Search results for: learning Maltese as a second language

Authors: Cunyu Zhang

Abstract:

Through literature review about studies related to tense, it is found that there exist disagreements on the definition and existence of Chinese tense. Influenced by some researches on English language which regard tense as a grammatical category based on the verbal inflections of English, some Chinese researchers claim that there is no tense in Chinese language as there are no verbal inflections involved. Meanwhile, other Chinese researchers hold that Chinese still has tense although its verbs are non-inflectional based on the fact that Chinese lexical expressions can imply temporal meaning. We assume that the reasons for the above disagreements in terms of Chinese tense lie in the fact that all the previous studies prefer to view language “from the below” which means expressions of tense are the core part of these studies. However, there are about 6,000 languages with distinct expressions all over the world. Hence, if the language studies only concentrate on expressions, it must become more difficult to understand the nature of language. By contrast, functions of languages are similar; otherwise, the human beings could not communicate with each other. Therefore, we believe that it is necessary for us to have a theoretical study on Chinese tense within the framework of SFL which holds that language is a system where meaning is the core part while form is just the realization of meaning. In addition, SFL is a general linguistic providing a universal framework for languages all over the world. Therefore, based on Systemic Functional Linguistics, the paper firstly redefines tense as a deictic semantic category for describing the speaker’s temporal location of processes and relevant temporal relations. With reference to this definition, this study explores the meaning system of tense. It is proposed that tense expresses four kinds of meaning, namely interpersonal, experiential, logical and textual meanings. From the interpersonal angle, tense helps to exchange temporal information between the speaker and the listener, and the temporal information refers to the anchoring of a concerned process in the past, present or future by the speaker. From the experiential angle, tense plays a role in the temporal locating of material, mental, relational, existential, behavioral and verbal processes by the speaker. From the logical angle, tense denotes the temporal relations at the two levels of clause and clause complex, and such relations fall into simultaneity, anteriority and posteriority. From the textual angle, tense refers to the temporal relations at the level of text, and the temporal relations in question concern linear serial relations and synchronous serial relations.

Keywords: Chinese, meaning system, Systemic Functional Linguistics, tense

Procedia PDF Downloads 421

Authors: Sibawu Witness Siyepu

Abstract:

This study explores the effects of instructional design using blended learning in the learning of radian measures among Engineering students. Blended learning is an education programme that combines online digital media with traditional classroom methods. It requires the physical presence of both lecturer and student in a mathematics computer laboratory. Blended learning provides element of class control over time, place, path or pace. The focus was on the use of Khan Academy to supplement traditional classroom interactions. Khan Academy is a non-profit educational organisation created by educator Salman Khan with a goal of creating an accessible place for students to learn through watching videos in a computer assisted computer. The researcher who is an also lecturer in mathematics support programme collected data through instructing students to watch Khan Academy videos on radian measures, and by supplying students with traditional classroom activities. Classroom activities entails radian measure activities extracted from the Internet. Students were given an opportunity to engage in class discussions, social interactions and collaborations. These activities necessitated students to write formative assessments tests. The purpose of formative assessments tests was to find out about the students’ understanding of radian measures, including errors and misconceptions they displayed in their calculations. Identification of errors and misconceptions serve as pointers of students’ weaknesses and strengths in their learning of radian measures. At the end of data collection, semi-structure interviews were administered to a purposefully sampled group to explore their perceptions and feedback regarding the use of blended learning approach in teaching and learning of radian measures. The study employed Algebraic Insight Framework to analyse data collected. Algebraic Insight Framework is a subset of symbol sense which allows a student to correctly enter expressions into a computer assisted systems efficiently. This study offers students opportunities to enter topics and subtopics on radian measures into a computer through the lens of Khan Academy. Khan academy demonstrates procedures followed to reach solutions of mathematical problems. The researcher performed the task of explaining mathematical concepts and facilitated the process of reinvention of rules and formulae in the learning of radian measures. Lastly, activities that reinforce students’ understanding of radian were distributed. Results showed that this study enthused the students in their learning of radian measures. Learning through videos prompted the students to ask questions which brought about clarity and sense making to the classroom discussions. Data revealed that sense making through reinvention of rules and formulae assisted the students in enhancing their learning of radian measures. This study recommends the use of Khan Academy in blended learning to be introduced as a socialisation programme to all first year students. This will prepare students that are computer illiterate to become conversant with the use of Khan Academy as a powerful tool in the learning of mathematics. Khan Academy is a key technological tool that is pivotal for the development of students’ autonomy in the learning of mathematics and that promotes collaboration with lecturers and peers.

Keywords: algebraic insight framework, blended learning, Khan Academy, radian measures

Procedia PDF Downloads 311

Authors: Juliet Charles Udoudom

Abstract:

In nonnative language use environments, language users have been known to demonstrate marked variations both in the spoken and written productions of the target language. For instance, analyses of the written productions of Nigerian users of English have shown inappropriate sequencing of sentence elements resulting in distortions in meaning and/or other problems of syntax. This study analyses the structure of sentences in the written production of 450 educated Nigerian users of English to establish their sensitivity to adjunct placement and the extent to which it exerts on meaning interpretation. The respondents were selected by a stratified random sampling technique from six universities in south-south Nigeria using education as the main yardstick for stratification. The systemic functional grammar analytic format was used in analyzing the sentences selected from the corpus. Findings from the analyses indicate that of the 8,576 tokens of adjuncts in the entire corpus, 4,550 (53.05%) of circumstantial adjuncts were appropriately placed while 2,839 (33.11%) of modal adjuncts occurred at appropriate locations in the clauses analyzed. Conjunctive adjunct placement accounted for 1,187 occurrences, representing 13.84% of the entire corpus. Further findings revealed that prepositional phrases (PPs) were not well construed by respondents to be capable of realizing adjunct functions, and were inappropriately placed.

