Search results for: module based teaching and learning

Authors: Islam Elsayed Hussein

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The aim of this paper is to discover the impact of students’ attitude towards social media and the skills required to adopt social media as a university e-learning (2.0) platform. In addition, it measures the effect of social media adoption on interactive learning effectiveness. The population of this study was students at Faculty of tourism and Hotels, Fayoum University. A questionnaire was used as a research instrument to collect data from respondents, which had been selected randomly. Data had been analyzed using quantitative data analysis method. Findings showed that the students have a positive attitude towards adopting social networking in the learning process and they have also good skills for effective use of social networking tools. In addition, adopting social media is effectively affecting the interactive learning environment.

Keywords: attitude, skills, e-learning 2.0, interactive learning, Egypt

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Authors: Srushti Patil, Preethi Baligar, Gopalkrishna Joshi, Gururaj N. Bhadri

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In designing learning environments, the instructional strategies can be tailored to suit the learning style of an individual to ensure effective learning. In this study, the information shared on social media like Facebook is being used to predict learning style of a learner. Previous research studies have shown that Facebook data can be used to predict user personality. Users with a particular personality exhibit an inherent pattern in their digital footprint on Facebook. The proposed work aims to correlate the user's’ personality, predicted from Facebook data to the learning styles, predicted through questionnaires. For Millennial learners, Facebook has become a primary means for information sharing and interaction with peers. Thus, it can serve as a rich bed for research and direct the design of learning environments. The authors have conducted this study in an undergraduate freshman engineering course. Data from 320 freshmen Facebook users was collected. The same users also participated in the learning style and personality prediction survey. The Kolb’s Learning style questionnaires and Big 5 personality Inventory were adopted for the survey. The users have agreed to participate in this research and have signed individual consent forms. A specific page was created on Facebook to collect user data like personal details, status updates, comments, demographic characteristics and egocentric network parameters. This data was captured by an application created using Python program. The data captured from Facebook was subjected to text analysis process using the Linguistic Inquiry and Word Count dictionary. An analysis of the data collected from the questionnaires performed reveals individual student personality and learning style. The results obtained from analysis of Facebook, learning style and personality data were then fed into an automatic classifier that was trained by using the data mining techniques like Rule-based classifiers and Decision trees. This helps to predict the user personality and learning styles by analysing the common patterns. Rule-based classifiers applied for text analysis helps to categorize Facebook data into positive, negative and neutral. There were totally two models trained, one to predict the personality from Facebook data; another one to predict the learning styles from the personalities. The results show that the classifier model has high accuracy which makes the proposed method to be a reliable one for predicting the user personality and learning styles.

Keywords: educational data mining, Facebook, learning styles, personality traits

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Authors: Ram A. Giri, Amna Bedri, Abdou Niane

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Exclusion in education on the basis of language in multilingual contexts operates at multiple levels. Learners of diverse ethnolinguistic backgrounds are often expected to learn through English and are pushed further down the learning ladder if they also have to access education through Information and Communication Technology (ICT). The paper explores marginalized children’s lived experiences in accessing technology and English in four low-income countries in Africa and Asia. Based on the findings of the first phase of a multinational qualitative research study, we report on the factors or barriers that affect children’s access, opportunities and motivation for learning through technology and English. ICT and English - the language of ICT and education - can enhance learning and can even be essential. However, these two important keys to education can also function as barriers to accessing quality education, and therefore as zones of exclusion. This paper looks into how marginalized children (aged 13-15) engage in learning through ICT and English and to what extent the restrictive access and opportunities contribute to the widening of the already existing gap in education. By applying the conceptual frameworks of “access and accessibility of learning” and “zones of exclusion,” the paper elucidates how the barriers prevent children’s effective engagement with learning and addresses such questions as to how marginalized children access technology and English for learning; whether the children value English, and what their motivation and opportunity to learn it are. In addition, the paper will point out policy and pedagogic implications.

Keywords: exclusion, inclusion, inclusive education, marginalization

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Authors: R. Hocine, A. Boudjemai, A. Amrani, K. Belkacemi

