Search results for: spatial learning

Authors: K. Ismail, A. Ali, R. C. Hasan, I. Khalil, Z. Bachok, N. M. Said, A. M. Muslim, M. S. Che Din, W. S. Chong

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The marine ecosystem in Malaysia holds invaluable potential in terms of economics, food security, pharmaceuticals components and protection from natural hazards. Although exploration of oil and gas industry and fisheries are active within Malaysian waters, knowledge of the seascape and ecological functioning of benthic habitats is still extremely poor in the marine parks around Malaysia due to the lack of detailed seafloor information. Consequently, it is difficult to manage marine resources effectively, protect ecologically important areas and set legislation to safeguard the marine parks. The limited baseline data hinders scientific linkage to support effective marine spatial management in Malaysia. This became the main driver behind the first seabed mapping effort at the national level. Taman Laut Labuan (TLL) is located to the west coast of Sabah and to the east of South China Sea. The total area of TLL is approximately 158.15 km2, comprises of three islands namely Pulau Kuraman, Rusukan Besar and Rusukan Kecil and is characterised by shallow fringing reef with few submerged shallow reef. The unfamiliar rocky shorelines limit the survey of multibeam echosounder to area with depth more than 10 m. Whereas, singlebeam and side scan sonar systems were used to acquire the data for area with depth less than 10 m. By integrating data from multibeam bathymetry and backscatter with singlebeam bathymetry and side sonar images, we produce a substrate map and coral coverage map for the TLL using i) marine landscape mapping technique and ii) RSOBIA ArcGIS toolbar (developed by T. Le Bas). We take the initiative to explore the ability of aerial drone and satellite image (WorldView-3) to derive the depths and substrate type within the intertidal and subtidal zone where it is not accessible via acoustic mapping. Although the coverage was limited, the outcome showed a promising technique to be incorporated towards establishing a guideline to facilitate a standard practice for efficient marine spatial management in Malaysia.

Keywords: habitat mapping, marine spatial management, South China Sea, National seabed mapping

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Authors: Sindile Ngubane-Mokiwa

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This paper addresses two questions: (1) what barriers do the blind students face with assessment and feedback in open distance learning contexts? And (2) How can these barriers be removed? The paper focuses on the distance education through which most students with disabilities elevate their chances of accessing higher education. Lack of genuine inclusion is also evident in the challenges the blind students face during the assessment. These barriers are experienced at both formative and summative stages. The insights in this paper emanate from a case study that was carried out through qualitative approaches. The data was collected through in-depth interview, life stories, and telephonic interviews. The paper provides a review of local, continental and international views on how best assessment barriers can be removed. A group of five blind students, comprising of two honours students, two master's students and one doctoral student participated in this study. The data analysis was done through thematic analysis. The findings revealed that (a) feedback to the assignment is often inaccessible; (b) the software used is incompatible; (c) learning and assessment are designed in exclusionary approaches; (d) assessment facilities are not conducive; and (e) lack of proactive innovative assessment strategies. The article concludes by recommending ways in which barriers to assessment can be removed. These include addressing inclusive assessment and feedback strategies in professional development initiatives.

Keywords: assessment design, barriers, disabilities, blind students, feedback, universal design for learning

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Authors: T. Hopkin, S. Lu, P. Rogers, M. Sexton

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Housing Associations (HAs) contribute circa 20% of the UK’s housing supply. HAs are however under increasing pressure as a result of funding cuts and rent reductions. Due to the increased pressure, a number of processes are currently being reviewed by HAs, especially how they manage and learn from defects. Learning from defects is considered a useful approach to achieving defect reduction within the UK housebuilding industry. This paper contributes to our understanding of how HAs learn from defects by undertaking an initial round table discussion with key HA stakeholders as part of an ongoing collaborative research project with the National House Building Council (NHBC) to better understand how house builders and HAs learn from defects to reduce their prevalence. The initial discussion shows that defect information runs through a number of groups, both internal and external of a HA during both the defects management process and organizational learning (OL) process. Furthermore, HAs are reliant on capturing and recording defect data as the foundation for the OL process. During the OL process defect data analysis is the primary enabler to recognizing a need for a change to organizational routines. When a need for change has been recognized, new options are typically pursued to design out defects via updates to a HAs Employer’s Requirements. Proposed solutions are selected by a review board and committed to organizational routine. After implementing a change, both structured and unstructured feedback is sought to establish the change’s success. The findings from the HA discussion demonstrates that OL can achieve defect reduction within the house building sector in the UK. The paper concludes by outlining a potential ‘learning from defects model’ for the housebuilding industry as well as describing future work.

Keywords: defects, new homes, housing association, organizational learning

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Authors: Catherine Chua, Kashif Raza

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Work-integrated learning (WIL) has been heightened in the last few years across countries. With a specific attention on working adults, the key objective is to integrate work experiences with academic studies so that they will be given more opportunities to advance, gather relevant skills and credentials to enable them to contribute more positively to the labour market. In Singapore, developing talent through WIL aims to develop specialist and enduring skills for the industries. Collaborating with the institutes of higher education in Singapore, the Integrated Work Study Programs (IWSP) seek to harmonize classroom learning with practical work experiences so that adult students can develop skills and knowledge that are needed in the existing and future workplaces. Local higher education institutions will also work closely with industry partners, and design courses that support these students to deepen their skills. Using Critical Discourse Analysis, this paper examines the Singapore government policies in WIL and argues that despite the various supports and interventions provided by the government, it is equally important to create a ‘space’ in the society whereby there is a greater recognition for WIL as a valuable education approach, i.e., “continuous meritocracy”. This is especially so in Singapore where academic excellence and conventional front-loaded approach to education are valued.