Keywords: adjunct, adjunct placement, conjunctive adjunct, circumstantial adjunct, systemic grammar

Procedia PDF Downloads 24

Authors: S. Studente, S. Ellis, S. F. Garivaldis

Abstract:

We report upon a study introducing a chatbot to develop learning communities at a London University, with a largely international student base. The focus of the chatbot was twofold; to ease the transition for students into their first year of university study, and to increase study engagement. Four learning communities were created using the chatbot; level 3 foundation, level 4 undergraduate, level 6 undergraduate and level 7 post-graduate. Students and programme leaders were provided with access to the chat bot via mobile app prior to their study induction and throughout the autumn term of 2019. At the end of the term, data were collected via questionnaires and focus groups with students and teaching staff to allow for identification of benefits and challenges. Findings indicated a positive correlation between study engagement and engagement with peers. Students reported that the chatbot enabled them to obtain support and connect to their programme leader. Both staff and students also made recommendation on how engagement could be further enhanced using the bot in terms of; clearly specified purpose, integration with existing university systems, leading by example and connectivity. Extending upon these recommendations, a second pilot study is planned for September 2020, for which the focus will be upon improving attendance rates, student satisfaction and module pass rates.

Keywords: chatbot, e-learning, learning communities, student engagement

Procedia PDF Downloads 125

Authors: Maria Visitacion N. Gumabay, Byron Joseph A. Hallar, Annjeannette Alain D. Galang

Abstract:

This study was intended to provide a more efficient and convenient way for mobile users to enhance their knowledge about ASEAN countries. The researchers evaluated the utility of the developed crossword puzzle application and assessed the general usability of its user interface for its intended purpose and audience of users. The descriptive qualitative research method for the research design and the Mobile-D methodology was employed for the development of the software application output. With a generally favorable reception from its users, the researchers concluded that the iSEA Mobile Based Learning Application can be considered ready for general deployment and use. It was also concluded that additional studies can also be done to make a more complete assessment of the knowledge gained by its users before and after using the application.

Keywords: mobile learning, eLearning, crossword, ASEAN, iSEA

Procedia PDF Downloads 314

Authors: Romisaa Ali

Abstract:

This paper presents a comparison between twin-delayed Deep Deterministic Policy Gradient (TD3) and Soft Actor-Critic (SAC) reinforcement learning algorithms in the context of training robust navigation policies for Jackal robots. By leveraging an open-source framework and custom motion control environments, the study evaluates the performance, robustness, and transferability of the trained policies across a range of scenarios. The primary focus of the experiments is to assess the training process, the adaptability of the algorithms, and the robot’s ability to navigate in previously unseen environments. Moreover, the paper examines the influence of varying environmental complexities on the learning process and the generalization capabilities of the resulting policies. The results of this study aim to inform and guide the development of more efficient and practical reinforcement learning-based navigation policies for Jackal robots in real-world scenarios.

Keywords: Jackal robot environments, reinforcement learning, TD3, SAC, robust navigation, transferability, custom environment

Procedia PDF Downloads 106

Authors: Edward Shizha, Edward Makwarimba

Abstract:

This literature review explores current research on the educational strengths and barriers of newcomer and refugee youth in Canada. Canada’s shift in immigration policy in the past three decades, from Europe to Asian and African countries as source continents of recent immigrants to Canada, has tremendously increased the ethnic, linguistic, cultural and religious diversity of the population, including that of students in its education system. Over 18% of the country’s population was born in another country, of which 70% are visible minorities. There has been an increase in admitted immigrants and refugees, with a total of 226,203 between July 2020 and June 2021. Newcomer parents and their children in all major destination countries, including Canada, face tremendous challenges, including racism and discrimination, lack of English language skills, poverty, income inequality, unemployment, and underemployment. They face additional challenges, including discrimination against those who cannot speak the official languages, English or French. The severity of the challenges depends on several intersectional factors, including immigrant status (asylum seeker, refugee, or immigrant), age, gender, level of education and others. Through the lens of intersectionality as an explanatory perspective, this literature review examines the educational attainment and outcomes of newcomer and refugee youth in Canada in order to understand their educational needs, educational barriers and strengths. Newcomer youths’ experiences are shaped by numerous intersectional and interconnected sociocultural, sociopolitical, and socioeconomic factors—including gender, migration status, racialized status, ethnicity, socioeconomic class, sexual minority status, age, race—that produce and perpetuate their disadvantage. According to research, immigrants and refugees from visible minority ethnic backgrounds experience exclusions more than newcomers from other backgrounds and groups from the mainstream population. For many immigrant parents, migration provides financial and educational opportunities for their children. Yet, when attending school, newcomer and refugee youth face unique challenges related to racism and discrimination, negative attitudes and stereotypes from teachers and other school authorities, language learning and proficiency, differing levels of acculturation, and different cultural views of the role of parents in relation to teachers and school, and unfamiliarity with the social or school context in Canada. Recognizing discrepancies in educational attainment of newcomer and refugee youth based on their race and immigrant status, the paper develops insights into existing research and data gaps related to educational strengths and challenges for visible minority newcomer youth in Canada. The paper concludes that the educational successes or failures of the newcomer and refugee youth and their settlement and integration into the school system in Canada may depend on where their families settle, the attitudes of the host community and the school officials (teachers, guidance counsellors and school administrators) after-school support programs and their own set of coping mechanisms. Conceivably a unique approach to after-school programming should provide learning supports and opportunities that consider newcomer and refugee youth’s needs, experiences, backgrounds and circumstances. This support is likely to translate into significant academic and psychological well-being of newcomer students.

