Search results for: Deep learning

Authors: Chen Wang, Gerard Rowe

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The number of undergraduate engineering students enrolled in university has been increasing rapidly recently, leading to challenges associated with increased student-instructor ratios and increased diversity in academic preparedness of the entrants. An increased student-instructor ratio makes the interaction between teachers and students more difficult, with the resulting student ‘anonymity’ known to be a risk to academic success. With increasing student numbers, there is also an increasing diversity in the academic preparedness of the students at entry to university. Conceptual understanding of the entrants has been quantified via diagnostic testing, with the results for the first-year course in electrical engineering showing significant conceptual misunderstandings amongst the entry cohort. The solution is clearly multi-faceted, but part of the solution likely involves greater demands being placed on students to be masters of their own learning. In consequence, it is highly desirable that instructors help students to develop better self-regulated learning skills. A self-regulated learner is one who is capable of setting up their own learning goals, monitoring their study processes, adopting and adjusting learning strategies, and reflecting on their own study achievements. The methods by which instructors might cultivate students’ self-regulated learning abilities is receiving increasing attention from instructors and researchers. The aim of this study was to help students understand fully their self-regulated learning skill levels and provide targeted instructions to help them improve particular learning abilities in order to meet the curriculum requirements. As a survey tool, this research applied the questionnaire ‘Motivated Strategies for Learning Questionnaire’ (MSLQ) to collect first year engineering student’s self-reported data of their cognitive abilities, motivational orientations and learning strategies. MSLQ is a widely-used questionnaire for assessment of university student’s self-regulated learning skills. The questionnaire was offered online as a part of the online-scaffolding-learning tools to develop student understanding of self-regulated learning theories and learning strategies. The online tools, which have been under development since 2015, are designed to help first-year students understand their self-regulated learning skill levels by providing prompt feedback after they complete the questionnaire. In addition, the online tool also supplies corresponding learning strategies to students if they want to improve specific learning skills. A total of 866 first year engineering students who enrolled in the first-year electrical engineering course were invited to participate in this research project. By the end of the course 857 students responded and 738 of their questionnaires were considered as valid questionnaires. Analysis of these surveys showed that 66% of the students thought the online-scaffolding-learning tools helped significantly to improve their self-regulated learning abilities. It was particularly pleasing that 16.4% of the respondents thought the online-scaffolding-learning tools were extremely effective. A current thrust of our research is to investigate the relationships between students’ self-regulated learning abilities and their academic performance. Our results are being used by the course instructors as they revise the curriculum and pedagogy for this fundamental first-year engineering course, but the general principles we have identified are applicable to most first-year STEM courses.

Keywords: academic preparedness, online-scaffolding-learning tool, self-regulated learning, STEM education

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Authors: Sanjeeb Kumar Mohanty

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Content Based Instruction (CBI) in English Language Teaching (ELT) basically helps English as Second Language (ESL) learners of English. At the same time, it fosters multidisciplinary style of learning by promoting collaborative learning style. It is an approach to teaching ESL that attempts to combine language with interdisciplinary learning for bettering language proficiency and facilitating content learning. Hence, the basic purpose of CBI is that language should be taught in conjunction with academic subject matter. It helps in establishing the content as well as developing language competency. This study aims at supporting the potential values of interdisciplinary approach in promoting English Language Learning (ELL) by teaching writing skills to a small group of learners and discussing the findings with the teachers from various disciplines in a workshop. The teachers who are oriented, they use the same approach in their classes collaboratively. The inputs from the learners as well as the teachers hopefully raise positive consciousness with regard to the vast benefits that Content Based Instruction can offer in advancing the language competence of the learners.

Keywords: content based instruction, interdisciplinary approach, writing skills, collaborative approach

Procedia PDF Downloads 277

Authors: U. Borasi, Amit Kr. Jain, Rakesh, Piyush Jain

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Data collection, data preparation, model training, model evaluation, and deployment are all processes in a typical machine learning workflow. Training data needs to be gathered and organised. This often entails collecting a sizable dataset and cleaning it to remove or correct any inaccurate or missing information. Preparing the data for use in the machine learning model requires pre-processing it after it has been acquired. This often entails actions like scaling or normalising the data, handling outliers, selecting appropriate features, reducing dimensionality, etc. This pre-processed data is then used to train a model on some machine learning algorithm. After the model has been trained, it needs to be assessed by determining metrics like accuracy, precision, and recall, utilising a test dataset. Every time a new model is built, both data pre-processing and model training—two crucial processes in the Machine learning (ML) workflow—must be carried out. Thus, there are various Machine Learning algorithms that can be employed for every single approach to data pre-processing, generating a large set of combinations to choose from. Example: for every method to handle missing values (dropping records, replacing with mean, etc.), for every scaling technique, and for every combination of features selected, a different algorithm can be used. As a result, in order to get the optimum outcomes, these tasks are frequently repeated in different combinations. This paper suggests a simple architecture for organizing this largely produced “combination set of pre-processing steps and algorithms” into an automated workflow which simplifies the task of carrying out all possibilities.

