Search results for: teaching learning based algorithm

Authors: Tryfon Mavropalias, Anastasia Alevriadou

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Co-teaching is a relatively recent model of providing teaching services to students with disabilities in Greece. According to recent studies, it seems that the largest number of students who take part in the Greek co-teaching programme are children with Autistic Spectrum Disorders (ASD). The aim of the suggested study is to investigate the effectiveness and usefulness of co-teaching to students with ASD as well as skills students with ASD develop during co-teaching in primary education classes. To conduct the research, quantitative method of research was used, with the means of research being a questionnaire including open and close type questions. The sample of this research consists of 142 primary school co-teachers from all over Northern Greece (71 general education teachers and 71 special education teachers). Given the results, it was concluded that co-teachers believe that including and educating children with Autistic Spectrum Disorders in the general class benefits those who autism is measured from the middle to the upper end of the spectrum. Additionally, children develop social skills first, followed by emotional and cognitive skills. Ultimately, educators declared that they are prepared only to a limited degree to effectively support students with Autistic Spectrum Disorders in general classes.

Keywords: Autistic spectrum disorders, co-teaching, co-teachers, co-taught class

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Authors: Oluwatofunmi Otobo

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This paper presents a review of the challenges of e-learning and e-learning technologies in tertiary institutions. This review is based on the researchers observations of the challenges of making use of ICT for learning in Nigeria using Adeyemi College of Education as a case study; this is in comparison to tertiary institutions in the UK, US and other more developed countries. In Nigeria and probably Africa as a whole, power is the major challenge. Its inconsistency and fluctuations pose the greatest challenge to making use of online education inside and outside the classroom. Internet and its supporting infrastructures in many places in Nigeria are slow and unreliable. This, in turn, could frustrate any attempt at making use of online education and e-learning technologies. Lack of basic knowledge of computer, its technologies and facilities could also prove to be a challenge as many young people up until now are yet to be computer literate. Personal interest on both the parts of lecturers and students is also a challenge. Many people are not interested in learning how to make use of technologies. This makes them resistant to changing from the ancient methods of doing things. These and others were reviewed by this paper, suggestions, and recommendations were proffered.

Keywords: education, e-learning, Nigeria, tertiary institutions

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Authors: Hahido Samaras

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In many cases, especially with the pandemic playing a major role in fast-tracking the growth of the digital industry, online learning has become a necessity or even a standard educational model nowadays, reliably overcoming barriers such as location, time and cost and frequently combined with a face-to-face format (e.g., in blended learning). This being the case, it is evident that students in many parts of the world, as well as their parents, will increasingly need to become aware of the pros and cons of online versus traditional courses. This fast-growing mode of learning, accelerated during the years of the pandemic, presents an abundance of exciting options especially matched for a large number of secondary school students in remote places of the world where access to stimulating educational settings and opportunities for a variety of learning alternatives are scarce, adding advantages such as flexibility, affordability, engagement, flow and personalization of the learning experience. However, online learning can also present several challenges, such as a lack of student motivation and social interactions in natural settings, digital literacy, and technical issues, to name a few. Therefore, educational researchers will need to conduct further studies focusing on the benefits and weaknesses of online learning vs. traditional learning, while instructional designers propose ways of enhancing student motivation and engagement in virtual environments. Similarly, teachers will be required to become more and more technology-capable, at the same time developing their knowledge about their students’ particular characteristics and needs so as to match them with the affordances the technology offers. And, of course, schools, education programs, and policymakers will have to invest in powerful tools and advanced courses for online instruction. By developing digital courses that incorporate intentional opportunities for community-building and interaction in the learning environment, as well as taking care to include built-in design principles and strategies that align learning outcomes with learning assignments, activities, and assessment practices, rewarding academic experiences can derive for all students. This paper raises various issues regarding the effectiveness of online learning on students by reviewing a large number of research studies related to the usefulness and impact of online learning following the COVID-19-induced digital education shift. It also discusses what students, teachers, decision-makers, and parents have reported about this mode of learning to date. Best practices are proposed for parties involved in the development of online learning materials, particularly for secondary school students, as there is a need for educators and developers to be increasingly concerned about the impact of virtual learning environments on student learning and wellbeing.

