Search results for: supervised learning algorithm

Authors: Irfan Ahmed Rind

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Science education has recently become the top priority of government of Pakistan. Number of schemes has been initiated for the improvement of science teaching and learning at primary and secondary levels of education, most importantly training in-service science teachers on inquiry based teaching and learning to empower students and encourage creativity, critical thinking, and innovation among them. Therefore, this approach has been promoted in the recent continuous professional development trainings for the in-service teachers. However, the follow ups on trained science teachers and educators suggest that these teachers fail to implement the inquiry based teaching and learning in their classes. In addition, these trainings also fail to bring any significant change in students’ science content knowledge and understanding as per the annual national level surveys conducted by government and independent agencies. Research suggests that science has been taught using scientific positivism, which supports objectivity based on experiments and mathematics. In contrary, the inquiry based teaching and learning are based on constructivism, which conflicts with the positivist epistemology of science teachers. It was, therefore, assumed that science teachers struggle to implement the inquiry based teaching approach as it conflicts with their basic epistemological beliefs. With this assumption, this research aimed to (i) understand how science teachers conceptualize the nature of science, and how this influence their understanding of learning, learners, their own roles as teachers and their teaching strategies, (ii) identify the conflict of science teachers’ epistemological beliefs with the inquiry based teaching approach, and (iii) find the ways in which science teachers epistemological beliefs may be developed from positivism to constructivism, so that they may effectively use the inquiry based teaching approach in teaching science. Using qualitative case study approach, thirty six secondary and higher secondary science teachers (21 male and 15 female) were selected. Data was collected using interviewed, participatory observations (sixty lessons were observed), and twenty interviews from students for verifications of teachers’ responses. The findings suggest that most of the science teacher were positivist in defining the nature of science. Most of them limit themselves to one fix answer that is provided in the books and that there is only one 'right' way to teach science. There is no room for students’ or teachers’ own opinion or bias when it comes to scientific concepts. Inquiry based teaching seems 'no right' to them. They find it difficult to allow students to think out of the box. However, some interesting exercises were found to be very effective in bringing the change in teachers’ epistemological beliefs. These will be discussed in detail in the paper. The findings have major implications for the teachers, educators, and policymakers.

Keywords: science teachers, epistemology, metacognition, inquiry based teaching

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Authors: Neda Jalaliyoon, Nooh Abu Bakar, Hamed Taherdoost

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The present research recommended balanced scorecard (BSC) framework to appraise the performance of the universities. As the original model of balanced scorecard has four perspectives in order to implement BSC in present research the same model with “financial perspective”, “customer”,” internal process” and “learning and growth” is used as well. With applying fuzzy Delphi method (FDM) and questionnaire sixteen measures of performance were identified. Moreover, with using the analytic network process (ANP) the weights of the selected indicators were determined. Results indicated that the most important BSC’s aspect were Internal Process (0.3149), Customer (0.2769), Learning and Growth (0.2049), and Financial (0.2033) respectively. The proposed BSC framework can help universities to enhance their efficiency in competitive environment.

Keywords: balanced scorecard, higher education, fuzzy delphi method, analytic network process (ANP)

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Authors: Vitalii Yu. Kapitan, Aleksandr V. Perzhu, Konstantin V. Nefedev

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The necessity of studying magnetic multilayer structures is explained by the prospects of their practical application as a technological base for creating new storages medium. Magnetic multilayer films have many unique features that contribute to increasing the density of information recording and the speed of storage devices. Multilayer structures are structures of alternating magnetic and nonmagnetic layers. In frame of the classical Heisenberg model, lattice spin systems with direct short- and long-range exchange interactions were investigated by Monte Carlo methods. The thermodynamic characteristics of multilayer structures, such as the temperature behavior of magnetization, energy, and heat capacity, were investigated. The processes of magnetization reversal of multilayer structures in external magnetic fields were investigated. The developed software is based on the new, promising programming language Rust. Rust is a new experimental programming language developed by Mozilla. The language is positioned as an alternative to C and C++. For the Monte Carlo simulation, the Metropolis algorithm and its parallel implementation using MPI and the Wang-Landau algorithm were used. We are planning to study of magnetic multilayer films with asymmetric Dzyaloshinskii–Moriya (DM) interaction, interfacing effects and skyrmions textures. This work was supported by the state task of the Ministry of Education and Science of the Russia # 3.7383.2017/8.9

Keywords: The Monte Carlo methods, Heisenberg model, multilayer structures, magnetic skyrmion

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Authors: Geir Sigurðsson

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This paper compares ancient Daoist and Confucian approaches to the human body as a locus for learning, edification or personal cultivation. While pointing out some major differences between ancient Chinese and mainstream Western visions of the body, it seeks at the same time inspiration in some seminal Western phenomenological and post-structuralist writings, in particular from Maurice Merleau-Ponty and Pierre Bourdieu. By clarifying the somewhat dissimilar scopes of foci found in Daoist and Confucian philosophies with regard to the role of and attitude to the body, the conclusion is nevertheless that their approaches are comparable, and that both traditions take the physical body to play a vital role in the cultivation of excellence. Lastly, it will be argued that cosmological underpinnings prevent the Confucian li from being rigid and invariable and that it rather emerges as a flexible learning device to train through active embodiment a refined sensibility for one’s cultural environment.