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Temperature rising is a negative factor in almost all systems. It could cause by self heating or ambient temperature. In solar photovoltaic cells this temperature rising affects on the behavior of cells. The ability of a PV module to withstand the effects of periodic hot-spot heating that occurs when cells are operated under reverse biased conditions is closely related to the properties of the cell semi-conductor material. In addition, the thermal effect also influences the estimation of the maximum power point (MPP) and electrical parameters for the PV modules, such as maximum output power, maximum conversion efficiency, internal efficiency, reliability, and lifetime. The cells junction temperature is a critical parameter that significantly affects the electrical characteristics of PV modules. For practical applications of PV modules, it is very important to accurately estimate the junction temperature of PV modules and analyze the thermal characteristics of the PV modules. Once the temperature variation is taken into account, we can then acquire a more accurate MPP for the PV modules, and the maximum utilization efficiency of the PV modules can also be further achieved. In this paper, the three-Dimensional Transmission Line Matrix (3D-TLM) method was used to map the surface temperature distribution of solar cells while in the reverse bias mode. It was observed that some cells exhibited an inhomogeneity of the surface temperature resulting in localized heating (hot-spot). This hot-spot heating causes irreversible destruction of the solar cell structure. Hot spots can have a deleterious impact on the total solar modules if individual solar cells are heated. So, the results show clearly that the solar cells are capable of self-generating considerable amounts of heat that should be dissipated very quickly to increase PV module's lifetime.

Keywords: thermal effect, conduction, heat dissipation, thermal conductivity, solar cell, PV module, nodes, 3D-TLM

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Authors: D. K. Kumador, E. A. Muthivhi

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Historically, reforms in early childhood education in Ghana have focused narrowly on structural and pedagogical aspects with little attention paid to the broader sociocultural framework within which schooling and child development systems interact. This preliminary study investigates inclusive early childhood education within rapidly changing Ghanaian socio-cultural context, and its consequences for the development of children with learning disabilities. The study addresses an important topic, which is largely under-researched outside of Europe, North America, and Australasia. While inclusive education has been widely accepted globally at the level of policy, its implementation is uneven, as is shown in numerous studies across an array of countries and education systems. Despite this burgeoning area of research internationally, there have been far fewer studies conducted in African settings and fewer still that use cultural-historical activity theory as an investigative approach. More so, specific literature on the subject in the Ghanaian context is non-existent and, as such, coming to a deeper understanding of the sociocultural practices that shape, and possibly impede, inclusive early childhood education in an African country, Ghana, is a worthwhile research endeavour. Using cultural-historical activity theory as a methodological framework, this study employed classroom observations, and in-depth interviews and focus group discussions of preschool teachers in three kindergarten centres in the Greater Accra Region of Ghana to qualitatively explore inclusive early childhood education and the development of children with learning disabilities. The findings showed that literature from Ghana rarely discusses child informed consent as an on-going process that must be articulated throughout the research process from data collection to analysis, reporting and dissemination. Further, the study showed that the introduction and implementation of inclusive education framework – with its concomitant revisions in the curriculum, policies, and school rules, as well as enhanced community and parent involvement – into existing schooling practices, generated contradictions in inclusive teachers’ approaches to teaching and learning, and classroom management. Generally, contradictions in the understanding and acceptability of approaches to teaching and learning occur when a new way of doing things is incorporated into existing practices. These contradictions are thought to be a source of change and development. Thus, they guide teachers to unlearn outmoded practices, relearn or learn new approaches that are beneficial to the development of all children. Nonetheless, the findings of the current study showed that preschool teachers’ belief systems and perceptions of disabilities mediated the outcomes of such contradictions. Also, that was evidenced in the way they engaged children with learning disabilities compared to their typically developing counterparts, showing disregard for what was prescribed by new policies and school rules. The findings have implications for research with young children and the development outcomes of children with learning disabilities in inclusive early childhood education settings.

Keywords: CHAT, classroom management, cultural-historical activity theory, ghana, inclusive early childhood education, schooling practices, young children with learning disabilities

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Authors: Kevin R. Wilson, Roger Mantie

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Community arts-based learning and participatory education are pedagogical techniques that serve to be advantageous for students, curriculum development, and local communities. Using an interpretive approach to examine the significance of this arts-informed research in relation to the eight ‘design imperatives’ proposed as the new model for measuring quality in scholarship for Arizona State University as ‘A New American University’, the purpose of this study was to investigate personal, social, and cultural benefits resulting from student engagement in interdisciplinary community-based projects. Students from a graduate level music education class at the ASU Tempe campus (n=7) teamed with students from an undergraduate level community development class at the ASU Downtown Phoenix campus (n=14) to plan, facilitate, and evaluate seven community-based projects in several locations around the Phoenix-metro area. Data was collected using photo evidence, student reports, and evaluative measures designed by the students. The effectiveness of each project was measured in terms of their ability to meet the eight design imperatives to: 1) leverage place; 2) transform society; 3) value entrepreneurship; 4) conduct use-inspired research; 5) enable student success; 6) fuse intellectual disciplines; 7) be socially embedded; and 8) engage globally. Results indicated that this community arts-based project sufficiently captured the essence of each of these eight imperatives. Implications for how the nature of this interdisciplinary initiative allowed for the eight imperatives to manifest are provided, and project success is expounded upon in relation to utility of each imperative. Discussion is also given for how this type of service learning project formatted within the ‘New American University’ model for measuring quality in academia can be a beneficial pedagogical tool in higher education.

