Search results for: conventional learning method

Authors: Karoliina Nisula, Samuli Pekkola

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Business education has been criticized for being too theoretical and distant from business life. Different types of experiential learning environments ranging from manual role-play to computer simulations and enterprise resource planning (ERP) systems have been used to introduce the realistic and practical experience into business learning. Each of these learning environments approaches business learning from a different perspective. The implementations tend to be individual exercises supplementing the traditional courses. We suggest combining them into a business skills laboratory resembling an actual workplace. In this paper, we present a concrete implementation of an ERP-supported business learning environment that is used throughout the first year undergraduate business curriculum. We validate the implementation by evaluating the learning outcomes through the different domains of Bloom’s taxonomy. We use the role-play oriented practice enterprise model as a comparison group. Our findings indicate that using the ERP simulation improves the poor and average students’ lower-level cognitive learning. On the affective domain, the ERP-simulation appears to enhance motivation to learn as well as perceived acquisition of practical hands-on skills.

Keywords: business simulations, experiential learning, ERP systems, learning environments

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Authors: Salina Budin, Shaira Ismail

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Students learn effectively in a learning environment with a suitable teaching approach that matches their learning preferences. The main objective of the study is to examine the learning preferences amongst the students in the Science and Technology (S&T), and Social Science (SS) fields of study at the Universiti Teknologi Mara (UiTM), Pulau Pinang. The measurement instrument is based on the Dunn and Dunn Learning Styles which measure five elements of learning styles; environmental, sociological, emotional, physiological and psychological. Questionnaires are distributed amongst undergraduates in the Faculty of Mechanical Engineering and Faculty of Business Management. The respondents comprise of 131 diploma students of the Faculty of Mechanical Engineering and 111 degree students of the Faculty of Business Management. The results indicate that, both S&T and SS students share a similar learning preferences on the environmental aspect, emotional preferences, motivational level, learning responsibility, persistent level in learning and learning structure. Most of the S&T students are concluded as analytical learners and the majority of SS students are global learners. Both S&T and SS students are concluded as visual learners, preferred to be in an active mobility in a relaxing and enjoying mode with some light of refreshments during the learning process and exhibited reflective characteristics in learning. Obviously, the S&T students are considered as left brain dominant, whereas the SS students are right brain dominant. The findings highlighted that both categories of students exhibited similar learning preferences except on psychological preferences.

Keywords: learning preferences, Dunn and Dunn learning style, teaching approach, science and technology, social science

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Authors: Allen A. Espinosa, Larkins A. Trinidad

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The present study investigated collegiate students’ problem solving strategies and misconceptions in solving stoichiometric problems and later on formulate a teaching framework from the result of the study. The study found out that the most prominent strategies among students are the mole method and the proportionality method, which are both algorithmic by nature. Misconception was also noted as some students rely on Avogadro’s number in converting between moles. It is suggested therefore that the teaching of stoichiometry should not be confined to demonstration. Students should be involved in the process of thinking of ways to solve the problem.

Keywords: stoichiometry, Svogadro’s number, mole method, proportionality method

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Authors: N. Ayob, N. C. Nkosi, R. P. Burger, S. J. Piketh, F. Letlaila, O. Maphosa