Keywords: body, Confucianism, Daoism, li (ritual), phenomenology

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Authors: Gaye Senbag

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In English language teaching, feedback is considered as one of the main components of writing instruction. Teachers put a lot of time and effort in order to provide learners with written feedback for effective language learning. At Anadolu University School of Foreign Languages (AUSFL) students are given written feedback for their each piece of writing through online platforms such as Edmodo and Turnitin, and traditional methods. However, little is known regarding how learners value and respond to teacher-provided feedback. As the perceptions of the students remarkably affect their learning, this study examines how they perceive the effectiveness of feedback provided by the teacher. Aiming to analyse it, 30 intermediate level (B1+ CEFR level) students were given a questionnaire, which includes Likert scale questions. The results will be discussed in detail.

Keywords: feedback, perceptions, writing, English Language Teaching (ELT)

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Authors: Jiangping Wang

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This presentation describes the design and implementation of PaaS (platform as a service) cloud-based labs that are used in database-related courses to teach students practical skills. Traditionally, all labs are implemented in a desktop-based environment where students have to install heavy client software to access database servers. In order to release students from that burden, we have successfully deployed the cloud-based solution to support database-related courses, from which students and teachers can practice and learn database topics in various database courses via cloud access. With its development environment, execution runtime, web server, database server, and collaboration capability, it offers a shared pool of configurable computing resources and comprehensive environment that supports students’ needs without the complexity of maintaining the infrastructure.

Keywords: PaaS, database environment, e-learning, web server

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Authors: Annette Cosgrove

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The objectives of this research study is to examine the impact of professional development in Technology Enhanced Learning (TEL) and the digitisation of learning in teaching communities across multiple higher education sites in the ATU (Atlantic Technological University *) ( 2020-2025), including the proposal of an evidence based digital teaching model for use in a future pandemic. The research strategy undertaken for this PhD Study is a multi-site study using mixed methods. Qualitative & quantitative methods are being used in the study to collect data. A pilot study was carried out initially , feedback collected and the research instrument was edited to reflect this feedback, before being administered. The purpose of the staff questionnaire is to evaluate the impact of professional development in the area of TEL, and to capture the practitioners views on the perceived impact on their teaching practice in the higher education sector across ATU (West of Ireland – 5 Higher education locations ). The phenomenon being explored is ‘ the impact of professional development in the area of technology enhanced learning and on teaching practice in a higher education institution.’ The research methodology chosen for this study is an Action based Research Study. The researcher has chosen this approach as it is a prime strategy for developing educational theory and enhancing educational practice . This study includes quantitative and qualitative methods to elicit data which will quantify the impact that continuous professional development in the area of digital teaching practice and technologies has on the practitioner’s teaching practice in higher education. The research instruments / data collection tools for this study include a lecturer survey with a targeted TEL Practice group ( Pre and post covid experience) and semi-structured interviews with lecturers.. This research is currently being conducted across the ATU multisite campus and targeting Higher education lecturers that have completed formal CPD in the area of digital teaching. ATU, a west of Ireland university is the focus of the study , The research questionnaire has been deployed, with 75 respondents to date across the ATU - the primary questionnaire and semi- formal interviews are ongoing currently – the purpose being to evaluate the impact of formal professional development in the area of TEL and its perceived impact on the practitioners teaching practice in the area of digital teaching and learning . This paper will present initial findings, reflections and data from this ongoing research study.

Keywords: TEL, DTL, digital teaching, digital assessment

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Authors: Vareesha Masood, Ammara Gul, Nabeeha Areej, Muhammad Asif Masood, Hamna Imran

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The universal use of PDF files has prompted hackers to use them for malicious intent by hiding malicious codes in their victim’s PDF machines. Machine learning has proven to be the most efficient in identifying benign files and detecting files with PDF malware. This paper has proposed an approach using a decision tree classifier with parameters. A modern, inclusive dataset CIC-Evasive-PDFMal2022, produced by Lockheed Martin’s Cyber Security wing is used. It is one of the most reliable datasets to use in this field. We designed a PDF malware detection system that achieved 99.2%. Comparing the suggested model to other cutting-edge models in the same study field, it has a great performance in detecting PDF malware. Accordingly, we provide the fastest, most reliable, and most efficient PDF Malware detection approach in this paper.

Keywords: PDF, PDF malware, decision tree classifier, random forest classifier

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Authors: Ozge Yalciner

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Intercultural communication is crucial in the education of multilingual learners in primary grades, significantly influencing their academic and social development. This study explores how intercultural communication intersects with multilingual education, highlighting the importance of culturally responsive teaching practices. It addresses the challenges and opportunities presented by diverse linguistic backgrounds and proposes strategies for creating inclusive and supportive learning environments. The research emphasizes the need for teacher training programs that equip educators with the skills to recognize and address cultural differences, thereby enhancing student engagement and participation. This study was completed in an elementary school in a city in the Midwest, USA. The data was collected through observations and interviews with students and teachers. It discusses the integration of multicultural perspectives in curricula and the promotion of language diversity as an asset. Peer interactions and collaborative learning are highlighted as crucial for developing intercultural competence among young learners. The findings suggest that meaningful intercultural communication fosters a sense of belonging and mutual respect, leading to improved educational outcomes for multilingual students. Prioritizing intercultural communication in primary education is essential for supporting the linguistic and cultural identities of multilingual learners. By adopting inclusive pedagogical approaches and fostering an environment of cultural appreciation, educators can better support their students' academic success and personal growth.