Keywords: deficit discourse, discrimination, educational outcomes, newcomer and refugee youth, racism, strength-based approach, whiteness

Procedia PDF Downloads 68

Authors: Cheikh Bamba Dione, Alla Lo, Elhadji Mamadou Nguer, Siley O. Ba

Abstract:

In this paper, we propose two neural machine translation (NMT) systems (French-to-Wolof and Wolof-to-French) based on sequence-to-sequence with attention and transformer architectures. We trained our models on a parallel French-Wolof corpus of about 83k sentence pairs. Because of the low-resource setting, we experimented with advanced methods for handling data sparsity, including subword segmentation, back translation, and the copied corpus method. We evaluate the models using the BLEU score and find that transformer outperforms the classic seq2seq model in all settings, in addition to being less sensitive to noise. In general, the best scores are achieved when training the models on word-level-based units. For subword-level models, using back translation proves to be slightly beneficial in low-resource (WO) to high-resource (FR) language translation for the transformer (but not for the seq2seq) models. A slight improvement can also be observed when injecting copied monolingual text in the target language. Moreover, combining the copied method data with back translation leads to a substantial improvement of the translation quality.

Keywords: backtranslation, low-resource language, neural machine translation, sequence-to-sequence, transformer, Wolof

Procedia PDF Downloads 149

Authors: Scott McCutcheon, Karen Schreder

Abstract:

Higher education is facing a new reality. Student connection with coursework, instructor, and peers competes with online gaming, screen time, and instant gratification. Pedagogical methods that align student connection and critical thinking in a content-rich environment are important in supporting student learning, a sense of community, and emotional health. This mixed methods study focuses on exploring how the use of educational escape rooms (EERs) can support student learning and learning retention while fostering engagement with each other, the instructor, and the coursework. EERs are content-specific, cooperative, team-based learning activities designed to be completed within a short segment of a typical class. Data for the study was collected over three semesters and includes results from the implementation of EERs in science-based and liberal studies courses taught by different instructors. Twenty-seven students were surveyed regarding their learning experiences with this pedagogy, and interviews with four student volunteers were conducted to add depth to the survey data. A key finding from this research indicates that students felt more connected to each other and the course content after participating in the escape room activity. Additional findings point to increased engagement and comprehension of the class material. Data indicates that the use of an EER pedagogy supports student engagement, well-being, subject comprehension, and student-student and student-instructor connection.

Keywords: gamification, innovative pedagogy, student engagement, student emotional well being

Procedia PDF Downloads 74

Authors: Norzaliza Md. Nor, Sh-Hussain Salleh, Mahyar Hamedi, Hadrina Hussain, Wahab Abdul Rahman

Abstract:

Motivational factor is mainly the students’ desire to involve in learning process. However, it also depends on the goal towards their involvement or non-involvement in academic activity. Even though, the students’ motivation might be in the same level, but the basis of their motivation may differ. In this study, it focuses on the intrinsic motivational factor which student enjoy learning or feeling of accomplishment the activity or study for its own sake. The intrinsic motivational factor of students in learning mathematics and science has found as difficult to be achieved because it depends on students’ interest. In the Program for International Student Assessment (PISA) for mathematics and science, Malaysia is ranked as third lowest. The main problem in Malaysian educational system, students tend to have extrinsic motivation which they have to score in exam in order to achieve a good result and enrolled as university students. The use of electroencephalogram (EEG) signals has found to be scarce especially to identify the students’ intrinsic motivational factor in learning science and mathematics. In this research study, we are identifying the correlation between precursor emotion and its dynamic emotion to verify the intrinsic motivational factor of students in learning mathematics and science. The 2-D Affective Space Model (ASM) was used in this research in order to identify the relationship of precursor emotion and its dynamic emotion based on the four basic emotions, happy, calm, fear and sad. These four basic emotions are required to be used as reference stimuli. Then, in order to capture the brain waves, EEG device was used, while Mel Frequency Cepstral Coefficient (MFCC) was adopted to be used for extracting the features before it will be feed to Multilayer Perceptron (MLP) to classify the valence and arousal axes for the ASM. The results show that the precursor emotion had an influence the dynamic emotions and it identifies that most students have no interest in mathematics and science according to the negative emotion (sad and fear) appear in the EEG signals. We hope that these results can help us further relate the behavior and intrinsic motivational factor of students towards learning of mathematics and science.