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South African higher tertiary institution have been faced with high dropout rates. About 50 to 60% of first years drop out to due to various reasons one being inadequate academic support. Geography 111 (GEOG 111) module is historically known for having below 50% pass rate, high dropout rate and identified as a first year risk module. For the first time GEOG 111 (2021) on the Mahikeng Campus admitted 150 students pursuing more than 6 different qualifications (BA and BSc) from the Humanities Faculty and FNAS. First year students had difficulties transitioning from secondary to tertiary institutions as we shifted to remote learning while we navigate through the Covid-19 pandemic. The traditional method of teaching does not encourage students to help each other. With remote learning we do not have control over what the students share and perhaps this can be a learning opportunity to embrace peer learning and change the manner in which we assess the students. The purpose of this pilot study was to assist GEOG111 students with academic challenges whilst improving their University experience. This was a qualitative study open to all GEOG111, repeaters, students who are not confident in their Geographical knowledge and never did Geography at high school level. The selected 9 Golden Key International Honour Society Geography mentors attended an academic mentor training program with module lecturers. About 17.6% of the mentees did not have a geography background however, 94% of the mentees passed, 1 mentee had a mark of 38%. 11 of the participants had a mark >60% with one student that excelled 70%. It is evident that mentorship helped students reach their academic potential. Peer learning and mentoring are associated with improved academic performance and allows the students to take charge of their learning and academic experience. Thus an important element as we transform pedagogies at higher learning institutions.

Keywords: geography, risk module, peer mentoring, peer learning

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Authors: Nguyen J. M., Lucas G., Brunner M., Ruan S., Antonioli D.

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Deep learning based on convolutional neural networks (CNN) is a very powerful technique for classifying information from an image. We propose a new method, DeepNic, to transform each variable of a tabular dataset into an image where each pixel represents a set of conditions that allow the variable to make an error-free prediction. The contrast of each pixel is proportional to its prediction performance and the color of each pixel corresponds to a sub-family of NICs. NICs are probabilities that depend on the number of inputs to each neuron and the range of coefficients of the inputs. Each variable can therefore be expressed as a function of a matrix of 2 vectors corresponding to an image whose pixels express predictive capabilities. Our objective is to transform each variable of tabular data into images into an image that can be analysed by CNNs, unlike other methods which use all the variables to construct an image. We analyse the NIC information of each variable and express it as a function of the number of neurons and the range of coefficients used. The predictive value and the category of the NIC are expressed by the contrast and the color of the pixel. We have developed a pipeline to implement this technology and have successfully applied it to genomic expressions on an Affymetrix chip.

Keywords: tabular data, deep learning, perfect trees, NICS

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Authors: Sajed Yaghoubnezhad, Sedygheh Rezai

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Background and Aim: Since currently in Iran, students with learning disabilities are identified after entering school, and with the approach to the gap between IQ and academic achievement, the purpose of this study is to design and calculate the content validity of the pre-school screening checklist (5-7) exposed to learning difficulties. Methods: This research is a fundamental study, and in terms of data collection method, it is quantitative research with a descriptive approach. In order to design this checklist, after reviewing the research background and theoretical foundations, cognitive abilities (visual processing, auditory processing, phonological awareness, executive functions, spatial visual working memory and fine motor skills) are considered the basic variables of school learning. The basic items and worksheets of the screening checklist of pre-school students 5 to 7 years old with learning difficulties were compiled based on the mentioned abilities and were provided to the specialists in order to calculate the content validity ratio index. Results: Based on the results of the table, the validity of the CVR index of the background information checklist is equal to 0.9, and the CVR index of the performance checklist of preschool children (5 to7 years) is equal to 0.78. In general, the CVR index of this checklist is reported to be 0.84. The results of this study provide good evidence for the validity of the pre-school sieve screening checklist (5-7) exposed to learning difficulties.

Keywords: checklist, screening, preschoolers, learning difficulties

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Authors: Kanika Sood, Sijie Shang

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A fundamental goal of education includes preparing students to become a part of the global workforce by making beneficial contributions to society. In this paper, we analyze student performance for multiple courses that involve different teaching pedagogies: a cooperative learning technique and an inquiry-based learning strategy. Student performance includes student engagement, grades, and attendance records. We perform this study in the Computer Science department for online and in-person courses for 450 students. We will perform correlation analysis to study the relationship between student scores and other parameters such as gender, mode of learning. We use natural language processing and machine learning to analyze student feedback data and performance data. We assess the learning outcomes of two teaching pedagogies for undergraduate and graduate courses to showcase the impact of pedagogical adoption and learning outcome as determinants of academic achievement. Early findings suggest that when using the specified pedagogies, students become experts on their topics and illustrate enhanced engagement with peers.

