Search results for: accelerated online learning

Authors: Seyedebrahim Afkhami, Meisam Abdi, Reza Baserinia

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Additive manufacturing is revolutionising production in different industries, including pharmaceuticals. This case study explores the influence of surface area on the dissolution of additively manufactured polyvinyl alcohol parts as a polymer candidate. Specimens of different geometries and constant mass were fabricated using a Fused Deposition Modelling 3D printer. The dissolution behaviour of these samples was compared with respect to their surface area. Improved and accelerated dissolution was observed for samples with a larger surface area. This study highlights the capabilities of additive manufacturing to produce samples of complex geometries that cannot be manufactured otherwise to control the dissolution behaviour for pharmaceutical and biopharmaceutical applications.

Keywords: additive manufacturing, polymer dissolution, fused deposition modelling, geometry optimization

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Authors: Oleg Vlasovets, Fabian Schaipp, Christian L. Mueller

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we conduct a network analysis and predict the sex of 1000 participants based on ”connectome” - pairwise Pearson’s correlation across 436 brain parcels. We solve the non-smooth convex optimization problem, known under the name of Graphical Lasso, where the solution includes a low-rank component. With this solution and machine learning model for a sex prediction, we explain the brain parcels-sex connectivity patterns.

Keywords: network analysis, neuroscience, machine learning, optimization

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Authors: Boon Yih Mah

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Web-based Cognitive Writing Instruction (WeCWI) is a hybrid e-framework that consolidates instructional design and language development towards the development of a web-based instruction (WBI). WeCWI divides instructional design into macro and micro perspectives. In macro perspective, a 21st century educator is encouraged to disseminate knowledge and share ideas with in-class and global learners. By leveraging the virtue of technology, WeCWI aims to transform the educator into an aggregator, curator, publisher, social networker and finally, a web-based instructor. Since the most notable contribution of integrating technology is being a tool of teaching as well as a stimulus for learning, WeCWI focuses on the use of contemporary web tools based on the multiple roles played by the 21st century educator. The micro perspective draws attention to the pedagogical approaches focussing on three main aspects: reading, discussion, and writing. With the effective use of pedagogical approaches, technology adds new dimensions and expands the bounds of learning capacity. Lastly, WeCWI also imparts the fundamental theoretical concepts for web-based instructors’ awareness such as interactionism, e-learning interactional-based model, computer-mediated communication (CMC), cognitive theories, and learning style model.

Keywords: web-based cognitive writing instruction, WeCWI, instructional design, e-framework, web-based instructor

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Authors: Md. Shaiful Islam, Mahani Bt. Stapa

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To help learners overcome their struggle in developing proficiency in spoken English, self-regulated learning strategies seem to be promising. Students in the private universities in Bangladesh are expected to communicate with the teachers, peers, and staff members in English, but most of them suffer from their inadequate oral communicative competence in English. To address this problem, the researchers adopted a qualitative research approach to answer the research questions. They employed the learner diary method to collect data from the first-semester undergraduate students of a reputed private university in Bangladesh who were involved in writing weekly diaries about their use of self-regulated learning strategies to improve speaking in an English speaking course. The learners were provided with prompts for writing the diaries. The thematic analysis method was applied to analyze the entries of the diaries for the identification of themes. Seven strategies related to the effectiveness of SRL for the improvement of spoken English were identified from the data, and they include goal-setting, strategic planning, identifying the sources of self-motivation, help-seeking, environmental restructuring, self-monitoring, and self-evaluation. However, the students reported in their diaries that they faced challenges that impeded their SRL strategy use. Five challenges were identified, and they entail the complex nature of SRL, lack of literacy on SRL, teachers’ preference for controlling the class, learners’ past habit of learning, and students’ addiction to gadgets. The implications the study addresses include revising the syllabus and curriculum, facilitating SRL training for students and teachers, and integrating SRL in the lessons.

Keywords: private university in Bangladesh, proficiency, self-regulated learning, spoken English

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Authors: Ghazi Alotaibi

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The current study examined and described the views of secondary school students and their parents on their reasons for seeking private tutors in English. These views were obtained through two group interviews with the students and parents separately. Several causes were brought up during the two interviews. These causes included difficulty of the English language, weak teacher performance, the need to pass exams with high marks, lack of parents’ follow-up of student school performance, social pressure, variability in student comprehension levels at school, weak English foundation in previous school years, repeated student absence from school, large classes, as well as English teachers’ heavy teaching loads. The study started with a description of the EFL educational system in Saudi Arabia and concluded with recommendations for the improvement of the school learning environment.

