Search results for: foreign language learning

Authors: Cristina Diez

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One of the most important challenges of discourse analysis is to find the linguistic mechanisms of subjectivity. The present article aims to raise the need for an argumentative and enunciative analysis to reach the subjective tissue of language. The intention is to prove that the instructions inscribed in the own language are those that indicate how a statement is to be interpreted and that the argumentative value is implied at the semantic level. For that, the theory of argumentation from Ducrot and Anscombre will be implemented. First, a reflection on the study about subjectivity and enunciation in language will be exposed, followed by concrete proposals on the linguistic mechanisms that speakers use either consciously or unconsciously, to finally focus on those argumentative tools that political discourse uses in order to influence the audience.

Keywords: argumentation, enunciation, discourse analysis, subjectivity

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Authors: Jude Harrison

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Child protection is a complex and sensitive practice. The core responsibility is the care and protection of children and young people who have been subject to or who are at risk from abuse and neglect. The work involves investigating allegations of harm, preparing for and making representations to the legal system, and case planning and management across a continuum of complicated care interventions. Professionals’ learning for child protection practice is evident in a range of literature investigating multiple learning processes such as university preparation, student placements, professional supervision, training, and other post-qualifying professional development experiences at work. There is, however, very limited research into how caseworkers learn in and through their daily practice. Little is known, therefore, about how learning at work unfolds for caseworkers, the dimensions in which it can be understood or the ways in which it can be best facilitated and supported. Compounding this, much of the current child protection learning literature reflects an orthodox conception of learning as mentalistic and individualised, in which knowledge is typically understood as abstract theory or as technical skill or competency. This presentation outlines key findings from a PhD research study that explored learning at work for statutory child protection caseworkers from an alternative interpretation of learning using a practice theory approach. Practice theory offers an interpretation of learning as performative and grounded in situated experience. The findings of the study show that casework practice is both a mode and site of learning. The study was ethnographic in design based and followed 17 child protection caseworkers via in-depth interviews, observations and participant reflective journaling. Inductive and abductive analysis was used to organise and interpret the data and expand analysis, leading to themes. Key findings show learning to be a sociomaterial property of doing; the social ontological character of learning; and teleoaffectivity as a feature of learning. The findings contribute to theoretical and practical understandings of learning and practice in child protection, child welfare and the professional learning literature more broadly. The findings have potential to contribute to policy directions at state, territory and national levels to enhance child protection practice and systems.

Keywords: adiult learning, workplace learning, child welfare, sociomaterial, practice theory

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Authors: Zahra Ebrahimi, Abbas Moradan

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This study investigated the effect of applying different layers of activity for different Iranian intermediate EFL learner’s oral proficiency and two of its components (fluency and accura-cy) for the beneficial use of films within speaking classes. For this purpose, thirty Iranian EFL intermediate learners were selected based on availability sampling, they were divided into one experimental group and one control group, each consisting of 15 participants, who were proved to be homogeneous based on the results obtained from IELTS oral proficien-cy test prior to the treatment. Experimental Group received the treatment which was apply-ing different layers of speaking tasks according to learners’ level of fluency and accuracy. Control group received ordinal treatment of speaking classrooms. The materials for this study consisted of 11 English movies for each session, voice-recorder device, and IELTS oral proficiency tests as well as two interviews based on Ur’s oral scale for measuring fluen-cy and accuracy. The treatment was run for 12 sessions in six weeks. At the end of the treatment, all the students both in experimental and control group were given a post-test interview based on Ur’s scale. To compare and contrast the amount of progress of the learners in different groups the results of the pre-test and post-test of speaking were analysed by using T-tests. Moreover, Multivariate analysis of variance was also used to check the hypotheses. Results showed that application of different layers of activity with regard to students’ level, led to a significantly superior performance in experimental group. Thus, this study verified the positive effect of implementation of different layers of activity and tasks to achieve progress in speaking skill. It can also help to create a less stressful at-mosphere of learning in which all the students will be given specific time to speak and lead them to be autonomous learners.

Keywords: differentiated instruction, learners’ style, multiple intelligence, speaking skill, task-based activities

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Authors: Oumaima Lahmar

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This paper aims to define a structured topography for finance researchers seeking to navigate the body of knowledge in their extrapolation of finance phenomena. To make sense of the body of knowledge in finance, a probabilistic topic modeling approach is applied on 6000 abstracts of academic articles published in three top journals in finance between 1976 and 2020. This approach combines both machine learning techniques and natural language processing to statistically identify the conjunctions between research articles and their shared topics described each by relevant keywords. The topic modeling analysis reveals 35 coherent topics that can well depict finance literature and provide a comprehensive structure for the ongoing research themes. Comparing the extracted topics to the Journal of Economic Literature (JEL) classification system, a significant similarity was highlighted between the characterizing keywords. On the other hand, we identify other topics that do not match the JEL classification despite being relevant in the finance literature.