Keywords: bag-of-words, cooperative learning, education, inquiry-based learning, in-person learning, natural language processing, online learning, sentiment analysis, teaching pedagogy

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Authors: Ambali Alade Odebowale, Andargachew Mekonnen Berhe, Haroldo T. Hattori, Andrey E. Miroshnichenko

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Solar thermophotovoltaic systems (STPV) have emerged as a promising solution to overcome the Shockley-Queisser limit, a significant impediment in the direct conversion of solar radiation into electricity using conventional solar cells. The STPV system comprises essential components such as an optical concentrator, selective emitter, and a thermophotovoltaic (TPV) cell. The pivotal element in achieving high efficiency in an STPV system lies in the design of a spectrally selective emitter or absorber. Traditional methods for designing and optimizing selective emitters are often time-consuming and may not yield highly selective emitters, posing a challenge to the overall system performance. In recent years, the application of machine learning techniques in various scientific disciplines has demonstrated significant advantages. This paper proposes a novel nanostructure composed of four-layered materials (SiC/W/SiO2/W) to function as a selective emitter in the energy conversion process of an STPV system. Unlike conventional approaches widely adopted by researchers, this study employs a machine learning-based approach for the design and optimization of the selective emitter. Specifically, a random forest algorithm (RFA) is employed for the design of the selective emitter, while the optimization process is executed using genetic algorithms. This innovative methodology holds promise in addressing the challenges posed by traditional methods, offering a more efficient and streamlined approach to selective emitter design. The utilization of a machine learning approach brings several advantages to the design and optimization of a selective emitter within the STPV system. Machine learning algorithms, such as the random forest algorithm, have the capability to analyze complex datasets and identify intricate patterns that may not be apparent through traditional methods. This allows for a more comprehensive exploration of the design space, potentially leading to highly efficient emitter configurations. Moreover, the application of genetic algorithms in the optimization process enhances the adaptability and efficiency of the overall system. Genetic algorithms mimic the principles of natural selection, enabling the exploration of a diverse range of emitter configurations and facilitating the identification of optimal solutions. This not only accelerates the design and optimization process but also increases the likelihood of discovering configurations that exhibit superior performance compared to traditional methods. In conclusion, the integration of machine learning techniques in the design and optimization of a selective emitter for solar thermophotovoltaic systems represents a groundbreaking approach. This innovative methodology not only addresses the limitations of traditional methods but also holds the potential to significantly improve the overall performance of STPV systems, paving the way for enhanced solar energy conversion efficiency.

Keywords: emitter, genetic algorithm, radiation, random forest, thermophotovoltaic

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Authors: Ashish Jaiswal, Ashwin Ramesh Babu, Mohammad Zaki Zadeh, Fillia Makedon, Glenn Wylie

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Functional magnetic resonance imaging (fMRI) is a neuroimaging technique that records neural activations in the brain by capturing the blood oxygen level in different regions based on the task performed by a subject. Given fMRI data, the problem of predicting the state of cognitive fatigue in a person has not been investigated to its full extent. This paper proposes tackling this issue as a multi-class classification problem by dividing the state of cognitive fatigue into six different levels, ranging from no-fatigue to extreme fatigue conditions. We built a spatio-temporal model that uses convolutional neural networks (CNN) for spatial feature extraction and a long short-term memory (LSTM) network for temporal modeling of 4D fMRI scans. We also applied a self-supervised method called MoCo (Momentum Contrast) to pre-train our model on a public dataset BOLD5000 and fine-tuned it on our labeled dataset to predict cognitive fatigue. Our novel dataset contains fMRI scans from Traumatic Brain Injury (TBI) patients and healthy controls (HCs) while performing a series of N-back cognitive tasks. This method establishes a state-of-the-art technique to analyze cognitive fatigue from fMRI data and beats previous approaches to solve this problem.