Keywords: diversity, intercultural communication, multilingual learners, primary grades

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Authors: Rachel Buchanan, Rebecca LaRiviere

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Context: The ongoing effects of colonialism continue to be experienced through paternalistic policies and funding processes that cause disjuncture between and across Indigenous early childhood programming on-reserve and in urban and Northern settings in Canada. While various educational organizations and social service providers have risen to address these challenges in the short, medium and long term, there continues to be a lack in nation-wide cohesive, culturally grounded, and meaningful early learning programming for Indigenous children in Canada. Indigenous-centered early learning programs tend to face one of two scaling dilemmas: their program goals are too prescriptive to enable the program to be meaningfully replicated in different cultural/ community settings, or their program goals are too broad to be meaningfully adapted to the unique cultural and contextual needs and desires of Indigenous communities (the “franchise approach”). There are over 600 First Nations communities in Canada representing more than 50 Nations and languages. Consequently, Indigenous early learning programming cannot be applied with a universal or “one size fits all” approach. Sustainable and comprehensive programming must be responsive to each community context, building upon existing strengths and assets to avoid program duplication and irrelevance. Thesis: Community-driven and culturally adapted early childhood programming is critical but cannot be achieved on a large scale within traditional program models that are constrained by prescriptive overarching program goals. Principles, rather than goals, are an effective way to navigate and evaluate complex and dynamic systems. Principles guide an intervention to be adaptable, flexible and scalable. The Martin Family Initiative (MFI) ’s Early Years program engages a principles-based approach to programming. As will be discussed in this paper, this approach enables the program to catalyze existing community-based strengths and organizational assets toward bridging gaps across and disjuncture between Indigenous early learning programs, as well as to scale programming in sustainable, context-responsive and dynamic ways. This paper argues that using a principles-driven and adaptive scaling approach, the Early Years model establishes important learnings for culturally adapted Indigenous early learning programming in Canada. Methodology: The Early Years has leveraged this approach to develop an array of programming with partner organizations and communities across the country. The Early Years began as a singular pilot project in one First Nation. In just three years, it has expanded to five different regions and community organizations. In each context, the program supports the partner organization through different means and to different ends, the extent to which is determined in partnership with each community-based organization: in some cases, this means supporting the organization to build home visiting programming from the ground-up; in others, it means offering organization-specific culturally adapted early learning resources to support the programming that already exists in communities. Principles underpin but do not define the practices of the program in each of these relationships. This paper will explore numerous examples of principles-based adaptability with the context of the Early Years, concluding that the program model offers theadaptability and dynamism necessary to respond to unique and ever-evolving community contexts and needs of Indigenous children today.

Keywords: culturally adapted programming, indigenous early learning, principles-based approach, program scaling

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Authors: Zahzouh Zoubir, Bouzaouit Azzeddine, Gahgah Mounir

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The use of more and more electronic power switches with a nonlinear behavior generates non-sinusoidal currents in distribution networks, which causes damage to domestic and industrial equipment. The multi-level shunt power active filter is subsequently shown to be an adequate solution to the problem raised. Nevertheless, the difficulty of adjusting the active filter DC supply voltage requires another technology to ensure it. In this article, a photovoltaic generator is associated with the DC bus power terminals of the active filter. The proposed system consists of a field of solar panels, three multi-level voltage inverters connected to the power grid and a non-linear load consisting of a six-diode rectifier bridge supplying a resistive-inductive load. Current control techniques of active and reactive power are used to compensate for both harmonic currents and reactive power as well as to inject active solar power into the distribution network. An algorithm of the search method of the maximum power point of type Perturb and observe is applied. Simulation results of the system proposed under the MATLAB/Simulink environment shows that the performance of control commands that reassure the solar power injection in the network, harmonic current compensation and power factor correction.

Keywords: Actif power filter, MPPT, pertub&observe algorithm, PV array, PWM-control

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Authors: Omar Elharrouss, Youssef Hmamouche, Assia Kamal Idrissi, Btissam El Khamlichi, Amal El Fallah-Seghrouchni

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Edge detection is represented as one of the most challenging tasks in computer vision, due to the complexity of detecting the edges or boundaries in real-world images that contains objects of different types and scales like trees, building as well as various backgrounds. Edge detection is represented also as a key task for many computer vision applications. Using a set of backbones as well as attention modules, deep-learning-based methods improved the detection of edges compared with the traditional methods like Sobel and Canny. However, images of complex scenes still represent a challenge for these methods. Also, the detected edges using the existing approaches suffer from non-refined results while the image output contains many erroneous edges. To overcome this, n this paper, by using the mechanism of residual learning, a refined edge detection network is proposed (RED-Net). By maintaining the high resolution of edges during the training process, and conserving the resolution of the edge image during the network stage, we make the pooling outputs at each stage connected with the output of the previous layer. Also, after each layer, we use an affined batch normalization layer as an erosion operation for the homogeneous region in the image. The proposed methods are evaluated using the most challenging datasets including BSDS500, NYUD, and Multicue. The obtained results outperform the designed edge detection networks in terms of performance metrics and quality of output images.