Keywords: blended learning, online learning, secondary schools, virtual environments

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Authors: Syed Ahmed Hasnain

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Instructors’ perception of blended learning plays an important role in the field of education. The literature review shows that there is a gap in research. Instructor perception of the blended learning approach has an impact on the motivation of the instructor to use technology in the classroom. The role of the student's perspective on the instructor’s perception is also important. Research also shows that instructor perceptions can be changed based on their past and present experiences with technology and blended learning. This paper draws the attention of the readers to the need for further research and contributions to studying instructor perceptions globally. Instructor perception affects the implementation of technology in the classroom, instructor-student relationship, and the class environment. Various publications, literature reviews, and articles are studied to show the importance of instructor perceptions. A lot of work has been published on student perceptions of the blended learning approach but there is a gap in research on instructor perceptions. The paper also makes recommendations for further research in the area of instructor perceptions of the blended learning approach. Institutions, administrators, senior management, and instructors can benefit from this paper.

Keywords: blended learning, education, literature review, instructor perceptions

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Authors: K. Bresilla, L. Manfrini, B. Morandi, A. Boini, G. Perulli, L. C. Grappadelli

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Image/video processing for fruit in the tree using hard-coded feature extraction algorithms have shown high accuracy during recent years. While accurate, these approaches even with high-end hardware are computationally intensive and too slow for real-time systems. This paper details the use of deep convolution neural networks (CNNs), specifically an algorithm (YOLO - You Only Look Once) with 24+2 convolution layers. Using deep-learning techniques eliminated the need for hard-code specific features for specific fruit shapes, color and/or other attributes. This CNN is trained on more than 5000 images of apple and pear fruits on 960 cores GPU (Graphical Processing Unit). Testing set showed an accuracy of 90%. After this, trained data were transferred to an embedded device (Raspberry Pi gen.3) with camera for more portability. Based on correlation between number of visible fruits or detected fruits on one frame and the real number of fruits on one tree, a model was created to accommodate this error rate. Speed of processing and detection of the whole platform was higher than 40 frames per second. This speed is fast enough for any grasping/harvesting robotic arm or other real-time applications.

Keywords: artificial intelligence, computer vision, deep learning, fruit recognition, harvesting robot, precision agriculture

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Authors: Mine Cekin

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Self-regulated learning (SRL), which can be defined as learning that takes place when an individual is an active controller over his cognition, behavior, and motivation in the learning process, seems to be an essential educational goal. However, it is asserted that students need an assistance to become self-regulated learners. Therefore, teachers appear to play an important role in the introduction of SRL. Even though the importance of SRL has been shown by many researchers, the issue of how teachers can introduce it in a classroom environment needs to be investigated thoroughly. When it comes to mathematics learning particularly, it seems really difficult to associate this area with self-regulated learning because of the fact that it is mainly seen as a domain that is overwhelmingly memorizing written notations. As a result, self-regulated learning in mathematics education and what roles teachers have seem to deserve a significant attention. In this study, the significance of SRL and the roles of teachers in promoting SRL in the field of mathematics education particularly with the help of current literature have been highlighted. Some of the roles of teachers are becoming self-regulated learners themselves, facilitating motivation and collaboration with their colleagues in their schools.

Keywords: mathematics education, motivation, self-regulated learning, teacher self-regulation

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Authors: Ritesh Kumar, Gitanjali Chhetri, Mandira Bhatia, Mohit Mishra, Abhijith Bailur, Abhinav

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The prevalence of the internet and technology in our day to day lives is creating more security issues than ever. The need for protecting and providing a secure access to private and business data has led to the development of many security systems. One of the potential solutions is to employ the bio-metric authentication technique. In this paper we present an innovative biometric authentication method that utilizes a person’s EEG signal, which is acquired in response to an auditory stimulus,and transferred wirelessly to a computer that has the necessary ANN algorithm-Multi layer perceptrol neural network because of is its ability to differentiate between information which is not linearly separable.In order to determine the weights of the hidden layer we use Gaussian random weight initialization. MLP utilizes a supervised learning technique called Back propagation for training the network. The complex algorithm used for EEG classification reduces the chances of intrusion into the protected public or private data.