Keywords: english, learning difficulty, private tutoring, Saudi, teaching practices, learning environment

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Authors: Migena Mana, Ahmed Khalid Syed, Abdul Malik, Nikhil Cherian

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In recent years, advancements in deep learning enabled researchers to tackle the problem of self-driving cars. Car companies use huge datasets to train their deep learning models to make autonomous cars a reality. However, this approach has certain drawbacks in that the state space of possible actions for a car is so huge that there cannot be a dataset for every possible road scenario. To overcome this problem, the concept of reinforcement learning (RL) is being investigated in this research. Since the problem of autonomous driving can be modeled in a simulation, it lends itself naturally to the domain of reinforcement learning. The advantage of this approach is that we can model different and complex road scenarios in a simulation without having to deploy in the real world. The autonomous agent can learn to drive by finding the optimal policy. This learned model can then be easily deployed in a real-world setting. In this project, we focus on three RL algorithms: Q-learning, Deep Deterministic Policy Gradient (DDPG), and Proximal Policy Optimization (PPO). To model the environment, we have used TORCS (The Open Racing Car Simulator), which provides us with a strong foundation to test our model. The inputs to the algorithms are the sensor data provided by the simulator such as velocity, distance from side pavement, etc. The outcome of this research project is a comparative analysis of these algorithms. Based on the comparison, the PPO algorithm gives the best results. When using PPO algorithm, the reward is greater, and the acceleration, steering angle and braking are more stable compared to the other algorithms, which means that the agent learns to drive in a better and more efficient way in this case. Additionally, we have come up with a dataset taken from the training of the agent with DDPG and PPO algorithms. It contains all the steps of the agent during one full training in the form: (all input values, acceleration, steering angle, break, loss, reward). This study can serve as a base for further complex road scenarios. Furthermore, it can be enlarged in the field of computer vision, using the images to find the best policy.

Keywords: autonomous driving, DDPG (deep deterministic policy gradient), PPO (proximal policy optimization), reinforcement learning

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Authors: Ganfeng Yu, Yuefeng Ma, Shanliang Yang

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The word discovery is a key problem in text information retrieval technology. Methods in new word discovery tend to be closely related to words because they generally obtain new word results by analyzing words. With the popularity of social networks, individual netizens and online self-media have generated various network texts for the convenience of online life, including network words that are far from standard Chinese expression. How detect network words is one of the important goals in the field of text information retrieval today. In this paper, we integrate the word embedding model and clustering methods to propose a network word discovery framework based on sentence semantic similarity (S³-NWD) to detect network words effectively from the corpus. This framework constructs sentence semantic vectors through a distributed representation model, uses the similarity of sentence semantic vectors to determine the semantic relationship between sentences, and finally realizes network word discovery by the meaning of semantic replacement between sentences. The experiment verifies that the framework not only completes the rapid discovery of network words but also realizes the standard word meaning of the discovery of network words, which reflects the effectiveness of our work.

Keywords: text information retrieval, natural language processing, new word discovery, information extraction

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Authors: Mehul Srivastava, Sharma Tushar Ravikant, Mridul Krishn Mishra

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In structural design, the evaluation of safety and probability failure of structure is of significant importance, mainly when the variables are random. On real structures, structural reliability can be evaluated obtaining an implicit limit state function. The structural reliability limit state function is obtained depending upon the statistically independent variables. In the analysis of reliability, we considered the statistically independent random variables to be the load intensity applied and the depth or height of the beam member considered. There are many approaches for structural reliability problems. In this paper Extreme Learning Machine technique and First Order Second Moment Method is used to determine the reliability indices for the same set of variables. The reliability index obtained using ELM is compared with the reliability index obtained using FOSM. Higher the reliability index, more feasible is the method to determine the reliability.

Keywords: reliability, reliability index, statistically independent, extreme learning machine

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Authors: Sakae Suzuki

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Although Japanese students study English for six years in secondary schools, they demonstrate little success with it when they enter higher education. Learners’ beliefs can predict the future behavior of students, so it may be effective to investigate how learners’ beliefs limit their success and how beliefs might be nudged in a positive direction. While many researchers still depend on a questionnaire called BALLI to reveal explicit beliefs, alternative approaches, especially those designed to reveal implicit beliefs, might be helpful for promoting learning. The present study seeks to identify beliefs with a discursive approach using visual metaphors and narratives. Employing a sociocultural framework, this study investigates how students’ beliefs are revealed by drawings of themselves and their surrounding environments and artifacts while they are engaged in language learning. Research questions are: (1) Can we identify beliefs through an analysis of students’ visual narratives? (2) What environments and artifacts can be found in students’ drawings, and what do they mean? (3) To what extent do students see language learning as a solitary, rather than a social, activity? Participants are university students majoring in science and technology in Japan. The questionnaire was administered to 70 entering students in April, 2014. Data included students drawings of themselves as learners of English as well as written descriptions of students’ backgrounds, English-learning experiences, and analogies and metaphors that they used in written descriptions of themselves as learners. Data will be analyzed qualitatively and quantitatively. Anticipated results include students’ perceptions of themselves as language learners, including their sense of agency, awareness of artifacts, and social contexts of language learning. Comments will be made on implications for teaching, as well as the use of visual narratives as research tools, and recommended further research.