Keywords: EEG, MLP, MFCC, intrinsic motivational factor

Procedia PDF Downloads 369

Authors: Gülay Dalgıç, Gildis Tachir

Abstract:

Architectural design studios are ambiencein where architecture design is realized as a palpable product in architectural education. In the design studios that the architect candidate will use in the design processthe information, the methods of approaching the design problem, the solution proposals, etc., are set uptogetherwith the studio coordinators. The architectural design process, on the other hand, is complex and uncertain.Candidate architects work in a process that starts with abstre and ill-defined problems. This process starts with the generation of alternative solutions with the help of representation tools, continues with the selection of the appropriate/satisfactory solution from these alternatives, and then ends with the creation of an acceptable design/result product. In the studio ambience, many designs and thought relationships are evaluated, the most important step is the early design phase. In the early design phase, the first steps of converting the information are taken, and converted information is used in the constitution of the first design decisions. This phase, which positively affects the progress of the design process and constitution of the final product, is complex and fuzzy than the other phases of the design process. In this context, the aim of the study is to investigate the effects of face-to-face learning model and e-learning model on the early design phase. In the study, the early design phase was defined by literature research. The data of the defined early design phase criteria were obtained with the feedback graphics created for the architect candidates who performed e-learning in the first year of architectural education and continued their education with the face-to-face learning model. The findings of the data were analyzed with the common graphics program. It is thought that this research will contribute to the establishment of a contemporary architectural design education model by reflecting the evaluation of the data and results on architectural education.

Keywords: education modeling, architecture education, design education, design process

Procedia PDF Downloads 139

Authors: Austin Vander Wel, Katherin Vargas Henao

Abstract:

Washington, DC, is a city in which Spanish, along with several other minority languages, is prevalent not only among tourists but also those living within city limits. In response to this linguistic diversity and DC’s adoption of the Language Access Act in 2004, the Washington Metropolitan Area Transit Authority (WMATA) committed to addressing the need for equal linguistic representation and established a five-step plan to provide the best multilingual information possible for public transportation users. The current study, however, strongly suggests that this de jure policy does not align with the reality of Spanish’s representation on DC public transportation–although perhaps doing so in an unexpected way. In order to investigate Spanish’s de facto representation and how it contrasts with de jure policy, this study implements a linguistic landscapes methodology that takes critical language-policy as its theoretical framework (Tollefson, 2005). Specifically concerning de facto representation, it focuses on the discrepancies between digital spaces and the actual physical spaces through which users travel. These digital vs. in situ conditions are further analyzed by separately addressing aural and visual modalities. In digital spaces, data was collected from WMATA’s website (visual) and their bilingual hotline (aural). For in situ spaces, both bus and metro areas of DC public transportation were explored, with signs comprising the visual modality and recordings, driver announcements, and interactions with metro kiosk workers comprising the aural modality. While digital spaces were considered to successfully fulfill WMATA’s commitment to representing Spanish as outlined in the de jure policy, physical spaces show a large discrepancy between what is said and what is done, particularly regarding the bus system, in addition to the aural modality overall. These discrepancies in situ spaces place Spanish speakers at a clear disadvantage, demanding additional resources and knowledge on the part of residents with limited or no English proficiency in order to have equal access to this public good. Based on our critical language-policy analysis, while Spanish is represented as a right in the de jure policy, its implementation in situ clearly portrays Spanish as a problem since those seeking bilingual information can not expect it to be present when and where they need it most (Ruíz, 1984; Tollefson, 2005). This study concludes with practical, data-based steps to improve the current situation facing DC’s public transportation context and serves as a model for responding to inadequate enactment of de jure policy in other language policy settings.

Keywords: Urban landscape, language access, critical-language policy, spanish, public transportation

Procedia PDF Downloads 73

Authors: Nan Yang, Hye Pae

Abstract:

English as a second language (ESL) learners are often observed to have transferred traits of their first languages (L1) and habits of using their L1s to their use of English (second language, L2), and this phenomenon is coined as language transfer. In addition to the transfer of linguistic features (e.g., grammar, vocabulary, etc.), which are relatively easy to observe and quantify, many cross-cultural theorists emphasized on a much subtle and fundamental transfer existing on a higher conceptual level that is referred to as conceptual transfer. Although a growing body of literature in linguistics has demonstrated evidence of L1 transfer in various discourse genres, very limited studies address the underlying conceptual transfer that is happening along with the language transfer, especially with the extended form of spontaneous discourses such as personal narrative. To address this issue, this study situates itself in the context of Chinese ESL learners’ written narratives, examines evidence of L1 conceptual transfer in comparison with native English speakers’ narratives, and provides discussion from the perspective of the conceptual transfer. It is hypothesized that Chinese ESL learners’ English narrative strategies are heavily influenced by the strategies that they use in Chinese as a result of the conceptual transfer. Understanding language transfer cognitively is of great significance in the realm of SLA, as it helps address challenges that ESL learners around the world are facing; allow native English speakers to develop a better understanding about how and why learners’ English is different; and also shed light in ESL pedagogy by providing linguistic and cultural expectations in native English-speaking countries. To achieve the goals, 40 college students were recruited (20 Chinese ESL learners and 20 native English speakers) in the United States, and their written narratives on the prompt 'The most frightening experience' were collected for quantitative discourse analysis. 40 written narratives (20 in Chinese and 20 in English) were collected from Chinese ESL learners, and 20 written narratives were collected from native English speakers. All written narratives were coded according to the coding scheme developed by the authors prior to data collection. Statistical descriptive analyses were conducted, and the preliminary results revealed that native English speakers included more narrative elements such as events and explicit evaluation comparing to Chinese ESL students’ both English and Chinese writings; the English group also utilized more evaluation device (i.e., physical state expressions, indirectly reported speeches, delineation) than Chinese ESL students’ both English and Chinese writings. It was also observed that Chinese ESL students included more orientation elements (i.e., the introduction of time/place, the introduction of character) in their Chinese and English writings than the native English-speaking participants. The findings suggest that a similar narrative strategy was observed in Chinese ESL learners’ Chinese narratives and English narratives, which is considered as the evidence of conceptual transfer from Chinese (L1) to English (L2). The results also indicate that distinct narrative strategies were used by Chinese ESL learners and native English speakers as a result of cross-cultural differences.

