Search results for: Kolb Learning Styles Inventory

Authors: Gurmail Singh

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Effective supply chain is the main priority of every organization which is the outcome of strategic corporate investments with deliberate management action. Value-driven supply chain is defined through development, procurement and by configuring the appropriate resources, metrics and processes. However, responsiveness of the supply chain can be improved by proper coordination. So the Bullwhip effect (BWE) and Net stock amplification (NSAmp) values were anticipated and used for the control of inventory in organizations by both discrete wavelet transform-Artificial neural network (DWT-ANN) and Adaptive Network-based fuzzy inference system (ANFIS). This work presents a comparative methodology of forecasting for the customers demand which is non linear in nature for a multilevel supply chain structure using hybrid techniques such as Artificial intelligence techniques including Artificial neural networks (ANN) and Adaptive Network-based fuzzy inference system (ANFIS) and Discrete wavelet theory (DWT). The productiveness of these forecasting models are shown by computing the data from real world problems for Bullwhip effect and Net stock amplification. The results showed that these parameters were comparatively less in case of discrete wavelet transform-Artificial neural network (DWT-ANN) model and using Adaptive network-based fuzzy inference system (ANFIS).

Keywords: bullwhip effect, hybrid techniques, net stock amplification, supply chain flexibility

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Authors: Hongmei Chi

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The Blockchain has become a necessity for many different societal industries and ordinary lives including cryptocurrency technology, supply chain, health care, public safety, education, etc. Therefore, training our future blockchain developers to know blockchain programming vulnerability and I.T. students' cyber security is in high demand. In this work, we propose a framework including learning modules and hands-on labs to guide future I.T. professionals towards developing secure blockchain programming habits and mitigating source code vulnerabilities at the early stages of the software development lifecycle following the concept of Secure Software Development Life Cycle (SSDLC). In this research, our goal is to make blockchain programmers and I.T. students aware of the vulnerabilities of blockchains. In summary, we develop a framework that will (1) improve students' skills and awareness of blockchain source code vulnerabilities, detection tools, and mitigation techniques (2) integrate concepts of blockchain vulnerabilities for IT students, (3) improve future IT workers’ ability to master the concepts of blockchain attacks.

Keywords: software vulnerability detection, hands-on lab, static analysis tools, vulnerabilities, blockchain, active learning

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Authors: Bhekisisa Nyoni, Nomakhosi Ndiweni, Annatoria Chinyama

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The aim of this paper was to explore ways to enhance the quality of higher education with a bias towards engineering education in Zimbabwe universities. A search through relevant literature was conducted looking at both international and local scholars. It also involved reviewing the Dakar Framework for Action and Incheon Declaration and Framework for Action plans for education for sustainable development. Goals were set for 2030 as a standard for quality to be adopted by all countries in improving access as well as the quality of education from early childhood and through to adult learning. Despite the definition of quality being difficult to express due to diverse expectations from different stakeholders, the view of quality adopted is based on the World Education Forum’s propositions on quality education going beyond the classroom experience. It considers factors such as learning environment, governance and management, and teacher caliber. The study concludes by illustrating that the quality of engineering education in Zimbabwe has come a long way. It has made strides in increasing access and variety to education though at the expense of quality in its totality. To improve the quality of engineering education, programs have been introduced to promote the professionalism of lecturers, such as industrial secondment and professional development courses.

Keywords: engineering education, quality of education, professional development, industrial secondment

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Authors: Ahmed Mohammed Omer Alghamdi