Keywords: fMRI, brain imaging, deep learning, self-supervised learning, contrastive learning, cognitive fatigue

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Authors: Sudhir Kumar Singh, Debashish Chakravarty

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Slope stability analysis is an important aspect in the field of geotechnical engineering. It is also important from safety, and economic point of view as any slope failure leads to loss of valuable lives and damage to property worth millions. This paper aims at mitigating the risk of slope failure by studying the effect of different joint sets on the stability of mine pit slopes under the influence of various external factors, namely degree of saturation, rainfall intensity, and seismic coefficients. Supervised machine learning approach has been utilized for making accurate and reliable predictions regarding the stability of slopes based on the value of Factor of Safety. Numerous cases have been studied for analyzing the stability of slopes using the popular Finite Element Method, and the data thus obtained has been used as training data for the supervised machine learning models. The input data has been trained on different supervised machine learning models, namely Random Forest, Decision Tree, Support vector Machine, and XGBoost. Distinct test data that is not present in training data has been used for measuring the performance and accuracy of different models. Although all models have performed well on the test dataset but Random Forest stands out from others due to its high accuracy of greater than 95%, thus helping us by providing a valuable tool at our disposition which is neither computationally expensive nor time consuming and in good accordance with the numerical analysis result.

Keywords: finite element method, geotechnical engineering, machine learning, slope stability

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Authors: Mohammad Shams Esfand Abadi, Mehrdad Zalaghi, Reza ebrahimpour

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In this paper, we propose a sign adaptive filter algorithm with the ability of dynamic selection of subband filters which leads to low computational complexity compared with conventional sign subband adaptive filter (SSAF) algorithm. Dynamic selection criterion is based on largest reduction of the mean square deviation at each adaption. We demonstrate that this simple proposed algorithm has the same performance of the conventional SSAF and somewhat faster than it. In the presence of impulsive interferences robustness of the simple proposed algorithm as well as the conventional SSAF and outperform the conventional normalized subband adaptive filter (NSAF) algorithm. Therefore, it is preferred for environments under impulsive interferences. Simulation results are presented to verify these above considerations very well have been achieved.

Keywords: acoustic echo cancellation (AEC), normalized subband adaptive filter (NSAF), dynamic selection subband adaptive filter (DS-NSAF), sign subband adaptive filter (SSAF), impulsive noise, robust filtering

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Authors: Mahdi Kiani, Hassan Salarieh, Aria Alasty, S. Mahdi Darbandi

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The design and implementation of the hybrid control method for a three-pole active magnetic bearing (AMB) is proposed in this paper. The system is inherently nonlinear and conventional nonlinear controllers are a little complicated, while the proposed hybrid controller has a piecewise linear form, i.e. linear in each sub-region. A state-feedback hybrid controller is designed in this study, and the unmeasurable states are estimated by an observer. The gains of the hybrid controller are obtained by the Linear Quadratic Regulator (LQR) method in each sub-region. To evaluate the performance, the designed controller is implemented on an experimental setup in static mode. The experimental results show that the proposed method can efficiently stabilize the three-pole AMB system. The simplicity of design, domain of attraction, uncomplicated control law, and computational time are advantages of this method over other nonlinear control strategies in AMB systems.

Keywords: active magnetic bearing, three pole AMB, hybrid control, Lyapunov function

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Authors: N. Paparisteidi, D. Rodamitou

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This article focuses on the skills development and path planning of students studying computer science in EPITECH: french private institute of Higher Education. The researchers examine students’ points of view and experience in a blended learning model based on a skills development curriculum. The study is based on the collection of four main categories of data: semi-participant observation, distribution of questionnaires, interviews, and analysis of internal school databases. The findings seem to indicate that a skills-based program on active learning enables students to develop their learning strategies as well as their personal skills and to actively engage in the creation of their career path and contribute to providing additional information to curricula planners and decision-makers about learning design in higher education.