Keywords: machine learning, automation, AUTOML, architecture, operator pool, configuration, scheduler

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Authors: Vasiliki Stratidou

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Modern simulation mobile games have the potential to enhance students’ interest, motivation and creativity. Research conducted on the effectiveness of digital games for educational purposes has shown that such games are also ideal at providing an appropriate environment for language learning. The paper examines the issue of simulation mobile games in regard to the potential positive impacts on L2 vocabulary learning. Sixteen intermediate level students, aged 10-14, participated in the experimental study for four weeks. The participants were divided into experimental (8 participants) and control group (8 participants). The experimental group was planned to learn some new vocabulary words via digital games while the control group used a reading passage to learn the same vocabulary words. The study investigated the effect of mobile games as well as the traditional learning methods on Greek EFL learners’ vocabulary learning in a pre-test, an immediate post-test, and a two-week delayed retention test. A teacher’s diary and learners’ interviews were also used as tools to estimate the effectiveness of the implementation. The findings indicated that the experimental group outperformed the control group in acquiring new words through mobile games. Therefore, digital games proved to be an effective tool in learning English vocabulary.

Keywords: control group, digital games, experimental group, second language vocabulary learning, simulation games

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Authors: Luis Miguel Méndez Díaz

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In this article, a mathematics teaching-learning strategy will be presented, specifically differential calculus in one variable, in a fun and competitive space in which the action on the part of the student is manifested and not only the repetition of information on the part of the teacher. Said action refers to motivating, problematizing, summarizing, and coordinating a game of dominoes whose thematic cards are designed around the basic and main contents of differential calculus. The strategies for teaching this area are diverse and precisely the game of dominoes is one of the most used strategies in the practice of mathematics because it stimulates logical reasoning and mental abilities. The objective on this investigation is to identify the way in which the game of dominoes affects the learning and understanding of fundamentals concepts of differential calculus in one variable through experimentation carried out on students of the first semester of the School of Engineering and Sciences of the Technological Institute of Monterrey Campus Querétaro. Finally, the results of this study will be presented and the use of this strategy in other topics around mathematics will be recommended to facilitate logical and meaningful learning in students.

Keywords: collaborative learning, logical-mathematical intelligence, mathematical games, multiple intelligences

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Authors: Ubon Asuquo Essien, Okwudili Bismark Ibeagwa, Daberechi Peace Ubabuko

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The Broiler Poultry subsector is dominated by small scale production with low aggregate output. The high cost of inputs currently experienced in Nigeria tends to aggravate the situation; hence many broiler farmers struggle to break-even. This study was designed to examine income and input factors in small scale deep liter broiler production in Imo state, Nigeria. Specifically, the study examined; socio-economic characteristics of small scale deep liter broiler producing Poultry farmers; estimate cost and returns of broiler production in the area; analyze input factors in broiler production in the area and examined marketability, age and profitability of the enterprise. A multi-stage sampling technique was adopted in selecting 60 small scale broiler farmers who use deep liter system from 6 communities through the use of structured questionnaire. The socioeconomic characteristics of the broiler farmers and the profitability/ marketability age of the birds were described using descriptive statistical tools such as frequencies, means and percentages. Gross margin analysis was used to analyze the cost and returns to broiler production, while Cobb Douglas production function was employed to analyze input factors in broiler production. The result of the study revealed that the cost of feed (P<0.1), deep liter material (P<0.05) and medication (P<0.05) had a significant positive relationship with the gross return of broiler farmers in the study area, while cost of labour, fuel and day old chicks were not significant. Furthermore, Gross profit margin of the farmers who market their broiler at the 8th week of rearing was 80.7%; and 78.7% and 60.8% for farmers who market at the 10th week and 12th week of rearing, respectively. The business is, therefore, profitable but at varying degree. Government and Development partners should make deliberate efforts to curb the current rise in the prices of poultry feeds, drugs and timber materials used as bedding so as to widen the profit margin and encourage more farmers to go into the business. The farmers equally need more technical assistance from extension agents with regards to timely and profitable marketing.

Keywords: broilers, factor analysis, income, small scale

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Authors: Mohamed Elhadi M. Sharif, Mona Masood

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The usage of e-health facilities is seen to be the first priority by the Libyan government. As such, this paper focuses on how the key factors or elements of working size in terms of technological availability, structural environment, and other competence-related matters may affect nurses’ sharing of knowledge in e-health. Hence, this paper investigates learning readiness assessment to raise e-health for Libyan regional hospitals by using e-health services in nursing education.