Keywords: EEG signal, auditory evoked potential, biometrics, multilayer perceptron neural network, back propagation rule, Gaussian random weight initialization

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Authors: Amir Ahmad Dehghani, Morteza Nabizadeh

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This paper presents the application of an Adaptive Neuro-Fuzzy Inference System (ANFIS) to flood hydrograph modeling of Shahid Rajaee reservoir dam located in Iran. This was carried out using 11 flood hydrographs recorded in Tajan river gauging station. From this dataset, 9 flood hydrographs were chosen to train the model and 2 flood hydrographs to test the model. The different architectures of neuro-fuzzy model according to the membership function and learning algorithm were designed and trained with different epochs. The results were evaluated in comparison with the observed hydrographs and the best structure of model was chosen according the least RMSE in each performance. To evaluate the efficiency of neuro-fuzzy model, various statistical indices such as Nash-Sutcliff and flood peak discharge error criteria were calculated. In this simulation, the coordinates of a flood hydrograph including peak discharge were estimated using the discharge values occurred in the earlier time steps as input values to the neuro-fuzzy model. These results indicate the satisfactory efficiency of neuro-fuzzy model for flood simulating. This performance of the model demonstrates the suitability of the implemented approach to flood management projects.

Keywords: adaptive neuro-fuzzy inference system, flood hydrograph, hybrid learning algorithm, Shahid Rajaee reservoir dam

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Authors: B. Selma, S. Chouraqui

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The pancreas is an elongated organ that extends across the abdomen, below the stomach. In addition, it secretes certain enzymes that aid in food digestion. The pancreas also manufactures hormones responsible for regulating blood glucose levels. In the present paper, we propose a mathematical model to study the homeostasis of glucose and insulin in healthy human, and a simulation of this model, which depicts the physiological events after a meal, will be represented in ordinary humans. The aim of this paper is to design an algorithm which regulates the level of glucose in the blood. The algorithm applied the concept of expert system for performing an algorithm control in the form of an "active" used to prescribe the rate of insulin infusion. By decomposing the system into subsystems, we have developed parametric models of each subsystem by using a forcing function strategy. The results showed a performance of the control system.

Keywords: modeling, algorithm, regulation, glucose-insulin, blood, control system

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Authors: Yiqiong Yuan, Jun Sun, Dongmei Zhou, Jianan Sun

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In this paper, we presented a Multi-Objective Random Drift Particle Swarm Optimization algorithm (MORDPSO-CD) based on RDPSO and crowding distance sorting to improve the convergence and distribution with less computation cost. MORDPSO-CD makes the most of RDPSO to approach the true Pareto optimal solutions fast. We adopt the crowding distance sorting technique to update and maintain the archived optimal solutions. Introducing the crowding distance technique into MORDPSO can make the leader particles find the true Pareto solution ultimately. The simulation results reveal that the proposed algorithm has better convergence and distribution

Keywords: multi-objective optimization, random drift particle swarm optimization, crowding distance sorting, pareto optimal solution

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Authors: Katharina Fellnhofer, Kaisu Puumalainen

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Despite the current worldwide increasing interest in entrepreneurship education (EE), little attention has been paid to innovative web-based ways such as the narrative approach by telling individual stories of entrepreneurs via multimedia for demonstrating the impact on individuals towards entrepreneurship. In addition, this research discipline is faced with no consensus regarding its effective content of teaching materials and tools. Therefore, a qualitative hypothesis-generating research contribution is required to aim at drawing new insights from published works in the EE field of research to serve for future research related to multimedia entrepreneurial narratives. Based on this background, our effort will focus on finding support regarding following introductory statement: Multimedia success and failure stories of real entrepreneurs show potential to change perceptions towards entrepreneurship in a positive way. The proposed qualitative conceptual paper will introduce the underlying background for this research framework. Therefore, as a qualitative hypothesis-generating research contribution it aims at drawing new insights from published works in the EE field of research related to entrepreneurial narratives to serve for future research. With the means of the triangulation of multiple theories, we will utilize the foundation for multimedia-based entrepreneurial narratives applying a learning-through-multimedia-real-entrepreneurial-narratives pedagogical tool to facilitate entrepreneurship. Our effort will help to demystify how value-oriented entrepreneurs telling their stories multimedia can simultaneously enhance EE. Therefore, the paper will build new-fangled bridges between well-cited theoretical constructs to build a robust research framework. Overall, the intended contribution seeks to emphasize future research of currently under-researched issues in the EE sphere, which are considered to be essential not only to academia, as well as to business and society having future jobs-providing growth-oriented entrepreneurs in mind. The Authors would like to thank the Austrian Science Fund FWF: [J3740 – G27].