Keywords: Chinese ESL learners, language transfer, thinking-for-speaking, written narratives

Procedia PDF Downloads 123

Authors: Mohd Khairezan Rahmat

Abstract:

Since the impetus of becoming a develop country by the year 2020, the Malaysian government have been proactive in strengthening the integration of ICT into the national educational system. Teacher-education programs have the responsibility to prepare the nation future teachers by instilling in them the desire, confidence, and ability to fully utilized the potential of ICT into their instruction process. In an effort to fulfill this responsibility, teacher-education program are beginning to create alternatives means for preparing cutting-edge teachers. One of the alternatives is the student’s learning portal. In line with this mission, this study investigates the Faculty of Education, University Teknologi MARA (UiTM) pre-service teachers’ perception of usefulness, attitude, and ability toward the usage of the university learning portal, known as iLearn. The study also aimed to predict factors that might hinder the pre-service teachers’ decision to used iLearn as their platform in learning. The Structural Equation Modeling (SEM), was employed in analyzed the survey data. The suggested findings informed that pre-service teacher’s successful integration of the iLearn was highly influenced by their perception of usefulness of the system. The findings also suggested that the more familiar the pre-service teacher with the iLearn, the more possibility they will use the system. In light of similar study, the present findings hope to highlight the important to understand the user’s perception toward any proposed technology.

Keywords: e-learning, prediction factors, pre-service teacher, structural equation modeling (SEM)

Procedia PDF Downloads 342

Authors: Claire Griffin

Abstract:

Recent years have witnessed a surge in the use of innovative teaching approaches to support student engagement and higher-order learning within higher education. This paper seeks to explore the use of collaborative, interactive teaching and learning strategies to support student engagement in a final year undergraduate Developmental Psychology module. In particular, the use of the jigsaw method, in-class presentations and online discussion fora were adopted in a ‘lectorial’ style teaching approach, aimed at scaffolding learning, fostering social interdependence and supporting various levels of student engagement in higher education. Using the ‘Student Course Engagement Questionnaire’, the impact of such teaching strategies on students’ college classroom experience was measured, with additional qualitative student feedback gathered. Results illustrate the positive impact of the teaching methodologies on students’ levels of engagement, with positive implications emerging across the four engagement factors: skills engagement, emotional engagement, participation/interaction engagement and performance engagement. Thematic analysis on students’ qualitative comments also provided greater insight into the positive impact of the ‘lectorial’ teaching approach on students’ classroom experience within higher level education. Implications of the findings are presented in terms of informing effective teaching practices within higher education. Additional avenues for future research and strategy usage will also be discussed, in light of evolving practice and cutting edge literature within the field.

Keywords: learning, higher education, scaffolding, student engagement

Procedia PDF Downloads 380

Authors: Marinella Majorano, Rachele Ferrari, Tamara Bastianello

Abstract:

The recent technological advance allows for applying innovative and multimedia screen-based assessment tools to test children's language and early literacy skills, monitor their growth over the preschool years, and test their readiness for primary school. Several are the advantages that a computer-based assessment tool offers with respect to paper-based tools. Firstly, computer-based tools which provide the use of games, videos, and audio may be more motivating and engaging for children, especially for those with language difficulties. Secondly, computer-based assessments are generally less time-consuming than traditional paper-based assessments: this makes them less demanding for children and provides clinicians and researchers, but also teachers, with the opportunity to test children multiple times over the same school year and, thus, to monitor their language growth more systematically. Finally, while paper-based tools require offline coding, computer-based tools sometimes allow obtaining automatically calculated scores, thus producing less subjective evaluations of the assessed skills and provide immediate feedback. Nonetheless, using computer-based assessment tools to test meta-phonological and language skills in children is not yet common practice in Italy. The present contribution aims to estimate the internal consistency of a computer-based assessment (i.e., the Simo-syl assessment). Sixty-three Italian pre-schoolers aged between 4;10 and 5;9 years were tested at the beginning of the last year of the preschool through paper-based standardised tools in their lexical (Peabody Picture Vocabulary Test), morpho-syntactical (Grammar Repetition Test for Children), meta-phonological (Meta-Phonological skills Evaluation test), and phono-articulatory skills (non-word repetition). The same children were tested through Simo-syl assessment on their phonological and meta-phonological skills (e.g., recognise syllables and vowels and read syllables and words). The internal consistency of the computer-based tool was acceptable (Cronbach's alpha = .799). Children's scores obtained in the paper-based assessment and scores obtained in each task of the computer-based assessment were correlated. Significant and positive correlations emerged between all the tasks of the computer-based assessment and the scores obtained in the CMF (r = .287 - .311, p < .05) and in the correct sentences in the RCGB (r = .360 - .481, p < .01); non-word repetition standardised test significantly correlates with the reading tasks only (r = .329 - .350, p < .05). Further tasks should be included in the current version of Simo-syl to have a comprehensive and multi-dimensional approach when assessing children. However, such a tool represents a good chance for the teachers to early identifying language-related problems even in the school environment.