Keywords: work-integrated learning, adult learners, continuous meritocracy, skillsfuture singapore

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Authors: Sitalakshmi Venkatraman, Fiona Wahr, Anthony de Souza-Daw, Samuel Kaspi

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There is a growing emphasis on generic skills in higher education to match the changing skill-set requirements of the labour market. However, researchers and policy makers have not arrived at a consensus on the generic skills that actually contribute towards workplace employability and performance that complement and/or underpin discipline-specific graduate attributes. In order to strengthen the qualifications framework, a range of ‘generic’ learning outcomes have been considered for students undergoing higher education programs and among them it is necessary to have the fundamental generic skills such as literacy and numeracy at a level appropriate to the qualification type. This warrants for curriculum design approaches to contextualise the form and scope of these fundamental generic skills for supporting both students’ learning engagement in the course, as well as the graduate attributes required for employability and to progress within their chosen profession. Little research is reported in integrating such generic skills into discipline-specific learning outcomes. This paper explores the literature of the generic skills required for graduates from the discipline of Information Technology (IT) in relation to an Australian higher education institution. The paper presents the rationale of a proposed Bachelor of IT curriculum designed to contextualize the learning of these generic skills within the students’ discipline studies.

Keywords: curriculum, employability, generic skills, graduate attributes, higher education, information technology

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Authors: Gholizadeh F. F., Goldansaz S. H., Bandani A. R., A. Ashouri

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This study aimed to investigate the direct effects of increasing carbon dioxide (CO₂) concentration on the behavior of Bombus terrestris bumblebees in laboratory conditions to understand the outcomes of the augmentation of this gas in the Earth's atmosphere on the decline of populations of these pollinators. Learning and memory duration of bumblebees were evaluated as two main behavioral factors in social insects at different concentrations of CO₂. In both series of experiments, the behavior of bees under the influence of CO₂ changes compared to the control. Insects kept at high CO₂ concentrations learn less than control bees and spend more time identifying and navigating to discover their food source and access time (nectar consumption). These results showed that bees maybe lose some of their food resources due to poorer identification and act weaker on searching due to less memory and avoiding the enemy in higher CO₂ concentration. Therefore, CO₂ increasing concentration can be one of the reasons for the decline of these pollinating insects' populations by negatively affecting their fitness.

Keywords: Bombus terrestris, CO₂, learning, memory duration

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Authors: Yen-Hui Lu

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In the past two decades, in order to increase university visibility and internationalization, English as a medium of instruction (EMI) has become one of the main language policies in higher education institutions where English is not a dominant language. However, given the complex, discipline-embedded nature of academic communication, academic literacy does not come with students’ everyday language experience, and it is a challenge for all students. Particularly, to engage students in the effective learning process of discipline concepts in the EMI classrooms, teachers need to provide explicit academic language instruction to assist students in deep understanding of discipline concepts. To bridge the gap between academic language development and discipline learning in the EMI classrooms, the researcher incorporates academic language strategies and key elements of project-based learning (PBL) into an Academic Language Strategy driven PBL (ALS-PBL) model. With clear steps and strategies, the model helps EMI teachers to scaffold students’ academic language development in the EMI classrooms. ALS-PBL model includes three major stages: preparation, implementation, and assessment. First, in the preparation stage, ALS-PBL teachers need to identify learning goals for both content and language learning and to design PBL topics for investigation. Second, during the implementation stage, ALS-PBL teachers use the model as a guideline to create a lesson structure and class routine. There are five important elements in the implementation stage: (1) academic language preparation, (2) connecting background knowledge, (3) comprehensible input, (4) academic language reinforcement, and (5) sustained inquiry and project presentation. Finally, ALS-PBL teachers use formative assessments such as student learning logs, teachers’ feedback, and peer evaluation to collect detailed information that demonstrates students’ academic language development in the learning process. In this study, ALS-PBL model was implemented in an interdisciplinary course entitled “Science is Everywhere”, which was co-taught by five professors from different discipline backgrounds, English education, civil engineering, business administration, international business, and chemical engineering. The purpose of the course was to cultivate students’ interdisciplinary knowledge as well as English competency in disciplinary areas. This study used a case-study design to systematically investigate students’ learning experiences in the class using ALS-PBL model. The participants of the study were 22 college students with different majors. This course was one of the elective EMI courses in this focal university. The students enrolled in this EMI course to fulfill the school language policy, which requires the students to complete two EMI courses before their graduation. For the credibility, this study used multiple methods to collect data, including classroom observation, teachers’ feedback, peer assessment, student learning log, and student focus-group interviews. Research findings show four major successful aspects of implementing ALS-PBL model in the EMI classroom: (1) clear focus on both content and language learning, (2) meaningful practice in authentic communication, (3) reflective learning in academic language strategies, and (4) collaborative support in content knowledge.This study will be of value to teachers involved in delivering English as well as content lessons to language learners by providing a theoretically-sound practical model for application in the classroom.

Keywords: academic language development, content and language integrated learning, english as a medium of instruction, project-based learning

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Authors: Jiaqi Huang, Yuheng Wang

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Premises selection, the task of selecting a set of axioms for proving a given conjecture, is a major bottleneck in automated theorem proving. An array of deep-learning-based methods has been established for premises selection, but a perfect performance remains challenging. Our study examines the inaccuracy of deep neural networks in premises selection. Through training network models using encoded conjecture and axiom pairs from the Mizar Mathematical Library, two potential biases are found: the network models classify more premises as necessary than unnecessary, referred to as the ‘positive bias’, and the network models perform better in proving conjectures that paired with more axioms, referred to as ‘length bias’. The ‘positive bias’ and ‘length bias’ discovered could inform the limitation of existing deep neural networks.

