The study aimed to investigate the language learning strategies and their contribution to the language competence of English major students in the teacher education program at Kapalong College of Agriculture Sciences and Technology. The researcher utilized a mixed-method design using the convergent parallel approach. Participants were English major students across all year levels at the college institution, with 204 students randomly selected for the quantitative phase and approximately 10 students purposively selected for the qualitative phase: 5 for (...) in-depth interviews and 5 for focused group discussions. The results indicated that both the level of language learning strategies and language competence were high; the findings were rejected, which reveals that there is significant relationship between them. Further, the findings from both the quantitative and qualitative phases largely converged however, there was one divergent indicator. The study confirmed that language learning strategies significantly impact the enhancement of language competencies among English major students, facilitating effective and efficient language use in realistic contexts. It is recommended that language learners must also prioritize memory strategies despite from the indicators’ lowest mean based from the results, such as mnemonic devices and spaced repetition techniques, to enhance vocabulary and grammar retention. Additionally, to improve speaking competency, students should engage in practical applications of the language within their specific contexts, allowing them to practice and develop fluency, essential for effective communication in professional, social, and academic environments. (shrink)

Abstract: The aim of this study was to investigate the factors that causes anxiety in learning of English as second language. Secondary school students, English language teachers and school factors were focused that ground the anxiety in learning of English language as second language among the learners. Under the umbrella of qualitative research, a case study design selected and one to one semi structured interview. Convenience sampling was used in selection of students and purposive (...) sampling for English language teachers. Findings were that ELL is important because it is international language and medium of instruction at higher education institutes. Moreover, teacher employ GMT and lecture based teaching which hinder the ELL. Likewise, our environment also do not support ELL because neither parents nor friends take it seriously. Findings of the study suggest that in addition to GMT English language teacher must use interactive ELL. Parents and friends are also support and create supportive environment for children that enable them to ELL. (shrink)

English is essential as an effective communication tool in both local and international contexts. In addition to being used in schools, it is also a teaching tool in colleges and universities. ESL (English as a Second Language) classes are now required in all educational institutions and can't be skipped. When learning a second language, anyone must be physically, mentally, and emotionally involved to communicate and understand what is being said. This systematic review employed qualitative documentary research and (...) adopted content analysis. Following a random selection of reliable and legitimate sources, purposive sampling was used to conduct a content analysis of the selected papers. For this systematic review, sources from EBSCO, Google Scholar, Scopus, Web of Science, and ScienceDirect were used. The findings reveal that English-language obstacles in this article include English learners' writing, speaking, listening, reading, translation, and interpretation skills. The conclusion focuses on English learning obstacles and their improvement through teaching methods and educational technology adoption. The recommendation is to look into quantitative and qualitative research for further study. (shrink)

Quine has been charged with eliminating the normative dimension from his naturalized epistemology. The aim of the paper is to look at the role of empathy in Quine's language learning situation, which in its simplest form is constituted by the parent-child relation. We will explore the normativity of the role of empathy thereof by exploiting the sociality of the language learning situation. Since the sociality of Quine's notion of empathy is implicit, to explore the normativity expression (...) thereof, we will examine the explicit sociality of Wittgenstein's language learning situation-also constituted in its simplest form by the master-novice relation-and the normative character of it. By explicating the normativity of the calibrating role of the master and of rule following generally, we will parse the social dimensions of the empathizing role of the linguist in Quine's language learning situation. Finally, by examining the nature of normativity in empathizing, we will establish that the normativity of empathizing involved in Quine's language learning situation is socially grounded without denying its individual dimension. We will conclude that the normativity objection against Quine's naturalism thus stands refuted. (shrink)

Reading tough books to achieve excellent marks, perform well in class, and gain attention from teachers and parents is less likely to drive students. Students used to evaluate their language learning requirements, define the abilities they wished to develop, pick effective study techniques, and set aside gadgets when studying. They also used to read the question before looking for hints in the relevant content, extract the essential lines that convey the major ideas, concentrate on titles, names, numbers, quotations, (...) or instances, and comprehend the overall context to infer an option. The survey discovered that most of the time, students utilized it to determine the progress of their learning and create learning objectives. It was also found that there was a link between the exogenous variables and the academic performance of students. (shrink)

This study examined the opportunities and challenges faced by Filipino learners in the newly introduced Korean language course within the Special Program in Foreign Language (SPFL) and its relationship to their proficiency. Using an explanatory sequential method, the research was conducted in three phases. In Phase 1, 32 students took the Test of Proficiency in Korean (TOPIK I) and completed a survey. The results indicated that 62.5% passed TOPIK I, suggesting that more than half had a solid grasp (...) of the Korean language. The survey revealed manageable challenges in learning Korean, with a composite mean of 1.85 and a verbal interpretation of “Disagree.” However, thematic analysis in Phase II identified specific challenges, such as difficulties with Korean tenses, particles, vocabulary, and anxiety over making mistakes, which affected students’ comprehension. In contrast, the survey indicated positive opportunities for learning Korean, with a composite mean of 3.57 and a verbal interpretation of “Strongly Agree.” Notable themes included improved college admissions, job prospects, and increased cultural awareness. Data also found no significant relationship between students’ proficiency levels—high or low—and their challenges and opportunities in learning Korean. Based on these findings, an Action Plan was proposed to enhance areas for improvement in Korean language learning for SPFL enrollees, aiming to involve school stakeholders in supporting the development of Korean language skills. (shrink)