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Since the COVID-19 pandemic started, a rapid, unexpected transition from face-to-face to virtual classroom (VC) teaching has involved several challenges and obstacles. However, there are also opportunities and thoughts that need to be examined and discussed. In addition, the entire world is witnessing that the teaching system and, more particularly, higher education institutes have been interrupted. To maintain the learning and teaching practices as usual, countries were forced to transition from traditional to virtual classes using various technology-based devices. In this regard, the Kingdom of Saudi Arabia (KSA) is no exception. Focusing on how the current situation has forced many higher education institutes to change to virtual classes may possibly provide a clear insight into adopted practices and implications. The main purpose of this study, therefore, was to investigate how both Saudi English as a foreign language (EFL) teachers and students perceived the implementation of virtual classes as a key factor for useful language teaching and learning process during the COVID-19 pandemic period at a Saudi university. The impetus for the research was, therefore, the need to find ways of identifying the deficiencies in this application and to suggest possible solutions that might rectify those deficiencies. This study seeks to answer the following overarching research question: “How do Saudi EFL instructors and students perceive the use of virtual classes during the COVID-19 pandemic period in their language teaching and learning context?” The following sub-questions are also used to guide the design of the study to answer the main research question: (1) To what extent are virtual classes important intra-pandemic from Saudi EFL instructors’ and students’ perspectives? (2) How effective are virtual classes for fostering English language students’ achievement? (3) What are the challenges and obstacles that instructors and students may face during the implementation of virtual teaching? A mixed method approach was employed in this study; the questionnaire data collection represented the quantitative method approach for this study, whereas the transcripts of recorded interviews represented the qualitative method approach. The participants included EFL teachers (N = 4) and male and female EFL students (N = 36). Based on the findings of this study, various aspects from teachers' and students’ perspectives were examined to determine the use of the virtual classroom applications in terms of fulfilling the students’ English language learning needs. The major findings of the study revealed that the virtual classroom applications during the current pandemic situation encountered three major challenges, among which the existence of the following essential aspects, namely lack of technology and an internet connection, having a large number of students in a virtual classroom and lack of students’ and teachers’ interactions during the virtual classroom applications. Finally, the findings indicated that although Saudi EFL students and teachers view the virtual classrooms in a positive light during the pandemic period, they reported that for long and post-pandemic period, they preferred the traditional face-to-face teaching procedure.

Keywords: virtual classes, English as a foreign language, COVID-19, Internet, pandemic

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Authors: Marzieh Imani

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Antoni Gaudi and Santiago Calatrava have reputation for designing bio-inspired creative and technical buildings. Even though they have followed different independent approaches towards design, the source of bio-inspiration seems to be common. Taking a closer look at their projects reveals that Calatrava has been influenced by Gaudi in terms of interpreting nature and applying natural principles into the design process. This research firstly discusses the dialogue between Biomimicry and architecture. This review also explores human/nature discourse during the history by focusing on how nature revealed itself to the fine arts. This is explained by introducing naturalism and romantic style in architecture as the outcome of designers’ inclination towards nature. Reviewing the literature, theoretical background and practical illustration of nature have been included. The most dominant practical aspects of imitating nature are form and function. Nature has been reflected in architectural science resulted in shaping different architectural styles such as organic, green, sustainable, bionic, and biomorphic. By defining a set of common aspects of Gaudi and Calatrava‘s design approach and by considering biomimetic design categories (organism, ecosystem, and behaviour as the main division and form, function, process, material, and construction as subdivisions), Gaudi’s and Calatrava’s project have been analysed. This analysis explores if their design approaches are equivalent or different. Based on this analysis, Gaudi’s architecture can be recognised as biomorphic while Calatrava’s projects are literally biomimetic. Referring to these architects, this review suggests a new set of principles by which a bio-inspired project can be determined either biomorphic or biomimetic.

Keywords: biomimicry, Calatrava, Gaudi, nature

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Authors: Horesh Reinman Netta