Keywords: community arts-based learning, participatory education, pedagogy, service learning

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Authors: Wisam H. Muragaa, Kamaruzzaman Seman, Mohd Fadzli Marhusin

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Software Defined Networking (SDN) is a new norm of networks. It is designed to facilitate the way of managing, measuring, debugging and controlling the network dynamically, and to make it suitable for the modern applications. Generally, measurement methods can be divided into two categories: Active and passive methods. Active measurement method is employed to inject test packets into the network in order to monitor their behaviour (ping tool as an example). Meanwhile the passive measurement method is used to monitor the traffic for the purpose of deriving measurement values. The measurement methods, both active and passive, are useful for the collection of traffic statistics, and monitoring of the network traffic. Although there has been a work focusing on measuring traffic statistics in SDN environment, it was only meant for measuring packets and bytes rates for non-web traffic. In this study, a feasible method will be designed to measure the number of packets and bytes in a certain time, and facilitate obtaining statistics for both web traffic and non-web traffic. Web traffic refers to HTTP requests that use application layer; while non-web traffic refers to ICMP and TCP requests. Thus, this work is going to be more comprehensive than previous works. With a developed module on POX OpenFlow controller, information will be collected from each active flow in the OpenFlow switch, and presented on Command Line Interface (CLI) and wireshark interface. Obviously, statistics that will be displayed on CLI and on wireshark interfaces include type of protocol, number of bytes and number of packets, among others. Besides, this module will show the number of flows added to the switch whenever traffic is generated from and to hosts in the same statistics list. In order to carry out this work effectively, our Python module will send a statistics request message to the switch requesting its current ports and flows statistics in every five seconds; while the switch will reply with the required information in a message called statistics reply message. Thus, POX controller will be notified and updated with any changes could happen in the entire network in a very short time. Therefore, our aim of this study is to prepare a list for the important statistics elements that are collected from the whole network, to be used for any further researches; particularly, those that are dealing with the detection of the network attacks that cause a sudden rise in the number of packets and bytes like Distributed Denial of Service (DDoS).

Keywords: mininet, OpenFlow, POX controller, SDN

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Authors: Nagore Guerra Bilbao, Clemente Lobato Fraile

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This paper outlines the design and development of the MENDEPRO questionnaire, designed to analyze mentoring performance within a professional development process carried out with professors at the University of the Basque Country, Spain. The study took into account the international research carried out over the past two decades into teachers' professional development, and was also based on a thorough review of the most common instruments used to identify and analyze mentoring styles, many of which fail to provide sufficient psychometric guarantees. The present study aimed to gather empirical data in order to verify the metric quality of the questionnaire developed. To this end, the process followed to validate the theoretical construct was as follows: The formulation of the items and indicators in accordance with the study variables; the analysis of the validity and reliability of the initial questionnaire; the review of the second version of the questionnaire and the definitive measurement instrument. Content was validated through the formal agreement and consensus of 12 university professor training experts. A reduced sample of professors who had participated in a lifelong learning program was then selected for a trial evaluation of the instrument developed. After the trial, 18 items were removed from the initial questionnaire. The final version of the instrument, comprising 33 items, was then administered to a sample group of 99 participants. The results revealed a five-dimensional structure matching theoretical expectations. Also, the reliability data for both the instrument as a whole (.98) and its various dimensions (between .91 and .97) were very high. The questionnaire was thus found to have satisfactory psychometric properties and can therefore be considered apt for studying the performance of mentoring in both induction programs for young professors and lifelong learning programs for senior faculty members.

Keywords: higher education, mentoring, professional development, university teaching

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Authors: Olga Castiblanco, Diego Vizcaíno

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Changing the traditional way of using experimentation in science teaching is quite a challenge. This research results talk about the characterization of physics experiments, not because of the topic it deals with, nor depending on the material used in the assemblies, but related to the possibilities it offers to enrich interaction in the classroom and thereby contribute to the development of scientific thinking skills. It is an action-research of type intervention in the classroom, with four courses of Physics Teaching undergraduate students from a public university in Bogotá. This process allows characterizing typologies such as discrepant, homemade, illustrative, research, recreational, crucial, mental, and virtual experiments. Students' production and researchers' reports on each class were the most relevant data. Content analysis techniques let to categorize the information and obtain results on the richness that each typology of experiment offers when interacting in the classroom. Results show changes in the comprehension of new teachers' role, far from being the possessor and transmitter of the truth. Besides, they understand strategies to engage students effectively since the class advances extending ideas, reflections, debates, and questions, either towards themselves, their classmates, or the teacher.