This paper explores the integration of multiple intelligences and artificial intelligence (AI) in language learning, focusing on its potential to enhance personalization and engagement. Drawing from existing research and studies conducted in various contexts, including the Philippines, this study aims to contribute to the understanding of the benefits, challenges, and effectiveness of this integration. The paper begins with an introduction that highlights the background and significance of integrating multiple intelligences and AI in language learning, identifying research (...) gaps, objectives, research questions, and the theoretical framework. A literature review provides an overview of multiple intelligences theory by Howard Gardner, the role of AI in language learning, and identifies gaps in the existing literature. The methodology section outlines the research design and approach, participant selection, data collection methods, validity and reliability measures, and ethical considerations. Findings and results are presented through the analysis of qualitative data, exploring emergent themes and patterns. The discussion section critically examines the identified research gaps, discusses the validity and reliability of the study, addresses the scope and limitations, and explores the implications of the findings for theory, practice, and future research. The conclusion summarizes the key findings and contributions of the study, reflects on the achievement of research objectives, offers recommendations for further research, and provides final remarks tying together the main points of the study. This paper contributes to the existing body of knowledge by providing insights into the integration of multiple intelligences and AI in language learning and its impact on personalization, engagement, and language learning outcomes. (shrink)

The advent of digital games in language classrooms has ushered in a new era of interactive and dynamic learning experiences. Among these platforms, Kahoot stands out as an engaging and entertaining gaming platform, capturing the attention of both instructors and students. Despite the previous studies on the impact of Kahoot on language learning motivation, they have predominantly focused on assessing the effects of Kahoot before and after instruction overlooking direct comparisons with traditional instructional methods. Consequently, the (...) present study utilized a quasi-experimental research design, and participants were divided into two groups: an experimental group that received instruction using Kahoot, and a control group that followed traditional instructional methods. This research design allowed for a direct comparison of the impact of Kahoot on students’ motivation to learn the language. The results revealed a significant positive impact of Kahoot on students’ motivation to learn English. The students perceived Kahoot as engaging and enjoyable, resulting in heightened enthusiasm and interest inlanguage learning. These findings highlight the transformative potential of Kahoot as a catalyst for enhancing language learning motivation. Integrating Kahoot and other innovative online platforms into EFL instruction can create dynamic, interactive learning environments that foster student engagement and motivation. (shrink)

Abstract: Sign language recognition is one of the most rapidly expanding fields of study today. Many new technologies have been developed in recent years in the fields of artificial intelligence the sign language-based communication is valuable to not only deaf and dumb community, but also beneficial for individuals suffering from Autism, downs Syndrome, Apraxia of Speech for correspondence. The biggest problem faced by people with hearing disabilities is the people's lack of understanding of their requirements. In this paper (...) we try to fill this gap. By trying to translate sign language using artificial intelligence algorithms, we focused in this paper using transfer learning technique based on deep learning by utilizing a MobileNet algorithm and compared it with the previous paper results[10a], where we get in the Mobilenet algorithm on the degree of Accuracy 93,48% but the VGG16 the accuracy was 100% For the same number of images (43500 in the dataset in size 64*64 pixel ) and the same data split training data into training dataset (70%) and validation dataset(15%) and testing dataset(15%) and 20 epoch . (shrink)

American Sign Language, or ASL as its acronym is commonly known, is a fascinating language, and many people outside of the Deaf community have begun to recognize its value and purpose. It is a visual language consisting of coordinated hand gestures, body movements, and facial expressions. Sign language is not a universal language; it varies by country and is heavily influenced by the native language and culture. The American Sign Language alphabet and the (...) British Sign Language alphabet are completely contrary. Fingerspelling is one-handed in ASL and two-handed in BSL, with the exception of the letter C. AI technologies, particularly deep learning, can play an important role in breaking down communication barriers between deaf or hearing-impaired people and other communities, significantly contributing to their social inclusion. Recent advances in sensing technologies and AI algorithms have paved the way for the development of a wide range of applications aimed at meeting the needs of the deaf and hearing-impaired communities. To that end, the purpose of this paper is By attempting to translate sign language using artificial intelligence algorithms, we focused in this paper on a transfer learning technique based on deep learning using a ResNet algorithm and compared it to previous papers in which we used VGG19[1]and mobileNet [2], where we get in the ResNet algorithm on the degree of Accuracy 93,48% e number of images (43500 in the dataset in size 64*64 pixel ) and the data split training data into training dataset (70%) and validation dataset(15%) and testing dataset(15%) and 20 epoch. (shrink)

In her ‘Spracherwerb’(2012) Ruth Millikan gives a compelling account of language acquisition based on our ability to track objects. I argue that, and how, it is undermined by her insistence on equating understanding language utterances and sense perception, point to idealist hazards, and plead against propositionality and for imagism in order to safeguard the account’s important potential for giving a comprehensive explication of meaning.

there is a communication gap between hearing-impaired people and those with normal hearing, sign language is the main means of communication in the hearing-impaired population. Continuous sign language recognition, which can close the communication gap, is a difficult task since the ordered annotations are weakly supervised and there is no frame-level label. To solve this issue, we compare the accuracy of each model using two deep learning models, Inception and Xception . To that end, the purpose of (...) this paper is By attempting to translate sign language using deep learning models, we focused in this paper a comparing between Inception and Xception ¬¬¬¬¬ algorithm and compared it to previous papers in which we used VGG19[1], mobileNet [2], where we get in the Inception and Xception algorithm on the degree of Accuracy 99.32%, 99,43% respectively. number of images (29000 in the dataset in size 75*75 pixel ) and the data split training data into training dataset (70%) and validation dataset(15%) and testing dataset(15%) and 20 epoch. (shrink)