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Objectives: To examine the relationship between stressful life events and recurrent major depressive disorders Methods: Three groups of 50 subjects were assessed. One group had a recurrent major depressive disorder with melancholic features; the second group met the criteria for borderline personality disorder, and the third consisted of healthy controls. The Structured Clinical Interview for AXIS I DSM-IV Disorders sand the Structured Clinical Interview for AXIS II DSM-IV Disorders were used for diagnosis. The Israel Psychiatric Epidemiology Research Interview (IPERI) Life Event Scale and the Coddington Life Events Schedule (CLES) were used to measure life events which were confirmed with a confirmatory semi-structured interview. The Beck Depression Inventory and the Satisfaction from Life scales were also administered. Results : The total number of loss-related events in childhood and in the year preceding the first episode was significantly higher in the affective disorder group than in the two control groups. Total number of LE, uncontrolled and independent events were also more common in the depressed patients in the year preceding the first episode. No category of SLE was differentiated among any of the three groups during any period of time following the first depressive episode. Conclusions: SLE play an important role in the onset of affective disorders. There appear to be specific kinds of SLE occurring in childhood and in the year preceding a first episode that have particular significance. SLE may have a lesser role in the maintenance of this illness.

Keywords: modd dosorders, recurrent depression, stress, life events

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Authors: Rui Yin, Haojie Wang, Xun Li

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Recently, mainstream dense retrieval methods have obtained state-of-the-art results on some datasets and tasks. However, they require large amounts of training data, which is not available in most domains. The severe performance degradation of dense retrievers on new data domains has limited the use of dense retrieval methods to only a few domains with large training datasets. In this paper, we propose an unsupervised domain-adaptive approach based on query generation. First, a generative model is used to generate relevant queries for each passage in the target corpus, and then, the generated queries are used for mining negative passages. Finally, the query-passage pairs are labeled with a cross-encoder and used to train a domain-adapted dense retriever. We also explore contrastive learning as a method for training domain-adapted dense retrievers and show that it leads to strong performance in various retrieval settings. Experiments show that our approach is more robust than previous methods in target domains that require less unlabeled data.

Keywords: dense retrieval, query generation, contrastive learning, unsupervised training

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Authors: Güzi̇n Ti̇rkeş, Özge Teki̇n, Kerem Kurtuluş, Y. Yekta Yurtseven, Murat Baran

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A scanning electron microscope (SEM) is a type of electron microscope mainly used in nanoscience and nanotechnology areas. Automatic image recognition and classification are among the general areas of application concerning SEM. In line with these usages, the present paper proposes a deep learning algorithm that classifies SEM images into nine categories by means of an online application to simplify the process. The NFFA-EUROPE - 100% SEM data set, containing approximately 21,000 images, was used to train and test the algorithm at 80% and 20%, respectively. Validation was carried out using a separate data set obtained from the Middle East Technical University (METU) in Turkey. To increase the accuracy in the results, the Inception ResNet-V2 model was used in view of the Fine-Tuning approach. By using a confusion matrix, it was observed that the coated-surface category has a negative effect on the accuracy of the results since it contains other categories in the data set, thereby confusing the model when detecting category-specific patterns. For this reason, the coated-surface category was removed from the train data set, hence increasing accuracy by up to 96.5%.

Keywords: convolutional neural networks, deep learning, image classification, scanning electron microscope

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Authors: Maria Poulou

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The study investigated how teachers’ self-rated Emotional Intelligence (EI), competence in implementing Social and Emotional Learning (SEL) skills and teaching efficacy relate to teacher-student relationships and students’ emotional and behavioral difficulties. Participants were 98 elementary teachers from public schools in central Greece. They completed the Self-Rated Emotional Intelligence Scale (SREIS), the Teacher SEL Beliefs Scale, the Teachers’ Sense of Efficacy Scale (TSES), the Student-Teacher Relationships Scale-Short Form (STRS-SF) and the Strengths and Difficulties Questionnaire (SDQ) for 617 of their students, aged 6-11 years old. Structural equation modeling was used to examine an exploratory model of the variables. It was demonstrated that teachers’ emotional intelligence, SEL beliefs and teaching efficacy were significantly related to teacher-student relationships, but they were not related to students’ emotional and behavioral difficulties. Rather, teachers’ perceptions of teacher-students relationships were significantly related to these difficulties. These findings and their implications for research and practice are discussed.