Keywords: active learning, blended learning, higher education, skills development

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Authors: Min-Su Song, Haeng-Bok Kil, Eui-Rim Jeong

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This paper proposes a new method to reduce the overhead by pilots for single carrier frequency domain equalization (SC-FDE) transmission. In the conventional SC-FDE transmission structure, the overhead by transmitting pilot is heavy because the pilot are transmitted at every SC-FDE block. The proposed SC-FDE structure has fewer pilots and many SC-FCE blocks are transmitted between pilots. The channel estimation and equalization is performed at the pilot period and the channels between pilots are estimated through linear interpolation. This reduces the pilot overhead by reducing the pilot transmission compared with the conventional structure, and enables reliable channel estimation and equalization.

Keywords: channel estimation, linear interpolation, pilot overhead, SC-FDE

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Authors: Pinar Ozdemir Ayber, Zeina Hojeij

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Blended Learning (BL) is a rapidly growing teaching and learning approach, which brings together the best of both face-to-face and online learning to expand learning opportunities for students. However, there is limited research on the practices, opportunities and quality of instruction in Blended Classrooms, and on the role of the teaching faculty as well as the learners in these types of classes. This paper will highlight the researchers’ experiences and reflections on blending their classes. It will focus on the importance of designing effective lesson plans that emphasize learner engagement and motivation in alignment with course learning outcomes. In addition, it will identify the changing roles of the teacher and the learners and suggest appropriate variations to the traditional classroom setting taking into consideration the benefits and the challenges of the Blended Classroom. It is hoped that this paper would provide sufficient input for participants to reflect on ways they can blend their own lessons to promote ubiquitous learning and student autonomy. Practical tips and ideas will be shared with the participants on various strategies and technologies that were used in the researchers’ classes.

Keywords: blended learning, learner autonomy, learner engagement, learner motivation, mobile learning tools

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Authors: K. D. Rajatha, S. Rajendra Prasad, N. Nethra

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Aeroponics is one of the advanced techniques to cultivate plants without soil with minimal water and nutrient consumption. This is the technology which could bring the vertical growth in agriculture. It is an eco-friendly approach widely used for commercial cultivation of vegetables to obtain the supreme quality and yield. In this context, to harvest potentiality of the technology, an experiment was designed to evaluate the suitability of the aeroponics method over the conventional method for hybrid seed production of tomato. The experiment was carried out under Completely Randomized Design with Factorial (FCRD) concept with three replications during the year 2017-18 at UAS, GKVK Bengaluru. Nutrients and pH were standardized; among the six different nutrient solutions, the crop performance was better in Hoagland’s solution with pH between 5.5-7. The results of the present study revealed that between TAG1F and TAG2F parental lines, TAG1F performed better in both the methods of seed production. Among the methods, aeroponics showed better performance for the quality parameters except for plant spread, due to better availability of nutrients and aeration, huge root biomass in aeroponics. Aeroponics method showed significantly higher plant length (124.9 cm), plant growth rate (0.669), seedling survival rate (100%), early flowering (27.5 days), highest fruit weight (121.5 g), 100 seed weight (0.373 g) and total seed yield plant⁻¹ (11.68 g) compared to the conventional method. By providing the best environment for plant growth, the genetically best possible plant could be grown, thus complete potentiality of the plant could be harvested. Hence, aeroponics could be a promising tool for quality and healthy hybrid seed production throughout the year within protected cultivation.