Keywords: physics teacher training, non-traditional experimentation, contextualized education, didactics of physics

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Authors: Georgi I. Petkov, Ivan I. Vankov, Yolina A. Petrova

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A structure-based model of category learning and categorization at different levels of abstraction is presented. The model compares different structures and expresses their similarity implicitly in the forms of mappings. Based on this similarity, the model can categorize different targets either as members of categories that it already has or creates new categories. The model is novel using two threshold parameters to evaluate the structural correspondence. If the similarity between two structures exceeds the higher threshold, a new sub-ordinate category is created. Vice versa, if the similarity does not exceed the higher threshold but does the lower one, the model creates a new category on higher level of abstraction.

Keywords: analogy-making, categorization, learning of categories, abstraction, hierarchical structure

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Authors: Mohsen Nouraei, Mohammad Molavi

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Muslim scholars for a long time have tried to prove the necessity of prophecy through the Qur'an verses, Hadith's concepts, and rational arguments. According to them, the human being cannot find his welfare way based on wisdom only. They emphasize that divine teaching of the prophets accompanied by wisdom (reason) helps people to find the best way of life and consequently they achieve perfection. In contrast, some believe that mentioned necessity is helpful for primitive and ancient societies, and, matured man in the modern era has flourished his wisdom and reached the peak of maturity. Hence, the modern human can recognize good and evil rely on the individual and social wisdom and as a result they can reach to the perfection without revelation and prophetic teaching. The essay via descriptive-analytical method has attempted to analyze and critic this thought through the study of Mottahari's works as a modern prominent scholars. Findings show that AyatuAllah Mottahari believes that not only modern human intellectual development is not needless of prophecy, but also they need religion and revelation teaching exactly like primitive and ancient societies. Wisdom inherent limitations common between primitive and modern human are the main reason of AyatuAllah Mottahari.

Keywords: wisdom, modernity, prophecy, AyatuAllah Mottahari

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Authors: Xiangrong Liu, Chuanhui Xiong

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With the concern of large pollution emissions from coal-fired power plants and new commitment to green energy, global solar power industry was emerging recently. Due to the advanced technology, the price of solar photovoltaic(PV) module was reduced at a fast rate, which arose an interesting but challenge question to solar supply chain. This research is modeling the inventory strategies for a PV supply chain with a PV manufacturer, an assembler and an end customer. Through characterizing the manufacturer's and PV assembler's optimal decision in decentralized and centralized situation, this study shed light on how to improve supply chain performance through parameters setting in the contract design. The results suggest the assembler to lower the optimal stock level gradually each period before price reduction and set up a newsvendor base-stock policy in all periods after price reduction. As to the PV module manufacturer, a non-stationary produce-up-to policy is optimal.

Keywords: photovoltaic, supply chain, inventory policy, base-stock policy

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Authors: Nir Wittenberg, Moshe Farhi

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This mixed-methods study examines the integration of artificial intelligence (AI) tools in a first-year social work course to assess their potential for enhancing professional knowledge and skills. The incorporation of digital technologies, such as AI, in social work interventions, training, and research has increased, with the expectation that AI will become as commonplace as email and mobile phones. However, policies and ethical guidelines regarding AI, as well as empirical evaluations of its usefulness, are lacking. As AI is gradually being adopted in the field, it is prudent to explore AI thoughtfully in alignment with pedagogical goals. The outcomes assessed include professional identity, course satisfaction, and motivation. AI offers unique reflective learning opportunities through personalized simulations, feedback, and queries to complement face-to-face lessons. For instance, AI simulations provide low-risk practices for situations such as client interactions, enabling students to build skills with less stress. However, it is essential to recognize that AI alone cannot ensure real-world competence or cultural sensitivity. Outcomes related to student learning, experience, and perceptions will help to elucidate the best practices for AI integration, guiding faculty, and advancing pedagogical innovation. This strategic integration of selected AI technologies is expected to diversify course methodology, improve learning outcomes, and generate new evidence on AI’s educational utility. The findings will inform faculty seeking to thoughtfully incorporate AI into teaching and learning.