Keywords: emotional intelligence, social and emotional learning, teacher-student relationships, teaching efficacy

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Authors: Ruwan Gunawardane

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

Keywords: English, competence, reading, curiosity

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Authors: Tumelo Jaquiline Ntsopi

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This study explored the academic writing challenges of first-year students who use English as an Additional Language (EAL) registered in the EAW101 module at an ODeL institution. Research shows that academic writing is a challenge for EAL teaching and learning contexts across the globe in higher education institutions (HEIs). Academic writing is an important aspect of academic literacy in any institution of higher learning, more so in an ODeL institution. This has probed research that shows that academic writing is and continues to pose challenges for EAL teaching and learning contexts in higher education institutions. This study stems from the researcher’s experience in teaching academic writing to first-year students in the EAW101 module. The motivation for this study emerged from the fact that EAW101 is a writing module that has a high number of students in the Department of English Studies with an average of between 50-80 percent pass rate. These statistics elaborate on the argument that most students registered in this module struggle with academic writing, and they need intervention to assist and support them in achieving competence in the module. This study is underpinned by Community of Inquiry (CoI) framework and Transactional distance theory. This study adopted a qualitative research methodology and utilised a case study approach as a research design. Furthermore, the study gathered data from first year students and the EAW101 module’s student support initiatives. To collect data, focus group discussions, structured open-ended evaluation questions, and an observation schedule were used to gather data. The study is vital towards exploring academic writing challenges that first-year students in EAW101 encounter so that lecturers in the module may consider re-evaluating their methods of teaching to improve EAL students’ academic writing skills. This study may help lecturers towards enhancing academic writing in a ODeL context by assisting first year students through using student support interventions.

Keywords: academic writing, academic writing challenge, ODeL, EAL

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Authors: Duygu Özdemir, Bilal Özçakır

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Usage of augmented reality in education helps students to make sense of the three-dimensional world of mathematics. In this study, it was aimed to develop activities about fractions for 5th-grade students by augmented reality and also aimed to assess these activities in terms of students’ understanding and views. Data obtained from 60 students in a private school in Marmaris, Turkey was obtained through classroom observations, students’ worksheets and semi-structured interviews during two weeks. Data analysis was conducted by using constant-comparative analysis which leads to meaningful categories of findings. Findings of this study indicated that usage of augmented reality is a facilitator to make concretize and provide real-life application for fractions. Moreover, students’ opinions about its usage were lead to categories as benefit for learning, enjoyment and creating awareness of usage of augmented reality in mathematics education. In general, this study could be a bridge to show the contributions of augmented reality applications to mathematics education and also highlights that augmented reality could be used with subjects like fractions rather than subjects only in geometry learning domain.

Keywords: augmented reality, mathematics, fractions, students

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Authors: Stephen Vera, Tabitha Black, Charalambos Cleanthous, Ryan Sain

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A gender comparison of USA commercial pilots’ demographics and views of CRM, social desirability and locus of control were surveyed. The Aviation safety locus of control (ASLOC) was used to measure external (ASLOC-E) or internal (ASLOC-I) aviation safety locus of control. The gender differences were explored using the ASLOC scores as a categorical variable. A differential comparison of crew resource management (CRM), based on the Federal Aviation Administration’s (FAA) guidelines was conducted. The results indicated that the proportion of female to male respondents matches the current ratio of USA commercial pilots. Moreover, there were no significant differences regarding overall education and the total number of communication classes one took. Regarding CRM issues, there were no significant differences on their views regarding the roles of the PIC, stress, time management, and managing a flight team. The females scored significantly lower on aeronautical decision making (ADM) and communications. There were no significant differences on either the Balanced Inventory of Desirable Responding (BIDR) impression management (IM) or self-deceptive enhancement (SDE). Although there were no overall significant differences on the ASLOC, the females did score higher on the internal subscale than did the males. An additional comparison of socially desirable responding indicates that all scores may be invalid, especially from the female respondents.