Keywords: drawings, learners' beliefs, metaphors, BALLI

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Authors: Jeongmin Kim, Eunju Lee, Kwang Ryel Ryu

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This paper addresses the problem of predictive control for energy management of large-scaled exhibition halls, where a lot of energy is consumed to maintain internal atmosphere under certain required conditions. Predictive control achieves better energy efficiency by optimizing the operation of air-conditioning facilities with not only the current but also some future status taken into account. In this paper, we propose to use predictive models learned from past sensor data of hall environment, for use in optimizing the operating plan for the air-conditioning facilities by simulating future environmental change. We have implemented an emulator of an exhibition hall by using EnergyPlus, a widely used building energy emulation tool, to collect data for learning environment-change models. Experimental results show that the learned models predict future change highly accurately on a short-term basis.

Keywords: predictive control, energy management, machine learning, optimization

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Authors: Fahd Hamad Alqasham

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This longitudinal study investigates Saudi students’ use trajectory and experiences of Twitter as an innovative tool for in-class learning of the English language in a Saudi tertiary English as a foreign language (EFL) context for a 12-week semester. The study adopted van Lier’s agency theory (2008, 2010) as the analytical framework to obtain an in-depth analysis of how the learners’ could utilize Twitter to create innovative ways for them to engage in English learning inside the language classroom. The study implemented a mixed methods approach, including six data collection instruments consisting of a research log, observations, focus group participation, initial and post-project interviews, and a post-project questionnaire. The study was conducted at Qassim University, specifically at Preparatory Year Program (PYP) on the main campus. The sample included 25 male students studying in the first level of PYP. The findings results revealed that although Twitter’s affordances initially paled a crucial role in motivating the learners to initiate their agency inside the classroom to learn English, the contextual constraints, mainly anxiety, the university infrastructure, and the teacher’s role negatively influenced the sustainability of Twitter’s use past week nine of its implementation.

Keywords: CALL, agency, innovation, EFL, language learning

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Authors: Christopher Webb

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This work presents a new model of mentoring in an organizational environment and has important implications for both practice and research, the model frames the organizational environment as organizational curriculum, which includes the elements that affect learning within the organization. This includes the organizational structure and culture, roles within the organization, and accessibility of knowledge. The program curriculum includes the elements of the mentoring program, including materials, training, and scheduled events for the program participants. The term dyadic curriculum is coined in this work. The dyadic curriculum describes the participation, behavior, and identities of the pairs participating in mentorships. This also includes the identity work of the participants and their views of each other. Much of this curriculum is unprescribed and is unique within each dyad. It describes how participants mediate the elements of organizational and program curricula. These three curricula interact and affect each other in predictable ways. A detailed example of a mentoring program framed in this model is provided.

Keywords: curriculum, mentoring, organizational learning and development, social learning

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Authors: Sindile Ngubane-Mokiwa

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This paper addresses two questions: (1) what barriers do the blind students face with assessment and feedback in open distance learning contexts? And (2) How can these barriers be removed? The paper focuses on the distance education through which most students with disabilities elevate their chances of accessing higher education. Lack of genuine inclusion is also evident in the challenges the blind students face during the assessment. These barriers are experienced at both formative and summative stages. The insights in this paper emanate from a case study that was carried out through qualitative approaches. The data was collected through in-depth interview, life stories, and telephonic interviews. The paper provides a review of local, continental and international views on how best assessment barriers can be removed. A group of five blind students, comprising of two honours students, two master's students and one doctoral student participated in this study. The data analysis was done through thematic analysis. The findings revealed that (a) feedback to the assignment is often inaccessible; (b) the software used is incompatible; (c) learning and assessment are designed in exclusionary approaches; (d) assessment facilities are not conducive; and (e) lack of proactive innovative assessment strategies. The article concludes by recommending ways in which barriers to assessment can be removed. These include addressing inclusive assessment and feedback strategies in professional development initiatives.

Keywords: assessment design, barriers, disabilities, blind students, feedback, universal design for learning

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Authors: T. Hopkin, S. Lu, P. Rogers, M. Sexton

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Housing Associations (HAs) contribute circa 20% of the UK’s housing supply. HAs are however under increasing pressure as a result of funding cuts and rent reductions. Due to the increased pressure, a number of processes are currently being reviewed by HAs, especially how they manage and learn from defects. Learning from defects is considered a useful approach to achieving defect reduction within the UK housebuilding industry. This paper contributes to our understanding of how HAs learn from defects by undertaking an initial round table discussion with key HA stakeholders as part of an ongoing collaborative research project with the National House Building Council (NHBC) to better understand how house builders and HAs learn from defects to reduce their prevalence. The initial discussion shows that defect information runs through a number of groups, both internal and external of a HA during both the defects management process and organizational learning (OL) process. Furthermore, HAs are reliant on capturing and recording defect data as the foundation for the OL process. During the OL process defect data analysis is the primary enabler to recognizing a need for a change to organizational routines. When a need for change has been recognized, new options are typically pursued to design out defects via updates to a HAs Employer’s Requirements. Proposed solutions are selected by a review board and committed to organizational routine. After implementing a change, both structured and unstructured feedback is sought to establish the change’s success. The findings from the HA discussion demonstrates that OL can achieve defect reduction within the house building sector in the UK. The paper concludes by outlining a potential ‘learning from defects model’ for the housebuilding industry as well as describing future work.