Keywords: aeroponics, Hoagland’s solution, hybrid seed production, Lycopersicon esculentum

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Authors: Asima Ranjan Parhi

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English language teaching-learning in higher education departments in Indian and Asian contexts needs to be one of innovation and experimentation rather than rigid prescription. The communicative language teaching has been proposing the context to be of primary importance in this process. Today, English print and electronic media have flooded the market with plenty of material suitable to the classroom context. The entries are poetic, catchy and contain a deliberate method in them which could be utilized to teach not only English language but literature, literary terms and the theory of literature. The Bollywood movies, especially through their songs have been propagating a package which may be useful to teach language and even theory in the sub-continent. While investigating, one may be fascinated to see how such material in the body of media (print and electronic), movies and popular songs generate a data for our classroom in our context, thereby developing a mass language with huge pedagogical implications. Harping on the four skills of teaching and learning of a language in general and English language in particular appears stale and mechanical in a decontextualised, matter of fact classroom. So this discussion visualizes a model beyond these skills as well as the conventional theory, literature, language classroom practices in order to build up a systematic pattern stressing the factors responsible in the particular context, that of specific language, society and culture in tune with language-literature teaching. This study intends to examine certain catchy use of the language entries in mass media which could be in the direction of inviting more such investigations in the Asian context in order to develop a common platform of decolonized pedagogy.

Keywords: pedagogy, electronic media, Bollywood, decolonized, mass media

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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: Khaleel Bader Bataineh

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Past studies have maintained that the Arab learners' beliefs about language learning hold vital effects on their performance. Thus, this study was carried out to investigate the language learning beliefs of Irbid National University students. It aimed at identifying the language learning beliefs according to gender. This study is a descriptive design that employed survey questionnaire of Language Learning Beliefs Inventory (BALLI). The data were elicited from 83 English major students during the class sessions. The data were analyzed using an SPSS program in which frequency analysis and t-test were performed to examine the students’ responses. Thus, the major findings of this research indicated that there is a variation in responses with regards to the subjects’ beliefs about English learning. Also, the findings show significant differences in four questionnaire items according to gender. It is hoped that the findings provide valuable insights to educators about the learners’ beliefs which assist them to develop the teaching and learning English language process in Jordan universities.

Keywords: foreign language, students’ beliefs, language learning, Arab students

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Authors: Timna Mayer

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This paper explores the vast potential of self-directed learning in violin pedagogy. Based in practice and drawing on concepts from neuropsychology, the author, a violinist and teacher, outlines five learning principles. Self-directed learning is defined as an ongoing process based on problem detection, definition, and resolution. The traditional roles of teacher and student are reimagined within this context. A step-by-step guide to applied self-directed learning suggests a model for both teachers and students that realizes student independence in the classroom, leading to higher-level understanding and more robust performance. While the value of self-directed learning is well-known in general pedagogy, this paper is novel in applying the approach to the study of musical performance, a field which is currently dominated by habit and folklore, rather than informed by science.

Keywords: neuropsychology and musical performance, self-directed learning, strategic problem solving, violin pedagogy

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Authors: Sokkhey Phauk, Takeo Okazaki

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The challenging task in educational institutions is to maximize the high performance of students and minimize the failure rate of poor-performing students. An effective method to leverage this task is to know student learning patterns with highly influencing factors and get an early prediction of student learning outcomes at the timely stage for setting up policies for improvement. Educational data mining (EDM) is an emerging disciplinary field of data mining, statistics, and machine learning concerned with extracting useful knowledge and information for the sake of improvement and development in the education environment. The study is of this work is to propose techniques in EDM and integrate it into a web-based system for predicting poor-performing students. A comparative study of prediction models is conducted. Subsequently, high performing models are developed to get higher performance. The hybrid random forest (Hybrid RF) produces the most successful classification. For the context of intervention and improving the learning outcomes, a feature selection method MICHI, which is the combination of mutual information (MI) and chi-square (CHI) algorithms based on the ranked feature scores, is introduced to select a dominant feature set that improves the performance of prediction and uses the obtained dominant set as information for intervention. By using the proposed techniques of EDM, an academic performance prediction system (APPS) is subsequently developed for educational stockholders to get an early prediction of student learning outcomes for timely intervention. Experimental outcomes and evaluation surveys report the effectiveness and usefulness of the developed system. The system is used to help educational stakeholders and related individuals for intervening and improving student performance.