Keywords: edge detection, convolutional neural networks, deep learning, scale-representation, backbone

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Authors: Armine Vahanyan

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Humanity has been still coping with the new COVID-19 pandemic. Healthcare providers, economists, psychologists, and other specialists speak about the impact of the virus on different spheres of our life. In the list of similar discussions, the impact of pandemics on global education is of utmost importance. Ideally, providing quality education services should be crucial, and the ways education programs are being adapted will determine the success or failure of the service providers. The paper aims to summarize the research touching upon the current situation of higher education in Armenia. The research includes data from official reports, surveys among education leads, faculty, and students, as well as personal observations and consideration. Through descriptive analysis, the findings of the research are being presented from various aspects. Interim results of the research unveiled two major issues in the sector of higher education in Armenia. On the one hand, the entire compulsory digitization of instruction, assessment, and grading has evoked serious gaps related to the lack of technical competencies. There is an urgent need for professional development programs that will address most of the concerns due to the shift to the online instruction mode. On the other hand, online teaching and learning require revision and adaptation of the existing curricula. Given that the content of certain programs may not be compromised, the teaching methods, the assignments, and evaluation require profound transformation, which will still be in line with course learning outcomes and student learning outcomes. The given paper focuses on the ways the mentioned issues are being addressed in Armenia. The extent of commitment for changes and adaptability to the new situation varies from the government-funded and private universities. In particular, the paper compares and contrasts activities and measures taken at the Armenian State Pedagogical University and the American University of Armenia. Thus, the Pedagogical University focused on the use of Google Classroom as the only means for teaching and learning as well as adopted the compulsory synchronous instruction mode. The American University, on the contrary, kept practicing the academic freedom, enabling both synchronous and asynchronous instruction modes, ensuring alignment of the course learning outcomes and student learning outcomes. The State University utilized the assignments and assessment, which would work for the on-campus instruction mode, while the American university employed a variety of assignments applicable for online teaching mode. The latter has suggested the utilization of multiple apps, internet sources, and online library access for a better online instant. Discussions with faculty through online forums and/or professional development workshops also facilitate restructuring and adaptation of the courses. Finally, the paper will synthesize the results of the undertaken research and will outline the e-learning perspectives and opportunities boosted by the known devastating healthcare issue.

Keywords: assessment, compulsory digitization of education services, online teaching, instruction mode, program restructuring

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Authors: Andrea Fiorista

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The learning of prepositions is a quite problematic aspect in foreign language instruction, and Italian is certainly not an exception. In their prototypical function, prepositions express schematic relations of two entities in a highly abstract, typically image-schematic way. In other terms, prepositions assume concepts such as directionality, collocation of objects in space and time and, in Cognitive Linguistics’ terms, the position of a trajector with respect to a landmark. Learners of different native languages may conceptualize them differently, implying that they are supposed to operate a recategorization (or create new categories) fitting with the target language. However, most current Italian Foreign/Second Language handbooks and didactic grammars do not facilitate learners in carrying out the task, as they tend to provide partial and idiosyncratic descriptions, with the consequent learner’s effort to memorize them, most of the time without success. In their prototypical meaning, prepositions are used to specify precise topographical positions in the physical environment which become less and less accurate as they radiate out from what might be termed a concrete prototype. According to that, the present study aims to elaborate a cognitive and conceptually well-grounded analysis of some extensive uses of the Italian preposition a, in order to propose effective pedagogical solutions in the Teaching/Learning process. Image schemas, cognitive metaphors and embodiment represent efficient cognitive tools in a task like this. Actually, while learning the merely spatial use of the preposition a (e.g. Sono a Roma = I am in Rome; vado a Roma = I am going to Rome,…) is quite straightforward, it is more complex when a appears in constructions such as verbs of motion +a + infinitive (e.g. Vado a studiare = I am going to study), inchoative periphrasis (e.g. Tra poco mi metto a leggere = In a moment I will read), causative construction (e.g. Lui mi ha mandato a lavorare = He sent me to work). The study reports data from a teaching intervention of Focus on Form, in which a basic cognitive schema is used to facilitate both teachers and students to respectively explain/understand the extensive uses of a. The educational material employed translates Cognitive Linguistics’ theoretical assumptions, such as image schemas and cognitive metaphors, into simple images or proto-scenes easily comprehensible for learners. Illustrative material, indeed, is supposed to make metalinguistic contents more accessible. Moreover, the concept of embodiment is pedagogically applied through activities including motion and learners’ bodily involvement. It is expected that replacing rote learning with a methodology that gives grammatical elements a proper meaning, makes learning process more effective both in the short and long term.

Keywords: cognitive approaches to language teaching, image schemas, embodiment, Italian as FL/SL

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Authors: Christine Böckmann, Julia Rosemann

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We present an inversion algorithm that is used in the European Aerosol Lidar Network for the inversion of data collected with multi-wavelength Raman lidar. These instruments measure backscatter coefficients at 355, 532, and 1064 nm, and extinction coefficients at 355 and 532 nm. The algorithm is based on manually controlled inversion of optical data which allows for detailed sensitivity studies and thus provides us with comparably high quality of the derived data products. The algorithm allows us to derive particle effective radius, volume, surface-area concentration with comparably high confidence. The retrieval of the real and imaginary parts of the complex refractive index still is a challenge in view of the accuracy required for these parameters in climate change studies in which light-absorption needs to be known with high accuracy. Single-scattering albedo (SSA) can be computed from the retrieve microphysical parameters and allows us to categorize aerosols into high and low absorbing aerosols. From mathematical point of view the algorithm is based on the concept of using truncated singular value decomposition as regularization method. This method was adapted to work for the retrieval of the particle size distribution function (PSD) and is called hybrid regularization technique since it is using a triple of regularization parameters. The inversion of an ill-posed problem, such as the retrieval of the PSD, is always a challenging task because very small measurement errors will be amplified most often hugely during the solution process unless an appropriate regularization method is used. Even using a regularization method is difficult since appropriate regularization parameters have to be determined. Therefore, in a next stage of our work we decided to use two regularization techniques in parallel for comparison purpose. The second method is an iterative regularization method based on Pade iteration. Here, the number of iteration steps serves as the regularization parameter. We successfully developed a semi-automated software for spherical particles which is able to run even on a parallel processor machine. From a mathematical point of view, it is also very important (as selection criteria for an appropriate regularization method) to investigate the degree of ill-posedness of the problem which we found is a moderate ill-posedness. We computed the optical data from mono-modal logarithmic PSD and investigated particles of spherical shape in our simulations. We considered particle radii as large as 6 nm which does not only cover the size range of particles in the fine-mode fraction of naturally occurring PSD but also covers a part of the coarse-mode fraction of PSD. We considered errors of 15% in the simulation studies. For the SSA, 100% of all cases achieve relative errors below 12%. In more detail, 87% of all cases for 355 nm and 88% of all cases for 532 nm are well below 6%. With respect to the absolute error for non- and weak-absorbing particles with real parts 1.5 and 1.6 in all modes the accuracy limit +/- 0.03 is achieved. In sum, 70% of all cases stay below +/-0.03 which is sufficient for climate change studies.