Keywords: artificial intelligence (AI), social work education, students, developing a professional identity, ethical considerations

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Authors: Oyetunji John Adenuga

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This study on the comparative analysis of the performance of teachers in private and public schools was carried out in Ibadan North West Local Government Area of Oyo State. This study examined the justification for the claim that there is difference in the performance of teachers in private and public primary schools and at the same time identified factors responsible for the difference in the performance of these teachers. A descriptive survey research design was used for the study. Data generated were analysed using t-test and regression analysis. The findings of the study revealed that there is significant difference in the performance of teachers in private and private primary schools in Ibadan North West Local Government Area of Oyo State (t=64.09; df=459; p,.05). The findings also revealed that the method of teaching in private primary schools is significantly different from the method of teaching in public primary schools in Ibadan North West Local Government Area of Oyo State (t=73.08; df=459; p,.05). Findings revealed that school leadership and management have significant contribution on the performance of private and public primary school teachers in Ibadan North West Local Area of Oyo State. Based on the finding, the following recommendations were made: Primary school teachers need to be motivated and rewarded for excellent performance. Primary schools should be properly equipped with teaching-aid facilities, laboratories and libraries. Government should use the findings of this study to improve on teaching materials provided to the primary school teachers in Nigeria. Public primary schools should be designed by education planners, administrators and government. Headmasters, proprietors and teachers of primary schools should look inward and give a performance appraisal and evaluation of themselves form time to time based on subject they taught. Finally, school administrators should be conscious of the way they manage the teachers in schools not only in informal situations but also in formal settings.

Keywords: private education, public education, school leadership, school management, teachers performance

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Authors: Birgit Heike Spohn

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Several authors (e.g., Krowatschek & Reid, 2011; Winkler, 1998) pronounce themselves in favor of the use of relaxation techniques in school because those techniques could help children to cope with stress, improve power of concentration, learning, and social behavior as well as class climate. Children with learning disabilities might profit from those techniques in a special way because they contribute to improved learning behavior. There is no study addressing the frequency of the use of relaxation techniques in special schools for children with learning disabilities in German speaking countries. The paper presents a study in which all teachers of special schools for children with learning disabilities in a district of South Germany (n = 625) were questioned about the use of relaxation techniques in school using a standardized questionnaire. Variables addressed were the use of these techniques in the classroom, aspects of their use (kind of relaxation technique, frequency, and regularity of their use), and potential influencing factors. The results are discussed, and implications for further research are drawn.

Keywords: special education, learning disabilities, relaxation training, concentration

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Authors: Abubakar Sadiq Mensah, Hassan Usman

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The study compared the effectiveness of Audition, Multiplication, subtraction and Division (AMSD) and Addition, subtraction, Multiplication and Division (ASMD), sequence of teaching these four basic operations in mathematics to primary one pupil’s in Katsina Local Government, Katsina State. The study determined the sequence that was more effective and mostly adopted by teachers of the operations. One hundred (100) teachers and sixty pupils (60) from primary one were used for the study. The pupils were divided into two equal groups. The researcher taught these operations to each group separately for four weeks (4 weeks). Group one was taught using the ASMD sequence, while group two was taught using ASMD sequence. In order to generate the needed data for the study, questionnaires and tests were administered on the samples. Data collected were analyzed and major findings were arrived at: (i) Two primary mathematics text books were used in all the primary schools in the area; (ii) Each of the textbooks contained the ASMD sequence; (iii) 73% of the teachers sampled adopted the ASMD sequence of teaching these operations; and (iv) Group one of the pupils (taught using AMSD sequence) performed significantly better than their counter parts in group two (taught using AMSD sequence). On the basis of this, the researcher concluded that the AMSD sequence was more effective in teaching the operations than the ASMD sequence. Consequently, the researcher concluded that primary schools teachers, authors of primary mathematics textbooks, and curriculum planner should adopt the AMSD sequence of teaching these operations.

Keywords: matematic, high school, four basic operations, effectiveness of teaching

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Authors: Vinayaka Gude Divya Sampath

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The research introduces an integrated prediction model to assess the susceptibility of roads in a future flooding event. The model consists of deep learning algorithm for forecasting gauge height data and Flood Inundation Mapper (FIM) for spatial flooding. An optimal architecture for Long short-term memory network (LSTM) was identified for the gauge located on Tangipahoa River at Robert, LA. Dropout was applied to the model to evaluate the uncertainty associated with the predictions. The estimates are then used along with FIM to identify the spatial flooding. Further geoprocessing in ArcGIS provides the susceptibility values for different roads. The model was validated based on the devastating flood of August 2016. The paper discusses the challenges for generalization the methodology for other locations and also for various types of flooding. The developed model can be used by the transportation department and other emergency response organizations for effective disaster management.

Keywords: deep learning, disaster management, flood prediction, urban flooding

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Authors: Oluyemi Christianah Ojo

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This study seeks to investigate the quality of ICT provided in the new Caring Heart schools in Ondo State, Nigeria. The population for the study was all caring Heart Mega Schools in Ondo State, Nigeria. Research questions were generated; two instruments CCCMS and TQCUC were used to elicit information from the schools and the teachers. The study adopts descriptive survey approach. The studies revealed and concluded that ICT components were available and adequate in these schools, Charts showing ICT components and other forms of computer devices used as instructional materials were available but were not adequate; teachers teaching computer studies are competent in the delivery of instructions and in handling computer gadgets in the laboratory. The study recommended the provision of steady electricity, uninterrupted internet facilities and provision of adequate ICT components and charts for effective teaching delivery and learning.