Keywords: academic performance prediction system, educational data mining, dominant factors, feature selection method, prediction model, student performance

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Authors: Leandro Marcos Alves Vaz

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The teaching of physics in Brazilian public schools emphasizes strongly the theoretical aspects of this science, showing its philosophical and mathematical basis, but neglecting its experimental character. Perhaps the lack of science laboratories explains this practice. In this work, we present a method of teaching physics using the computer. As alternatives to real experiments, we have the trials through simulators, many of which are free software available on the internet. In order to develop a study on the use of simulators in teaching, knowing the impossibility of simulations on all topics in a given subject, we combined these programs with phenomenological and/or experimental texts in order to mitigate this limitation. This study proposes the use of simulators and the debate using phenomenological/experimental texts on electrostatic theme in groups of the 3rd year of EJA (Adult and Youth Education) in order to verify the advantages of this methodology. Some benefits of the hybridization of the traditional method with the tools used were: Greater motivation of the students in learning, development of experimental notions, proactive socialization to learning, greater easiness to understand some concepts and the creation of collaborative activities that can reduce timidity of part of the students.

Keywords: experimentation, learning physical, simulators, youth and adult

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Authors: Hameed Olalekan Bolaji

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The digital natives are driving the trends of literacy in the use of electronic devices for learning purposes. This has reconfigured the context of learning in the exploration of knowledge in a social learning environment. This study explores the impact of Ubiquitous Collaborative Mobile Learning (UCML) instructional design model in a quantitative designed-based research approach. The UCML model was a synergetic blend of four models that are relevant to the design of instructional content for a social learning environment. The UCML model serves as the treatment and instructions were transmitted via mobile device based on the principle of ‘bring your own device’ (BYOD) to promote social learning. Three research questions and two hypotheses were raised to guide the conduct of this study. A researcher-designed questionnaire was used to collate data and the it was subjected to reliability of Cronbach Alpha which yielded 0.91. Descriptive statistics of mean and standard deviation were used to answer research questions while inferential statistics of independent sample t-test was used to analyze the hypotheses. The findings reveal that the UCML model was adequately evolved and it promotes social learning its design principles through the use of mobile devices.

Keywords: collaboration, mobile device, social learning, ubiquitous

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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: Fuad A. A. Trayek, Tunku Badariah Tunku Ahmad, Mohamad Sahari Nordin, Mohammed AM Dwikat

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This paper reports on the results of an exploratory factor analysis procedure applied on the e-learning readiness data obtained from a survey of four hundred and seventy-nine (N = 479) teachers from secondary schools in Nablus, Palestine. The data were drawn from a 23-item Likert questionnaire measuring e-learning readiness based on Chapnick's conception of the construct. Principal axis factoring (PAF) with Promax rotation applied on the data extracted four distinct factors supporting four of Chapnick's e-learning readiness dimensions, namely technological readiness, psychological readiness, infrastructure readiness and equipment readiness. Together these four dimensions explained 56% of the variance. These findings provide further support for the construct validity of the items and for the existence of these four factors that measure e-learning readiness.

Keywords: e-learning, e-learning readiness, technological readiness, psychological readiness, principal axis factoring

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Authors: Filomena Lopes, Sandra Fernandes

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Active learning strategies are at the center of any change process aimed to improve the development of student skills. This paper aims to analyse the impact of teaching strategies, including problem-based learning (PBL), in the curricular unit of information system for management, based on students’ perceptions of how they contribute to develop the desired learning outcomes of the curricular unit. This course is part of the 1st semester and 3rd year of the graduate degree program in management at a private higher education institution in Portugal. The methodology included an online questionnaire to students (n=40). Findings from students reveal a positive impact of the teaching strategies used. In general, 35% considered that the strategies implemented in the course contributed to the development of courses’ learning objectives. Students considered PBL as the learning strategy that better contributed to enhance the courses’ learning outcomes. This conclusion brings forward the need for further reflection and discussion on the impact of student feedback on teaching and learning processes.