Text classification is one of the most important task in natural language processing, In this research, we carried out several experimental research on three (3) of the most popular Text classification NLP classifier in Convolutional Neural Network (CNN), Multinomial Naive Bayes (MNB), and Support Vector Machine (SVN). In the presence of enough training data, Deep Learning CNN work best in all parameters for evaluation with 77% accuracy, followed by SVM with accuracy of 76%, and multinomial Bayes with least (...) performance of 69% accuracy. CNN has the best performance in the presence of large enough training dataset because of the presence of filter/ kernels which help to indentify patterns in text data regardless of their position in the sentence. We repeated the training again with just one-third of our data, at this point SVM comes with the best performance, the performance of CNN noticeably drops but still better than Multinomial Naive Bayes, the reason why SVM works best when we reduce the training data was because of its ability to look for a hyper-plane that creates a boundary between different classes of data so as to properly classify them, so we believed that getting the hyper-plane was more efficient when we reduce the dataset, hence reason for the good performance. Multinomial Naive Bayes have the least performance which we attributed to its assumption of independency between the features which sometimes does not hold true. We concluded that availability of data should be an important factor when choosing classifier for Natural Language Processing Text Classification task. CNN should be use in the presence of enough dataset, and SVM should be use when data is not enough. Multinomial Naive Bayes must not be trusted with state of the art NLP task due to its assumption of independency between the features . (shrink)

Digital Literacy (DL) is defined as the ability to use information and communication technology to communicate with cognitive and technical skills. One of the Digital Literacy is Mobile-Assisted Language Learning (MALL) or mobile phones-based language learning. Merits of this study are worthy of helping learners easier understand the language learning materials presented by either guided face to face in the classroom or self-learning out of the school. The study used experimental and control classes (...) to compare the results that the significance of Mobile-Assisted Language Learning in learning language could be prescribed. Refer to the initial students’ ability, this study designed pre and post-test for the experiment. Furthermore, participants were 40 students of second-year students at the English Education Department. Same topics were taught for experiment and control class in alter methods. The results claimed that the using post-test of MALL had merits on improving experimental group more than control group performance. The results declared that using MALL would encourage students learning activities such as self-language learning, enriching vocabulary, promoting teacher’s pedagogic, student’s cognitive, writing skill, reading comprehension, speaking, grammar and listening skill. Lastly, this paper implied MALL as a reference for future curriculum and material development. (shrink)

The development and ubiquitous availability of large language model based systems (LLMs) poses a plurality of potentials and risks for education in schools and universities. In this paper, we provide an analysis and discussion of the overreliance concern as one specific risk: that students might fail to acquire important capacities, or be inhibited in the acquisition of these capacities, because they overly rely on LLMs. We use the distinction between global and local goals of education to guide our investigation. (...) In our view, the harm of LLM overreliance is specifically that it severs the connection between local educational goals (e.g., solving a specific math problem) and global educational goals (e.g., acquiring general skills for mathematics). Based on this analysis, we sketch three possible responses to the overreliance concern: preserving the educational goals while distinguishing admissible from inadmissible uses of LLMs (a conservative approach), changing global and local educational goals (a revisionary perspective), and preserving global educational goals while changing local goals (an in-between view). Since different types of responses have different benefits and weaknesses, we think that it is likely that an optimal response ultimately combines elements from all three types. (shrink)

Students with high motivation to learn English as a second language become efficient language learners and ultimately acquire second language proficiency. However, demotivation in learning English as a second language remains to be a serious challenge. Thus, research-based information is needed to shed light in unravelling the factors of demotivation among second language learners and to guide teachers in putting forward practical solutions to increase students’ motivation in second language learning. This study (...) was conducted to find out the specific factors that hinder students’ desire to learn English as a second language. The researcher used descriptive research design and involved 1,302 students of Palawan State University Cuyo Campus selected through random sampling. Demotivating factors were measured using a modified questionnaire with reliability index of 0.85. Students’ self-confidence, learning content and context, focus of teaching and school facilities are revealed as demotivation to second language learning. The findings of this study may guide English teachers in designing teaching-learning contexts that are interesting and can boost student’s confidence in using English as a second language. It is also beneficial to policymakers and curriculum developers so that necessary policies may be implemented to improve school facilities, teaching strategies, and learning content and context. (shrink)

Sign Language recongnition is getting more and more attention of the researchers due to its widespread applicability in many fileds. Conversation between both the deaf and the general population is becoming exceedingly challenging, and there is no reputable translator accessible in society to aid. This program enables real- time voice and signal language translation, in distinctive : 1. Recognizing male or female signals 2. Establishing a system learning model for interpreting image-to-text data. 3. Seeking innovative terms Four. (...) 4. Constructing Sentences.5. After creating all of the content. 6. Is to obtain the audio output. The goal of this research is yto develop a framework for potential sign language interpreter who could also translate conversations between sign languages into written and spoken English. If there had a translator like this, it would be much easier for many deaf and partially deaf people to interact with others in everyday situations. (shrink)