Keywords: assessment, computer-based, early identification, language-related skills

Procedia PDF Downloads 186

Authors: T. Damak, O. Kriaa, A. Baccar, M. A. Ben Ayed, N. Masmoudi

Abstract:

In the last few years, Automatic Number Plate Recognition (ANPR) systems have become widely used in the safety, the security, and the commercial aspects. Forethought, several methods and techniques are computing to achieve the better levels in terms of accuracy and real time execution. This paper proposed a computer vision algorithm of Number Plate Localization (NPL) and Characters Segmentation (CS). In addition, it proposed an improved method in Optical Character Recognition (OCR) based on Deep Learning (DL) techniques. In order to identify the number of detected plate after NPL and CS steps, the Convolutional Neural Network (CNN) algorithm is proposed. A DL model is developed using four convolution layers, two layers of Maxpooling, and six layers of fully connected. The model was trained by number image database on the Jetson TX2 NVIDIA target. The accuracy result has achieved 95.84%.

Keywords: ANPR, CS, CNN, deep learning, NPL

Procedia PDF Downloads 307

Authors: Emma Nemishalyan

Abstract:

It is believed that learners’ mother tongue (L1 hereafter) has a huge impact on their second language acquisition (L2 hereafter). This hypothesis has been exposed to both positive and negative criticism. Based on research results of a wide range of learners’ corpora (Chinese, Japanese, Spanish among others) the hypothesis has either been proved or disproved. However, no such study has been conducted on the Armenian learners. The aim of this paper is to understand the implication of the hypothesis on the Armenian learners’ corpus in terms of the use of the passive voice. To this end, the method of Contrastive Interlanguage Analysis (hereafter CIA) has been used on native speakers’ corpus (Louvain Corpus of Native English Essays (LOCNESS)) and Armenian learners’ corpus which has been compiled by me in compliance with International Corpus of Learner English (ICLE) guidelines. CIA compares the interlanguage (the language produced by learners) with the one produced by native speakers. With the help of this method, it is possible not only to highlight the mistakes that learners make, but also to underline the under or overuses. The choice of the grammar issue (passive voice) is conditioned by the fact that typologically Armenian and English are drastically different as they belong to different branches. Moreover, the passive voice is considered to be one of the most problematic grammar topics to be acquired by learners of the English language. Based on this difference, we hypothesized that Armenian learners would either overuse or underuse some types of the passive voice. With the help of Lancsbox software, we have identified the frequency rates of passive voice usage in LOCNESS and Armenian learners’ corpus to understand whether the latter have the same usage pattern of the passive voice as the native speakers. Secondly, we have identified the types of the passive voice used by the Armenian leaners trying to track down the reasons in their mother tongue. The results of the study showed that Armenian learners underused the passive voices in contrast to native speakers. Furthermore, the hypothesis that learners’ L1 has an impact on learners’ L2 acquisition and production was proved.

Keywords: corpus linguistics, applied linguistics, second language acquisition, corpus compilation

Procedia PDF Downloads 112

Authors: Rabia Bashir, Sajjad Akbar

Abstract:

There is an inevitable demand of web mining due to rapid increase of huge information on the Internet, but the striking variety of web structures has made required content retrieval a difficult task. To counter this issue, Web Content Mining (WCM) emerges as a potential candidate which extracts and integrates suitable resources of data to users. In past few years, research has been done on several extraction techniques for WCM i.e. agent-based, template-based, assumption-based, statistic-based, wrapper-based and machine learning. However, it is still unclear that either these approaches are efficiently tackling the significant challenges of WCM or not. To answer this question, this paper identifies these challenges such as language independency, structure flexibility, performance, automation, dynamicity, redundancy handling, intelligence, relevant content retrieval, and privacy. Further, mapping of these challenges is done with existing extraction mechanisms which helps to adopt the most suitable WCM approach, given some conditions and characteristics at hand.

Keywords: content mining challenges, web content mining, web content extraction approaches, web information retrieval

Procedia PDF Downloads 550

Authors: Shubham Bhonde, Nekzad Doctor, Shashwat Gawande

Abstract:

For the use and the import of Keys and ID Transmitter as well as Body Control Modules with radio transmission in a lot of countries, homologation is required. Final deliverables in homologation of the product are certificates. In considering the world of homologation, there are approximately 200 certificates per product, with most of the certificates in local languages. It is challenging to manually investigate each certificate and extract relevant data from the certificate, such as expiry date, approval date, etc. It is most important to get accurate data from the certificate as inaccuracy may lead to missing re-homologation of certificates that will result in an incompliance situation. There is a scope of automation in reading the certificate data in the field of homologation. We are using deep learning as a tool for automation. We have first trained a model using machine learning by providing all country's basic data. We have trained this model only once. We trained the model by feeding pdf and jpg files using the ETL process. Eventually, that trained model will give more accurate results later. As an outcome, we will get the expiry date and approval date of the certificate with a single click. This will eventually help to implement automation features on a broader level in the database where certificates are stored. This automation will help to minimize human error to almost negligible.

Keywords: homologation, re-homologation, data science, deep learning, machine learning, ETL (extract transform loading)

Procedia PDF Downloads 164

Authors: M. Omer, D. Wilson

Abstract:

Creating a database scheme is essentially a manual process. From a requirement specification, the information contained within has to be analyzed and reduced into a set of tables, attributes and relationships. This is a time-consuming process that has to go through several stages before an acceptable database schema is achieved. The purpose of this paper is to implement a Natural Language Processing (NLP) based tool to produce a from a requirement specification. The Stanford CoreNLP version 3.3.1 and the Java programming were used to implement the proposed model. The outcome of this study indicates that the first draft of a relational database schema can be extracted from a requirement specification by using NLP tools and techniques with minimum user intervention. Therefore, this method is a step forward in finding a solution that requires little or no user intervention.