Keywords: facilities, information communication technology, mega primary school, primary education

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Authors: Nihal Murali, Kunal Gupta, Surekha Bhanot

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Training of artificial neural networks (ANNs) using reinforcement learning (RL) techniques is being widely discussed in the robot learning literature. The high model complexity of ANNs along with the model-free nature of RL algorithms provides a desirable combination for many robotics applications. There is a huge need for algorithms that generalize using raw sensory inputs, such as vision, without any hand-engineered features or domain heuristics. In this paper, the standard control problem of line following robot was used as a test-bed, and an ANN controller for the robot was trained on images from a live video feed using Q-learning. A virtual agent was first trained in simulation environment and then deployed onto a robot’s hardware. The robot successfully learns to traverse a wide range of curves and displays excellent generalization ability. Qualitative analysis of the evolution of policies, performance and weights of the network provide insights into the nature and convergence of the learning algorithm.

Keywords: artificial neural networks, q-learning, reinforcement learning, robot learning

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Authors: L. A. Alfarani, M. McPherson, N. Morris

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The growth of mobile learning depends primarily on the participation of teachers and their belief in the possibilities that this technology has for enhancing learning. The need to integrate technology into education seems clear-cut, however, its acceptance in Saudi higher education remains low. Thus, determining the particular factors that affect faculty acceptance of technology is vital. This paper focuses on TAM which depends on two factors: perceived usefulness and perceived ease of use, this theory are used to predict faculty members’ behavioural intentions towards using mobile learning technology. 279 faculty members in one Saudi university have responded to the online questionnaire. The findings have revealed that there is a statistically significant difference in both usefulness and ease of using m-learning factors.

Keywords: TAM theory, mobile learning technology acceptance, usefulness, ease of use

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Authors: Michael Stewart

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Mutation testing is a type of software testing proposed in the 1970s where program statements are deliberately changed to introduce simple errors so that test cases can be validated to determine if they can detect the errors. Test cases are executed against the mutant code to determine if one fails, detects the error and ensures the program is correct. One major issue with this type of testing was it became intensive computationally to generate and test all possible mutations for complex programs. This paper used reinforcement learning and parallel processing within the context of mutation testing for the selection of mutation operators and test cases that reduced the computational cost of testing and improved test suite effectiveness. Experiments were conducted using sample programs to determine how well the reinforcement learning-based algorithm performed with one live mutation, multiple live mutations and no live mutations. The experiments, measured by mutation score, were used to update the algorithm and improved accuracy for predictions. The performance was then evaluated on multiple processor computers. With reinforcement learning, the mutation operators utilized were reduced by 50 – 100%.

Keywords: automated-testing, machine learning, mutation testing, parallel processing, reinforcement learning, software engineering, software testing

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Authors: Medjadj Tarek, Ghribi Hayet

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This study aims to develop a flood sensitivity assessment tool using machine learning (ML) techniques and geographic information system (GIS). The importance of this study is integrating the geographic information systems (GIS) and machine learning (ML) techniques for mapping flood risks, which help decision-makers to identify the most vulnerable areas and take the necessary precautions to face this type of natural disaster. To reach this goal, we will study the case of the city of M'sila, which is among the areas most vulnerable to floods. This study drew a map of flood-prone areas based on the methodology where we have made a comparison between 3 machine learning algorithms: the xGboost model, the Random Forest algorithm and the K Nearest Neighbour algorithm. Each of them gave an accuracy respectively of 97.92 - 95 - 93.75. In the process of mapping flood-prone areas, the first model was relied upon, which gave the greatest accuracy (xGboost).

Keywords: Geographic information systems (GIS), machine learning (ML), emergency mapping, flood disaster management

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Authors: Lizmol Mathew, Divya Thomas, Shiney Rajan

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Educational paradigm all over the globe is undergoing significant reform today. Because of this, so-called flipped classroom model is becoming increasingly popular in higher education. Flipped classroom has proved to be more effective than traditional lecture based model as flipped classroom model promotes active learning by encouraging students to work on in collaborative tasks and peer-led learning during the class-time. However, success of flipped classrooms relies on students’ ability and their attitudes towards collaboration and group work. This paper examines: 1) Students’ attitudes towards collaborative learning; 2) Main challenges to successful collaboration from students’ experience and 3) Students’ perception of criteria for successful team work. 4) Recommendations for enhancing collaborative learning. This study’s methodology involves quantitative analysis of surveys collected from students enrolled in undergraduate Architecture program at Qatar University. Analysis indicates that in general students enrolled in the program do not have positive perceptions or experiences associated with group work. Positive and negative factors that influence collaborative learning in higher education have been identified. Recommendations for improving collaborative work experience have been proposed.