The article examines the basics of learning a foreign language. The fundamental foundations of this process are chosen. These judgments are made at the intersection of philosophical and pedagogical platforms. Therefore, research is of importance in both aspects, both philosophical and pedagogical. A new concept called ”Intuitive language base" is put forward. With the help of this concept, judgments about the fundamental foundations are made. The main issue explained within the framework of the concept is about words. (...) Thus, it is shown that, unlike the grammatical rules, words have a different fundamental aspect. At the same time, fundamental ideas about translation and scientific language are taken from this concept. In addition, the number of possible words in the world is calculated, judgments about creativity are put forward, fundamental issues such as the concept of the minilex and the music of the language are touched upon, and the attitude is expressed within the proposed concept. (shrink)

How does philosophy learn to speak a new language? That is, how does some particular language come to serve as the means for the expression of philosophical ideas? In this paper, I present an answer grounded in four historical case studies and suggest that this answer has broad implications for contemporary philosophy. I begin with Jonathan Rée’s account of philosophical translation into English in the sixteenth century, and the debate between philosopher-translators who wanted to acquire – wholesale or (...) with modifications – foreign terms, and those who wished to take existing words and transform them from their ordinary to a philosophical use. I sketch how these twin processes of ‘acquisition’ and ‘transformation’ manifested themselves in philosophical translations from Greek to Latin, Greek to Arabic and both Greek and Arabic to Gə’əz and argue that comparative work in this vein could yield interesting and significant results. I suggest that not only is Rée’s approach useful for thinking about philosophical translation historically, but that philosophical translation between very different languages is important for contemporary philosophy insofar as it reveals the linguistic presuppositions of philosophical theories expressed in some particular language, and that this constitutes an argument against the prevailing monolingualism in philosophy. (shrink)

Aesthetic non-cognitivists deny that aesthetic statements express genuinely aesthetic beliefs and instead hold that they work primarily to express something non-cognitive, such as attitudes of approval or disapproval, or desire. Non-cognitivists deny that aesthetic statements express aesthetic beliefs because they deny that there are aesthetic features in the world for aesthetic beliefs to represent. Their assumption, shared by scientists and theorists of mind alike, was that language-users possess cognitive mechanisms with which to objectively grasp abstract rules fixed independently of (...) human responses, and that cognizers are thereby capable of grasping rules for the correct application of aesthetic concepts without relying on evaluation or enculturation. However, in this article I use Wittgenstein’s rule-following considerations to argue that psychological theories grounded upon this so-called objective model of rule-following fail to adequately account for concept acquisition and mastery. I argue that this is because linguistic enculturation, and the perceptual learning that’s often involved, influences and enables the mastery of aesthetic concepts. I argue that part of what’s involved in speaking aesthetically is to belong to a cultural practice of making sense of things aesthetically, and that it’s within a socio-linguistic community, and that community’s practices, that such aesthetic sense can be made intelligible. (shrink)

The present study assessed the language teachers' pedagogical beliefs and orientations in integrating technology in the online classroom and its effect on students' motivation and engagement. It utilized a cross-sectional correlational research survey. The study respondents were the randomly sampled 205 language teachers (μ= 437, n= 205) and 317 language students (μ= 1800, n= 317) of select higher educational institutions in the Philippines. The study results revealed that respondents hold positive pedagogical beliefs and orientations using technology-based teaching (...) in their language classroom. Test of difference showed that female teachers manifested a firmer belief in student-centered online language teaching than their male counterparts. However, the utilization and attitude towards technology in the language classroom is favorably associated with the male teachers. As to students' level of language learning motivation and engagement, it was found out that male and female students have high level of language learning engagement. Further, the test of relationship showed that the higher the teachers' belief in utilizing student-centered teaching to integrate technology in the language classroom, the higher the students are motivated and engaged in learning. In like manner, it was also revealed that teacher-centered belief is negatively correlated to student’s motivation and engagement in online language learning. In this regard, the pedagogical assumptions that hold EFL teachers positively to integrate technology in the language classroom. This study generally offers implications for enhancing language teacher's digital literacy to promote motivating, fruitful, and engaging language lessons for 21ts century learning. (shrink)

Due to the emergence of ICT in ELT sector, seasoned English teachers find it resistant to such a shift despite having a positive attitude towards its use. This quasi-experimental study aimed to examine the extent to which seasoned English language teachers developed their ICT skills through a Service-Learning Activity (SLA). Using a one-group pre- and post-test design, this study collected the data through a modified Needs Assessment Survey (NAS) distributed to fourteen purposively selected participants. It was administered to (...) examine what professional ICT development would greatly benefit them. The data were analyzed using descriptive statistics and themes according to the Service-Learning Activity (SLA) topics. A Post Evaluation Survey (PES) was administered, and its result was compared to the initial test. The results showed that the seasoned teachers gained significant learning gains in terms of (1) sharing of knowledge from other teachers; (2) being encouraged to use ICT tools; (3) training opportunities; (4) working with other colleagues; and 5) attending professional workshops which include SLA. However, this study unveiled that the English teachers had no significant difference in perceptions regarding the roles of computers in teaching before and after the intervention. Limitations and recommendations for future studies were discussed. (shrink)