Keywords: automated theorem proving, premises selection, deep learning, interpreting deep learning

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Authors: M. A. Mabasa, O. Ramokolo, M. Z. Mnikathi, D. Mathabatha, T. Manyapelo

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The study examines the importance of translating South African folklore from Oral into Written Literature in a Multilingual Education. Therefore, the study postulates that translation can be regarded as a valuable tool when oral and written literature is transmitted from one generation to another. The study entails that translation does not take place in a haphazard fashion; for that reason, skills such as translation principles are required to translate folklore significantly and effectively. The purpose of the study is to indicate the significance of using translation relating to folklore in teaching and learning. The study also observed that Modernism in literature should be shared amongst varieties of cultures because folklore is interactive in narrating stories, folktales and myths to sharpen the reader’s knowledge and intellect because they are informative and educative in nature. As a technological tool, the study points out that translation is of paramount importance in the sense that the meanings of different data can be made available in all South African official languages using oral and written forms of folklore. The study opines that tradition and customary beliefs and practices in the institution of higher learning. The study envisages the way in which literature of folklore can be juxtaposed to ensure that translated folklore is of quality assured standards. The study alludes that well-translated folklore can serve as oral and written literature, which may contribute to the child’s learning and acquisition of knowledge and insights during cognitive development toward maturity. Methodologically, the study selects a qualitative research approach and selects content analysis as an instrument for data gathering, which will be analyzed qualitatively in consideration of the significance of translating folklore as written and spoken literature in a documented way. The study reveals that the translation of folktales promotes functional multilingualism in high-function formal contexts like a university. The study emphasizes that translated and preserved literary folklore may serve as a language repository from one generation to another because of the archival and storage of information in the form of a term bank.

Keywords: translation, editing, teaching, learning, folklores

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Authors: Ryoo Hye Jin Agnes

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This study aims to investigate the efficacy of clickers in fostering L2 class interaction. In an L2 classroom, active learner-to-learner interactions and learner-to-teacher interactions play an important role in language acquisition. In light of this, introducing learning tools that promote such interactions would benefit L2 classroom by fostering interaction. This is because the anonymity of clickers allows learners to express their needs without the social risks associated with speaking up in the class. clickers therefore efficiently help learners express their level of understanding during the process of learning itself. This allows for an evaluative feedback loop where both learners and teachers understand the level of progress of the learners, better enabling classrooms to adapt to the learners’ needs. Eventually this tool promotes participation from learners. This, in turn, is believed to be effective in fostering classroom interaction, allowing learning to take place in a more comfortable yet vibrant way. This study is finalized by presenting the result of an experiment conducted to verify the effectiveness of this approach when teaching pragmatic aspect of Korean expressions with similar semantic functions. The learning achievement of learners in the experimental group was found higher than the learners’ in a control group. A survey was distributed to the learners, questioning them regarding the efficacy of clickers, and how it contributed to their learning in areas such as motivation, self-assessment, increasing participation, as well as giving feedback to teachers. Analyzing the data collected from the questionnaire given to the learners, the study presented data suggesting that this approach increased the scope of interactivity in the classroom, thus not only increasing participation but enhancing the type of classroom participation among learners. This participation in turn led to a marked improvement in their communicative abilities.

Keywords: second language acquisition, interaction, clickers, learner response system, output from learners, learner’s cognitive process

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Authors: Majid Habib Khan, Jinwei Zhao, Xinhong Hei, Liu Jiedong, Rana Shahzad Noor, Muhammad Imran

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Deep learning is increasingly employed in image classification, yet the scarcity and high cost of labeled data for training remain a challenge. Limited samples often lead to overfitting due to biased sample distribution. This paper introduces a dynamic distribution calibration method for few-shot learning. Initially, base and new class samples undergo normalization to mitigate disparate feature magnitudes. A pre-trained model then extracts feature vectors from both classes. The method dynamically selects distribution characteristics from base classes (both adjacent and remote) in the embedding space, using a threshold value approach for new class samples. Given the propensity of similar classes to share feature distributions like mean and variance, this research assumes a Gaussian distribution for feature vectors. Subsequently, distributional features of new class samples are calibrated using a corrected hyperparameter, derived from the distribution features of both adjacent and distant base classes. This calibration augments the new class sample set. The technique demonstrates significant improvements, with up to 4% accuracy gains in few-shot classification challenges, as evidenced by tests on miniImagenet and CUB datasets.

Keywords: deep learning, computer vision, image classification, few-shot learning, threshold

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Authors: Shweta Singh, Sudaman Katti

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The most well-known sequence models make use of complex recurrent neural networks in an encoder-decoder configuration. The model used in this research makes use of a transformer, which is based purely on a self-attention mechanism, without relying on recurrence at all. More specifically, encoders and decoders which make use of self-attention and operate based on a memory, are used. In this research work, results for various 3D visual and non-visual reinforcement learning tasks designed in Unity software were obtained. Convolutional neural networks, more specifically, nature CNN architecture, are used for input processing in visual tasks, and comparison with standard long short-term memory (LSTM) architecture is performed for both visual tasks based on CNNs and non-visual tasks based on coordinate inputs. This research work combines the transformer architecture with the proximal policy optimization technique used popularly in reinforcement learning for stability and better policy updates while training, especially for continuous action spaces, which are used in this research work. Certain tasks in this paper are long horizon tasks that carry on for a longer duration and require extensive use of memory-based functionalities like storage of experiences and choosing appropriate actions based on recall. The transformer, which makes use of memory and self-attention mechanism in an encoder-decoder configuration proved to have better performance when compared to LSTM in terms of exploration and rewards achieved. Such memory based architectures can be used extensively in the field of cognitive robotics and reinforcement learning.