Keywords: Libyan nurses, e-learning readiness, e-health, nursing education

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Authors: Gladys Gakenia Njoroge

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Mathematics is a compulsory subject in both primary and secondary schools in Kenya. However, learners’ poor performance in the subject in Kenya national examinations year in year out remains a serious concern for teachers of Mathematics, parents, curriculum developers, and the general public. This is particularly worrying because of the importance attached to the subject in national development hence the need to find out what could be affecting learning of Mathematics in Kenyan schools. The research on which this paper is based sought to examine the factors that influence performance in Mathematics in Kenyan schools; identify the characteristics of Mathematics learning disabilities; determine how the learners with such learning disabilities can be assessed and identified and interventions for these difficulties implemented. A case study was undertaken on class six learners in a primary school in Nairobi County. The tools used for the research were: classroom observations and an Individualized Education Program (IEP) developed by the teachers with the help of the researcher. This paper therefore highlights the findings from the research, discusses the implications of the findings and suggests the way forward as far as teaching, learning and assessment of Mathematics in Kenyan schools is concerned. Perhaps with the application of the right interventions, poor performance in Mathematics in the national examinations in Kenya will be a thing of the past.

Keywords: demystifying mathematics, individualized education program, learning difficulties, assessment

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Authors: Muhammad Ahnaf Zahin, Yaw Adu-Gyamfi

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Bus transit is a crucial component of transportation networks, especially in urban areas. Any intelligent transportation system must have accurate real-time information on bus travel times since it minimizes waiting times for passengers at different stations along a route, improves service reliability, and significantly optimizes travel patterns. Bus agencies must enhance the quality of their information service to serve their passengers better and draw in more travelers since people waiting at bus stops are frequently anxious about when the bus will arrive at their starting point and when it will reach their destination. For solving this issue, different models have been developed for predicting bus travel times recently, but most of them are focused on smaller road networks due to their relatively subpar performance in high-density urban areas on a vast network. This paper develops a deep learning-based architecture using a single-step multi-station forecasting approach to predict average bus travel times for numerous routes, stops, and trips on a large-scale network using heterogeneous bus transit data collected from the GTFS database. Over one week, data was gathered from multiple bus routes in Saint Louis, Missouri. In this study, Gated Recurrent Unit (GRU) neural network was followed to predict the mean vehicle travel times for different hours of the day for multiple stations along multiple routes. Historical time steps and prediction horizon were set up to 5 and 1, respectively, which means that five hours of historical average travel time data were used to predict average travel time for the following hour. The spatial and temporal information and the historical average travel times were captured from the dataset for model input parameters. As adjacency matrices for the spatial input parameters, the station distances and sequence numbers were used, and the time of day (hour) was considered for the temporal inputs. Other inputs, including volatility information such as standard deviation and variance of journey durations, were also included in the model to make it more robust. The model's performance was evaluated based on a metric called mean absolute percentage error (MAPE). The observed prediction errors for various routes, trips, and stations remained consistent throughout the day. The results showed that the developed model could predict travel times more accurately during peak traffic hours, having a MAPE of around 14%, and performed less accurately during the latter part of the day. In the context of a complicated transportation network in high-density urban areas, the model showed its applicability for real-time travel time prediction of public transportation and ensured the high quality of the predictions generated by the model.

Keywords: gated recurrent unit, mean absolute percentage error, single-step forecasting, travel time prediction.

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Authors: Gunniga Anugkakul, Suwaree Yordchim

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The objectives were to study language learning strategies (LLSs) employed by Chinese students, and the frequency of LLSs they used, and examine the relationship between the use of LLSs and gender. The Strategy Inventory for Language Learning (SILL) by Oxford was administered to thirty-six Chinese students at Suan Sunandha Rajabhat University in Thailand. The data obtained was analyzed using descriptive statistics and chi-square tests. Three useful findings were found on the use of LLSs reported by Chinese students. First, Chinese students used overall LLSs at a high level. Second, among the six strategy groups, Chinese students employed compensation strategy most frequently and memory strategy least frequently. Third, the research results also revealed that gender had significant effect on Chinese Student’s use of overall LLSs.

Keywords: English language, language learning strategy, Chinese students, compensation strategy

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Authors: Nigar Hussain

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It is a subset of big data. Dark data means those data in which we fail to use for future decisions. There are many issues in existing work, but some need powerful tools for utilizing dark data. It needs sufficient techniques to deal with dark data. That enables users to exploit their excellence, adaptability, speed, less time utilization, execution, and accessibility. Another issue is the way to utilize dark data to extract helpful information to settle on better choices. In this paper, we proposed upgrade strategies to remove the dark side from dark data. Using a supervised model and machine learning techniques, we utilized dark data and achieved an F1 score of 89.48%.