Keywords: defects, new homes, housing association, organizational learning

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Authors: Catherine Chua, Kashif Raza

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Work-integrated learning (WIL) has been heightened in the last few years across countries. With a specific attention on working adults, the key objective is to integrate work experiences with academic studies so that they will be given more opportunities to advance, gather relevant skills and credentials to enable them to contribute more positively to the labour market. In Singapore, developing talent through WIL aims to develop specialist and enduring skills for the industries. Collaborating with the institutes of higher education in Singapore, the Integrated Work Study Programs (IWSP) seek to harmonize classroom learning with practical work experiences so that adult students can develop skills and knowledge that are needed in the existing and future workplaces. Local higher education institutions will also work closely with industry partners, and design courses that support these students to deepen their skills. Using Critical Discourse Analysis, this paper examines the Singapore government policies in WIL and argues that despite the various supports and interventions provided by the government, it is equally important to create a ‘space’ in the society whereby there is a greater recognition for WIL as a valuable education approach, i.e., “continuous meritocracy”. This is especially so in Singapore where academic excellence and conventional front-loaded approach to education are valued.

Keywords: work-integrated learning, adult learners, continuous meritocracy, skillsfuture singapore

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Authors: Sitalakshmi Venkatraman, Fiona Wahr, Anthony de Souza-Daw, Samuel Kaspi

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There is a growing emphasis on generic skills in higher education to match the changing skill-set requirements of the labour market. However, researchers and policy makers have not arrived at a consensus on the generic skills that actually contribute towards workplace employability and performance that complement and/or underpin discipline-specific graduate attributes. In order to strengthen the qualifications framework, a range of ‘generic’ learning outcomes have been considered for students undergoing higher education programs and among them it is necessary to have the fundamental generic skills such as literacy and numeracy at a level appropriate to the qualification type. This warrants for curriculum design approaches to contextualise the form and scope of these fundamental generic skills for supporting both students’ learning engagement in the course, as well as the graduate attributes required for employability and to progress within their chosen profession. Little research is reported in integrating such generic skills into discipline-specific learning outcomes. This paper explores the literature of the generic skills required for graduates from the discipline of Information Technology (IT) in relation to an Australian higher education institution. The paper presents the rationale of a proposed Bachelor of IT curriculum designed to contextualize the learning of these generic skills within the students’ discipline studies.

Keywords: curriculum, employability, generic skills, graduate attributes, higher education, information technology

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Authors: Kristy Howells, Catherine Meehan

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This position paper presents current research findings into the proposed gap between teachers’ and practitioners’ thinking and acting about physical activity health and well-being in childhood. Within the new Primary curriculum, there is a focus on sustained physical activity within a Physical Education and healthy lifestyles in Personal, Health, Social and Emotional lessons, but there is no curriculum guidance about what sustained physical activity is and how it is defined. The current health guidance on birth to five suggests that children should not be inactive for long periods and specify light and energetic activities, however there is the a suggested period of time per day for young children to achieve, but the guidance does not specify how this should be measured. The challenge therefore for teachers and practitioners is their own confidence and understanding of what “good / moderate intensity” physical activity and healthy living looks like for children and the children understanding what they are doing. There is limited research about children from birth to eight years and also the perceptions and attitudes of those who work with this age group of children, however it was found that children at times can identify different levels of activity and it has been found that children can identify healthy foods and good choices for healthy living at a basic level. Authors have also explored teachers’ beliefs about teaching and learning and found that teachers could act in accordance to their beliefs about their subject area only when their subject knowledge, understanding and confidence of that area is high. It has been proposed that confidence and competence of practitioners and teachers to integrate ‘well-being’ within the learning settings has been reported as being low. This may be due to them not having high subject knowledge. It has been suggested that children’s life chances are improved by focusing on well-being in their earliest years. This includes working with parents and families, and being aware of the environmental contexts that may impact on children’s wellbeing. The key is for practitioners and teachers to know how to implement these ideas effectively as these key workers have a profound effect on young children as role models and due to the time of waking hours spent with them. The position paper is part of a longitudinal study at Canterbury Christ Church University and currently we will share the research findings from the initial questionnaire (online, postal, and in person) that explored and evaluated the knowledge, competence and confidence levels of practitioners and teachers as to the structure and planning of sustained physical activity and healthy lifestyles and how this progresses with the children’s age.

Keywords: health, perceptions, physical activity, well-being

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Authors: Siriwan Chatmaneerungcharoen