Keywords: convolutional neural networks, reinforcement learning, self-attention, transformers, unity

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Authors: Shiao-Wei Chu

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In order to enhance the ability of their graduates to compete in an increasingly globalized economy, the majority of universities in Taiwan require students to pass Freshman English in order to earn a bachelor's degree. However, many college students show low motivation in English class for several important reasons, including exam-oriented lessons, unengaging classroom activities, a lack of opportunities to use English in authentic contexts, and low levels of confidence in using English. Students’ lack of motivation in English classes is evidenced when students doze off, work on assignments from other classes, or use their phones to chat with others, play video games or watch online shows. Cooperative learning aims to address these problems by encouraging language learners to use the target language to share individual experiences, cooperatively complete tasks, and to build a supportive classroom learning community whereby students take responsibility for one another’s learning. This study includes approximately 50 student participants in a low-proficiency Freshman English class. Each week, participants will work together in groups of between 3 and 4 students to complete various in-class interactive tasks. The instructor will employ a reward system that incentivizes students to be responsible for their own as well as their group mates’ learning. The rewards will be based on points that team members earn through formal assessment scores as well as assessment of their participation in weekly in-class discussions. The instructor will record each team’s week-by-week improvement. Once a team meets or exceeds its own earlier performance, the team’s members will each receive a reward from the instructor. This cooperative learning approach aims to stimulate EFL freshmen’s learning motivation by creating a supportive, low-pressure learning environment that is meant to build learners’ self-confidence. Students will practice all four language skills; however, the present study focuses primarily on the learners’ reading comprehension. Data sources include in-class discussion notes, instructor field notes, one-on-one interviews, students’ midterm and final written reflections, and reading scores. Triangulation is used to determine themes and concerns, and an instructor-colleague analyzes the qualitative data to build interrater reliability. Findings are presented through the researcher’s detailed description. The instructor-researcher has developed this approach in the classroom over several terms, and its apparent success at motivating students inspires this research. The aims of this study are twofold: first, to examine the possible benefits of this cooperative approach in terms of students’ learning outcomes; and second, to help other educators to adapt a more cooperative approach to their classrooms.

Keywords: freshman English, cooperative language learning, EFL learners, learning motivation, zone of proximal development

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Authors: Bilel Chalghaf, Mathieu Varin

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Forest characterization in Quebec, Canada, is usually assessed based on photo-interpretation at the stand level. For species identification, this often results in a lack of precision. Very high spatial resolution imagery, such as DigitalGlobe, and Light Detection and Ranging (LiDAR), have the potential to overcome the limitations of aerial imagery. To date, few studies have used that data to map a large number of species at the tree level using machine learning techniques. The main objective of this study is to map 11 individual high tree species ( > 17m) at the tree level using an object-based approach in the broadleaf forest of Kenauk Nature, Quebec. For the individual tree crown segmentation, three canopy-height models (CHMs) from LiDAR data were assessed: 1) the original, 2) a filtered, and 3) a corrected model. The corrected CHM gave the best accuracy and was then coupled with imagery to refine tree species crown identification. When compared with photo-interpretation, 90% of the objects represented a single species. For modeling, 313 variables were derived from 16-band WorldView-3 imagery and LiDAR data, using radiance, reflectance, pixel, and object-based calculation techniques. Variable selection procedures were employed to reduce their number from 313 to 16, using only 11 bands to aid reproducibility. For classification, a global approach using all 11 species was compared to a semi-hierarchical hybrid classification approach at two levels: (1) tree type (broadleaf/conifer) and (2) individual broadleaf (five) and conifer (six) species. Five different model techniques were used: (1) support vector machine (SVM), (2) classification and regression tree (CART), (3) random forest (RF), (4) k-nearest neighbors (k-NN), and (5) linear discriminant analysis (LDA). Each model was tuned separately for all approaches and levels. For the global approach, the best model was the SVM using eight variables (overall accuracy (OA): 80%, Kappa: 0.77). With the semi-hierarchical hybrid approach, at the tree type level, the best model was the k-NN using six variables (OA: 100% and Kappa: 1.00). At the level of identifying broadleaf and conifer species, the best model was the SVM, with OA of 80% and 97% and Kappa values of 0.74 and 0.97, respectively, using seven variables for both models. This paper demonstrates that a hybrid classification approach gives better results and that using 16-band WorldView-3 with LiDAR data leads to more precise predictions for tree segmentation and classification, especially when the number of tree species is large.

Keywords: tree species, object-based, classification, multispectral, machine learning, WorldView-3, LiDAR

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Authors: Binay Pattanayak

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More than 9 out of every 10 children in Jharkhand struggle to understand the texts and teachers in public schools. The medium of learning in the schools is Hindi, which is very different in structure and vocabulary than those in children’s home languages. Hence around 3 out of 10 children enrolled in early grades drop out in these schools. The state realized the cause of children’s high dropout in 2013-14 when the M-TALL, the language research shared the findings of a state-wide socio-linguistic study. The study findings suggested that there was a great need for initiating a mother-tongue based multilingual education (MTB-MLE) programme for the state in early grades starting from pre-school level. Accordingly, M-TALL in partnership with department of education designed two learning packages: Bhasha Puliya pre-school education programme for 3-6-year-old children for their school readiness with bilingual picture dictionaries in 9 tribal and regional languages. This was followed by a plan for MTB-MLE programme for early primary grades. For this textbooks in five tribal and two regional languages were developed under the guidance of the author. These books were printed and circulated in the 1000 schools of the state for each child. Teachers and community members were trained for facilitating culturally sensitive mother-tongue based learning activities in and around the schools. The mother-tongue based approach of learning has worked very effectively in enabling them to acquire the basic literacy and numeracy skills in own mother-tongues. Using this basic early grade reading skills, these children are able to learn Hindi and English systematically. Community resource groups were constituted in each school for promoting storytelling, singing, painting, dancing, acting, riddles, humor, sanitation, health, nutrition, protection, etc. and were trained. School academic calendar was designed in each school to enable the community resource persons to visit the school as per the learning plan to assist children and teacher in facilitating rich cultural activities in mother-tongue. This enables children to take part in plethora of learning activities and acquire desired knowledge, skills and interest in mother-tongues. Also in this process, it is attempted to promote 21st Century learning skills by enabling children to apply their new knowledge and skills to look at their local issues and address those in a collective manner through team work, innovations and leadership.