Keywords: information extraction, natural language processing, relation extraction

Procedia PDF Downloads 263

Authors: Mahmoud I. Syam, Osama K. El-Hafy

Abstract:

With lack of student motivation, there will be a little or no real learning in the class and this directly effects student achievement and test scores. Some students are naturally motivated to learn, but many students are not motivated, they do care little about learning and need their instructors to motivate them. Thus, motivating students is part of the instructor’s job. It’s a tough task to motivate students and make them have more attention and enthusiasm. As a part of this research, a questionnaire has been distributed among a sample of 155 students out of 1502 students from Foundation Program at Qatar University. The questionnaire helped us to determine some methods to motivate the students and encourage them to study such as variety of teaching activities, encouraging students to participate during the lectures, creating intense competition between the students, using instructional technology, not using grades as a threat and respecting the students and treating them in a good manner. Accordingly, some hypotheses are tested and some recommendations are presented.

Keywords: learning, motivating, student, teacher, testing hypotheses

Procedia PDF Downloads 474

Authors: Prashanth Pillai, Purnaprajna Mangsuli

Abstract:

Oil exploration and production companies invest considerable time and efforts to extract essential well attributes (like well status, surface, and target coordinates, wellbore depths, event timelines, etc.) from unstructured data sources like technical reports, which are often non-standardized, multimodal, and highly domain-specific by nature. It is also important to consider the context when extracting attribute values from reports that contain information on multiple wells/wellbores. Moreover, semantically similar information may often be depicted in different data syntax representations across multiple pages and document sources. We propose a hierarchical multi-source fact extraction workflow based on a deep learning framework to extract essential well attributes at scale. An information retrieval module based on the transformer architecture was used to rank relevant pages in a document source utilizing the page image embeddings and semantic text embeddings. A question answering framework utilizingLayoutLM transformer was used to extract attribute-value pairs incorporating the text semantics and layout information from top relevant pages in a document. To better handle context while dealing with multi-well reports, we incorporate a dynamic query generation module to resolve ambiguities. The extracted attribute information from various pages and documents are standardized to a common representation using a parser module to facilitate information comparison and aggregation. Finally, we use a probabilistic approach to fuse information extracted from multiple sources into a coherent well record. The applicability of the proposed approach and related performance was studied on several real-life well technical reports.

Keywords: natural language processing, deep learning, transformers, information retrieval

Procedia PDF Downloads 194

Authors: Marcel Chevalier, Léo Dupont, Sylvain Marié, Frédérique Roffet, Elena Stolyarova, William Templier, Costin Vasile

Abstract:

Industrial end-users are currently facing an increasing need to reduce the risk of unexpected failures and optimize their maintenance. This calls for both short-term analysis and long-term ageing anticipation. At Schneider Electric, we tackle those two issues using both machine learning and first principles models. Machine learning models are incrementally trained from normal data to predict expected values and detect statistically significant short-term deviations. Ageing models are constructed by breaking down physical systems into sub-assemblies, then determining relevant degradation modes and associating each one to the right kinetic law. Validating such anomaly detection and maintenance models is challenging, both because actual incident and ageing data are rare and distorted by human interventions, and incremental learning depends on human feedback. To overcome these difficulties, we propose to simulate physics, systems, and humans -including asset maintenance operations- in order to validate the overall approaches in accelerated time and possibly choose between algorithmic alternatives.

Keywords: degradation models, ageing, anomaly detection, soft sensor, incremental learning

Procedia PDF Downloads 127

Authors: Gizem Barreto Martins

Abstract:

This paper explores the subversive potential inherent in the theatrical language employed within Arthur Miller's The Crucible. The research argues that this play intricately weaves ideological connections with its audience and the historical epoch it represents, effectively serving as a channel for ideological and cultural interaction potentially exerting subversive influences on social and political realms. Using a historical-materialist methodology that situates the play within its historical and political context, all while examining its connections with theater and literary theories, the paper raises a fundamental query: How does this dramatic work embody subversion, presenting a style unburdened by the performative conventions of daily life and prevailing codes and systems of representation? In response to this inquiry, the study asserts that theatrical language has the capacity to function as a subversive catalyst against prevailing ideologies, actively contributing to the process of social transformation. To substantiate this claim, the research conducts a detailed analysis of the selected play, employing the semiotic framework pioneered by Gilles Deleuze and Felix Guattari.

Keywords: arthur miller, The crucible, gilles deleuze, felix guattari, theater and literary theories

Procedia PDF Downloads 64

Authors: Shiyin He, Zheng Huang

Abstract:

In this paper, deep learning methods are applied in bio-medical field to detect and count different types of cells in an automatic way instead of manual work in medical practice, specifically in bone marrow examination. The process is mainly composed of two steps, detection and recognition. Mask-Region-Convolutional Neural Networks (Mask-RCNN) was used for detection and image segmentation to extract cells and then Convolutional Neural Networks (CNN), as well as Deep Residual Network (ResNet) was used to classify. Result of cell detection network shows high efficiency to meet application requirements. For the cell recognition network, two networks are compared and the final system is fully applicable.