Keywords: higher education, active learning strategies, skills development, student assessment

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Authors: G. Çelik Gül, F. Kurtuluş

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Colemanite is the most common borate mineral, and the main source of the boron required by plants, human, and earth. Transition metals exhibit optical and physical properties such as; non-linear optical character, structural diversity, thermal stability, long cycle life and luminescent radiation. The doping of colemanite with a transition metal, bring it very interesting and attractive properties which make them applicable in industry. Iron doped calcium borate was synthesized by conventional solid state method at 1200 °C for 12 h with a systematic pathway. X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, scanning electron microscopy/energy dispersive analyze (SEM/EDS) were used to characterize structural and morphological properties. Also, thermal properties were recorded by thermogravimetric-differential thermal analysis (TG/DTA). 

Keywords: colemanite, conventional synthesis, powder x-ray diffraction, borates

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Authors: Kasra Afsahi, Maryam Soheilifar, S. Hossein Hosseini, Omid Seyed Esmaeili, Rouzbeh Kezemi, Noushin Mehrbod, Nazanin Vahed, Tahereh Hajiahmad, Noureddin Nakhostin Ansari

Abstract:

Background: Stroke is a disabling neurological disease. Rehabilitative therapies are important treatment methods. This clinical trial was done to compare the effects of VR beside conventional rehabilitation versus conventional rehabilitation alone on spasticity and motor function in stroke patients. Materials and Methods: In this open-label randomized controlled clinical trial, 40 consecutive patients with stable first-ever ischemic stroke in the past three to 12 months that were referred to a rehabilitation clinic in Tehran, Iran, in 2020 were enrolled. After signing the informed written consent form, subjects were randomly assigned by block randomization of five in each block as cases with 1:1 into two groups of 20 cases; conventional plus VR therapy group: 45-minute conventional therapy session plus 15-minute VR therapy, and conventional group: 60-minute conventional therapy session. VR rehabilitation is designed and developed with different stages. Outcomes were modified Ashworth scale, recovery stage score for motor function, range of motion (ROM) of shoulder abduction/wrist extension, and patients’ satisfaction rate. Data were compared after study termination. Results: The satisfaction rate among the patients was significantly better in the combination group (P=0.003). Only wrist extension was varied between groups and was better in the combination group. The variables generally had a statistically significant difference (P < 0.05). Conclusion: Virtual reality plus conventional rehabilitation therapy is superior versus conventional rehabilitation alone on the wrist and elbow spasticity and motor function in patients with stroke.

Keywords: stroke, virtual therapy, rehabilitation, treatment

Procedia PDF Downloads 204

Authors: Muhammad Shujaat Saleem, Imamuddin

Abstract:

In reply to the argument made by the non-believers of Makkah “Sale is similar to riba”, Almighty Allah ordered “Sale is permissible while riba is impermissible”. The main intent of the study was to clarify the fallacy prevailing among the Muslims that in practical terms the product of Murabaha which is being offered by the Islamic banks is similar to that of conventional interest based business loan. However, specific objective was to ascertain the degree of financial efficiency on the basis of fund/loan utilization for intended purpose of Murabaha financing vis-à-vis conventional interest based business loan. The study employed survey strategy to collect primary data through structured close ended questionnaires from the sample of 98 Murabaha officers and 178 loan officers out of the whole population of 5 Islamic and 10 conventional banks respectively. Quantitative and qualitative techniques were used to analyze the data and the same is tabulated by use of frequency tables. The study found that the financial efficiency of Murabaha financing is more than that of conventional interest based business loan by 28% as Murabaha funds of Islamic banks are utilized for its intended purpose to the extent of 97% on average, compared to 69% of business loan offered by conventional banks.

Keywords: financial efficiency, murabaha funds, loan amount, intended purpose

Procedia PDF Downloads 321