Keywords: aerosol particles, inverse problem, microphysical particle properties, regularization

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Authors: C. A. Anser Pasha

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In this paper, a new Vehicular Speed Detection Camera System that is applicable as an alternative to traditional radars with the same accuracy or even better is presented. The real-time measurement and analysis of various traffic parameters such as speed and number of vehicles are increasingly required in traffic control and management. Image processing techniques are now considered as an attractive and flexible method for automatic analysis and data collections in traffic engineering. Various algorithms based on image processing techniques have been applied to detect multiple vehicles and track them. The SDCS processes can be divided into three successive phases; the first phase is Objects detection phase, which uses a hybrid algorithm based on combining an adaptive background subtraction technique with a three-frame differencing algorithm which ratifies the major drawback of using only adaptive background subtraction. The second phase is Objects tracking, which consists of three successive operations - object segmentation, object labeling, and object center extraction. Objects tracking operation takes into consideration the different possible scenarios of the moving object like simple tracking, the object has left the scene, the object has entered the scene, object crossed by another object, and object leaves and another one enters the scene. The third phase is speed calculation phase, which is calculated from the number of frames consumed by the object to pass by the scene.

Keywords: radar, image processing, detection, tracking, segmentation

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Authors: Shofiayuningtyas Luftiani

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Some private schools in Indonesia started integrating the online program Gizmos in the teaching-learning process. Gizmos was developed to supplement the existing curriculum by integrating it into the instructional programs. The program has some features using an inquiry-based simulation, in which students conduct exploration by using a worksheet while teachers use the teacher guidelines to direct and assess students’ performance In this study, the discussion about Gizmos highlights its features as the assessment media of mathematics learning for secondary school students. The discussion is based on the case study and literature review from the Indonesian context. The purpose of applying Gizmos as an assessment media refers to the diagnostic assessment. As a part of the diagnostic assessment, the teachers review the student exploration sheet, analyze particularly in the students’ difficulties and consider findings in planning future learning process. This assessment becomes important since the teacher needs the data about students’ persistent weaknesses. Additionally, this program also helps to build student’ understanding by its interactive simulation. Currently, the assessment over-emphasizes the students’ answers in the worksheet based on the provided answer keys while students perform their skill in translating the question, doing the simulation and answering the question. Whereas, the assessment should involve the multiple perspectives and sources of students’ performance since teacher should adjust the instructional programs with the complexity of students’ learning needs and styles. Consequently, the approach to improving the assessment components is selected to challenge the current assessment. The purpose of this challenge is to involve not only the cognitive diagnosis but also the analysis of skills and error. Concerning the selected setting for this diagnostic assessment that develops the combination of cognitive diagnosis, skills analysis and error analysis, the teachers should create an assessment rubric. The rubric plays the important role as the guide to provide a set of criteria for the assessment. Without the precise rubric, the teacher potentially ineffectively documents and follows up the data about students at risk of failure. Furthermore, the teachers who employ the program of Gizmos as the diagnostic assessment might encounter some obstacles. Based on the condition of assessment in the selected setting, the obstacles involve the time constrain, the reluctance of higher teaching burden and the students’ behavior. Consequently, the teacher who chooses the Gizmos with those approaches has to plan, implement and evaluate the assessment. The main point of this assessment is not in the result of students’ worksheet. However, the diagnostic assessment has the two-stage process; the process to prompt and effectively follow-up both individual weaknesses and those of the learning process. Ultimately, the discussion of Gizmos as the media of the diagnostic assessment refers to the effort to improve the mathematical learning process.

Keywords: diagnostic assessment, error analysis, Gizmos online program, skills analysis

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Authors: Elisabeth Unterfrauner, Christian Voigt