Keywords: cell detection, cell recognition, deep learning, Mask-RCNN, ResNet

Procedia PDF Downloads 192

Authors: Ghiwa Dandach

Abstract:

By challenging the anti-failure bias and contributing to the theoretical territory of the attribution theory, this thesis develops a comprehensive process for entrepreneurial learning from failure. The practical implication of the findings suggests assisting entrepreneurs (current, failing, and nascent) in effectively anticipating and reflecting upon failure. Additionally, the process is suggested to enhance the level of institutional and private (accelerators and financers) support provided to entrepreneurs, the implications of which may improve future opportunities for entrepreneurial success. Henceforth, exploring learning from failure is argued to impact the potential survival of future ventures, subsequently revitalizing the economic contribution of entrepreneurship. This learning process can be enhanced with the cognitive development of causal ascriptions for failure, which eventually impacts learning outcomes. However, the mechanism with which entrepreneurs make sense of failure, reflect on the journey, and transform experience into knowledge is still under-researched. More specifically, the cognitive process of failure attribution is under-explored, majorly in the context of developing economies, calling for a more insightful understanding on how entrepreneurs ascribe failure. Responding to the call for more thorough research in such cultural contexts, this study expands the understanding of the dimensions of failure attributions as perceived by entrepreneurs and the impact of these dimensions on learning outcomes in the Lebanese context. The research adopted the exploratory interpretivism paradigm and collected data from interviews with industry experts first, followed by narratives of entrepreneurs using the qualitative multimethod approach. The holistic and categorical content analysis of narratives, preceded by the thematic analysis of interviews, unveiled how entrepreneurs ascribe failure by developing minor and major dimensions of each failure attribution. The findings have also revealed how each dimension impacts the learning from failure when accompanied by emotional resilience. The thesis concludes that exploring in-depth the dimensions of failure attributions significantly determines the level of learning generated. They are moving beyond the simple categorisation of ascriptions as primary internal or external unveiled how learning may occur with each attribution at the individual, venture, and ecosystem levels. This has further accentuated that a major internal attribution of failure combined with a minor external attribution generated the highest levels of transformative and double-loop learning, emphasizing the role of personal blame and responsibility on enhancing learning outcomes.

Keywords: attribution, entrepreneurship, reflection, sense-making, emotions, learning outcomes, failure, exit

Procedia PDF Downloads 228

Authors: David A. Harness

Abstract:

Natural evolution of ATP cognitive systems is to meet AI peer review standards. ATP process of axiom selection from Mizar to prove a conjecture would be further refined, as in all human and machine learning, by solving the real world problem of the proposed AI peer review challenge: Determine which conjecture forms the higher confidence level constructive proof between Standard Model of Physics SU(n) lattice gauge group operation vs. present non-standard 4D GEM EOS SU(n) lattice gauge group spatially extended operation in which the photon and electron are the first two trace angular momentum invariants of a gravitoelectromagnetic (GEM) energy momentum density tensor wavetrain integration spin-stress pressure-volume equation of state (EOS), initiated via 32 lines of Mathematica code. Resulting gravitoelectromagnetic spectrum ranges from compressive through rarefactive of the central cosmological constant vacuum energy density in units of pascals. Said self-adjoint group operation exclusively operates on the stress energy momentum tensor of the Einstein field equations, introducing quantization directly on the 4D spacetime level, essentially reformulating the Yang-Mills virtual superpositioned particle compounded lattice gauge groups quantization of the vacuum—into a single hyper-complex multi-valued GEM U(1) × SU(1,3) lattice gauge group Planck spacetime mesh quantization of the vacuum. Thus the Mizar corpus already contains all of the axioms required for relevant DeepMath premise selection and unambiguous formal natural language parsing in context deep learning.

Keywords: automated theorem proving, constructive quantum field theory, information theory, neural networks

Procedia PDF Downloads 180

Authors: Ijaz Ahmed, Anwar Zada, Muhammad Waqas, M. U. Ashraf

Abstract:

We demonstrate the performance of a very efficient tagger applies on hadronically decaying top quark pairs as signal based on deep neural network algorithms and compares with the QCD multi-jet background events. A significant enhancement of performance in boosted top quark events is observed with our limited computing resources. We also compare modern machine learning approaches and perform a multivariate analysis of boosted top-pair as well as single top quark production through weak interaction at √s = 14 TeV proton-proton Collider. The most relevant known background processes are incorporated. Through the techniques of Boosted Decision Tree (BDT), likelihood and Multlayer Perceptron (MLP) the analysis is trained to observe the performance in comparison with the conventional cut based and count approach

Keywords: top tagger, multivariate, deep learning, LHC, single top

Procedia PDF Downloads 112

Authors: Alhusein Almahjoub, Dongyu Qiu

Abstract:

This paper deals with the random access procedure in next-generation networks and presents the solution to reduce total service time (TST) which is one of the most important performance metrics in current and future internet of things (IoT) based networks. The proposed solution focuses on the calculation of optimal transmission probability which maximizes the success probability and reduces TST. It uses the information of several idle preambles in every time slot, and based on it, it estimates the number of backlogged IoT devices using Naïve Bayes estimation which is a type of supervised learning in the machine learning domain. The estimation of backlogged devices is necessary since optimal transmission probability depends on it and the eNodeB does not have information about it. The simulations are carried out in MATLAB which verify that the proposed solution gives excellent performance.

Keywords: random access, LTE/LTE-A, 5G, machine learning, Naïve Bayes estimation

Procedia PDF Downloads 146