Keywords: finance literature, textual analysis, topic modeling, perplexity

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Authors: Sharon Diaz Ruiz

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The population of Latinx adult English language learners (ELLs) in the United States will increase in the next few years and become even more racially and linguistically diverse. Our classrooms reflect these demographic changes; therefore, there will always be the need to identify language teaching practices that would allow educators to meet this linguistic diversity. This qualitative study explores Latinx adult English language learners' perceptions of culturally responsive teaching strategies. Participants in this study will be enrolled in an English developmental course for the Fall of 2022. The data collection process will consist of overt observation during five presentations/activities, including culturally inclusive readings and student reflections. The teaching materials selected will align with the course module's goals and objectives. The result of this investigation will shed light on the gap in the literature documenting the application of culturally responsive pedagogy to Latino adult language learners.

Keywords: emergent bilinguals, adult learners, Latinx learners, ELL

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Authors: Marta Bas-Szymaszek

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This research examines the intricate relationship between language practices and beliefs within international environmental non-governmental organizations (ENGOs), with a particular focus on the Climate Action Network Europe (CAN Europe). While acknowledging that ENGOs often employ multilingual staff, this study aims to analyze the dual role of English within this sector. While English facilitates practical communication among individuals from diverse backgrounds, it also perpetuates inequalities and marginalization within CAN Europe. Instances of linguistic dominance impede participation and representation, reinforcing language hierarchies. Furthermore, the symbolic power of English risks overshadowing the multilingual skills of NGO employees. Through fourteen in-depth interviews, focus group discussions, and observations, this research uncovers the lived experiences of individuals navigating Europe’s largest environmental NGO network. By analyzing CAN Europe’s implicit language policy and the hegemony of English, this study illuminates the challenges within multilingual settings. The organization advocates for the implementation of more inclusive language policies and practices, with the objective of recognizing and embracing linguistic diversity within international environmental NGOs.

Keywords: language policy, English, NGOs, linguistic inclusion, multilingualism

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Authors: Vincent Liu

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Machine learning algorithms (ML) can achieve high accuracy in predicting outcomes compared to classical models. Metaheuristic, nature-inspired algorithms can enhance traditional ML algorithms by optimizing them such as by performing feature selection. We compare ten ML algorithms to predict 30-day hospital readmission rates for diabetes patients in the US using a dataset from UCI Machine Learning Repository with feature selection performed by Greywolf nature-inspired algorithm. The baseline accuracy for the initial random forest model was 65%. After performing feature engineering, SMOTE for class balancing, and Greywolf optimization, the machine learning algorithms showed better metrics, including F1 scores, accuracy, and confusion matrix with improvements ranging in 10%-30%, and a best model of XGBoost with an accuracy of 95%. Applying machine learning this way can improve patient outcomes as unnecessary rehospitalizations can be prevented by focusing on patients that are at a higher risk of readmission.

Keywords: diabetes, machine learning, 30-day readmission, metaheuristic

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Authors: Tiago do Carmo Nogueira, Cássio Dener Noronha Vinhal, Gélson da Cruz Júnior, Matheus Rudolfo Diedrich Ullmann

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Generating automatic image descriptions through natural language is a challenging task. Image captioning is a task that consistently describes an image by combining computer vision and natural language processing techniques. To accomplish this task, cutting-edge models use encoder-decoder structures. Thus, Convolutional Neural Networks (CNN) are used to extract the characteristics of the images, and Recurrent Neural Networks (RNN) generate the descriptive sentences of the images. However, cutting-edge approaches still suffer from problems of generating incorrect captions and accumulating errors in the decoders. To solve this problem, we propose a model based on the encoder-decoder structure, introducing a module that generates the weights according to the importance of the word to form the sentence, using the part-of-speech (PoS). Thus, the results demonstrate that our model surpasses state-of-the-art models.