Keywords: community resource groups, learning, MTB-MLE, multilingual, socio-linguistic survey

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Authors: Alanoud Moraya Aldalan, Abdulaziz Almaleh

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A crucial component of maintaining a customer-oriented business as in the telecom industry is understanding the reasons and factors that lead to customer churn. Competition between telecom companies has greatly increased in recent years. It has become more important to understand customers’ needs in this strong market of telecom industries, especially for those who are looking to turn over their service providers. So, predictive churn is now a mandatory requirement for retaining those customers. Machine learning can be utilized to accomplish this. Churn Prediction has become a very important topic in terms of machine learning classification in the telecommunications industry. Understanding the factors of customer churn and how they behave is very important to building an effective churn prediction model. This paper aims to predict churn and identify factors of customers’ churn based on their past service usage history. Aiming at this objective, the study makes use of feature selection, normalization, and feature engineering. Then, this study compared the performance of four different machine learning algorithms on the Orange dataset: Logistic Regression, Random Forest, Decision Tree, and Gradient Boosting. Evaluation of the performance was conducted by using the F1 score and ROC-AUC. Comparing the results of this study with existing models has proven to produce better results. The results showed the Gradients Boosting with feature selection technique outperformed in this study by achieving a 99% F1-score and 99% AUC, and all other experiments achieved good results as well.

Keywords: machine learning, gradient boosting, logistic regression, churn, random forest, decision tree, ROC, AUC, F1-score

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Authors: Jiwan Kumar, Pooja, Sandeep Negi, Anjum Rouf, Amit Kumar, Naveen Lakra

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In modern times where, health issues are increasing day by day, breast cancer is also one of them, which is very crucial and really important to find in the early stages. Doctors can use this model in order to tell their patients whether a cancer is not harmful (benign) or harmful (malignant). We have used the knowledge of machine learning in order to produce the model. we have used algorithms like Logistic Regression, Random forest, support Vector Classifier, Bayesian Network and Radial Basis Function. We tried to use the data of crucial parts and show them the results in pictures in order to make it easier for doctors. By doing this, we're making ML better at finding breast cancer, which can lead to saving more lives and better health care.

Keywords: Bayesian network, radial basis function, ensemble learning, understandable, data making better, random forest, logistic regression, breast cancer

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Authors: H. Weigelt-Marom

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Over the years and up to the arousal of the COVID-19 pandemic, deaf or hard of hearing students studying in higher education institutions, participated lectures on campus using hearing aids and strategies adapted for frontal learning in a classroom. Usually, these aids were well known to them from their earlier study experience in school. However, the transition to online lessons, due to the latest pandemic, led deaf or hard of hearing students to study outside of their physical, well known learning environment. The change of learning environment and structure rose new challenges for these students. The present study examined the learning experience, limitations, challenges and benefits regarding learning online with lecture and classmates via the “Zoom” video conference program, among deaf or hard of hearing students in academia setting. In addition, emotional and social aspects related to learning in general versus the “Zoom” were examined. The study included 18 students diagnosed as deaf or hard of hearing, studying in various higher education institutions in Israel. All students had experienced lessons on the “Zoom”. Following allocation of the group study by the deaf and hard of hearing non-profit organization “Ma’agalei Shema”, and receiving the participants inform of consent, students were requested to answer a google form questioner and participate in an interview. The questioner included background information (e.g., age, year of studying, faculty etc.), level of computer literacy, and level of hearing and forms of communication (e.g., lip reading, sign language etc.). The interviews included a one on one, semi-structured, in-depth interview, conducted by the main researcher of the study (interview duration: up to 60 minutes). The interviews were held on “ZOOM” using specific adaptations for each interviewee: clear face screen of the interviewer for lip and face reading, and/ or professional sign language or live text transcript of the conversation. Additionally, interviewees used their audio devices if needed. Questions regarded: learning experience, difficulties and advantages studying using “Zoom”, learning in a classroom versus on “Zoom”, and questions concerning emotional and social aspects related to learning. Thematic analysis of the interviews revealed severe difficulties regarding the ability of deaf or hard of hearing students to comprehend during ”Zoom“ lessons without adoptive aids. For example, interviewees indicated difficulties understanding “Zoom” lessons due to their inability to use hearing devices commonly used by them in the classroom (e.g., FM systems). 80% indicated that they could not comprehend “Zoom” lessons since they could not see the lectures face, either because lectures did not agree to open their cameras or, either because they did not keep a straight forward clear face appearance while teaching. However, not all descriptions regarded learning via the “zoom” were negative. For example, 20% reported the recording of “Zoom” lessons as a main advantage. Enabling then to repeatedly watch the lessons at their own pace, mostly assisted by friends and family to translate the audio output into an accessible input. These finding and others regarding the learning experience of the group study on the “Zoom”, as well as their recommendation to enable deaf or hard of hearing students to study inclusively online, will be presented at the conference.