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Since the foundation of the first Fab Lab by the Massachusetts Institute of Technology about 17 years ago, the Maker movement has spread globally with the foundation of maker spaces and Fab Labs worldwide. In these workshops, citizens have access to digital fabrication technologies such as 3D printers and laser cutters to develop and test their own ideas and prototypes, which makes it an attractive place for start-up companies. Know-How is shared not only in the physical space but also online in diverse communities. According to the Horizon report, the Maker movement, however, will also have an impact on educational settings in the following years. The European project ‘DOIT - Entrepreneurial skills for young social innovators in an open digital world’ has incorporated key elements of making to develop an early entrepreneurial education program for children between the age of six and 16. The Maker pedagogy builds on constructive learning approaches, learning by doing principles, learning in collaborative and interdisciplinary teams and learning through trial and error where mistakes are acknowledged as learning opportunities. The DOIT program consists of seven consecutive elements. It starts with a motivation phase where students get motivated by envisioning the scope of their possibilities. The second step is about Co-design: Students are asked to collect and select potential ideas for innovations. In the Co-creation phase students gather in teams and develop first prototypes of their ideas. In the iteration phase, the prototype is continuously improved and in the next step, in the reflection phase, feedback on the prototypes is exchanged between the teams. In the last two steps, scaling and reaching out, the robustness of the prototype is tested with a bigger group of users outside of the educational setting and finally students will share their projects with a wider public. The DOIT program involves 1,000 children in two pilot phases at 11 pilot sites in ten different European countries. The comprehensive evaluation design is based on a mixed method approach with a theoretical backbone on Lackeus’ model of entrepreneurship education, which distinguishes between entrepreneurial attitudes, entrepreneurial skills and entrepreneurial knowledge. A pre-post-test with quantitative measures as well as qualitative data from interviews with facilitators, students and workshop protocols will reveal the effectiveness of the program. The evaluation results will be presented at the conference.

Keywords: early entrepreneurial education, Fab Lab, maker education, Maker movement

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Authors: Andrea Tundis, Carlos García Cordero, Rolf Egert, Alfredo Garro, Max Mühlhäuser

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Resilience is an important system property that relies on the ability of a system to automatically recover from a degraded state so as to continue providing its services. Resilient systems have the means of detecting faults and failures with the added capability of automatically restoring their normal operations. Mastering resilience in the domain of Cyber-Physical Systems is challenging due to the interdependence of hybrid hardware and software components, along with physical limitations, laws, regulations and standards, among others. In order to overcome these challenges, this paper presents a modeling approach, based on the concept of Dynamic Cells, tailored to the management of Smart Grids. Additionally, a heuristic algorithm that works on top of the proposed modeling approach, to find resilient configurations, has been defined and implemented. More specifically, the model supports a flexible representation of Smart Grids and the algorithm is able to manage, at different abstraction levels, the resource consumption of individual grid elements on the presence of failures and faults. Finally, the proposal is evaluated in a test scenario where the effectiveness of such approach, when dealing with complex scenarios where adequate solutions are difficult to find, is shown.

Keywords: cyber-physical systems, energy management, optimization, smart grids, self-healing, resilience, security

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Authors: Michael Dreyfuss, Yahel Giat

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Limited battery range and long recharging times are the greatest obstacles to the successful adoption of electric cars. One of the suggestions to overcome these problems is that carmakers retain ownership of batteries and provide battery swapping service so that customers exchange their depleted batteries for recharged batteries. Motivated by this example, we consider the problem of optimal spares allocation in an exchangeable-item, multi-location repair system. We generalize the standard service measures of fill rate and average waiting time to reflect the fact that customers penalize the service provider only if they have to wait more than a ‘tolerable’ time window. These measures are denoted as the window fill rate and the truncated waiting time, respectively. We find that the truncated waiting time is convex and therefore a greedy algorithm solves the spares allocation problem efficiently. We show that the window fill rate is generally S-shaped and describe an efficient algorithm to find a near-optimal solution and detail a priori and a posteriori upper bounds to the distance from optimum. The theory is complemented with a large scale numerical example demonstrating the spare battery allocation in battery swapping stations.

Keywords: convex-concave optimization, exchangeable item, M/G/infinity, multiple location, repair system, spares allocation, window fill rate

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Authors: Kourosh Modarresi

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The abundance of media channels and devices has given users a variety of options to extract, discover, and explore information in the digital world. Since, often, there is a long and complicated path that a typical user may venture before taking any (significant) action (such as purchasing goods and services), it is critical to know how each node (media channel) in the path of user has contributed to the final action. In this work, the significance of each media channel is computed using statistical analysis and machine learning techniques. More specifically, “Regularized Singular Value Decomposition”, and “Sparse Principal Component” has been used to compute the significance of each channel toward the final action. The results of this work are a considerable improvement compared to the present approaches.

Keywords: multimedia attribution, sparse principal component, regularization, singular value decomposition, feature significance, machine learning, linear systems, variable shrinkage

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Authors: Mohammed Alhammad

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The movement towards the inclusion of students with special educational needs (SEN) in mainstream schools has become widely accepted practice in many countries. However in Saudi Arabia, this is not happening. Instead the practice for students with learning difficulties (LD) is to study in special classrooms in mainstream schools and they are not included with their peers, except at break times and morning assembly, and on school trips. There are a number of barriers that face implementing inclusion for students with LD in mainstream classrooms: one such barrier is the training of teachers. The training, either pre- or in-service, that teachers receive is seen as playing an important role in leading to the successful implementation of inclusion. The aim of this presentation is to explore how pre-service training and in-service training are acting as barriers for implementing inclusion of students with LD in mainstream primary schools in Saudi Arabia from the perspective of teachers. The qualitative research approach was used to explore this barrier. Twenty-four teachers (general education teachers, special education teachers) were interviewed using semi-structured interview and a number of documents were used as method of data collection. The result showed teachers felt that not much attention was paid to inclusion in pre-services training for general education teachers and special education teachers in Saudi Arabia. In addition, pre-service training for general education teachers does not normally including modules on special education. Regarding the in-service training, no courses at all about inclusion are provided for teachers. Furthermore, training courses in special education are few. As result, the knowledge and skills required to implemented inclusion successfully.