Keywords: gated recurrent units, caption generation, convolutional neural network, part-of-speech

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Authors: Mahalingam Palaniandi

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Higher education plays vital role in the nation building process for a country and the rest of world. The higher education sector develops the change-agents for the various fields which will help the human-kind wheel to run further. Conventional and traditional class-room based learning and teaching was followed in many decades which is one-to-one and one-to-many. In a way, these are simplest form of learners to be assembled in a class room wherein the teacher used the blackboard to demonstrate the theory and laboratories used for practical. As the technology evolved tremendously for the last 40 years, the teaching and learning environment changed slowly, wherein, the learning community will be anywhere in the world and teacher deliver the content through internet based tools such as video conferencing, web based conferencing tools or E-learning platforms such as Blackboard or noodle. Present day, the mobile technologies plays an important tool to deliver the teaching content on-the-go. Both PC based and mobile based learning technology brought the learning and teaching community together in various aspects. However, as the learning technology also brought various hurdles for learning processes such as plagiarism and not using the reference books entirely as most of the students wants the information instantaneously using internet without actually going to the library to take the notes from the millions of the books which are not available online as e-books which result lack of fundamental knowledge of the concepts complex theories. However, technology is inseparable in human life, now-a-days and every part of it contains piece of information technology right from computers to home appliances. To make use of the IT based learning and teaching at most efficiency, we should have a proper framework and recommendations laid to the learning community in order to derive the maximum efficiency from the IT based teaching and leaning. This paper discusses various IT based tools available for the learning community, efficiency from its usage and recommendations for the suitable framework that needs to be implemented at higher education institutions which makes the learners stronger in both theory as well as real-time knowledge of their studies that is going to be used in their future for the better world.

Keywords: higher education, e-learning, teaching learning, eLearning tools

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Authors: Bahareh Mostofian

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Foreign Direct Investment (FDI) has long been recognized as a crucial driver of economic growth and development in less-developed countries and their integration into Global Production Networks (GPNs). FDI not only brings capital from the core countries but also technology, innovation, and know-how knowledge that can upgrade the capabilities of host automotive industries. On the other hand, FDI can also have negative impacts on host countries if it leads to significant import dependency. In the case of the Iranian automotive sector, the industry greatly benefited from FDI, with Western carmakers dominating the market. Over time, various types of know-how knowledge, including joint ventures (JVs), trade licenses, and technical assistance, have been provided, helping Iran upgrade its automotive industry. While after the severe geopolitical obstacles imposed by both the EU and the U.S., the industry became over-reliant on the car and spare parts imports, and the lack of emphasis on knowledge transfer further affected the growth and development of the Iranian automotive sector. To address these challenges, current research has adopted a descriptive-analytical methodology to illustrate the gradual changes accrued with foreign suppliers through FDI. The research finding shows that after the two-phase imposed sanctions, the detrimental linkages created by overreliance on the car and spare parts imports without any industrial upgrading negatively affected the growth and development of the national and assembled products of the Iranian automotive sector.

Keywords: less-developed country, FDI, GPNs, automotive industry, Iran

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Authors: S. K. Ashiquer Rahman

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This paper presents a knowledge mediation platform, “ePLANETe Blue” that addresses the challenge of building knowledge partnerships for higher education. The purpose is to present, as an institutional perception, the ‘ePLANETe' idea and functionalities as a practical and pedagogical innovation program contributing to the collaborative learning goals in higher education. In consequence, the set of functionalities now amalgamated in ‘ePLANETe’ can be seen as an investigation of the challenges of “Collaborative Learning Digital Process.” It can exploit the system to facilitate collaborative education, research and student learning in higher education. Moreover, the platform is projected to support the identification of best practices at explicit levels of action and to inspire knowledge interactions in a “virtual community” and thus to advance in deliberation and learning evaluation of higher education through the engagement of collaborative activities of different sorts.