Keywords: big data, dark data, machine learning, heatmap, random forest

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Authors: Danute Karcauskiene, Dalia Ambrazaitiene, Regina Skuodiene, Monika Vilkiene, Regina Repsiene, Ieva Jokubauskaite

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The main ambition for nowadays agriculture is to get the economically effective yield and to secure the soil ecological sustainability. According to the effect on the main soil quality indexes, tillage systems may be separated into two types, conventional and conservation tillage. The goal of this study was to determine the impact of conservation and conventional primary soil tillage methods and soil fertility improvement measures on soil properties and crop productivity. Methods: The soil of the experimental site is Dystric Glossic Retisol (WRB 2014) with texture of sandy loam. The trial was established in 2003 in the experimental field of crop rotation of Vėžaičiai Branch of Lithuanian Research Centre for Agriculture and Forestry. Trial factors and treatments: factor A- primary soil tillage in (autumn): deep ploughing (20-25cm), shallow ploughing (10-12cm), shallow ploughless tillage (8-10cm); factor B – soil fertility improvement measures: plant residues, plant residues + straw, green manure 1st cut + straw, farmyard manure 40tha-1 + straw. The four - course crop rotation consisted of red clover, winter wheat, spring rape and spring barley with undersown. Results: The tillage had no statistically significant effect on topsoil (0-10 cm) pHKCl level, it was 5.5 - 5.7. During all experiment period, the highest soil pHKCl level (5.65) was in the shallow ploughless tillage. The organic fertilizers particularly the biomass of grass and farmyard manure had tendency to increase the soil pHKCl. The content of plant - available phosphorus and potassium significantly increase in the shallow ploughing compared with others tillage systems. The farmyard manure increases those elements in whole arable layer. The dissolved organic carbon concentration was significantly higher in the 0 - 10 cm soil layer in the shallow ploughless tillage compared with deep ploughing. After the incorporation of clover biomass and farmyard manure the concentration of dissolved organic carbon increased in the top soil layer. During all experiment period the largest amount of water stable aggregates was determined in the soil where the shallow ploughless tillage was applied. It was by 12% higher compared with deep ploughing. During all experiment time, the soil moisture was higher in the shallow ploughing and shallow ploughless tillage (9-27%) compared to deep ploughing. The lowest emission of CO2 was determined in the deep ploughing soil. The highest rate of CO2 emission was in shallow ploughless tillage. The addition of organic fertilisers had a tendency to increase the CO2 emission, but there was no statistically significant effect between the different types of organic fertilisers. The crop yield was larger in the deep ploughing soil compared to the shallow and shallow ploughless tillage.

Keywords: reduced tillage, soil structure, soil pH, biological activity, crop productivity

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Authors: Didiosky Benítez-Erice, Frederik Questier, Dalgys Pérez-Luján

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This paper aims to present two models around the production of students’ experiential knowledge in the teaching-learning process of higher education: the teacher-centered production model and the student-centered production model. From a range of knowledge management and experiential learning theories, the paper elaborates into the nature of students’ experiential knowledge and proposes further adjustments of existing second-generation knowledge management theories taking into account the particularities of higher education. Despite its theoretical nature the paper can be relevant for future studies that stress student-driven improvement and innovation at higher education institutions.

Keywords: experiential knowledge, higher education, knowledge management, teaching-learning process

Procedia PDF Downloads 446

Authors: Umar Albalawi, Sang C. Suh, Jinoh Kim

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As internet continues to expand its usage with an enormous number of applications, cyber-threats have significantly increased accordingly. Thus, accurate detection of malicious traffic in a timely manner is a critical concern in today’s Internet for security. One approach for intrusion detection is to use Machine Learning (ML) techniques. Several methods based on ML algorithms have been introduced over the past years, but they are largely limited in terms of detection accuracy and/or time and space complexity to run. In this work, we present a novel method for intrusion detection that incorporates a set of supervised learning algorithms. The proposed technique provides high accuracy and outperforms existing techniques that simply utilizes a single learning method. In addition, our technique relies on partial flow information (rather than full information) for detection, and thus, it is light-weight and desirable for online operations with the property of early identification. With the mid-Atlantic CCDC intrusion dataset publicly available, we show that our proposed technique yields a high degree of detection rate over 99% with a very low false alarm rate (0.4%).