Keywords: inclusion, learning difficulties, Saudi Arabia, training

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Authors: Abdelrahman A. Ramzy, Bassel S. Abdallah, Mohamed E. Bahgat, Sarah M. Abdelkader, Sherif H. ElGohary

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Attention-Deficit/Hyperactivity Disorder (ADHD), epilepsy, and autism affect millions of children worldwide, many of which are undiagnosed despite the fact that all of these disorders are detectable in early childhood. Late diagnosis can cause severe problems due to the late treatment and to the misconceptions and lack of awareness as a whole towards these disorders. Moreover, electroencephalography (EEG) has played a vital role in the assessment of neural function in children. Therefore, quantitative EEG measurement will be utilized as a tool for use in the evaluation of patients who may have ADHD, epilepsy, and autism. We propose a screening tool that uses EEG signals and machine learning algorithms to detect these disorders at an early age in an automated manner. The proposed classifiers used with epilepsy as a step taken for the work done so far, provided an accuracy of approximately 97% using SVM, Naïve Bayes and Decision tree, while 98% using KNN, which gives hope for the work yet to be conducted.

Keywords: ADHD, autism, epilepsy, EEG, SVM

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Authors: Delphine Vendryes, Dushyanth Sekhar, Baojia Tong, Matthew Theisen, Chester Curme

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Much of the data that inform the decisions of governments, corporations and individuals are harvested from unstructured documents. Data extraction is defined here as a process that turns non-machine-readable information into a machine-readable format that can be stored, for instance, in a database. In financial services, introducing more automation in data extraction pipelines is a major challenge. Information sought by financial data consumers is often buried within vast bodies of unstructured documents, which have historically required thorough manual extraction. Automated solutions provide faster access to non-machine-readable datasets, in a context where untimely information quickly becomes irrelevant. Data quality standards cannot be compromised, so automation requires high data integrity. This multifaceted task is broken down into smaller steps: ingestion, table parsing (detection and structure recognition), text analysis (entity detection and disambiguation), schema-based record extraction, user feedback incorporation. Selected intermediary steps are phrased as machine learning problems. Solutions leveraging cutting-edge approaches from the fields of computer vision (e.g. table detection) and natural language processing (e.g. entity detection and disambiguation) are proposed.

Keywords: computer vision, entity recognition, finance, information retrieval, machine learning, natural language processing

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Authors: Cristina Costa-Lobo, Sandra Fernandes, Miguel Magalhães, José Dinis-Carvalho, Alfredo Regueiro, Ana Carvalho

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This paper is a report on the findings of the construction and the validation of a questionnaire monetized in a portuguese higher education context with undergraduate students. The Questionnaire for the Evaluation of Entrepreneurship Project Psychopedagogical Practices consists of six scales: Critical appraisal of the project, Developed Learning and Skills, Teamwork, Teacher and Tutor Roles, Evaluation of Student Performance, and Project Effectiveness as a Teaching-Learning Methodology. The proceedings of its construction are analyzed, and the validity and internal consistency analysis are described. Findings indicate good indicators of validity, good fidelity and an interpretable factorial structure.

Keywords: entrepreneurship project, higher education, psychopedagogical practices, teacher and tutor roles

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Authors: Marta Fonseca, Pedro Marvão, Beatriz Oliveira, Bruno Heleno, Pedro Carreiro-Martins, Nuno Neuparth, António Rendas

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Background: Concept maps (CMs) visually represent hierarchical connections among related ideas. They foster logical organization and clarify idea relationships, potentially aiding medical students in critical thinking (to think clearly and rationally about what to do or what to believe). However, there are inconsistent claims about the use of CMs in undergraduate medical education. Our three research questions are: 1) What studies have been published on concept mapping in undergraduate medical education? 2) What was the impact of CMs on students’ critical thinking? 3) How and why have these interventions had an educational impact? Methods: Eight databases were systematically searched (plus a manual and an additional search were conducted). After eliminating duplicate entries, titles, and abstracts, and full-texts were independently screened by two authors. Data extraction and quality assessment of the studies were independently performed by two authors. Qualitative and quantitative data were integrated using mixed-methods. The results were reported using the structured approach to the reporting in healthcare education of evidence synthesis statement and BEME guidance. Results: Thirty-nine studies were included from 26 journals (19 quantitative, 8 qualitative and 12 mixed-methods studies). CMs were considered as a tool to promote critical thinking, both in the perception of students and tutors, as well as in assessing students’ knowledge and/or skills. In addition to their role as facilitators of knowledge integration and critical thinking, CMs were considered both teaching and learning methods. Conclusions: CMs are teaching and learning tools which seem to help medical students develop critical thinking. This is due to the flexibility of the tool as a facilitator of knowledge integration, as a learning and teaching method. The wide range of contexts, purposes, and variations in how CMs and instruments to assess critical thinking are used increase our confidence that the positive effects are consistent.

Keywords: concept map, medical education, undergraduate, critical thinking, meaningful learning

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Authors: Rabab M. Ramadan, Elaraby A. Elgallad

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With extensive application, the performance of unimodal biometrics systems has to face a diversity of problems such as signal and background noise, distortion, and environment differences. Therefore, multimodal biometric systems are proposed to solve the above stated problems. This paper introduces a bimodal biometric recognition system based on the extracted features of the human palm print and iris. Palm print biometric is fairly a new evolving technology that is used to identify people by their palm features. The iris is a strong competitor together with face and fingerprints for presence in multimodal recognition systems. In this research, we introduced an algorithm to the combination of the palm and iris-extracted features using a texture-based descriptor, the Scale Invariant Feature Transform (SIFT). Since the feature sets are non-homogeneous as features of different biometric modalities are used, these features will be concatenated to form a single feature vector. Particle swarm optimization (PSO) is used as a feature selection technique to reduce the dimensionality of the feature. The proposed algorithm will be applied to the Institute of Technology of Delhi (IITD) database and its performance will be compared with various iris recognition algorithms found in the literature.