Keywords: mediation, collaboration, deliberation, evaluation

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Authors: Shamsher Singh

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The Diaspora Literature involves a concept of native land, from where the displacement occurs and a record of harsh journeys undertaken on account of economic compulsions. Basically, Diaspora is a splintered community living in eviction. The scattering (initially) signifies the location of a fluid human autonomous space involving a complex set of negotiations and exchange between the nostalgia and desire for the native land and the making of a new home, adapting to the relationships between the minority and majority, being spokes persons for minority rights and their people back native place and significantly transacting the Contact Zone - a space changed with the possibility of multiple challenges. They write in the background of the sublime qualities of their homeland and, at the same time, try to fit themselves into the traditions and cultural values of other strange communities or land. It also serves as an interconnection of the various cultures involved, and it is used to understand the customs of different cultures and countries; it is also a source of inspiration globally. Although diasporic literature originated back in the 20th century, it spread to other countries like Britain, Canada, America, Denmark, Netherland, Australia, Kenya, Sweden, Kuwait and different parts of Europe. Meaning of Diaspora is the combination of two words which means the movement of people away from their own country or motherland. From a historical point of view, the ‘Diaspora’ is often associated with Jewish bigotry. At the moment, the Diaspora is used for the dispersal of social or cultural groups. This group will be living in two different streams of cultures at the same time. One who left behind his culture and the other has to adapt himself to new cultural situations. The diasporic mind hangs between his birth land and place of work at the same time. A person’s mental state, living in dual existence, gives birth to Dysphoria sensation. Litterateurs had different experiences in this type of sensation e.g., social, universal, political, economic and experiences from the strange land. The struggle of these experiences is seen in diasporic literature. When a person moves to different land or country to fulfill his dreams, the discrimination of language, work and other difficulties with strangers make his relationship more emotional and deeper into his past. These past memories and relations create more difficulties in settling in a foreign land. He lives there physically, but his mental state is in his past constantly, and he ends up his life in those background memories. A person living in Diaspora is actually a dual visionary man. Although this double vision expands his global consciousness, due to this vision, he gains judgemental qualities to understand others. At the same time, he weighs his respect for his native land and the situations of foreign land he experiences, and he finds it difficult to survive in those conditions. It can be said that diaspora literature indicates a person or social organization who lives dual life inquisition structure which becomes the cause of diasporic literature.

Keywords: homeland sickness, language problem, quest for identity, materialistic desire

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Authors: Ying Zhou, Jian-Hua Wang

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Based upon the self-determination theory and self-regulated learning theory, this study examined the predictiveness of goal orientation and self-regulated learning strategies on academic achievement of adult students in distance learning. The results show a positive relation between goal orientation and the use of self-regulated strategies, and academic achievements. A significant and positive indirect relation of mastery goal orientation through self-regulated learning strategies was also found. In addition, results pointed to a positive indirect impact of performance-approach goal orientation on academic achievement. The effort regulation strategy fully mediated this relation. The theoretical and instructional implications are discussed. Interventions can be made to motivate students’ mastery or performance approach goal orientation and help them manage their time or efforts.

Keywords: goal orientation, self-regulated strategies, achievement, adult distance students

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Authors: Christie DeGregorio

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In today's rapidly evolving educational landscape, adult learners are becoming an increasingly significant demographic. These individuals often possess a wealth of life experiences and diverse interests that can greatly influence their learning styles. Recognizing and incorporating these interests into educational practices can lead to enhanced engagement, motivation, and overall learning outcomes for adult learners. This essay aims to explore the significance of incorporating adult learners' interests into learning styles and provide an overview of the methodologies used in related studies. When investigating the incorporation of adult learners' interests into learning styles, researchers have employed various methodologies to gather valuable insights. These methodologies include surveys, interviews, case studies, and classroom observations. Surveys and interviews allow researchers to collect self-reported data directly from adult learners, providing valuable insights into their interests, preferences, and learning styles. Case studies offer an in-depth exploration of individual adult learners, highlighting how their interests can be integrated into personalized learning experiences. Classroom observations provide researchers with a firsthand understanding of the dynamics between adult learners' interests and their engagement within a learning environment. The major findings from studies exploring the incorporation of adult learners' interests into learning styles reveal the transformative impact of this approach. Firstly, aligning educational content with adult learners' interests increases their motivation and engagement in the learning process. By connecting new knowledge and skills to topics they are passionate about, adult learners become active participants in their own education. Secondly, integrating interests into learning styles fosters a sense of relevance and applicability. Adult learners can see the direct connection between the knowledge they acquire and its real-world applications, which enhances their ability to transfer learning to various contexts. Lastly, personalized learning experiences tailored to individual interests enable adult learners to take ownership of their educational journey, promoting lifelong learning habits and self-directedness.