Keywords: intrusion detection, supervised learning, traffic classification, computer networks

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Authors: Amal A. Abdel-Sattar

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The curriculum of architecture department in Prince Sultan University includes ‘Building Surveying’ course which is usually a part of civil engineering courses. As a fundamental requirement of the course, it requires a strong background in mathematics and physics, which are not usually preferred subjects to the architecture students and many of them are not giving the required and necessary attention to these courses during their preparation year before commencing their architectural study. This paper introduces the concept and the methodology of the student-centered learning approach in the course of building surveying for architects. One of the major outcomes is the improvement in the students’ involvement in the course and how this will cover and strength their analytical weak points and improve their mathematical skills. The study is conducted through three semesters with a total number of 99 students. The effectiveness of the student-centered learning approach is studied using the student survey at the end of each semester and teacher observations. This survey showed great acceptance of the students for these methods. Also, the teachers observed a great improvement in the students’ mathematical abilities and how keener they became in attending the classes which were clearly reflected on the low absence record.

Keywords: architecture, building surveying, student-centered learning, teaching and learning

Procedia PDF Downloads 252

Authors: Kanlaya Ratanasuphakarn, Suttipong Boonphadung

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The research on the development of ability in reading comprehension based on metacognitive strategies aimed to (1) improve the students’development of ability in reading comprehension based on metacognitive strategies, (2) evaluate the students’ satisfaction on using metacognitive strategies in learning as a tool developing the ability in reading comprehension. Forty-eight of Mattayom 3 students who have enrolled in the subject of research for learning development of semester 2 in 2013 were purposively selected as the research cohort. The research tools were lesson plans for reading comprehension, pre-posttest and satisfaction questionnaire that were approved as content validity and reliability (IOC=.66-1.00,0.967). The research found that the development of ability in reading comprehension of the research samples before using metacognitive strategies in learning activities was in the normal high level. Additionally, the research discovered that the students’ satisfaction of the research cohort after applying model in learning activities appeared to be high level of satisfaction on using metacognitive strategies in learning as a tool for the development of ability in reading comprehension.

Keywords: development of ability, metacognitive strategies, satisfaction, reading comprehension

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Authors: C. W. Kan

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This study examines the results of optical whitening process of different textiles such as cotton, wool and polyester. The optical whitening agents used are commercially available products, and the optical whitening agents were applied to the textiles with manufacturers’ suggested methods. The aim of this study is to illustrate the proper application methods of optical whitening agent to different textiles and hence to provide guidance note to the students in learning this topic. Acknowledgment: Authors would like to thank the financial support from the Hong Kong Polytechnic University for this work.

Keywords: learning materials, optical whitening agent, wool, cotton, polyester

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Authors: R. Abdulrahman, A. Eardley, A. Soliman

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The proliferation in the development of mobile learning (m-learning) has played a vital role in the rapidly growing electronic learning market. This relatively new technology can help to encourage the development of in learning and to aid knowledge transfer a number of areas, by familiarizing students with innovative information and communications technologies (ICT). M-learning plays a substantial role in the deployment of learning methods for nursing students by using the Internet and portable devices to access learning resources ‘anytime and anywhere’. However, acceptance of m-learning by students is critical to the successful use of m-learning systems. Thus, there is a need to study the factors that influence student’s intention to use m-learning. This paper addresses this issue. It outlines the outcomes of a study that evaluates the unified theory of acceptance and use of technology (UTAUT) model as applied to the subject of user acceptance in relation to m-learning activity in nurse education. The model integrates the significant components across eight prominent user acceptance models. Therefore, a standard measure is introduced with core determinants of user behavioural intention. The research model extends the UTAUT in the context of m-learning acceptance by modifying and adding individual innovativeness (II) and quality of service (QoS) to the original structure of UTAUT. The paper goes on to add the factors of previous experience (of using mobile devices in similar applications) and the nursing students’ readiness (to use the technology) to influence their behavioural intentions to use m-learning. This study uses a technique called ‘convenience sampling’ which involves student volunteers as participants in order to collect numerical data. A quantitative method of data collection was selected and involves an online survey using a questionnaire form. This form contains 33 questions to measure the six constructs, using a 5-point Likert scale. A total of 42 respondents participated, all from the Nursing Institute at the Armed Forces Hospital in Saudi Arabia. The gathered data were then tested using a research model that employs the structural equation modelling (SEM), including confirmatory factor analysis (CFA). The results of the CFA show that the UTAUT model has the ability to predict student behavioural intention and to adapt m-learning activity to the specific learning activities. It also demonstrates satisfactory, dependable and valid scales of the model constructs. This suggests further analysis to confirm the model as a valuable instrument in order to evaluate the user acceptance of m-learning activity.