Keywords: entrepreneurship education, entrepreneurial attitudes and perceptions, entrepreneurial intention, entrepreneurial narratives

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Authors: Heba Salem

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This paper aims to share the researcher’s experience of using e-Portfolios as an assessment tool to follow up on students’ learning experiences and performance throughout the semester. It also aims at highlighting the importance of students’ self-reflection in the process of language learning. The paper begins by introducing the advanced media course, with its focus on listening and speaking skills, and introduces the students’ profiles. Then it explains the students’ role in the e-portfolio process as they are given the option to choose a listening text they studied throughout the semester and to choose a recorded oral production of their collection of artifacts throughout the semester. Students showcase and reflect on their progress in both listening comprehension and speaking. According to the research, re-listening to work given to them and to their production is a means of reflecting on both their progress and achievement. And choosing the work students want to showcase is a means to promote independent learning as well as self-expression. Students are encouraged to go back to the class learning outcomes in the process of choosing the work. In their reflections, students express how they met the specific learning outcome. While giving their presentations, students expressed how useful the experience of returning and going over what they covered to select one and going over their production as well. They also expressed how beneficial it was to listen to themselves and literally see their progress in both listening comprehension and speaking. Students also reported that they grasped more details from the texts than they did when first having it as an assignment, which coincided with one of the class learning outcomes. They also expressed the fact that they had more confidence speaking as well as they were able to use a variety of vocabulary and idiomatic expressions that students have accumulated. For illustration, this paper includes practical samples of students’ tasks and instructions as well as samples of their reflections. The results of students’ reflections coincide with what the research confirms about the effectiveness of the e-portfolios as a means of assessment. The employment of e-Portfolios has two-folded benefits; students are able to measure the achievement of the targeted learning outcomes, and teachers receive constructive feedback on their teaching methods.

Keywords: e-portfolios, assessment, self assessment, listening and speaking progress, foreign language, reflection, learning out comes, sharing experience

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Authors: Nurhak Altın, Ayhan Kucukmanisa, Oguzhan Urhan

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It is important that highways are in good condition for traffic safety. Road crashes (road cracks, erosion of lane markings, etc.) can cause accidents by affecting driving. Image processing based methods for detecting road cracks are available in the literature. In this paper, a deep learning based road crack detection approach is proposed. YOLO (You Look Only Once) is adopted as core component of the road crack detection approach presented. The YOLO network structure, which is developed for object detection, is trained with road crack images as a new class that is not previously used in YOLO. The performance of the proposed method is compared using different training methods: using randomly generated weights and training their own pre-trained weights (transfer learning). A similar training approach is applied to the simplified version of the YOLO network model (tiny yolo) and the results of the performance are examined. The developed system is able to process 8 fps on NVIDIA Jetson TX1 development kit.

Keywords: deep learning, embedded platform, real-time processing, road crack detection

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Authors: Ratima Damkham, Natasha Dejdumrong, Priyakorn Pusawiro

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This paper explored the solution in game design to help game designers in the educational game designing using digital educational game model canvas (DEGMC) and digital educational game form (DEGF) based on Outcome-based Education program. DEGMC and DEGF can help designers develop an overview of the game while designing and planning their own game. The way to clearly assess players’ ability from learning outcomes and support their game learning design is by using the tools. Designers can balance educational content and entertainment in designing a game by using the strategies of the Business Model Canvas and design the gameplay and players’ ability assessment from learning outcomes they need by referring to the Constructive Alignment. Furthermore, they can use their design plan in this research to write their Game Design Document (GDD). The success of the research was evaluated by four experts’ perspectives in the education and computer field. From the experiments, the canvas and form helped the game designers model their game according to the learning outcomes and analysis of their own game elements. This method can be a path to research an educational game design in the future.