Keywords: integration, personalization, transferability, learning style

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Authors: Elcin Timur Cakmak, Ayse Oguzlar

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This study presents the results of the tweets sent by Twitter users on social media about the Russia-Ukraine war by bigram and trigram methods. On February 24, 2022, Russian President Vladimir Putin declared a military operation against Ukraine, and all eyes were turned to this war. Many people living in Russia and Ukraine reacted to this war and protested and also expressed their deep concern about this war as they felt the safety of their families and their futures were at stake. Most people, especially those living in Russia and Ukraine, express their views on the war in different ways. The most popular way to do this is through social media. Many people prefer to convey their feelings using Twitter, one of the most frequently used social media tools. Since the beginning of the war, it is seen that there have been thousands of tweets about the war from many countries of the world on Twitter. These tweets accumulated in data sources are extracted using various codes for analysis through Twitter API and analysed by Python programming language. The aim of the study is to find the word sequences in these tweets by the n-gram method, which is known for its widespread use in computational linguistics and natural language processing. The tweet language used in the study is English. The data set consists of the data obtained from Twitter between February 24, 2022, and April 24, 2022. The tweets obtained from Twitter using the #ukraine, #russia, #war, #putin, #zelensky hashtags together were captured as raw data, and the remaining tweets were included in the analysis stage after they were cleaned through the preprocessing stage. In the data analysis part, the sentiments are found to present what people send as a message about the war on Twitter. Regarding this, negative messages make up the majority of all the tweets as a ratio of %63,6. Furthermore, the most frequently used bigram and trigram word groups are found. Regarding the results, the most frequently used word groups are “he, is”, “I, do”, “I, am” for bigrams. Also, the most frequently used word groups are “I, do, not”, “I, am, not”, “I, can, not” for trigrams. In the machine learning phase, the accuracy of classifications is measured by Classification and Regression Trees (CART) and Naïve Bayes (NB) algorithms. The algorithms are used separately for bigrams and trigrams. We gained the highest accuracy and F-measure values by the NB algorithm and the highest precision and recall values by the CART algorithm for bigrams. On the other hand, the highest values for accuracy, precision, and F-measure values are achieved by the CART algorithm, and the highest value for the recall is gained by NB for trigrams.

Keywords: classification algorithms, machine learning, sentiment analysis, Twitter

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Authors: Layla Albdr

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Saudi Arabia instituted the policy of Sensitizing and Training Stakeholders for E-learning and witnessed wide adoption in many institutions. However, it is at the infancy stage and needs time to develop to mirror the US and UK. The majority of the higher education institutions in Saudi Arabia have adopted E-learning as an alternative to traditional methods to advance education. Conversely, effective implementation of the policy of sensitization and training of stakeholders for E-learning implementation has not been attained because of various challenges. The objectives included determining the challenges and opportunities of the E-learning policy of sensitization and training of stakeholders in Saudi Arabia's higher education and examining if sensitization and training of stakeholder's policy will help promote the implementation of E-learning in institutions. The study employed a descriptive research design based on qualitative analysis. The researcher recruited 295 students and 60 academic staff from four Saudi Arabian universities to participate in the study. An online questionnaire was used to collect the data. The data was then analyzed and reported both quantitatively and qualitatively. The analysis provided an in-depth understanding of the opportunities and challenges of E-learning policy in Saudi Arabian universities. The main challenges identified as internal challenges were the lack of educators’ interest in adopting the policy, and external challenges entailed lack of ICT infrastructure and Internet connectivity. The study recommends encouraging, sensitizing, and training all stakeholders to address these challenges and adopt the policy.

Keywords: e-learning, educational policy, Saudi Arabia, policy of sensitization and training

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Authors: Nasrin Mohammadhasani, Rosa Angela Fabio

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The attention to relevance information is the key element for learning. Otherwise, Attention Deficit Hyperactivity Disorder (ADHD) students have a fuzzy visual pattern that prevents them to attention and remember learning subject. The present study aimed to test the hypothesis that the presence of a pedagogical agent can effectively support ADHD learner's attention and learning outcomes in a multimedia learning environment. The learning environment was integrated with a pedagogical agent, named Koosha as a social peer. This study employed a pretest and posttest experimental design with control group. The statistical population was 30 boys students, age 10-11 with ADHD that randomly assigned to learn with/without an agent in well designed environment for mathematic. The results suggested that experimental and control groups show a significant difference in time when they participated and mathematics achievement. According to this research, using the pedagogical agent can enhance learning of ADHD students by gaining and guiding their attention to relevance information part on display, so it can be considered as asocial cue that provides theme cognitive supports.