Keywords: iris recognition, particle swarm optimization, feature extraction, feature selection, palm print, the Scale Invariant Feature Transform (SIFT)

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Authors: Lana Burmistrova

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Introduction: The influence of visual impairments on several cognitive processes used in the music learning process is an increasingly important area in special education and cognitive musicology. Many children have several visual impairments due to the refractive errors and irreversible inhibitors. However, based on the compensatory neuroplasticity and functional reorganization, congenitally blind (CB) and early blind (EB) individuals use several areas of the occipital lobe to perceive and process auditory and tactile information. CB individuals have greater memory capacity, memory reliability, and less false memory mechanisms are used while executing several tasks, they have better working memory (WM) and short-term memory (STM). Blind individuals use several strategies while executing tactile and working memory n-back tasks: verbalization strategy (mental recall), tactile strategy (tactile recall) and combined strategies. Methods and design: The aim of the pilot study was to substantiate similar tendencies while executing attention, memory and combined auditory tasks in blind and sighted individuals constructed for this study, and to investigate attention, memory and combined mechanisms used in the music learning process. For this study eight (n=8) blind and eight (n=8) sighted individuals aged 13-20 were chosen. All respondents had more than five years music performance and music learning experience. In the attention task, all respondents had to identify pitch changes in tonal and randomized melodic pairs. The memory task was based on the mismatch negativity (MMN) proportion theory: 80 percent standard (not changed) and 20 percent deviant (changed) stimuli (sequences). Every sequence was named (na-na, ra-ra, za-za) and several items (pencil, spoon, tealight) were assigned for each sequence. Respondents had to recall the sequences, to associate them with the item and to detect possible changes. While executing the combined task, all respondents had to focus attention on the pitch changes and had to detect and describe these during the recall. Results and conclusion: The results support specific features in CB and EB, and similarities between late blind (LB) and sighted individuals. While executing attention and memory tasks, it was possible to observe the tendency in CB and EB by using more precise execution tactics and usage of more advanced periodic memory, while focusing on auditory and tactile stimuli. While executing memory and combined tasks, CB and EB individuals used passive working memory to recall standard sequences, active working memory to recall deviant sequences and combined strategies. Based on the observation results, assessment of blind respondents and recording specifics, following attention and memory correlations were identified: reflective attention and STM, reflective attention and periodic memory, auditory attention and WM, tactile attention and WM, auditory tactile attention and STM. The results and the summary of findings highlight the attention and memory features used in the music learning process in the context of blindness, and the tendency of the several attention and memory types correlated based on the task, strategy and individual features.

Keywords: attention, blindness, memory, music learning, strategy

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Authors: Imen Boudali, Marwa Ragmoun

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The Vehicle Routing Problem with Hard Time Windows (VRPHTW) is a basic distribution management problem that models many real-world problems. The objective of the problem is to deliver a set of customers with known demands on minimum-cost vehicle routes while satisfying vehicle capacity and hard time windows for customers. In this paper, we propose to deal with our optimization problem by using a new hybrid stochastic algorithm based on two metaheuristics: Chemical Reaction Optimization (CRO) and Greedy Randomized Adaptive Search Procedure (GRASP). The first method is inspired by the natural process of chemical reactions enabling the transformation of unstable substances with excessive energy to stable ones. During this process, the molecules interact with each other through a series of elementary reactions to reach minimum energy for their existence. This property is embedded in CRO to solve the VRPHTW. In order to enhance the population diversity throughout the search process, we integrated the GRASP in our method. Simulation results on the base of Solomon’s benchmark instances show the very satisfactory performances of the proposed approach.

Keywords: Benchmark Problems, Combinatorial Optimization, Vehicle Routing Problem with Hard Time Windows, Meta-heuristics, Hybridization, GRASP, CRO

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Authors: Aaditya U. Jhamb

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Due to the current energy crisis that many countries are battling, energy-efficient buildings are the subject of extensive research in the modern technological era because of growing worries about energy consumption and its effects on the environment. The paper explores 8 factors that help determine energy efficiency for a building: (relative compactness, surface area, wall area, roof area, overall height, orientation, glazing area, and glazing area distribution), with Tsanas and Xifara providing a dataset. The data set employed 768 different residential building models to anticipate heating and cooling loads with a low mean squared error. By optimizing these characteristics, machine learning algorithms may assess and properly forecast a building's heating and cooling loads, lowering energy usage while increasing the quality of people's lives. As a result, the paper studied the magnitude of the correlation between these input factors and the two output variables using various statistical methods of analysis after determining which input variable was most closely associated with the output loads. The most conclusive model was the Decision Tree Regressor, which had a mean squared error of 0.258, whilst the least definitive model was the Isotonic Regressor, which had a mean squared error of 21.68. This paper also investigated the KNN Regressor and the Linear Regression, which had to mean squared errors of 3.349 and 18.141, respectively. In conclusion, the model, given the 8 input variables, was able to predict the heating and cooling loads of a residential building accurately and precisely.

Keywords: energy efficient buildings, heating load, cooling load, machine learning models

Procedia PDF Downloads 78