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An emerging body of ‘21st century skills’-such as adaptability, complex communication skills, technology skills and the ability to solve non-routine problems--are valuable across a wide range of jobs in the national economy. Within the Thai context, a focus on the Philosophy of Sufficiency Economy is integrated into Science Education. Thai science education has advocated infusing 21st century skills and Philosophy of Sufficiency Economy into the school curriculum and several educational levels have launched such efforts. Therefore, developing science teachers to have proper knowledge is the most important factor to success of the goals. The purposes of this study were to develop 40 Cooperative Science teachers’ Technological Pedagogical Content Knowledge (TPACK) and to develop Professional Development Model integrated with Co-teaching Model and Coaching System (Co-TPACK). TPACK is essential to career development for teachers. Forty volunteer In-service teachers who were science cooperative teachers participated in this study for 2 years. Data sources throughout the research project consisted of teacher refection, classroom observations, Semi-structure interviews, Situation interview, questionnaires and document analysis. Interpretivist framework was used to analyze the data. Findings indicate that at the beginning, the teachers understood only the meaning of Philosophy of Sufficiency Economy but they did not know how to integrate the Philosophy of Sufficiency Economy into their science classrooms. Mostly, they preferred to use lecture based teaching and experimental teaching styles. While the Co- TPACK was progressing, the teachers had blended their teaching styles and learning evaluation methods. Co-TPACK consists of 3 cycles (Student Teachers’ Preparation Cycle, Cooperative Science Teachers Cycle, Collaboration cycle (Co-teaching, Co-planning, and Co-Evaluating and Coaching System)).The Co-TPACK enhances the 40 cooperative science teachers, student teachers and university supervisor to exchange their knowledge and experience on teaching science. There are many channels that they used for communication including online. They have used more Phuket context-integrated lessons, technology-integrated teaching and Learning that can explicit Philosophy of Sufficiency Economy. Their sustained development is shown in their lesson plans and teaching practices.

Keywords: technological pedagogical content knowledge, philosophy of sufficiency economy, professional development, coaching system

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Authors: Gholizadeh F. F., Goldansaz S. H., Bandani A. R., A. Ashouri

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This study aimed to investigate the direct effects of increasing carbon dioxide (CO₂) concentration on the behavior of Bombus terrestris bumblebees in laboratory conditions to understand the outcomes of the augmentation of this gas in the Earth's atmosphere on the decline of populations of these pollinators. Learning and memory duration of bumblebees were evaluated as two main behavioral factors in social insects at different concentrations of CO₂. In both series of experiments, the behavior of bees under the influence of CO₂ changes compared to the control. Insects kept at high CO₂ concentrations learn less than control bees and spend more time identifying and navigating to discover their food source and access time (nectar consumption). These results showed that bees maybe lose some of their food resources due to poorer identification and act weaker on searching due to less memory and avoiding the enemy in higher CO₂ concentration. Therefore, CO₂ increasing concentration can be one of the reasons for the decline of these pollinating insects' populations by negatively affecting their fitness.

Keywords: Bombus terrestris, CO₂, learning, memory duration

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Authors: Anushtha Saxena

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This paper examines the process of data monetisation bye-commerce companies operating in India. Data monetisation is collecting, storing, and analysing consumers’ data to use further the data that is generated for profits, revenue, etc. Data monetisation enables e-commerce companies to get better businesses opportunities, innovative products and services, a competitive edge over others to the consumers, and generate millions of revenues. This paper analyses the issues and challenges that are faced due to the process of data monetisation. Some of the issues highlighted in the paper pertain to the right to privacy, protection of data of e-commerce consumers. At the same time, data monetisation cannot be prohibited, but it can be regulated and monitored by stringent laws and regulations. The right to privacy isa fundamental right guaranteed to the citizens of India through Article 21 of The Constitution of India. The Supreme Court of India recognized the Right to Privacy as a fundamental right in the landmark judgment of Justice K.S. Puttaswamy (Retd) and Another v. Union of India . This paper highlights the legal issue of how e-commerce businesses violate individuals’ right to privacy by using the data collected, stored by them for economic gains and monetisation and protection of data. The researcher has mainly focused on e-commerce companies like online shopping websitesto analyse the legal issue of data monetisation. In the Internet of Things and the digital age, people have shifted to online shopping as it is convenient, easy, flexible, comfortable, time-consuming, etc. But at the same time, the e-commerce companies store the data of their consumers and use it by selling to the third party or generating more data from the data stored with them. This violatesindividuals’ right to privacy because the consumers do not know anything while giving their data online. Many times, data is collected without the consent of individuals also. Data can be structured, unstructured, etc., that is used by analytics to monetise. The Indian legislation like The Information Technology Act, 2000, etc., does not effectively protect the e-consumers concerning their data and how it is used by e-commerce businesses to monetise and generate revenues from that data. The paper also examines the draft Data Protection Bill, 2021, pending in the Parliament of India, and how this Bill can make a huge impact on data monetisation. This paper also aims to study the European Union General Data Protection Regulation and how this legislation can be helpful in the Indian scenarioconcerning e-commerce businesses with respect to data monetisation.