Keywords: attention, computer assisted instruction, multimedia learning environment, pedagogical agent

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Authors: Mahesh Balan U, Rohith Srinivaas Mohanakrishnan, Venkat Subramanian

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Positive and unlabeled learning (PU) has gained more attention in both academic and industry research literature recently because of its relevance to existing business problems today. Yet, there still seems to be some existing challenges in terms of validating the performance of PU learning, as the actual truth of unlabeled data points is still unknown in contrast to a binary classification where we know the truth. In this study, we propose a novel PU learning technique based on the Pseudo-F measure, where we address this research gap. In this approach, we train the PU model to discriminate the probability distribution of the positive and unlabeled in the validation and spy data. The predicted probabilities of the PU model have a two-fold validation – (a) the predicted probabilities of reliable positives and predicted positives should be from the same distribution; (b) the predicted probabilities of predicted positives and predicted unlabeled should be from a different distribution. We experimented with this approach on a credit marketing case study in one of the world’s biggest fintech platforms and found evidence for benchmarking performance and backtested using historical data. This study contributes to the existing literature on semi-supervised learning.

Keywords: PU learning, semi-supervised learning, pseudo f measure, classification

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Authors: S. Turkan

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In this paper, the Turkey’s Top 500 Industrial Enterprises data in 2014 were analyzed by data envelopment analysis. Data envelopment analysis is used to detect efficient decision-making units such as universities, hospitals, schools etc. by using inputs and outputs. The decision-making units in this study are enterprises. To detect efficient enterprises, some financial ratios are determined as inputs and outputs. For this reason, financial indicators related to productivity of enterprises are considered. The efficient foreign weighted owned capital enterprises are detected via super efficiency model. According to the results, it is said that Mercedes-Benz is the most efficient foreign weighted owned capital enterprise in Turkey.

Keywords: data envelopment analysis, super efficiency, logistic regression, financial ratios

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Authors: Naduni Ranasinghe

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E-learning environments are getting more popular than any other due to the impact of COVID19. Even though e-learning is one of the best solutions for the teaching-learning process in the academic process, it’s not without major challenges. Nowadays, machine learning approaches are utilized in the analysis of how behavioral factors lead to better adoption and how they related to better performance of the students in eLearning environments. During the pandemic, we realized the academic process in the eLearning approach had a major issue, especially for the performance of the students. Therefore, an approach that investigates student behaviors in eLearning environments using a data-intensive machine learning approach is appreciated. A hybrid approach was used to understand how each previously told variables are related to the other. A more quantitative approach was used referred to literature to understand the weights of each factor for adoption and in terms of performance. The data set was collected from previously done research to help the training and testing process in ML. Special attention was made to incorporating different dimensionality of the data to understand the dependency levels of each. Five independent variables out of twelve variables were chosen based on their impact on the dependent variable, and by considering the descriptive statistics, out of three models developed (Random Forest classifier, SVM, and Decision tree classifier), random forest Classifier (Accuracy – 0.8542) gave the highest value for accuracy. Overall, this work met its goals of improving student performance by identifying students who are at-risk and dropout, emphasizing the necessity of using both static and dynamic data.

Keywords: academic performance prediction, e learning, learning analytics, machine learning, predictive model

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Authors: Clement C. Aladi, Zhaoxia Yi

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This study investigates factors influencing the implementation of flexible curricula in e-learning in Information Systems (IS) higher education. Drawing from curriculum theorists and contemporary literature, and using the Technology, Pedagogy, and Content Knowledge (TPACK) framework, it explores teacher-related challenges and their impact on curriculum flexibility implementation. By using the PLS-SEM, the study uncovers these factors and hopes to contribute to enhancing curriculum flexibility in delivering online and blended learning in IS higher education.

Keywords: flexible curriculum, online learning, e-learning, technology

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Authors: Promise Ekpo Osaine, Daniel Melesse

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Image captioning is an active area of research in the multi-modal artificial intelligence (AI) community as it connects vision and language understanding, especially in settings where it is required that a model understands the content shown in an image and generates semantically and grammatically correct descriptions. In this project, we followed a standard approach to a deep learning-based image captioning model, injecting architecture for the encoder-decoder setup, where the encoder extracts image features, and the decoder generates a sequence of words that represents the image content. As such, we investigated image encoders, which are ResNet101, InceptionResNetV2, EfficientNetB7, EfficientNetV2M, and CLIP. As a caption generation structure, we explored long short-term memory (LSTM). The CLIP-LSTM model demonstrated superior performance compared to the encoder-decoder models, achieving a BLEU-1 score of 0.904 and a BLEU-4 score of 0.640. Additionally, among the CNN-LSTM models, EfficientNetV2M-LSTM exhibited the highest performance with a BLEU-1 score of 0.896 and a BLEU-4 score of 0.586 while using a single-layer LSTM.