Keywords: constructive alignment, constructivist theory, educational game, outcome-based education

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Authors: T. Konst

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Most jobs include training and communication tasks, but often the people in these jobs lack pedagogical competences to plan, implement and assess learning. This paper aims to discuss how a learning approach called innovation pedagogy developed in higher education can be utilized for learning development in various organizations. The methods presented how to implement innovation pedagogy such as process consultation and train the trainer model can provide added value to develop pedagogical knowhow in organizations and thus support their internal learning and development.

Keywords: innovation pedagogy, learning, organizational development, process consultation

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Authors: Maria Gonzalez Alriols, Itziar Egues, Maria A. Andres, Mirari Antxustegi

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Peer to peer learning is an educational tool very useful to enhance teamwork and reinforce cooperation between mates. It is particularly successful to work with students of different level of previous knowledge, as it often happens among pupils of subjects in the first course of science and engineering studies. Depending on the performed pre-university academic itinerary, the acquired knowledge in disciplines as mathematics, physics, or chemistry may be quite different. This fact is an added difficulty to the tuition of first-course basic science subjects of engineering degrees, with inexperienced students that do not know each other. In this context, peer to peer learning applied in small groups facilitates the communication between mates and makes it easier for the students with low level to be helped by the ones with better prior knowledge. In this work, several collaborative learning strategies were designed to be applied in the tuition of the subject 'chemistry', which is imparted in the first course of an engineering degree. Students were organized in groups combining mates with different level of prior knowledge. The teaching role was offered to the more experienced students who were responsible for designing learning pills to help the other mates in their group. This workload was rewarded with an extra mark, and more extra points were offered to all the group mates if every student in the group reached a determined level at the end of the semester. It was very important to start these activities from the beginning of the semester in order to avoid absenteeism. The obtained results were positive as a higher percentage of mates signed up and passed the final exam, the obtained final marks were higher, and a much better atmosphere was observed in the class.

Keywords: peer to peer tuition, collaborative learning, engineering instruction, chemistry

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Authors: Jeugert Kujtila, Kristi Hoxhalli, Ramazan Dalipi, Erjon Cota, Ardit Murati, Erind Bedalli

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Clustering is a versatile instrument in the analysis of collections of data providing insights of the underlying structures of the dataset and enhancing the modeling capabilities. The fuzzy approach to the clustering problem increases the flexibility involving the concept of partial memberships (some value in the continuous interval [0, 1]) of the instances in the clusters. Several fuzzy clustering algorithms have been devised like FCM, Gustafson-Kessel, Gath-Geva, kernel-based FCM, PCM etc. Each of these algorithms has its own advantages and drawbacks, so none of these algorithms would be able to perform superiorly in all datasets. In this paper we will experimentally compare FCM, GK, GG algorithm and a hybrid two-stage fuzzy clustering model combining the FCM and Gath-Geva algorithms. Firstly we will theoretically dis-cuss the advantages and drawbacks for each of these algorithms and we will describe the hybrid clustering model exploiting the advantages and diminishing the drawbacks of each algorithm. Secondly we will experimentally compare the accuracy of the hybrid model by applying it on several benchmark and synthetic datasets.

Keywords: fuzzy clustering, fuzzy c-means algorithm (FCM), Gustafson-Kessel algorithm, hybrid clustering model

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Authors: Te-Jen Chang, I-Hui Pan, Ping-Sheng Huang, Shan-Jen Cheng

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In this paper, a fast multiplication computing method utilizing the complement representation method and canonical recoding technique is proposed. By performing complements and canonical recoding technique, the number of partial products can be reduced. Based on these techniques, we propose an algorithm that provides an efficient multiplication method. On average, our proposed algorithm is to reduce the number of k-bit additions from (0.25k+logk/k+2.5) to (k/6 +logk/k+2.5), where k is the bit-length of the multiplicand A and multiplier B. We can therefore efficiently speed up the overall performance of the multiplication. Moreover, if we use the new proposes to compute common-multiplicand multiplication, the computational complexity can be reduced from (0.5 k+2 logk/k+5) to (k/3+2 logk/k+5) k-bit additions.