The objective of the research is to test the feasibility of implementing Structured Rational Thinking to learn disciplinary principles, evaluate written language, and answer the questions: What are its epistemological foundations? What explains why rational thinking is not common in people? How do students modify their conceptualization of thematic principles through it? And how does it help students to build knowledge and express it? Rational thinking was theoretically framed and its derivation into types of structured thinking: logical, methodical, and (...) narrative; and its characterization according to its content, purpose, and structure, in its classical and modern forms. The hypothesis was: "people stop thinking rationally due to the lack of applying a method to order and properly conduct thoughts; one aspect is the method and another is the thought that it generates." Mixed methodology; results, it is expected that 50 students surveyed generate knowledge and language attached to objectified reality. Test 1: the level of understanding was assessed according to types of thinking, in ranges of: little, moderately and a lot, coded with ordinal values in intervals from 0 to 2, by interaction matrix. Test 2: table identifying levels of rational thinking, interval scale: 1 to 2 low level, 3 to 4 medium, 5 to 6 high, more than 6 very high. Conclusions, the effects of not applying a type of thinking that orders ideas to interpret reality and generate proven knowledge, far from conjectures, are outlined. The best thinking, guides reason when faced with compound and dynamic facts. (shrink)

This paper aims to exemplify the language acquisition model by tracing back to the Socratic model of language learning procedure that sets down inborn knowledge, a kind of implicit knowledge that becomes explicit in our language. Jotting down the claims in Meno, Plato triggers a representationalist outline basing on the deductive reasoning, where the conclusion follows from the premises (inborn knowledge) rather than experience. This revolution comes from the pen of Noam Chomsky, who amends the empiricist (...) position on the creativity of language by pinning down it with the innateness hypothesis. However, Chomsky never rejects the external world or the linguistic stipulation that relies on the objective reality. Wittgenstein’s model of language acquisition upholds a liaison centric appeal that stands between experience (use theory of meaning) and mentalism (mind based inner experiences). Wittgenstein’s Tractatus never demarcates the definite mental processes that entangle with the method of understanding and meaning. Wittgenstein’s ‘language game’ takes care of the model of language acquisition in a paradigmatic way. The way portrait language as the form of life and the process of language acquisition is nothing but a language game that relies on the activity of men. (shrink)

The study has been presented the role of home environment to learn English language particularly in Bangladesh. Parental as well as siblings role is very essential to grow the sense of learning and the learners can grow a great influence by it. Parents’ as well as siblings’ positive attitude, education and awareness according to individual requirements and needs are provided constant encouragement and support for the learners. Parents make the greatest difference to achievement through supporting their learning (...) at home rather than supporting activities in school. A learner, whose family members are habituated to use English at home, feels encouraged to learn English which facilitates learning process. My findings, on the other hand, show that children of those parents who are ignorant of providing sound family atmosphere, lack confidence as well as self-esteem. This study also inspects the impact of home environment on children’s achievement in English language. The findings reveal that there is a constant relationship between the role of family and students’ academic achievement. (shrink)

Education is essential to ensure the overall development of individuals. However, there exists a symbiotic relationship between language and education: the language of education determines one’s socio-economic position. Notably, knowledge production and dissemination in South Africa is dominated by English and vernacular languages are neglected. This discriminatory binary exists from primary schools to universities. It creates challenges for black, underprivileged, rural and semi-urban students, as they lack proficiency in English (known as the language of elites). Along with (...) cultural and racial discrimination, students from South Africa are victims of linguicism. Similarly, the modern Indian state has made education mandatory as a policy measure but students from marginalised sections face a language barrier. Consequently, students feel physiological trauma including inferiority complexes, humiliation. (shrink)

The purpose of this research is to design a system using machine learning to automate sign language gesture recognition and facilitate unproblematic interaction between the hearing/speech impaired community and society as a whole. This research works towards solving the communication disability faced by the deaf and mute community through a computer vision framework for recognizing hand gestures and mapping them to relevant text or speech. The work employs a rich dataset of static American Sign Language (ASL) hand (...) signs and uses Convolutional Neural Networks (CNNs) for efficient feature extraction and gesture classification. The suggested model is trained and evaluated on a huge collection of labeled gesture images and exhibits high accuracy with robust generalization to novel data. One of the primary contributions of the work is the implementation of the trained model into an interactive, realtime graphical user interface developed with Python's Tkinter library. The interface captures live input from a webcam, processes each frame to identify gestures, and shows the identified character on the screen. The results of the evaluation confirm the ability of CNNs to accurately identify ASL alphabets with little delay. The proposed system presents an effective and scalable approach towards real-time sign language interpretation, supporting inclusiveness and accessibility of the disabled community. The present research also creates a scope for extension in development, i.e., inclusion of dynamic gesture detection and portability to mobile or embedded platforms to provide enhanced use in real-life situations. (shrink)

This paper is both systematic and historical in nature. From a historical viewpoint, I aim to show that to establish Wittgenstein’s claim that “an ‘inner process’ stands in need of outward criteria” (PI §580) there is an enthymeme in Wittgenstein’s private language argument (henceforth PLA) overlooked in the literature, namely Wittgenstein’s suggestion that both perceptual and bodily experiences are transparent in the relevant sense that one cannot point to a mental state and wonder “What is that?” From a systematic (...) viewpoint, I aim to show that Wittgenstein’s PLA teaches us that the prevailing picture of the nature of phenomenal concepts (henceforth PCs) is upside down: we can only introspectively know what is going on inside our heads after we learn of what is going on outside (PI §580). In this regard, I aim to defend two associate claims against the prevailing view of PCs on the basis of PLA. First, by means of transparency, I aim to show that there is no de re awareness of our private sensation that could determine the meaning of sensation words; for example, I am never aware of the phenomenal blueness of my experience of something blue. The second associated claim is that introspective self-knowledge of our private sensations is always de dicto. We can only know introspectively that phenomenal blueness is the phenomenal character of the experience we are undergoing after we have learned that (de dicto knowledge) blue is the color that usually causes us that kind of experience. Likewise, we can only introspectively know that pain is the phenomenal character of the experience we are undergoing after we have learned that pain is what usually causes some typical pain behavior. (shrink)