Keywords: multi-modal AI systems, image captioning, encoder, decoder, BLUE score

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Authors: Engku Haliza Engku Ibrahim, Isarji Sarudin, Ainon Jariah Muhamad

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It is generally agreed that many factors contribute to one’s reading comprehension and there is consensus that vocabulary size one of the main factors. This study explores the relationship between second language learners’ vocabulary size and their reading comprehension scores. 130 Malay pre-university students of a public university participated in this study. They were students of an intensive English language programme doing preparatory English courses to pursue bachelors degree in English. A quantitative research method was employed based on the Vocabulary Levels Test by Nation (1990) and the reading comprehension score of the in-house English Proficiency Test. A review of the literature indicates that a somewhat positive correlation is to be expected though findings of this study can only be explicated once the final analysis has been carried out. This is an ongoing study and it is anticipated that results of this research will be finalized in the near future. The findings will help provide beneficial implications for the prediction of reading comprehension performance. It also has implications for the teaching of vocabulary in the ESL context. A better understanding of the relationship between vocabulary size and reading comprehension scores will enhance teachers’ and students’ awareness of the importance of vocabulary acquisition in the L2 classroom.

Keywords: vocabulary size, vocabulary learning, reading comprehension, ESL

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Authors: Maria Gabrielle "Abby" Dalmacio

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Social-emotional learning is a concept that is garnering more importance when considering the development of young children. The aim of this scoping literature review is to explore the implementation of social-emotional learning programs conducted with first-generation immigrant young children ages 3-12 years in North America. This review of literature focuses on social-emotional learning programs taking place in early childhood education centres and elementary school settings that include the first-generation immigrant children population to determine if and how their understanding of social-emotional learning skills may be impacted by the curriculum being taught through North American educational pedagogy. Research on early childhood education and social-emotional learning reveals the lack of inter-cultural adaptability in social emotional learning programs and the potential for immigrant children as being assessed as developmentally delayed due to programs being conducted through standardized North American curricula. The results of this review point to a need for more research to be conducted with first-generation immigrant children to help reform social-emotional learning programs to be conducive for each child’s individual development. There remains to be a gap of knowledge in the current literature on social-emotional learning programs and how educators can effectively incorporate the intercultural perspectives of first-generation immigrant children in early childhood education.

Keywords: early childhood education, social-emotional learning, first-generation immigrant children, north america, inter-cultural perspectives, cultural diversity, early educational frameworks

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Authors: Iran Kalbasi, Foroozandeh Zardashti

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Dialectology is a branch of social linguistics that studies systematic language variations. Dialects are the branches of a unique language that have structural, morphological and phonetic differences with each other. In Iran, these dialects and language variations themselves have a lot of cultural loads, and studying them have linguistic and cultural importance. In this study, phonetic structure of two Iranian dialects, Bakhtiyari Lori of Masjedsoleyman and Shushtari in Khuzestan Province of Iran have been surveyed. Its statistical community includes twenty speakers of two dialects. The theoretic bases of this research is based on structuralism. Its data have been collected by interviewing the questionnaire that consist of 3000 words, 410 sentences and 110 complex and simple verbs. These datas are analysed and described synchronically. Then, the phonetic characteristics of these two dialects and standard Persian have been compared. Therefore, we can say that in phonetic level of these two dialects and standard Persian, there are clearly differences.

Keywords: standard language, dialectology, bakhtiyari lori dialect of Masjedsoleyman, Shushtari dialect, vowel, consonant

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Authors: Ladda Silanoi

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One of the main purposes in establishment of ASEAN Community is educational development. All countries in ASEAN shall then prepare for plans and strategies for country development. Therefore, Thailand set up the policy concerning educational management for all educational institutions to understand about ASEAN Community. However, some educational institutions lack of precision in determining the curriculums of ASEAN Community, especially schools in rural areas, for example, schools along the common border with Laos, and Cambodia. One of the effective methods to promote the precision in ASEAN Community is to design additional learning courses. The important process of additional learning courses design is to provide learning outcomes of ASEAN Community for course syllabus determination. Therefore, the researcher is interested in developing teachers in the schools of common border with Laos, and Cambodia to provide learning outcomes and learning process. This research has the objective of developing the learning outcomes and learning process management of basic education along Thailand, Laos, and Cambodia Common Border for the ASEAN Community Preparation. Research methodology consists of 2 steps. Step 1: Delphi Technique was used to provide guidelines in development of learning outcomes and learning process. Step 2: Action Research procedures was employed to study the result of additional learning courses design. Result of the study: By using Delphi technique, consensus is expected to be achieved, from 50 experts in the study within 3 times of the survey. The last survey found that experts’ opinions were compatible on every item (inter-quartile range = 0) leading to the arrangement of training courses in step of Action Research. The result from the workshop found that teachers in schools of Srisaket and Bueng Kan provinces could be able to provide learning outcomes of all courses.