Keywords: data monetization, e-commerce companies, regulatory framework, GDPR

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Authors: Yen-Hui Lu

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In the past two decades, in order to increase university visibility and internationalization, English as a medium of instruction (EMI) has become one of the main language policies in higher education institutions where English is not a dominant language. However, given the complex, discipline-embedded nature of academic communication, academic literacy does not come with students’ everyday language experience, and it is a challenge for all students. Particularly, to engage students in the effective learning process of discipline concepts in the EMI classrooms, teachers need to provide explicit academic language instruction to assist students in deep understanding of discipline concepts. To bridge the gap between academic language development and discipline learning in the EMI classrooms, the researcher incorporates academic language strategies and key elements of project-based learning (PBL) into an Academic Language Strategy driven PBL (ALS-PBL) model. With clear steps and strategies, the model helps EMI teachers to scaffold students’ academic language development in the EMI classrooms. ALS-PBL model includes three major stages: preparation, implementation, and assessment. First, in the preparation stage, ALS-PBL teachers need to identify learning goals for both content and language learning and to design PBL topics for investigation. Second, during the implementation stage, ALS-PBL teachers use the model as a guideline to create a lesson structure and class routine. There are five important elements in the implementation stage: (1) academic language preparation, (2) connecting background knowledge, (3) comprehensible input, (4) academic language reinforcement, and (5) sustained inquiry and project presentation. Finally, ALS-PBL teachers use formative assessments such as student learning logs, teachers’ feedback, and peer evaluation to collect detailed information that demonstrates students’ academic language development in the learning process. In this study, ALS-PBL model was implemented in an interdisciplinary course entitled “Science is Everywhere”, which was co-taught by five professors from different discipline backgrounds, English education, civil engineering, business administration, international business, and chemical engineering. The purpose of the course was to cultivate students’ interdisciplinary knowledge as well as English competency in disciplinary areas. This study used a case-study design to systematically investigate students’ learning experiences in the class using ALS-PBL model. The participants of the study were 22 college students with different majors. This course was one of the elective EMI courses in this focal university. The students enrolled in this EMI course to fulfill the school language policy, which requires the students to complete two EMI courses before their graduation. For the credibility, this study used multiple methods to collect data, including classroom observation, teachers’ feedback, peer assessment, student learning log, and student focus-group interviews. Research findings show four major successful aspects of implementing ALS-PBL model in the EMI classroom: (1) clear focus on both content and language learning, (2) meaningful practice in authentic communication, (3) reflective learning in academic language strategies, and (4) collaborative support in content knowledge.This study will be of value to teachers involved in delivering English as well as content lessons to language learners by providing a theoretically-sound practical model for application in the classroom.

Keywords: academic language development, content and language integrated learning, english as a medium of instruction, project-based learning

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Authors: Jiaqi Huang, Yuheng Wang

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Premises selection, the task of selecting a set of axioms for proving a given conjecture, is a major bottleneck in automated theorem proving. An array of deep-learning-based methods has been established for premises selection, but a perfect performance remains challenging. Our study examines the inaccuracy of deep neural networks in premises selection. Through training network models using encoded conjecture and axiom pairs from the Mizar Mathematical Library, two potential biases are found: the network models classify more premises as necessary than unnecessary, referred to as the ‘positive bias’, and the network models perform better in proving conjectures that paired with more axioms, referred to as ‘length bias’. The ‘positive bias’ and ‘length bias’ discovered could inform the limitation of existing deep neural networks.

Keywords: automated theorem proving, premises selection, deep learning, interpreting deep learning

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Authors: M. A. Mabasa, O. Ramokolo, M. Z. Mnikathi, D. Mathabatha, T. Manyapelo

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The study examines the importance of translating South African folklore from Oral into Written Literature in a Multilingual Education. Therefore, the study postulates that translation can be regarded as a valuable tool when oral and written literature is transmitted from one generation to another. The study entails that translation does not take place in a haphazard fashion; for that reason, skills such as translation principles are required to translate folklore significantly and effectively. The purpose of the study is to indicate the significance of using translation relating to folklore in teaching and learning. The study also observed that Modernism in literature should be shared amongst varieties of cultures because folklore is interactive in narrating stories, folktales and myths to sharpen the reader’s knowledge and intellect because they are informative and educative in nature. As a technological tool, the study points out that translation is of paramount importance in the sense that the meanings of different data can be made available in all South African official languages using oral and written forms of folklore. The study opines that tradition and customary beliefs and practices in the institution of higher learning. The study envisages the way in which literature of folklore can be juxtaposed to ensure that translated folklore is of quality assured standards. The study alludes that well-translated folklore can serve as oral and written literature, which may contribute to the child’s learning and acquisition of knowledge and insights during cognitive development toward maturity. Methodologically, the study selects a qualitative research approach and selects content analysis as an instrument for data gathering, which will be analyzed qualitatively in consideration of the significance of translating folklore as written and spoken literature in a documented way. The study reveals that the translation of folktales promotes functional multilingualism in high-function formal contexts like a university. The study emphasizes that translated and preserved literary folklore may serve as a language repository from one generation to another because of the archival and storage of information in the form of a term bank.