Keywords: algorithm design, complexity analysis, canonical recoding, public key cryptography, common-multiplicand multiplication

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Authors: Ruwan Gunawardane

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Second language teaching and learning is a complex process in which various factors are identified as having a negative impact on the competency in English among undergraduates of Sri Lanka. One such issue is the lack of intrinsic motivation among them to learn English despite the fact that they all know the importance of English. This study attempted to ascertain how the intrinsic motivation of undergraduates to learn English can be improved through reading out of curiosity. Humans are curious by nature, and cognitive psychology says that curiosity facilitates learning, memory, and motivation. The researcher carried out this study during the closure of universities due to the outbreak of the coronavirus through ‘Online Reading Café’, an online reading programme introduced by himself. He invited 1166 students of the Faculty of Science, University of Ruhuna, to read 50 articles taken from CNN and the BBC and posted at least two to three articles on the LMS of the faculty almost every day over a period of 23 days. The themes of the articles were based on the universe, exploration of planets, scientific experiments, evolution, etc., and the students were encouraged to collect as many words, phrases, and sentence structures as possible while reading and to form meaningful sentences using them. The data obtained through the students’ feedback was qualitatively analyzed. It was found that these undergraduates were interested in reading something out of curiosity, due to which intrinsic motivation is enhanced, and it facilitates competence in L2.

Keywords: English, competence, reading, curiosity

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Authors: Piyanut Sujit

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The purposes of this study were to: 1) create knowledge and develop web based instruction on the puppet show, 2) evaluate the effectiveness of the web based instruction on the puppet show by using the criteria of 80/80, and 3) compare and analyze the achievement of the students before and after learning with web based instruction on the puppet show. The population of this study included 53 students in the Program of Library and Information Sciences who registered in the subject of Reading and Reading Promotion in semester 1/2011, Suansunandha Rajabhat University. The research instruments consisted of web based instruction on the puppet show, specialist evaluation form, achievement test, and tests during the lesson. The research statistics included arithmetic mean, variable means, standard deviation, and t-test in SPSS for Windows. The results revealed that the effectiveness of the developed web based instruction was 84.67/80.47 which was higher than the set criteria at 80/80. The student achievement before and after learning showed statistically significant difference at 0.05 as in the hypothesis.

Keywords: puppet, puppet show, web based instruction, library and information sciences

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Authors: Zuoji Huang, Haiming Qian, Chunlin Wang, Jinyan Sun, Nan Xu

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In this paper, the strategy to extract double road edge lines from acquired road stripe image was explored. The workflow is as follows: the road stripes are acquired by probabilistic boosting tree algorithm and morphological algorithm immediately, and road centerlines are detected by thinning algorithm, so the initial road edge lines can be acquired along the road centerlines. Then we refine the results with big variation of local curvature of centerlines. Specifically, the energy function of edge line is constructed by gradient feature and spectral information, and Dijkstra algorithm is used to optimize the initial road edge lines. The Snake model is constructed to solve the fracture problem of intersection, and the discrete dynamic programming algorithm is used to solve the model. After that, we could get the final road network. Experiment results show that the strategy proposed in this paper can be used to extract the continuous and smooth road edge lines from high-resolution remote sensing images with an accuracy of 88% in our study area.

Keywords: road edge lines extraction, energy function, intersection fracture, Snake model

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Authors: Mohamed Ramdani, Hassen Abdellaoui, Abdenour Boudrassen

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Mobile platform’s attitude estimation approaches mainly based on combined positioning techniques and developed algorithms; which aim to reach a fast and accurate solution. In this work, we describe the design and the implementation of an attitude determination (AD) process, using only measurements from GPS sensors. The major issue is based on smoothed GPS code data using Hatch filter and raw carrier-phase measurements integrated into attitude algorithm based on vectors measurement using least squares (LSQ) estimation method. GPS dataset from a static experiment is used to investigate the effectiveness of the presented approach and consequently to check the accuracy of the attitude estimation algorithm. Attitude results from GPS multi-antenna over short baselines are introduced and analyzed. The 3D accuracy of estimated attitude parameters using smoothed measurements is over 0.27°.

Keywords: attitude determination, GPS code data smoothing, hatch filter, carrier-phase measurements, least-squares attitude estimation

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Authors: Shervin Alaei, Reza Moradi

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Trading in financial markets is subject to risks due to their high volatilities. Here, using an LSTM neural network, and by doing some risk-based feature engineering tasks, we developed a method that can accurately predict trends of the Tehran stock exchange market index from a few days ago. Our test results have shown that the proposed method with an average prediction accuracy of more than 94% is superior to the other common machine learning algorithms. To the best of our knowledge, this is the first work incorporating deep learning and risk factors to accurately predict market trends.