Keywords: mobile learning, nursing institute students’ acceptance of m-learning activity in Saudi Arabia, unified theory of acceptance and use of technology model (UTAUT), structural equation modelling (SEM)

Procedia PDF Downloads 188

Authors: Naser Alajmi, Ali Alobaidly, Mubarak Alhajri, Salem Salamah, Muhammad Alsubaie

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Iterative Learning Control (ILC) known to be a controlling tool to overcome periodic disturbances for repetitive systems. This technique is required to let the error signal tends to zero as the number of operation increases. The learning process that lies within this context is strongly dependent on the initial input which if selected properly tends to let the learning process be more effective compared to the case where a system starts from blind. ILC uses previous recorded execution data to update the following execution/trial input such that a reference trajectory is followed to a high accuracy. Error convergence in ILC is generally highly dependent on the input applied to a plant for trial $1$, thus a good choice of initial starting input signal would make learning faster and as a consequence the error tends to zero faster as well. In the work presented within, an upper limit based on the Singular Values Principle (SV) is derived for the initial input signal applied at trial $1$ such that the system follow the reference in less number of trials without responding aggressively or exceeding the working envelope where a system is required to move within in a robot arm, for example. Simulation results presented illustrate the theory introduced within this paper.

Keywords: initial input, iterative learning control, maximum input, singular values

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Authors: Payal Maheshwari, Maheaswari Brindavan

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The present study aimed at studying the level of perceived self-efficacy of children with learning disability and their mother’s perception about the efficacy of the child and the relationship between the two. The study further aimed at finding out the relationship between the level of perceived self-efficacy of children with learning disability and their academic achievement and their mother’s perception about the Efficacy of the child and child’s Academic Achievement. The sample comprised of 80 respondents (40 children with learning disability and their mothers). Children with learning disability as their primary condition, belonging to middle or upper middle class, living with both the parents, residing in Mumbai and their mothers were selected. Purposive or judgmental and snowball sampling technique was used to select the sample for the present study. Proformas in the form of questionnaires were used to obtain the background information of the children with learning disability and their mother’s. A self-constructed Mother’s Perceived Efficacy of their Child Assessment Scale was used to measure mothers perceived level of efficacy of their child with learning disability. Self-constructed Child’s Perceived Self-Efficacy Assessment Scale was used to measure the level of child’s perceived self-efficacy. Academic scores of the child were collected from the child’s parents or teachers and were converted into percentage. The data were analyzed quantitatively using frequencies, mean and standard deviation. Correlations were computed to ascertain the relationships between the different variables. The findings revealed that majority of the mother’s perceived efficacy about their child with learning disability was above average as well as majority of the children with learning disability also perceived themselves as having above average level of self-efficacy. Further in the domains of self-regulated learning and emotional self-efficacy majority of the mothers perceived their child as having average or below average efficacy, 50% of the children also perceived their self-efficacy in the two domains at average or below average level. A significant (r=.322, p < .05) weak correlation (Spearman’s rho) was found between mother’s perceived efficacy about their child, and child’s perceived self-efficacy and a significant (r=.377, p < .01) weak correlation (Pearson Correlation) was also found between mother’s perceived efficacy about their child and child’s academic achievement. Significant weak positive correlation was found between child’s perceived self-efficacy and academic achievement (r=.332, p < .05). Based on the findings, the study discussed the need for intervention program for children in non-academic skills like self-regulation and emotional competence.

Keywords: learning disability, perceived self efficacy, academic achievement, mothers, children

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Authors: Khan Zeenat, S. B. Dandegaonkar

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Dyslexia is a neurological disorder which affects the reading and writing ability of children. A sample of 72 dyslexic children (36 from English medium and 36 from Marathi medium schools) of class V from English and Marathi medium schools were selected. The Experimental method was used to study the effect of Remedial Teaching Programme on the Learning outcome of Dyslexic students. The findings showed that there is a Positive effect of remedial teaching programme on the Learning outcome of English and Marathi medium students.

Keywords: remedial teaching, Dyslexic students, learning outcome, neurological

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Authors: Asra Yousuf, Ajaykumar Tannirkulum

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Inferring rural-urban migration trends can help design effective policies that promote better urban planning and rural development. In this paper, we describe how machine learning algorithms can be applied to predict internal migration decisions of people. We consider data collected from household surveys in Tamil Nadu to train our model. To measure the performance of the model, we use data on past migration from National Sample Survey Organisation of India. The factors for training the model include socioeconomic characteristic of each individual like age, gender, place of residence, outstanding loans, strength of the household, etc. and his past migration history. We perform a comparative analysis of the performance of a number of machine learning algorithm to determine their prediction accuracy. Our results show that machine learning algorithms provide a stronger prediction accuracy as compared to statistical models. Our goal through this research is to propose the use of data science techniques in understanding human decisions and behaviour in developing countries.