Keywords: translation, editing, teaching, learning, folklores

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Authors: Ryoo Hye Jin Agnes

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This study aims to investigate the efficacy of clickers in fostering L2 class interaction. In an L2 classroom, active learner-to-learner interactions and learner-to-teacher interactions play an important role in language acquisition. In light of this, introducing learning tools that promote such interactions would benefit L2 classroom by fostering interaction. This is because the anonymity of clickers allows learners to express their needs without the social risks associated with speaking up in the class. clickers therefore efficiently help learners express their level of understanding during the process of learning itself. This allows for an evaluative feedback loop where both learners and teachers understand the level of progress of the learners, better enabling classrooms to adapt to the learners’ needs. Eventually this tool promotes participation from learners. This, in turn, is believed to be effective in fostering classroom interaction, allowing learning to take place in a more comfortable yet vibrant way. This study is finalized by presenting the result of an experiment conducted to verify the effectiveness of this approach when teaching pragmatic aspect of Korean expressions with similar semantic functions. The learning achievement of learners in the experimental group was found higher than the learners’ in a control group. A survey was distributed to the learners, questioning them regarding the efficacy of clickers, and how it contributed to their learning in areas such as motivation, self-assessment, increasing participation, as well as giving feedback to teachers. Analyzing the data collected from the questionnaire given to the learners, the study presented data suggesting that this approach increased the scope of interactivity in the classroom, thus not only increasing participation but enhancing the type of classroom participation among learners. This participation in turn led to a marked improvement in their communicative abilities.

Keywords: second language acquisition, interaction, clickers, learner response system, output from learners, learner’s cognitive process

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Authors: Majid Habib Khan, Jinwei Zhao, Xinhong Hei, Liu Jiedong, Rana Shahzad Noor, Muhammad Imran

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Deep learning is increasingly employed in image classification, yet the scarcity and high cost of labeled data for training remain a challenge. Limited samples often lead to overfitting due to biased sample distribution. This paper introduces a dynamic distribution calibration method for few-shot learning. Initially, base and new class samples undergo normalization to mitigate disparate feature magnitudes. A pre-trained model then extracts feature vectors from both classes. The method dynamically selects distribution characteristics from base classes (both adjacent and remote) in the embedding space, using a threshold value approach for new class samples. Given the propensity of similar classes to share feature distributions like mean and variance, this research assumes a Gaussian distribution for feature vectors. Subsequently, distributional features of new class samples are calibrated using a corrected hyperparameter, derived from the distribution features of both adjacent and distant base classes. This calibration augments the new class sample set. The technique demonstrates significant improvements, with up to 4% accuracy gains in few-shot classification challenges, as evidenced by tests on miniImagenet and CUB datasets.

Keywords: deep learning, computer vision, image classification, few-shot learning, threshold

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Authors: Shweta Singh, Sudaman Katti

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The most well-known sequence models make use of complex recurrent neural networks in an encoder-decoder configuration. The model used in this research makes use of a transformer, which is based purely on a self-attention mechanism, without relying on recurrence at all. More specifically, encoders and decoders which make use of self-attention and operate based on a memory, are used. In this research work, results for various 3D visual and non-visual reinforcement learning tasks designed in Unity software were obtained. Convolutional neural networks, more specifically, nature CNN architecture, are used for input processing in visual tasks, and comparison with standard long short-term memory (LSTM) architecture is performed for both visual tasks based on CNNs and non-visual tasks based on coordinate inputs. This research work combines the transformer architecture with the proximal policy optimization technique used popularly in reinforcement learning for stability and better policy updates while training, especially for continuous action spaces, which are used in this research work. Certain tasks in this paper are long horizon tasks that carry on for a longer duration and require extensive use of memory-based functionalities like storage of experiences and choosing appropriate actions based on recall. The transformer, which makes use of memory and self-attention mechanism in an encoder-decoder configuration proved to have better performance when compared to LSTM in terms of exploration and rewards achieved. Such memory based architectures can be used extensively in the field of cognitive robotics and reinforcement learning.

Keywords: convolutional neural networks, reinforcement learning, self-attention, transformers, unity

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Authors: Binay Pattanayak

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More than 9 out of every 10 children in Jharkhand struggle to understand the texts and teachers in public schools. The medium of learning in the schools is Hindi, which is very different in structure and vocabulary than those in children’s home languages. Hence around 3 out of 10 children enrolled in early grades drop out in these schools. The state realized the cause of children’s high dropout in 2013-14 when the M-TALL, the language research shared the findings of a state-wide socio-linguistic study. The study findings suggested that there was a great need for initiating a mother-tongue based multilingual education (MTB-MLE) programme for the state in early grades starting from pre-school level. Accordingly, M-TALL in partnership with department of education designed two learning packages: Bhasha Puliya pre-school education programme for 3-6-year-old children for their school readiness with bilingual picture dictionaries in 9 tribal and regional languages. This was followed by a plan for MTB-MLE programme for early primary grades. For this textbooks in five tribal and two regional languages were developed under the guidance of the author. These books were printed and circulated in the 1000 schools of the state for each child. Teachers and community members were trained for facilitating culturally sensitive mother-tongue based learning activities in and around the schools. The mother-tongue based approach of learning has worked very effectively in enabling them to acquire the basic literacy and numeracy skills in own mother-tongues. Using this basic early grade reading skills, these children are able to learn Hindi and English systematically. Community resource groups were constituted in each school for promoting storytelling, singing, painting, dancing, acting, riddles, humor, sanitation, health, nutrition, protection, etc. and were trained. School academic calendar was designed in each school to enable the community resource persons to visit the school as per the learning plan to assist children and teacher in facilitating rich cultural activities in mother-tongue. This enables children to take part in plethora of learning activities and acquire desired knowledge, skills and interest in mother-tongues. Also in this process, it is attempted to promote 21st Century learning skills by enabling children to apply their new knowledge and skills to look at their local issues and address those in a collective manner through team work, innovations and leadership.