Keywords: deaf or hard of hearing, learning experience, Zoom, qualitative research

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Authors: Evmorfia Koukia, Polyxeni Mangoulia

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Workshops tend to be a vivid and productive way as an in vivo teaching method. Due to the pandemic, COVID-19 university courses were conducted through the internet. Method It was tried for the first time to integrate online art therapy workshops in a core course named “Special Themes of Mental Health Nursing” in a MSc Program in Mental Health. The duration of the course is 3-hours per week for 11 weeks in a single semester. The course has a main instructor, a professor of psychiatric nursing experienced in arts therapies workshops and visiting art therapists. All art therapists were given a certain topic to cover. Students were encouraged to keep a logbook that was evaluated at the end of the semester and was submitted as a part of the examination process of the course. An interview of 10 minutes was conducted with each student at the end of the course from an independent investigator (an assistant professor) Participants The students (sample) of the program were: nurses, psychologists, and social workers Results: All students who participated in the courses found that the learning process was vivid, encouraging participation and self-motivation, and there were no main differences from in vivo learning. The students identified their personal needs, and they felt a personal connection with the learning experience. The result of the personalized learning was that students discovered their strengths and weaknesses and developed skills like critical thinking. All students admitted that the workshops were the optimal way for them to comprehend the courses’ content, their capability to become therapists, as well as their obstacles and weaknesses while working with patients in mental health. Conclusion: There were no important differences between the views of students in online and in vivo teaching method of the workshops. The result has shown that workshops in mental health can contribute equally in the learning experience.

Keywords: mental health, workshops, students, nursing

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Authors: Zhou Yang, Heli Sun, Jianbin Huang, Jizhong Zhao, Shaojie Qiao

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Traffic prediction is essential in a multitude of ways in modern urban life. The researchers of earlier work in this domain carry out the investigation chiefly with two major focuses: (1) the accurate forecast of future values in multiple time series and (2) knowledge extraction from spatial-temporal correlations. However, two key considerations for traffic prediction are often missed: the completeness of raw data and the full context of the prediction timestamp. Concentrating on the two drawbacks of earlier work, we devise an approach that can address these issues in a two-phase framework. First, we utilize the raw trajectories to a greater extent through building a VLA table and data compression. We obtain the intra-trajectory features with graph-based encoding and the intertrajectory ones with a grid-based model and the technique of back projection that restore their surrounding high-resolution spatial-temporal environment. To the best of our knowledge, we are the first to study direct feature extraction from raw trajectories for traffic prediction and attempt the use of raw data with the least degree of reduction. In the prediction phase, we provide a broader context for the prediction timestamp by taking into account the information that are around it in the training dataset. Extensive experiments on several well-known datasets have verified the effectiveness of our solution that combines the strength of raw trajectory data and prediction context. In terms of performance, our approach surpasses several state-of-the-art methods for traffic prediction.

Keywords: traffic prediction, raw data utilization, context building, data reduction

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Authors: Taku Numao, Kazu Amimoto, Tomoko Shimada, Kyohei Ichikawa

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Background: Unilateral spatial neglect (USN) is a common syndrome following damage to one hemisphere of the brain (usually the right side), in which a patient fails to report or respond to stimulation from the contralesional side. These symptoms are not due to primary sensory or motor deficits, but instead, reflect an inability to process input from that side of their environment. Prism adaptation (PA) is a therapeutic treatment for USN, wherein a patient’s visual field is artificially shifted laterally, resulting in a sensory-motor adaptation. However, patients with USN also tend to perceive a left-leaning subjective vertical in the frontal plane. The traditional PA cannot be used to correct a tilt in the subjective vertical, because a prism can only polarize, not twist, the surroundings. However, this can be accomplished using a head mounted display (HMD) and a web-camera. Therefore, this study investigated whether an HMD system could be used to correct the spatial perception of USN patients in the frontal as well as the horizontal plane. We recruited healthy subjects in order to collect data for the refinement of USN patient therapy. Methods: Eight healthy subjects sat on a chair wearing a HMD (Oculus rift DK2), with a web-camera (Ovrvision) displaying a 10 degree leftward rotation and a 10 degree counter-clockwise rotation along the frontal plane. Subjects attempted to point a finger at one of four targets, assigned randomly, a total of 48 times. Before and after the intervention, each subject’s body-centre judgment (BCJ) was tested by asking them to point a finger at a touch panel straight in front of their xiphisternum, 10 times sight unseen. Results: Intervention caused the location pointed to during the BCJ to shift 35 ± 17 mm (Ave ± SD) leftward in the horizontal plane, and 46 ± 29 mm downward in the frontal plane. The results in both planes were significant by paired-t-test (p<.01). Conclusions: The results in the horizontal plane are consistent with those observed following PA. Furthermore, the HMD and web-camera were able to elicit 3D effects, including in both the horizontal and frontal planes. Future work will focus on applying this method to patients with and without USN, and investigating whether subject posture is also affected by the HMD system.

Keywords: head mounted display, posture, prism adaptation, unilateral spatial neglect

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Authors: Yidan Shao

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With the advancement of the economy, technology promotes online teaching, and learning has become one of the common features in the educational field. Meanwhile, the dramatic expansion of the online environment provides opportunities for more learners, including second language learners. A greater command of vocabulary improves students’ learning capacity, and word acquisition and development play a critical role in learning. Furthermore, the Word Wall is an effective tool to improve students’ knowledge of words, which works for a wide range of age groups. Therefore, this study is going to use the Word Wall as an intervention to examine whether it can bring some memorization changes in an online English language class for a second language learner based on the word morphology method. The participant will take ten courses in the experiment as it plans. The findings show that the Word Wall activity plays a slight role in improving word memorizing, but it does affect instant memorization. If longer periods and more comprehensive designs of research can be applied, it is expected to have more value.