Keywords: development, migration, internal migration, machine learning, prediction

Procedia PDF Downloads 271

Authors: G. S. Androulakis, G. Deli, M. Kaisari, N. Mihos

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Teaching practices at the university level have changed and developed during the last decade. Implementation of inverted classroom method in secondary education consists of a well-formed basis for academic teachers. On the other hand, distance learning is a well-known field in education research and widespread as a method of teaching. Nonetheless, the new pandemic found many Universities all over the world unprepared, which made adaptations to new methods of teaching a necessity. In this paper, we analyze a model of an inverted university classroom in a distance learning context. Thus, the main purpose of our research is to investigate students’ difficulties as they transit to a new style of teaching and explore their learning development during a semester totally different from others. Our teaching experiment took place at the Business Administration department of the University of Patras, in the context of two courses: Calculus, a course aimed at first-year students, and Statistics, a course aimed at second-year students. Second-year students had the opportunity to attend courses in the university classroom. First-year students started their semester with distance learning. Using a comparative study of these two groups, we explored significant differences in students’ learning procedures. Focused group interviews, written tests, analyses of students’ dialogues were used in a mixed quantity and quality research. Our analysis reveals students’ skills, capabilities but also a difficulty in following, non-traditional style of teaching. The inverted classroom model, according to our findings, offers benefits in the educational procedure, even in a distance learning environment.

Keywords: distance learning, higher education, inverted classroom, mathematics teaching

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Authors: Prakash Kumar Nayak, Avinash Kumar, Uma Dash, Kalpana Rayaguru

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Soybean oil is one of the most widely consumed cooking oils, worldwide. Deep-fat frying of foods at higher temperatures adds unique flavour, golden brown colour and crispy texture to foods. But it brings in various changes like hydrolysis, oxidation, hydrogenation and thermal alteration to oil. The presence of Peroxide value (PV) is one of the most important factors affecting the quality of the deep-fat fried oil. Using bentonite as an adsorbent, the PV can be reduced, thereby improving the quality of the soybean oil. In this study, operating parameters like heating time of oil (10, 15, 20, 25 & 30 h), contact time ( 5, 10, 15, 20, 25 h) and concentration of adsorbent (0.25, 0.5, 0.75, 1.0 and 1.25 g/ 100 ml of oil) have been optimized by response surface methodology (RSM) considering percentage reduction of PV as a response. Adsorption data were analysed by fitting with Langmuir and Freundlich isotherm model. The results show that the Langmuir model shows the best fit compared to the Freundlich model. The adsorption process was also found to follow a pseudo-second-order kinetic model.

Keywords: bentonite, Langmuir isotherm, peroxide value, RSM, soybean oil

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Authors: Olukemi E. Adetuyi-Olu-Francis

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Learning is natural for living. One stops learning when life ends. Hence, there is no negotiating life-long learning. An individual has the innate ability to learn as many languages as he/she desires as long as life exists. French language education to every Nigerian teacher-trainee is a necessity. Nigeria’s geographical location requires that the French language should be upheld for economic and cultural co-operations between Nigeria and the francophone countries sharing borders with her. The French language will enhance the leadership roles of the teacher-trainees and their ability to function across borders. The 21st century learning tools are basically digital, and many apps are complementing the actual classroom interactions. This study examined the communicative competence in the French language to equip Nigerian teacher-trainees in the new-normal society using mobile apps as a lifelong learning tool. Three research questions and hypotheses guided the study, and the researcher adopted a pre-test, a post-test experimental design, using a sample size of 87 teacher-trainees in South-south geopolitical zone of Nigeria. Results showed that the use of mobile apps is effective for learning the French language. One of the recommendations is that the use of mobile apps should be encouraged for all Nigerian youths to learn the French language for enhancing leadership roles in the world of work and for international interactions for socio-economic co-operations with Nigerian neighboring countries.

Keywords: communicative competence, french language, life long learning, mobile apps, new normal society, teacher trainees

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Authors: Agah Tugrul Korucu

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Significant changes have taken place for the better in the bulk of information and in the use of technology available in the field of education induced by technological changes in the 21st century. It is mainly the job of the teachers and pre-service teachers to integrate information and communication technologies into education by means of conveying the use of technology to individuals. While the pre-service teachers are conducting lessons by using technology, the methods they have developed are important factors for the requirements of the lesson and for the satisfaction levels of the students. The study of this study is to examine the satisfaction levels of pre-service teachers as regards e-learning in a technological environment in which there are lesson activities conducted through an online learning environment in terms of various variables. The study group of the research is composed of 156 pre-service teachers that were students in the departments of Computer and Teaching Technologies, Art Teaching and Pre-school Teaching in the academic year of 2014 - 2015. The qualitative research method was adopted for this study; the scanning model was employed in collecting the data. “The Satisfaction Scale regarding the E-learning Process”, developed by Gülbahar, and the personal information form, which was developed by the researcher, were used as means of collecting the data. Cronbach α reliability coefficient, which is the internal consistency coefficient of the scale, is 0.91. SPSS computerized statistical package program and the techniques of medium, standard deviation, percentage, correlation, t-test and variance analysis were used in the analysis of the data.