Keywords: community resource groups, learning, MTB-MLE, multilingual, socio-linguistic survey

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Authors: Richard Harrison

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Developing competency in mathematics and related critical thinking skills is essential to the education of undergraduate students of Science, Technology, Engineering and Mathematics (STEM). Recently, the HE sector has been impacted by a seemingly widening disconnect between the mathematical competency of incoming first-year STEM students and their entrance qualification tariffs. Despite relatively high grades in A-Level Mathematics, students may initially lack fundamental skills in key areas such as algebraic manipulation and have limited capacity to apply problem solving strategies. Compounded by compensatory measures applied to entrance qualifications during the pandemic, there has been an associated decline in student performance on introductory university mathematics modules. In the UK, a number of online resources have been developed to help scaffold the transition to university mathematics. However, in general, these do not offer a structured learning journey focused on individual developmental needs, nor do they offer an experience coherent with the teaching and learning characteristics of the destination institution. In order to address some of these issues, a bespoke framework has been designed and implemented on our VLE in the Faculty of Engineering & Physical Sciences (FEPS) at the University of Surrey. Called the FEPS Maths Support Framework, it was conceived to scaffold the mathematical development of individuals prior to entering the university and during the early stages of their transition to undergraduate studies. More than 90% of our incoming STEM students voluntarily participate in the process. Students complete a set of initial diagnostic questions in the late summer. Based on their performance and feedback on these questions, they are subsequently guided to self-select specific mathematical topic areas for review using our proprietary resources. This further assists students in preparing for discipline related diagnostic tests. The framework helps to identify students who are mathematically weak and facilitates early intervention to support students according to their specific developmental needs. This paper presents a summary of results from a rich data set captured from the framework over a 3-year period. Quantitative data provides evidence that students have engaged and developed during the process. This is further supported by process evaluation feedback from the students. Ranked performance data associated with seven key mathematical topic areas and eight engineering and science discipline areas reveals interesting patterns which can be used to identify more generic relative capabilities of the discipline area cohorts. In turn, this facilitates evidence based management of the mathematical development of the new cohort, informing any associated adjustments to teaching and learning at a more holistic level. Evidence is presented establishing our framework as an effective early intervention strategy for addressing the sector-wide issue of supporting the mathematical development of STEM students transitioning to HE

Keywords: competency, development, intervention, scaffolding

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Authors: Constant Akama, Frank Kulor, Frederick Agyemang

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All over the world, due to increasing population, electric power distribution companies are looking for more efficient ways of reading electricity meters. In Ghana, the prepaid metering system was introduced in 2007 to replace the manual system of reading which was fraught with inefficiencies. However, the prepaid system in Ghana is not capable of integration with online systems such as e-commerce platforms and remote monitoring systems. In this paper, we present a design framework for an automatic metering system that can be integrated with e-commerce platforms and remote monitoring systems. The meter was designed using ADE 7755 which reads the energy consumption and the reading is processed by a microcontroller connected to Sim900 General Packet Radio Service module containing a GSM chip provisioned with an Access Point Name. The system also has a billing server and a management server located at the premises of the utility company which communicate with the meter over a Virtual Private Network and GPRS. With this system, customers can buy credit online and the credit will be transferred securely to the meter. Also, when a fault is reported, the utility company can log into the meter remotely through the management server to troubleshoot the problem.

Keywords: access point name, general packet radio service, GSM, virtual private network

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Authors: Alanoud Moraya Aldalan, Abdulaziz Almaleh

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A crucial component of maintaining a customer-oriented business as in the telecom industry is understanding the reasons and factors that lead to customer churn. Competition between telecom companies has greatly increased in recent years. It has become more important to understand customers’ needs in this strong market of telecom industries, especially for those who are looking to turn over their service providers. So, predictive churn is now a mandatory requirement for retaining those customers. Machine learning can be utilized to accomplish this. Churn Prediction has become a very important topic in terms of machine learning classification in the telecommunications industry. Understanding the factors of customer churn and how they behave is very important to building an effective churn prediction model. This paper aims to predict churn and identify factors of customers’ churn based on their past service usage history. Aiming at this objective, the study makes use of feature selection, normalization, and feature engineering. Then, this study compared the performance of four different machine learning algorithms on the Orange dataset: Logistic Regression, Random Forest, Decision Tree, and Gradient Boosting. Evaluation of the performance was conducted by using the F1 score and ROC-AUC. Comparing the results of this study with existing models has proven to produce better results. The results showed the Gradients Boosting with feature selection technique outperformed in this study by achieving a 99% F1-score and 99% AUC, and all other experiments achieved good results as well.

Keywords: machine learning, gradient boosting, logistic regression, churn, random forest, decision tree, ROC, AUC, F1-score

Procedia PDF Downloads 134