Keywords: second language acquisition, word morphology, word memorization, the Word Wall

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Authors: Lan Cheng, Harry Qin, Yang Wang

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Background: COVID-19 has induced the largest digital learning experiment in history. There is also emerging research evidence that students have paid a high cost of learning loss from virtual learning. University-wide survey results demonstrate that digital learning remains difficult for students who struggle with learning challenges, isolation, or a lack of resources. Large-scale efforts are therefore increasingly utilized for digital education. To better prepare students in higher education for this grand scientific and technological transformation, STEM education has been prioritized and promoted as a strategic imperative in the ongoing curriculum reform essential for unfinished learning needs and whole-person development. Building upon five key elements identified in the STEM education literature: Problem-based Learning, Community and Belonging, Technology Skills, Personalization of Learning, Connection to the External Community, this case study explores the potential of pedagogical innovation that integrates computational and experimental methodologies to support, enrich, and navigate STEM education. Objectives: The goal of this case study is to create a high-fidelity prototype design for STEM education with knowledge transfer technology that contains a Cooperative Multi-Agent System (CMAS), which has the objectives of (1) conduct assessment to reveal a virtual learning mechanism and establish strategies to facilitate scientific learning engagement, accessibility, and connection within and beyond university setting, (2) explore and validate an interactional co-creation approach embedded in project-based learning activities under the STEM learning context, which is being transformed by both digital technology and student behavior change,(3) formulate and implement the STEM-oriented campaign to guide learning network mapping, mitigate the loss of learning, enhance the learning experience, scale-up inclusive participation. Methods: This study applied a case study strategy and a methodology informed by Social Network Analysis Theory within a cross-disciplinary communication paradigm (students, peers, educators). Knowledge transfer technology is introduced to address learning challenges and to increase the efficiency of Reinforcement Learning (RL) algorithms. A co-creation learning framework was identified and investigated in a context-specific way with a learning analytic tool designed in this study. Findings: The result shows that (1) CMAS-empowered learning support reduced students’ confusion, difficulties, and gaps during problem-solving scenarios while increasing learner capacity empowerment, (2) The co-creation learning phenomenon have examined through the lens of the campaign and reveals that an interactive virtual learning environment fosters students to navigate scientific challenge independently and collaboratively, (3) The deliverables brought from the STEM educational campaign provide a methodological framework both within the context of the curriculum design and external community engagement application. Conclusion: This study brings a holistic and coherent pedagogy to cultivates students’ interest in STEM and develop them a knowledge base to integrate and apply knowledge across different STEM disciplines. Through the co-designing and cross-disciplinary educational content and campaign promotion, findings suggest factors to empower evidence-based learning practice while also piloting and tracking the impact of the scholastic value of co-creation under the dynamic learning environment. The data nested under the knowledge transfer technology situates learners’ scientific journey and could pave the way for theoretical advancement and broader scientific enervators within larger datasets, projects, and communities.

Keywords: co-creation, cross-disciplinary, knowledge transfer, STEM education, social network analysis

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Authors: Justin P. Pool, Haruyo Yoshida

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This research focuses on the effects of creating an English as a foreign language curriculum that combines online learning and classroom teaching in a complementary manner. Through pre- and post-test results, teacher observation, and learner reflection, it will be shown that learners can benefit from online programs focusing on receptive skills if combined with a communicative classroom environment that encourages learners to develop their productive skills. Much research has lamented the fact that many modern mobile assisted language learning apps do not take advantage of the affordances of modern technology by focusing only on receptive skills rather than inviting learners to interact with one another and develop communities of practice. This research takes into account the realities of the state of such apps and focuses on how to best create a curriculum that complements apps which focus on receptive skills. The research involved 15 adult learners working for a business in Japan simultaneously engaging in 1) a commercial online English language learning application that focused on reading, listening, grammar, and vocabulary and 2) a 15-week class focused on communicative language teaching, presentation skills, and mitigation of error aversion tendencies. Participants of the study experienced large gains on a standardized test, increased motivation and willingness to communicate, and asserted that they felt more confident regarding English communication. Moreover, learners continued to study independently at higher rates after the study than they had before the onset of the program. This paper will include the details of the program, reveal the improvement in test scores, share learner reflections, and critically view current evaluation models for mobile assisted language learning applications.

Keywords: adult learners, communicative language teaching, mobile assisted language learning, motivation

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Authors: Maslin Masrom, Nik Hasnaa Nik Mahmood, Wan Normeza Wan Zakaria, Azizul Azizan, Norshaliza Kamaruddin

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Traditionally, in science education, the teacher provides facts and the students learn them. It is outmoded for today’s students to equip them with real-life situations, mainly because knowledge and life skills are acquired passively from the instructors. Inquiry-Based Science Education (IBSE) is an approach that allows students to experiment, ask questions, and develop responses based on reasoning. It has provided students and teachers with opportunities to actively engage in collaborative learning via inquiry. This approach inspires the students to become active thinkers, research for solutions, and gain life-long experience and self-confidence. Therefore, the research aims to investigate how the primary-school teacher supports students or pupils through an inquiry-based science education approach for computer science, specifically coding skills. The results are presented and described.

Keywords: inquiry-based science education, student-centered learning, computer science, primary school

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Authors: Lin Xie, Yang Wang

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An extensive body of research studies suggest that students, teachers, and supervisors can enhance the likelihood of reaching their goals by improving their communication skills. It is highly important to learn how and when to provide different kinds of feedback, e.g. anticipatory, corrective and positive) will gain better result and higher morale. The purpose of this mixed methods research is twofold: 1) To find out what factors affect effective communication among different stakeholders and how these factors affect student learning 2) What are the good practices for improving communication among different stakeholders and improve student achievement. This presentation first begins with an introduction to the recent research on Marshall’s Nonviolent Communication Techniques (NVC), including four important components: observations, feelings, needs, requests. These techniques can be effectively applied at all levels of communication. To develop an in-depth understanding of the relationship among different techniques within, this research collected, compared, and combined qualitative and quantitative data to better improve communication and support student learning.