This study focused on determining the attitudes and academic performance of engineering students in Technological University of the Philippines-Manila. A total of 139 male engineering and 47 female engineering students were the respondents of the study. This only dwell on the attitude in learning English Language Vocabulary in terms of their behavioral aspects, cognitive aspects, and emotional aspects. This is a quantitative study utilized by descriptive and inferential method as the research design. Based on the findings, academic grades (...) strongly correlate with their attitude in learning English vocabulary which is a negative correlation coefficient in all its components with r value of -0.3695 in behavioral, -0.5261 in Cognitive, and -0.4332 in emotional aspect. Their P values is less than .00001 which is significant at p<0.05. Thus, the null hypothesis where there is no significant relationship between their ALEV and academic performance is rejected. The researcher recommends that teachers should enhance creativity in teaching vocabulary which inculcate the positive attitudes and motivation towards learning process. Teachers and parents should encourage the learners to read and watch educational related materials. (shrink)

Communication between a specially abled person who is deaf and mute and a normal person is a challenging task. We are so used to communicating through speech but it is extremely important to remove the barriers of communication and facilitate smoother conversations. One of the ways of doing this is through Sign language. Thus, recognition of sign language through computerized systems and software development can be very helpful for real time communication. This paper reviews the different processes through (...) which an assistive application can be made for facilitating communication with the people who are a part of the specially abled deaf and mute community. The main objective is to develop an image-based Sign Language recognizer software which can identify the hand gestures realtime, using Convolution Neural Networks. (shrink)

In order for students to succeed, especially in times of crisis like the Covid 19 Pandemic, they must be trained to be self-sufficient in their language studies. This research investigates using a self-access language learning strategy in an emergency virtual reading class during the covid 19 pandemics to improve language learners' Autonomy. It employed a descriptive correlational research design. The study involved 89 randomly selected language students in one University of Peru. Results of the study (...) showed that the students can utilize internet as their learning resource using devices they have. This shows that all of the students have devices to be used for their online and blended language learning. It is interesting to note the all the sampled students have access to internet for their online language learning. Hence the students have a motivated level of learning Autonomy in reading classes. As to the assessment of internet self-access reading skills of the students. This shows that the students have a favorable attitude towards using the internet in their reading lessons. It shows that the students have a fair level of technology acceptance and utilization for their language learning. Self-Access Skills in Reading was shown to be closely linked to Students' Learning Autonomy. This suggests that the relevant factors in the research have a positive correlation. This means that the students are more likely to adopt online self-access reading skills if they have a good attitude about learning Autonomy. This result shed light on the gap in addressing students' online language learning engagement in the COVID 19 era, particularly in the context of Peru. (shrink)

In LOT 2: The Language of Thought Revisited, Jerry Fodor argues that concept learning of any kind—even for complex concepts—is simply impossible. In order to avoid the conclusion that all concepts, primitive and complex, are innate, he argues that concept acquisition depends on purely noncognitive biological processes. In this paper, we show (1) that Fodor fails to establish that concept learning is impossible, (2) that his own biological account of concept acquisition is unworkable, and (3) that there (...) are in fact many promising general models for explaining how concepts are learned. (shrink)

The rise of fake news on digital platforms has become a major societal issue, shaping public opinion and eroding trust in legitimate news sources. As misinformation spreads rapidly, it becomes increasingly difficult to discern fact from fiction, leading to harmful consequences in various domains such as politics, public health, and social relationships. To combat this, there is a growing need for advanced systems that can accurately detect and classify fake news. This project aims to develop a robust machine learning (...) system, leveraging Natural Language Processing (NLP) techniques and machine learning algorithms, to identify deceptive information in textual data with high precision. By focusing on automation, this system promises to scale effectively and provide a timely solution to the growing problem of fake news. The proposed solution incorporates a pre-processing phase that includes Part-of-Speech (POS) tagging, a technique used to analyze the grammatical structure of the text. POS tagging helps in understanding the syntactic roles of words, which can significantly enhance the ability of the model to detect subtle linguistic patterns often associated with misinformation. The system will align these POS-tagged texts with their original content, ensuring that the underlying meaning is preserved while enabling further analysis. This pre-processing is a crucial step before integrating advanced models, such as General Pre-trained Transformers (GPT), which are known for their strong language modeling capabilities. The combination of these techniques will ensure the model achieves a high level of accuracy in detecting fake news. (shrink)

The ever-evolving ways attacker continues to improve their phishing techniques to bypass existing state-of-the-art phishing detection methods pose a mountain of challenges to researchers in both industry and academia research due to the inability of current approaches to detect complex phishing attack. Thus, current anti-phishing methods remain vulnerable to complex phishing because of the increasingly sophistication tactics adopted by attacker coupled with the rate at which new tactics are being developed to evade detection. In this research, we proposed an adaptable (...) framework that combines Deep learning and Randon Forest to read images, synthesize speech from deep-fake videos, and natural language processing at various predictions layered to significantly increase the performance of machine learning models for phishing attack detection. (shrink)