Keywords: architecture, collaborative learning, female, group work, higher education, Middle East, Qatar, student experience

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Authors: Y. Salfati, D. Sharef Bussel, J. Zamir

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In this paper, we present an Evaluation Case Study implementing the eight principles of Collaborative Approaches to Evaluation (CAE) as designed by Brad Cousins in the past decade. The focus of this paper is sharing a rich experience in which we achieved two main goals. The first was the development of a valuable and meaningful new teacher training program, and the second was a successful implementation of the CAE principles. The innovative teacher training program is based on the idea of including physical movement during the process of teaching and learning academic themes. The program is called Learning through Movement. This program is a response to a call from the Ministry of Education, claiming that today children sit in front of screens and do not exercise any physical activity. In order to contribute to children’s health, physical, and cognitive development, the Ministry of Education promotes learning through physical activities. Research supports the idea that sports and physical exercise improve academic achievements. The Learning through Movement program is operated by Kaye Academic College. Students in the Elementary School Training Program, together with students in the Physical Education Training Program, implement the program in collaboration with two mentors from the College. The program combines academic learning with physical activity. The evaluation began at the beginning of the program. During the evaluation process, data was collected by means of qualitative tools, including interviews with mentors, observations during the students’ collaborative planning, class observations at school and focus groups with students, as well as the collection of documentation related to the teamwork and to the program itself. The data was analyzed using content analysis and triangulation. The preliminary results show outcomes relating to the Teacher Training Programs, the student teachers, the pupils in class, the role of Physical Education teachers, and the evaluation. The Teacher Training Programs developed a collaborative approach to lesson planning. The students' teachers demonstrated a change in their basic attitudes towards the idea of integrating physical activities during the lessons. The pupils indicated higher motivation through full participation in classes. These three outcomes are indicators of the success of the program. An additional significant outcome of the program relates to the status and role of the physical education teachers, changing their role from marginal to central in the school. Concerning evaluation, a deep sense of trust and confidence was achieved, between the evaluator and the whole team. The paper includes the perspectives and challenges of the heads and mentors of the two programs as well as the evaluator’s conclusions. The evaluation unveils challenges in conducting a CAE evaluation in such a complex setting.

Keywords: collaborative evaluation, training teachers, learning through movement

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Authors: Abiola A. Sokoya

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Handheld devices are now in use as educational tools for learning in most of the higher institutions, because of the features and functions which can be used in an academic environment. This study examined the usage and the benefits of handheld devices as learning tools. A structured questionnaire was used to collect data, while the data collected was analyzed using simple percentage. It was, however, observed that handheld devices offer numerous functions and application for learning, which could improve academic performance of students. Students are now highly interested in using handheld devices for mobile learning apart from making and receiving calls. The researchers recommended that seminars be organized for students on functions of some common handheld devices that can aid learning for academic purposes. It is also recommended that management of each higher institution should make appropriate policies in-line with the usage of handheld technologies to enhance mobile learning. Government should ensure that appropriate policies and regulations are put in place for the importation of high quality handheld devices into the country, Nigeria being a market place for the technologies. By this, using handheld devices for mobile learning will be enhanced.

Keywords: handheld devices, educational tools, mobile e- learning, usage, benefits

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Authors: Emmanuel Habiyakare

Abstract:

The COVID-19 pandemic has highlighted the significance of educational technologies in teaching and learning. The global pandemic led to the closure of educational institutions worldwide, prompting the widespread implementation of online learning as a substitute method for delivering curricula. The communication platform is known as WhatsApp has gained widespread adoption and extensive utilisation within the realm of education. The primary aims of this literature review are to examine the utilisation patterns and obstacles linked to the implementation of WhatsApp in the realm of education, assess the advantages and possibilities that students and facilitators can derive from utilising this platform for educational purposes, and comprehend the hindrances and restrictions that arise when employing WhatsApp in an academic environment. The literature was acquired through the utilisation of keywords that are linked to both WhatsApp and education from diverse databases. Having a thorough comprehension of current trends, potential advantages, obstacles, and gains linked to the use of WhatsApp is imperative for lecturers and administrators. Scholarly investigations have revealed a noticeable trend of lecturers and students increasingly utilising WhatsApp as a means of communication and collaboration. The objective of this literature review is to make a noteworthy contribution to the domain of education and technology through an investigation of the potential of WhatsApp as a learning tool. Additionally, this review seeks to offer valuable insights on how to effectively incorporate WhatsApp into pedagogical practices. The article underscores the significance of taking into account privacy and security concerns while utilising WhatsApp for educational objectives and puts forth recommendations for additional investigation.