Keywords: communication, education, language learning, goal achievement, academic success

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Authors: Frazer McDonald Ng'oma

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Online Learning in Malawi has only immersed in recent years due to the need to increase access to higher education, the need to accommodate upgrading students who wish to study on a part time basis while still continuing their work, and the COVID-19 pandemic, which forced the closure of schools resulting in academic institutions seeking alternative modes of teaching and Learning to ensure continued teaching and Learning. Realizing that this mode of Learning is becoming a norm, institutions of higher Learning have started pioneering online post-graduate programs from which they can draw lessons before fully implementing it in undergraduate programs. Online learning pedagogy has not been fully grasped and institutions are still experimenting with this mode of Learning until online Learning guiding policies are created and its standards improved. This single case descriptive qualitative research study sought to investigate online postgraduate students’ perceptions and experiences with Student to student interactive pedagogy in their programs. The results of the study are to inform institutions and educators how to structure their programs to ensure that their students get the full satisfaction. 25 Masters students in 3 recently introduced online programs at Kamuzu University of Health Sciences (KUHES), were engaged; 19 were interviewed and 6 responded to questionnaires. The findings from the students were presented and categorized in themes and subthemes that emerged from the qualitative data that was collected and analysed following Colaizzi’s framework for data analysis that resulted in themes formulation. Findings revealed that Student to student interactions occurred in the online programme during live sessions, on class Whatsapp group, in discussion boards as well as on emails. Majority of the students (n=18) felt the level of students’ interaction initiated by the institution was too much, referring to mandatory interactions activities like commenting in discussion boards and attending to live sessons. Some participants (n=7) were satisfied with the level of interaction and also pointed out that they would be fine with more program-initiated student–to–student interactions. These participants attributed having been out of school for some time as a reason for needing peer interactions citing that it is already difficult to get back to a traditional on-campus school after some time, let alone an online class where there is no physical interaction with other students. In general, majority of the participants (n=18) did not value Student to student interaction in online Learning. The students suggested that having intensive student-to-student interaction in postgraduate online studies does not need to be a high priority for the institution and they further recommended that if a lecturer decides to incorporate student-to-student activities into a class, they should be optional.

Keywords: online learning, interactions, student interactions, post graduate students

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Authors: Ulil Afidah, Muhamad Fathan Mubin, Firdha Aulia

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Code riverbanks Yogyakarta is a settlement area with middle to lower social classes. Socio-economic situation is affecting the behavior of society. This research aimed to find and explain the implementation and the assessment of character education which were done in elementary schools in Code riverside, Yogyakarta region of Indonesia. This research is a qualitative research which the subjects were the kids of Code riverbanks, Yogyakarta. The data were collected through interviews and document studies and analyzed qualitatively using the technique of interactive analysis model of Miles and Huberman. The results show that: (1) The learning process of character education was done by integrating all aspects such as democratic and interactive learning session also introducing role model to the students. 2) The assessment of character education was done by teacher based on teaching and learning process and an activity in outside the classroom that was the criterion on three aspects: Cognitive, affective and psychomotor.

Keywords: character, Code riverbanks, education, Yogyakarta

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Authors: Sagheer Ahmad

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Teaching is a sacred profession whereby students are developed in their mental abilities to cope with the challenges of the remote world. Thinkers have developed plenty of interesting ways to make the learning process quick and absorbing for the students. However, third world countries are still lacking these remote facilities in the institutions, and therefore, teaching is totally dependent upon the skills of the teachers. Skillful teachers use self-devised and stimulating ideas to grab the attention of their students. Most of the time their ideas are based on local grounds with which the students are already familiar. This self-explanatory characteristic is the base of several local ideologies to disseminate scientific knowledge to new generations. Biology is such a subject which largely bases upon hypotheses, and teaching it in an interesting way is needful to create a friendly relationship between teacher and student, and to make a fantastic learning environment. Taxonomic classification if presented as it is, may not be attractive for the secondary school students who just start learning about biology at elementary levels. Presenting this hierarchy by exemplifying Kingdom, Phylum, Class, Order, family, genus and Species as comparatives of our division into continents, countries, cities, towns, villages, homes and finally individuals could be an attention-grabbing approach to make this concept get into bones of students. Similarly, many other interesting approaches have also been adopted to teach students in a fascinating way so that learning science subjects may not be boring for them. Discussing these appealing ways of teaching students can be a valuable stimulus to refine teaching methodologies about science, thereby promoting the concept of friendly learning.

Keywords: biology, innovative approaches, taxonomic classification, teaching

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Authors: Josué Alfredo Tomas Machaca Fajardo, Jhon Elvis Chahua Janampa, Pedro Rau Lavado

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A flood vulnerability index was developed for the Piura River watershed in northern Peru using Principal Component Analysis (PCA) to assess flood risk. The official methodology to assess risk from natural hazards in Peru was introduced in 1980 and proved effective for aiding complex decision-making. This method relies in part on decision-makers defining subjective correlations between variables to identify high-risk areas. While risk identification and ensuing response activities benefit from a qualitative understanding of influences, this method does not take advantage of the advent of national and international data collection efforts, which can supplement our understanding of risk. Furthermore, this method does not take advantage of broadly applied statistical methods such as PCA, which highlight central indicators of vulnerability. Nowadays, information processing is much faster and allows for more objective decision-making tools, such as PCA. The approach presented here develops a tool to improve the current flood risk assessment in the Peruvian basin. Hence, the spatial analysis of the census and other datasets provides a better understanding of the current land occupation and a basin-wide distribution of services and human populations, a necessary step toward ultimately reducing flood risk in Peru. PCA allows the simplification of a large number of variables into a few factors regarding social, economic, physical and environmental dimensions of vulnerability. There is a correlation between the location of people and the water availability mainly found in rivers. For this reason, a comprehensive vision of the population location around the river basin is necessary to establish flood prevention policies. The grouping of 5x5 km gridded areas allows the spatial analysis of flood risk rather than assessing political divisions of the territory. The index was applied to the Peruvian region of Piura, where several flood events occurred in recent past years, being one of the most affected regions during the ENSO events in Peru. The analysis evidenced inequalities for the access to basic services, such as water, electricity, internet and sewage, between rural and urban areas.

Keywords: assess risk, flood risk, indicators of vulnerability, principal component analysis

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