Keywords: learning outcome and learning process, basic education, ASEAN Community preparation, Thailand Laos and Cambodia common border

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Authors: Asish O. Mathew, Lewlyn L. R. Rodrigues

Abstract:

The organizations in the knowledge economy era have recognized the importance of building knowledge assets for sustainable growth and development. In comparison to other industries, Information Technology (IT) enterprises, holds an edge in developing an effective Knowledge Management (KM) program, thanks to their in-house technological abilities. This paper tries to study the various knowledge-based incentive programs and its effect on Knowledge Sharing and Learning in the context of the Indian IT sector. A conceptual model is developed linking KM incentives, knowledge sharing, and learning. A questionnaire study is conducted to collect primary data from the knowledge workers of the IT organizations located in India. The data was analysed using Structural Equation Modeling using Partial Least Square method. The results show a strong influence of knowledge management incentives on knowledge sharing and an indirect influence on learning.

Keywords: knowledge management, knowledge management incentives, knowledge sharing, learning

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Authors: Samar Alharbi, Yota Dimitriadi

Abstract:

With the exponential growth of information and communication technologies in higher education, new online teaching strategies have become increasingly important for student engagement and learning. In particular, some institutions depend solely on asynchronous e-learning to provide courses for their students. The major challenge facing these institutions is how to improve the quality of teaching and learning in their asynchronous tools. One of the most important methods that can help e-learner to enhance their social learning and social presence in asynchronous learning setting is immediacy. This study explores tutors perceptions of their instructional immediacy practices as part of their communication actions in online learning environments. It was used a mixed-methods design under the umbrella of pragmatic philosophical assumption. The participants included tutors at an educational institution in a Saudi university. The participants were selected with a purposive sampling approach and chose an institution that offered fully online courses to students. The findings of the quantitative data show the importance of teachers’ immediacy practices in an online text-based learning environment. The qualitative data contained three main themes: the tutors’ encouragement of student interaction; their promotion of class participation; and their addressing of the needs of the students. The findings from these mixed methods can provide teachers with insights into instructional designs and strategies that they can adopt in order to use e-immediacy in effective ways, thus improving their students’ online learning experiences.

Keywords: asynchronous e-learning, higher education, immediacy, tutor

Procedia PDF Downloads 184

Authors: Lei Zhang, Tingting Xu, Jun He, Zhenyu Yan

Abstract:

Email marketing is one of the most important segments of online marketing. It has been proved to be the most effective way to acquire and retain customers. The email content is vital to customers. Different customers may have different familiarity with a product, so a successful marketing strategy must personalize email content based on individual customers’ product affinity. In this study, we build our personalized email marketing strategy with three types of emails: nurture, promotion, and conversion. Each type of email has a different influence on customers. We investigate this difference by analyzing customers’ open rates, click rates and opt-out rates. Feature importance from response models is also analyzed. The goal of the marketing strategy is to improve the click rate on conversion-type emails. To build the personalized strategy, we formulate the problem as a reinforcement learning problem and adopt a Q-learning algorithm with variations. The simulation results show that our model-based strategy outperforms the current marketer’s strategy.

Keywords: email marketing, email content, reinforcement learning, machine learning, Q-learning

Procedia PDF Downloads 178

Authors: Krongthong Khairiree

Abstract:

The purpose of this research study is to explore mathematics project-based learning approach and the use of technology in the context of school mathematics in Thailand. Data of the study were collected from 6 sample secondary schools and the students were 6-14 years old. Research findings show that through mathematics project-based learning approach and the use of GSP, students were able to make mathematics learning fun and challenging. Based on the students’ interviews they revealed that, with GSP, they were able to visualize and create graphical representations, which will enable them to develop their mathematical thinking skills, concepts and understanding. The students had fun in creating variety of graphs of functions which they can not do by drawing on graph paper. In addition, there are evidences to show the students’ abilities in connecting mathematics to real life outside the classroom and commercial products, such as weaving, patterning of broomstick, and ceramics design.

Keywords: mathematics, project-based learning, Geometer’s Sketchpad (GSP), commercial products

Procedia PDF Downloads 322