qualitatively. The aims of the study are to understand the impact of SpLD/dyslexia on writing and how texts from students with SpLd/dyslexia differ or otherwise, from the writing produced by students without AAs. The results show how the scores achieved by students who have SpLD/dyslexia in literacy assessments administered at pre-examination stage, correlate with the marks and grades achieved in their language examinations. Results in this study are consistent with the literature, showing how overall, the performance of students with SpLD/dyslexia in writing is poorer in quality, reflecting poorer marks and grades in the essays. Nevertheless, the analysis of writing belonging to the two groups reveals overlapping qualities that often point to poor bilingual development or poor proficiency in the second language. The results have various implications for education policy, including bilingual teaching and learning, assessment and the diagnosis of SpLD/dyslexia. Description: Ph.D.(Melit.) Sat, 01 Jan 2022 00:00:00 GMT https://www.um.edu.mt/library/oar/handle/123456789/94783 2022-01-01T00:00:00Z https://www.um.edu.mt/library/oar/handle/123456789/80628 Title: Demystifying the Voynich manuscript using computational linguistic techniques Abstract: The Voynich manuscript is a medieval codex written in undeciphered text by unknown people. In the paper 'How Many Glyphs and How Many Scribes? Digital Paleography and the Voynich Manuscript' by Dr Lisa Fagin Davis (Davis, 2020a), it is proposed that the manuscript is written by five scribes, and a detailed classification is provided. The goal of this research is to provide further evidence to strengthen this proposed classification and to surface any possible misclassification. Towards this end, an experiment was conducted that takes this proposed classification as ground truth and puts it to the test. The data acquired is a transliteration of the manuscript written in the Extensible Voynich Alphabet. It is split into an equal number of pages per scribe; taking into consideration three of the five scribes due to scribes 4 and 5 having much less data. The experiment utilizes stylometric features, namely character bigrams and character trigrams, as features in four different machine learning classifiers; a Deep Neural Network, a Multinomial Naive Bayes classifier, Support Vector Machines and a Decision Tree classifier. This is done in a ten-fold cross-validation where models are trained and predict a scribe for each page. Separately, a k-means unsupervised clustering algorithm is implemented using the same features with k = 3. The results of cross-validation and clustering are compared with the proposal of Dr Fagin Davis. Description: B.Sc. (Hons) HLT (Melit.) Fri, 01 Jan 2021 00:00:00 GMT https://www.um.edu.mt/library/oar/handle/123456789/80628 2021-01-01T00:00:00Z https://www.um.edu.mt/library/oar/handle/123456789/80626 Title: A cross-linguistic investigation into the connotation of basic colour terms using a distributional semantic model Abstract: The aim of this project is to discover associations and levels of distributional similarity between basic colour terms in different languages. This is done using a distributional semantic model known as Word2Vec. The languages investigated in this project were English, Maltese and Italian. The programming language used in this project was Python. Description: B.Sc. (Hons) HLT (Melit.) Fri, 01 Jan 2021 00:00:00 GMT https://www.um.edu.mt/library/oar/handle/123456789/80626 2021-01-01T00:00:00Z https://www.um.edu.mt/library/oar/handle/123456789/80625 Title: Detecting gender bias and cross-cultural differences from text Abstract: This study is centered on detecting cultural differences and gender bias in text. By building a word embedding model that is trained over a text of corpora in two different languages which are Arabic and English. These models will then be tested to obtain results from all the corpora used. Three different corpora will be used in each model which are News, Wikipedia and Twitter corpus. There are two sets of words that will be checked. The first set is the emotion words such as honorable and fear. And profession words such as nurse and teacher. A survey will be conducted for gender_bias which aims to look at the cultural difference as the participants are two groups, one of English speakers and of the Arabic speakers. So the results of the models can be compared to the results of the survey. The study presents interesting results and shows the task of detecting gender_bias automatically in text. It is still based on a relatively limited sample of corpora, such that these results can be improved if they were trained and tested in a large corpora. However, the results still showed gender_bias, cultural differences and the importance of the corpus used as the type of the corpus can be biased. Description: B.Sc. (Hons) HLT (Melit.) Fri, 01 Jan 2021 00:00:00 GMT https://www.um.edu.mt/library/oar/handle/123456789/80625 2021-01-01T00:00:00Z