Keywords: deep learning, LSTM, trend prediction, risk management, artificial neural networks

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Authors: Miroslav Popelka, Jakub Nozicka

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The whole work is based on possibility to use Lego Mindstorms robotics systems to reduce costs. Lego Mindstorms consists of a wide variety of hardware components necessary to simulate, programme and test of robotics systems in practice. To programme algorithm, which simulates space using the ultrasonic sensor, was used development environment supplied with kit. Software Matlab was used to render values afterwards they were measured by ultrasonic sensor. The algorithm created for this paper uses theoretical knowledge from area of signal processing. Data being processed by algorithm are collected by ultrasonic sensor that scans 2D space in front of it. Ultrasonic sensor is placed on moving arm of robot which provides horizontal moving of sensor. Vertical movement of sensor is provided by wheel drive. The robot follows map in order to get correct positioning of measured data. Based on discovered facts it is possible to consider Lego Mindstorm for low-cost and capable kit for real-time modelling.

Keywords: LEGO Mindstorms, ultrasonic sensor, real-time modeling, 2D object, low-cost robotics systems, sensors, Matlab, EV3 Home Edition Software

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Authors: Brogan Guest, Amy Donaldson-Perrott

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The Master’s of Physician Associate Studies (MPAS) programme at St George’s, University of London (SGUL), is an intensive two-year course that trains students to become physician associates (PAs). PAs are generalized healthcare providers who work in primary and secondary care across the UK. PA programmes face the difficult task of preparing students to become safe medical providers in two short years. Our goal is to teach students to develop clinical reasoning early on in their studies and historically, this has been done predominantly though problem-based learning (PBL). We have had an increase concern about student engagement in PBL and difficulty recruiting facilitators to maintain the low student to facilitator ratio required in PBL. To address this issue, we created ‘Clinical Application of Anatomy and Physiology (CAAP)’. These peer-led, interactive, problem-based, small group sessions were designed to facilitate students’ clinical reasoning skills. The sessions were designed using the concept of Team-Based Learning (TBL). Students were divided into small groups and each completed a pre-session quiz consisting of difficult questions devised to assess students’ application of medical knowledge. The quiz was completed in small groups and they were not permitted access of external resources. After the quiz, students worked through a series of openended, clinical tasks using all available resources. They worked at their own pace and the session was peer-led, rather than facilitator-driven. For a group of 35 students, there were two facilitators who observed the sessions. The sessions utilised an infinite space whiteboard software. Each group member was encouraged to actively participate and work together to complete the 15-20 tasks. The session ran for 2 hours and concluded with a post-session quiz, identical to the pre-session quiz. We obtained subjective feedback from students on their experience with CAAP and evaluated the objective benefit of the sessions through the quiz results. Qualitative feedback from students was generally positive with students feeling the sessions increased engagement, clinical understanding, and confidence. They found the small group aspect beneficial and the technology easy to use and intuitive. They also liked the benefit of building a resource for their future revision, something unique to CAAP compared to PBL, which out students participate in weekly. Preliminary quiz results showed improvement from pre- and post- session; however, further statistical analysis will occur once all sessions are complete (final session to run December 2022) to determine significance. As a post-graduate healthcare professional programme, we have a strong focus on self-directed learning. Whilst PBL has been a mainstay in our curriculum since its inception, there are limitations and concerns about its future in view of student engagement and facilitator availability. Whilst CAAP is not TBL, it draws on the benefits of peer-led, small group work with pre- and post- team-based quizzes. The pilot of these sessions has shown that students are engaged by CAAP, and they can make significant progress in clinical reasoning in a short amount of time. This can be achieved with a high student to facilitator ratio.