This paper reflects the students' attitude toward learning English in secondary schools. The current study was conducted following 57 students at Dire Dawa secondary Schools. The findings suggest that students were generally uncomfortable with the language and subject areas offered in secondary school and agreed that learning English is important for them. Respondents to the current study, who had recently received their primary education, reported that the secondary school syllabus helped them to acquire the language needed (...) for work and personal development. The findings of this study also showed a positive attitude towards English learning at Dire Dawa secondary Schools. (shrink)

What can contemporary machine learning (ML) models do? Given the proliferation of ML models in society, answering this question matters to a variety of stakeholders, both public and private. The evaluation of models' capabilities is rapidly emerging as a key subfield of modern ML, buoyed by regulatory attention and government grants. Despite this, the notion of an ML model possessing a capability has not been interrogated: what are we saying when we say that a model is able to do (...) something? And what sorts of evidence bear upon this question? -/- In this paper, we aim to answer these questions, using the capabilities of large language models (LLMs) as a running example. Drawing on the large philosophical literature on abilities, we develop an account of ML models' capabilities which can be usefully applied to the nascent science of model evaluation. Our core proposal is a conditional analysis of model abilities (CAMA): crudely, a machine learning model has a capability to X just when it would reliably succeed at doing X if it 'tried'. The main contribution of the paper is making this proposal precise in the context of ML, resulting in an operationalisation of CAMA applicable to LLMs. We then put CAMA to work, showing that it can help make sense of various features of ML model evaluation practice, as well as suggest procedures for performing fair inter-model comparisons. (shrink)

Natural Language Processing (NLP) is a crucial area within artificial intelligence (AI) that focuses on the interaction between computers and human language. By enabling machines to process and understand human language, NLP bridges the gap between computers and human communication. The aim of this paper is to explore key concepts and methodologies in NLP, including text analysis, language modeling, and machine learning techniques. We also discuss challenges faced in NLP such as ambiguity, contextual understanding, and (...) the evolution of language. This paper highlights recent advancements, applications in real-world scenarios, and suggests directions for future research. (shrink)

Natural Language Processing (NLP) is a rapidly growing field at the intersection of artificial intelligence and linguistics, aiming to enable machines to understand, interpret, and generate human language. This paper explores various aspects of NLP and its applications, from basic language processing to advanced machine learning models. The focus is on the evolution of NLP techniques, challenges, and current trends, with a particular emphasis on deep learning methods that have revolutionized the field. The paper also (...) highlights significant NLP applications, including sentiment analysis, machine translation, and conversational AI systems. (shrink)

ABSTRACT For learning any language, motivation plays a vital role. This study aims to investigate collegiate students’ predictive motivational factors toward students’ attitude toward learning English as secondary language. This is a cross-sectional study in which questionnaire was adapted from the existing literature for data collection. For this quantitative study data were collected from two government degree colleges of Larkana. Total 400 questionnaires were randomly distributed among intermediate students both boys and girls, out of that 247 (...) were returned. Data were analyzed using statistical packages for social sciences (SPSS) version 24. Initially, data were cleaned by identifying missing values and outliers. Study hypotheses were examined using Multiple Regression Analysis (MRA). The findings of this study revealed that instrumental motivation and parental encouragement (independent variables) have positive and significant relationship with attitude toward learning English. However, one variable i.e. integrative motivation was not found as a significant and positive predictor of the dependent variable. Like any study, this study also possesses few limitations, such as sample size, time horizon, and context of the study. In the end, future directions are given for further exploration. (shrink)

Text classification is one of the most important task in natural language processing, In this research, we carried out several experimental research on three (3) of the most popular Text classification NLP classifier in Convolutional Neural Network (CNN), Multinomial Naive Bayes (MNB), and Support Vector Machine (SVN). In the presence of enough training data, Deep Learning CNN work best in all parameters for evaluation with 77% accuracy, followed by SVM with accuracy of 76%, and multinomial Bayes with least (...) performance of 69% accuracy. CNN has the best performance in the presence of large enough training dataset because of the presence of filter/ kernels which help to indentify patterns in text data regardless of their position in the sentence. -/- We repeated the training again with just one-third of our data, at this point SVM comes with the best performance, the performance of CNN noticeably drops but still better than Multinomial Naive Bayes, the reason why SVM works best when we reduce the training data was because of its ability to look for a hyper-plane that creates a boundary between different classes of data so as to properly classify them, so we believed that getting the hyper-plane was more efficient when we reduce the dataset, hence reason for the good performance. Multinomial Naive Bayes have the least performance which we attributed to its assumption of independency between the features which sometimes does not hold true. We concluded that availability of data should be an important factor when choosing classifier for Natural Language Processing Text Classification task. CNN should be use in the presence of enough dataset, and SVM should be use when data is not enough. Multinomial Naive Bayes must not be trusted with state of the art NLP task due to its assumption of independency between the features. (shrink)