Keywords: tool, COVID-19, opportunities, challenges, learning, WhatsApp

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Authors: Jimeng Shi, Mahek Jain, Giri Narasimhan

Abstract:

Time Series Forecasting (TSF) is used to predict the target variables at a future time point based on the learning from previous time points. To keep the problem tractable, learning methods use data from a fixed-length window in the past as an explicit input. In this paper, we study how the performance of predictive models changes as a function of different look-back window sizes and different amounts of time to predict the future. We also consider the performance of the recent attention-based Transformer models, which have had good success in the image processing and natural language processing domains. In all, we compare four different deep learning methods (RNN, LSTM, GRU, and Transformer) along with a baseline method. The dataset (hourly) we used is the Beijing Air Quality Dataset from the UCI website, which includes a multivariate time series of many factors measured on an hourly basis for a period of 5 years (2010-14). For each model, we also report on the relationship between the performance and the look-back window sizes and the number of predicted time points into the future. Our experiments suggest that Transformer models have the best performance with the lowest Mean Average Errors (MAE = 14.599, 23.273) and Root Mean Square Errors (RSME = 23.573, 38.131) for most of our single-step and multi-steps predictions. The best size for the look-back window to predict 1 hour into the future appears to be one day, while 2 or 4 days perform the best to predict 3 hours into the future.

Keywords: air quality prediction, deep learning algorithms, time series forecasting, look-back window

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Authors: Rakkrit Duangsoithong, Jermphiphut Jaruenpunyasak, Alba Garcia

Abstract:

The use of foot recognition can be applied in many medical fields such as the gait pattern analysis and the knee exercises of patients in rehabilitation. Generally, a camera-based foot recognition system is intended to capture a patient image in a controlled room and background to recognize the foot in the limited views. However, this system can be inconvenient to monitor the knee exercises at home. In order to overcome these problems, this paper proposes to use the deep learning method using Convolutional Neural Networks (CNNs) for foot recognition. The results are compared with the traditional classification method using LBP and HOG features with kNN and SVM classifiers. According to the results, deep learning method provides better accuracy but with higher complexity to recognize the foot images from online databases than the traditional classification method.

Keywords: foot recognition, deep learning, knee rehabilitation, convolutional neural network

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Authors: Gayathri Sadanala, Shibam Pokhrel, Owen Murphy

Abstract:

In the ever-evolving landscape of education, Virtual Reality (VR) environments offer a promising avenue for enhancing student engagement and learning experiences. However, understanding and predicting student behavior within these immersive settings remain challenging tasks. This paper presents a comprehensive study on the predictive modeling of student behavior in VR using machine learning techniques. We introduce a rich data set capturing student interactions, movements, and progress within a VR orientation program. The dataset is divided into training and testing sets, allowing us to develop and evaluate predictive models for various aspects of student behavior, including engagement levels, task completion, and performance. Our machine learning approach leverages a combination of feature engineering and model selection to reveal hidden patterns in the data. We employ regression and classification models to predict student outcomes, and the results showcase promising accuracy in forecasting behavior within VR environments. Furthermore, we demonstrate the practical implications of our predictive models for personalized VR-based learning experiences and early intervention strategies. By uncovering the intricate relationship between student behavior and VR interactions, we provide valuable insights for educators, designers, and developers seeking to optimize virtual learning environments.

Keywords: interaction, machine learning, predictive modeling, virtual reality

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Authors: Mahmoud Timar, Javad Joukar Borazjani

Abstract:

A dynamic organization helps the management to overcome both internal and external uncertainties and complexities of the organization with more confidence and efficiency. Regarding this issue, in this paper, the influence of organizational culture factors over organizational learning components, which both of them are considered as important characteristics of a dynamic organization, has been studied in three subsidiary companies (production, consultation and service) of National Iranian Oil Company, and moreover we also tried to identify the most dominant culture in these three subsidiaries. Analysis of 840 received questionnaires by SPSS shows that there is a significant relationship between the components of organizational culture and organizational learning; however the rate of relationship between these two factors was different among the examined companies. By the use of Regression, it has been clarified that in the servicing company the highest relationship is between mission and learning environment, while in production division, there is a significant relationship between adaptability and learning needs satisfaction and however in consulting company the highest relationship is between involvement and applying learning in workplace.

Keywords: denison model, culture, leaning, organizational culture, organizational learning

Procedia PDF Downloads 370