Keywords: problem based learning, team based learning, active learning, peer-to-peer teaching, engagement

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Authors: Arvind Kumar, Manoj Kumar, Dattatraya H. Nagaraj, Amanpreet Singh, Jayanthi Prattapati

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The purpose of this paper is to study and compare two maximum power point tracking (MPPT) algorithms in a photovoltaic simulation system and also show a simulation study of maximum power point tracking (MPPT) for photovoltaic systems using perturb and observe algorithm and Incremental conductance algorithm. Maximum power point tracking (MPPT) plays an important role in photovoltaic systems because it maximize the power output from a PV system for a given set of conditions, and therefore maximize the array efficiency and minimize the overall system cost. Since the maximum power point (MPP) varies, based on the irradiation and cell temperature, appropriate algorithms must be utilized to track the (MPP) and maintain the operation of the system in it. MATLAB/Simulink is used to establish a model of photovoltaic system with (MPPT) function. This system is developed by combining the models established of solar PV module and DC-DC Boost converter. The system is simulated under different climate conditions. Simulation results show that the photovoltaic simulation system can track the maximum power point accurately.

Keywords: incremental conductance algorithm, perturb and observe algorithm, photovoltaic system, simulation results

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Authors: Ágoston Nagy

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This paper introduces a method of using unsupervised machine learning to visualize the feature space of a dataset in 2D, in order to find most characteristic segments in the set. After dimension reduction, users can select clusters by manual drawing. Selected clusters are recorded into a data model that is used for later predictions, based on realtime data. Predictions are made with supervised learning, using Gesture Recognition Toolkit. The paper introduces two example applications: a semantic audio organizer for analyzing incoming sounds, and a gesture database organizer where gestural data (recorded by a Leap motion) is visualized for further manipulation.

Keywords: gesture recognition, machine learning, real-time interaction, visualization

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Authors: Claire Goode

Abstract:

This paper reports on a doctoral research project using narrative inquiry to investigate the stories of twelve national Tertiary Teaching Excellence Award winners in New Zealand. Preliminary findings highlight awardees’ views on their identity, their professional practice, and on what they consider to be excellence in tertiary teaching. The research also reports on common themes in the personal qualities that awardees describe, and on what these nationally recognised educators would like to see in place around Tertiary Teacher Development. Educators, mentors, trainers, and curriculum designers can gain a deeper understanding of what teaching excellence looks like, and of how teachers perceive their own practice and their impact on others. This may enable different interventions to develop best practice from staff, and to raise standards. It is hoped too that, by reflecting on the stories of teachers who have been recognised for ‘excellence’, educators will relate to and recognise elements of their own practice, and will feel motivated and inspired to share these with their peers and the wider academic community.

Keywords: academic identity, narrative inquiry, teacher development, teaching excellence

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Authors: Malik Ghulam Behlol, Alison Fox, Faiza Masood, Sabiha Arshad

Abstract:

This paper explores the barriers to the application of learning-supportive assessment at teaching practicum while investigating the role of university teachers (UT), cooperative teachers (CT), prospective teachers ( PT) and heads of the practicum schools (HPS) in the selected universities of Pakistan and the UK. It is a qualitative case study and data were collected through the lesson observation of UT in the pre-service teacher education setting and PT in practicum schools. Interviews with UT, HPS, and Focus Group Discussions with PT were conducted too. The study has concluded that as compared to the UK counterpart, PT in Pakistan faces significant barriers in applying learning-supportive assessment in the school practicum settings because of large class sizes, lack of institutionalised collaboration between universities and schools, poor modelling of the lesson, ineffective feedback practices, lower order thinking assignments, and limited opportunities to use technology in school settings.

Keywords: assessment, pre-service teacher education, theory-practice gap, teacher education

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Authors: Joelle Thng, Li Fang

Abstract:

Objective: As programming becomes a highly valued and sought-after skill in the economy, many universities have started offering Python courses to help students keep up with the demands of employers. This study focuses on designing a university module that effectively educates undergraduate students on financial analysis using Python programming. Methodology: To better satisfy the specific demands for each sector, this study adopted a qualitative research modus operandi to craft a module that would complement students’ existing financial skills. The lessons were structured using research-backed educational learning tools, and important Python concepts were prudently screened before being included in the syllabus. The course contents were streamlined based on criteria such as ease of learning and versatility. In particular, the skills taught were modelled in a way to ensure they were beneficial for financial data processing and analysis. Results: Through this study, a 6-week course containing the chosen topics and programming applications was carefully constructed for finance students. Conclusion: The findings in this paper will provide valuable insights as to how teaching programming could be customised for students hailing from various academic backgrounds.

Keywords: curriculum development, designing effective instruction, higher education strategy, python for finance students

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