Keywords: online learning environment, integration of information technologies, e-learning, e-learning satisfaction, pre-service teachers

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Authors: Manthekeleng Linake, Fesi Liziwe

Abstract:

The ongoing argument over the use of English as a learning and teaching language in schools was examined in this study. The nature of the language proficiency gap is particularly relevant in light of the present emphasis on learning and educational quality in contemporary debates, as well as the education sustainable development goal. As a result, an interpretivist paradigm, a qualitative technique, and a case study-based research design were used in the work. Two school principals, two teachers, two members of the School Governing Body (SGB), and four learners were chosen using purposive sampling from two schools in the Amathole West Education District. The researchers were able to acquire in-depth information on the disputes surrounding the use of English as a language of learning and teaching by using semi-structured interview questions and focus groups. Despite knowing that they do not have the potential to do well in English, teachers found that despite appreciating the value of mother tongue and cultural identity, they prefer to use English as the language of teaching in schools. The findings, on the other hand, revealed that proponents of mother-language-based education argue that learning one's mother tongue is a human right.

Keywords: English first additional language learners, social justice, human capabilities, language proficiency

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Authors: Asha Dukkipati

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Cognitive neuroscience explores neural functioning and aberrant brain activity during cognitive and perceptual tasks. Neurocinematics is a subfield of cognitive neuroscience that observes neural responses of individuals watching a film to see similarities and differences between individuals. This method is typically used for commercial use, allowing directors and filmmakers to produce better visuals and increasing their results in the box office. However, neurocinematics is increasingly becoming a common tool for neuroscientists interested in studying similar patterns of brain activity across viewers outside of the film industry. In this review, it argue that neurocinematics provides an easy, naturalistic approach for studying and diagnosing learning disorders. While the neural underpinnings of developmental learning disorders are traditionally assessed with well-established methods like EEG and fMRI that target particular cognitive domains, such as simple visual and attention tasks, there is initial evidence and theoretical background in support of neurocinematics as a biomarker for learning differences. By using ADHD, dyslexia, and autism as case studies, this literature review discusses the potential advantages of neurocinematics as a new tool for learning disorders research.

Keywords: behavioral and social sciences, neuroscience, neurocinematics, biomarkers, neurobehavioral disorders

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Authors: Khaled M. Alhawiti

Abstract:

Natural Language Processing (NLP) is an effective approach for bringing improvement in educational setting. This involves initiating the process of learning through the natural acquisition in the educational systems. It is based on following effective approaches for providing the solution for various problems and issues in education. Natural Language Processing provides solution in a variety of different fields associated with the social and cultural context of language learning. It is based on involving various tools and techniques such as grammar, syntax, and structure of text. It is effective approach for teachers, students, authors, and educators for providing assistance for writing, analysis, and assessment procedure. Natural Language Processing is widely integrated in the large number of educational contexts such as research, science, linguistics, e-learning, evaluations system, and various other educational settings such as schools, higher education system, and universities. Natural Language Processing is based on applying scientific approach in the educational settings. In the educational settings, NLP is an effective approach to ensure that students can learn easily in the same way as they acquired language in the natural settings.

Keywords: natural language processing, education, application, e-learning, scientific studies, educational system

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Authors: Jinan Fiaidhi, Sabah Mohammed, Petros Zezos

Abstract:

Capsule endoscopy (CE) is an established noninvasive diagnostic modality in investigating small bowel disease. CE has a pivotal role in assessing patients with suspected bleeding or identifying evidence of active Crohn's disease in the small bowel. However, CE produces lengthy videos with at least eighty thousand frames, with a frequency rate of 2 frames per second. Gastroenterologists cannot dedicate 8 to 15 hours to reading the CE video frames to arrive at a diagnosis. This is why the issue of analyzing CE videos based on modern artificial intelligence techniques becomes a necessity. However, machine learning, including deep learning, has failed to report robust results because of the lack of large samples to train its neural nets. In this paper, we are describing a thick data approach that learns from a few anchor images. We are using sound datasets like KVASIR and CrohnIPI to filter candidate frames that include interesting anomalies in any CE video. We are identifying candidate frames based on feature extraction to provide representative measures of the anomaly, like the size of the anomaly and the color contrast compared to the image background, and later feed these features to a decision tree that can classify the candidate frames as having a condition like the Crohn's Disease. Our thick data approach reported accuracy of detecting Crohn's Disease based on the availability of ulcer areas at the candidate frames for KVASIR was 89.9% and for the CrohnIPI was 83.3%. We are continuing our research to fine-tune our approach by adding more thick data methods for enhancing diagnosis accuracy.

Keywords: thick data analytics, capsule endoscopy, Crohn’s disease, siamese neural network, decision tree

Procedia PDF Downloads 156