Speech therapy is a clinical intervention that addresses communication disorders affecting speech production, language comprehension, fluency, and voice quality. While essential for improving quality of life and social participation, speech therapy faces significant challenges including professional shortages, accessibility barriers, engagement difficulties, subjective assessment practices, and limited personalization. These challenges are magnified for low-resource languages like Malayalam, which lacks standardized assessment tools, therapy materials, and trained professionals familiar with its unique phonological features such as distinctive phonemes and geminate consonants. Conventional (...) speech therapy approaches designed for widely spoken languages often fail to address language-specific articulation patterns, creating a critical need for technology-assisted solutions that can overcome geographical barriers, standardize assessment procedures, and preserve linguistic authenticity while providing accessible intervention for Malayalam speakers with speech disorders. This paper proposes an AI-driven speech therapy assistant tailored for Malayalam speakers with speech disorders. The proposed system leverages deep learning techniques to address common articulation errors, such as mispronunciations and fluency issues like stammering. The framework aims to analyse speech patterns, identify errors, and recommend personalized therapeutic exercises. By focusing on Malayalam-specific phonetics, this research bridges the gap in accessible and culturally relevant speech therapy solutions. (shrink)

Cyberbullying, a contemporary menace within the realm of social media, has emerged alongside the surge in social media usage, leading to the exploitation of freedom of expression. Statistics indicate that a substantial 36.5% of individuals believe they have experienced cyberbullying at some point in their lives. This figure has more than doubled since 2007, and there has been a noticeable increase from 2018 to 2023, indicating an unfavorable trend. Although existing solutions in the market aim to mitigate this issue, they (...) often come with usage limitations or inefficient algorithms. (shrink)

Self-supervised learning (SSL) is an emerging paradigm in machine learning that bridges the gap between supervised and unsupervised learning by allowing models to learn from unlabeled data. The core idea behind SSL is to generate supervisory signals from the data itself, thereby reducing the dependency on large labeled datasets. This paper explores the evolution of self-supervised learning, its underlying principles, key techniques, and recent advancements that make it a promising approach for the development of AI models (...) with minimal labeled data. We discuss the applications of SSL in various domains, such as natural language processing, computer vision, and speech recognition, and its potential to revolutionize industries that suffer from the scarcity of labeled data. Furthermore, we present challenges and future research directions in SSL, including the trade-offs between performance and label efficiency, generalization across tasks, and scalability for large datasets. (shrink)

P. F. Strawson famously distinguishes what a speaker presupposes from what she asserts in uttering a sentence like “The present King of France is bald”. This paper defends a claim about presupposition's epistemic significance, namely that presupposition can provide a distinctive testimony‐based way for an audience to learn about the world.

Abstract: The incorporation of Artificial Intelligence (AI) into educational technology has dramatically transformed learning through Intelligent Tutoring Systems (ITS). These systems utilize AI to offer personalized, adaptive instruction tailored to each student's needs, thereby improving learning outcomes and engagement. This paper examines the development and impact of ITS, focusing on AI technologies such as machine learning, natural language processing, and adaptive algorithms that drive their functionality. Through various case studies and applications, it illustrates how ITS have (...) revolutionized traditional educational methods and addresses the challenges and limitations, including data privacy and system biases. The discussion also covers future directions in ITS development, highlighting emerging trends and potential advancements. The goal is to provide a thorough understanding of how ITS use AI to enhance educational experiences and suggest avenues for future research in this evolving field. (shrink)

This is Appendix B to the note, Deconstructing the Physical World (DPW). This appendix extends DPW to provide a set of new conceptual tools able inter alia to deliver a systematic, well-structured and highly novel set of insights into: core aspects of how language learning and use might work; what precisely is going on in inverted qualia thought experiments and in relation to the knowledge argument; and how incorporating differentiated forms of qualia into some fundamental ideas about (...) class='Hi'>language learning and use can help more clearly define what we mean when we refer to such things as ‘concepts’ and ‘imagination’. (shrink)

The Complex Emergent Model of Language Acquisition (CEMLA) offers a new perspective on how humans acquire language, drawing on principles from complexity theory to explain this dynamic, adaptive process. Moving beyond linear and reductionist models, CEMLA views language acquisition as a system of interconnected nodes, feedback loops, and emergent patterns, operating at the edge of chaos. This framework captures the fluidity and adaptivity of language learning, highlighting how understanding and fluency arise through self-organisation, phase transitions, (...) and interaction with diverse linguistic input. By embracing the complexity of language acquisition, CEMLA provides a comprehensive model that reflects the true nature of human communication. (shrink)

Bayesianism can be characterized as the following twofold position: (i) rational credences obey the probability calculus; (ii) rational learning, i.e., the updating of credences, is regulated by some form of conditionalization. While the formal aspect of various forms of conditionalization has been explored in detail, the philosophical application to learning from experience is still deeply problematic. Some philosophers have proposed to revise the epistemology of perception; others have provided new formal accounts of conditionalization that are more in line (...) with how we learn from perceptual experience. The current investigation argues that Bayesian epistemology is still incomplete; the epistemology of perception and the epistemology of rational reasoning have not been reconciled. (shrink)

This paper examines Augustine’s views on language, learning, and testimony in De Magistro. It is often held that, in De Magistro, Augustine is especially concerned with explanatory understanding (a complex cognitive state characterized by its synoptic nature and awareness of explanatory relations) and that he thinks testimony is deficient in imparting explanatory understanding. I argue against this view and give a clear analysis of the different kinds of cognitive state Augustine is concerned with and a careful examination of (...) his arguments concerning the deficiencies of testimony in producing these cognitive states. (shrink)