Keywords: social desirability, safety locus of control, crew resource management, commercial pilots

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Authors: Zunaira Zaman, David Bohannon

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This study explores the application of machine learning (ML) for detecting security vulnerabilities in source code. The research aims to assist organizations with large application portfolios and limited security testing capabilities in prioritizing security activities. ML-based approaches offer benefits such as increased confidence scores, false positives and negatives tuning, and automated feedback. The initial approach using natural language processing techniques to extract features achieved 86% accuracy during the training phase but suffered from overfitting and performed poorly on unseen datasets during testing. To address these issues, the study proposes using the abstract syntax tree (AST) for Java and C++ codebases to capture code semantics and structure and generate path-context representations for each function. The Code2Vec model architecture is used to learn distributed representations of source code snippets for training a machine-learning classifier for vulnerability prediction. The study evaluates the performance of the proposed methodology using two datasets and compares the results with existing approaches. The Devign dataset yielded 60% accuracy in predicting vulnerable code snippets and helped resist overfitting, while the Juliet Test Suite predicted specific vulnerabilities such as OS-Command Injection, Cryptographic, and Cross-Site Scripting vulnerabilities. The Code2Vec model achieved 75% accuracy and a 98% recall rate in predicting OS-Command Injection vulnerabilities. The study concludes that even partial AST representations of source code can be useful for vulnerability prediction. The approach has the potential for automated intelligent analysis of source code, including vulnerability prediction on unseen source code. State-of-the-art models using natural language processing techniques and CNN models with ensemble modelling techniques did not generalize well on unseen data and faced overfitting issues. However, predicting vulnerabilities in source code using machine learning poses challenges such as high dimensionality and complexity of source code, imbalanced datasets, and identifying specific types of vulnerabilities. Future work will address these challenges and expand the scope of the research.

Keywords: code embeddings, neural networks, natural language processing, OS command injection, software security, code properties

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Authors: Oseni Taiwo Amoo, Bloodless Dzwairo

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In this paper, we extend the versatility and usefulness of GIS as a methodology for any river basin hydrologic characteristics analysis (HCA). The Gurara River basin located in North-Central Nigeria is presented in this study. It is an on-going research using spatial Digital Elevation Model (DEM) and Arc-Hydro tools to take inventory of the basin characteristics in order to predict water abstraction quantification on streamflow regime. One of the main concerns of hydrological modelling is the quantification of runoff from rainstorm events. In practice, the soil conservation service curve (SCS) method and the Conventional procedure called rational technique are still generally used these traditional hydrological lumped models convert statistical properties of rainfall in river basin to observed runoff and hydrograph. However, the models give little or no information about spatially dispersed information on rainfall and basin physical characteristics. Therefore, this paper synthesizes morphometric parameters in generating runoff. The expected results of the basin characteristics such as size, area, shape, slope of the watershed and stream distribution network analysis could be useful in estimating streamflow discharge. Water resources managers and irrigation farmers could utilize the tool for determining net return from available scarce water resources, where past data records are sparse for the aspect of land and climate.

Keywords: hydrological characteristic, stream flow, runoff discharge, land and climate

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Authors: Sophia Ming Lee Wen, Chao-Ching Kuo, Yu-Line Hu, Yu-Lung Ho, Chih-Cheng Huang, Yi-Hwa Lee

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Teaching and learning should involve social issues by which effectiveness and humanity is due consideration as a guideline for sharing and co-creating knowledge. A qualitative method was used after a pioneer study to confirm pre-service teachers’ awareness of open knowledge. There are 17 in-service teacher candidates sampling from 181 schools in Taiwan. Two questions are to resolve: a) How did teachers change their educational ideas, in particular, their attitudes to meet the needs of knowledge sharing and co-creativity; and b) How did they acknowledge the necessity of working out an appropriate way between the educational efficiency and the nature of education for high performance management. This interview investigated teachers’ attitude of sharing and co-creating knowledge. The results show two facts in Taiwan: A) Individuals who must be able to express themselves will be capable of taking part in an open learning environment; and B) Teachers must lead the direction to inspire high performance and improve students’ capacity via knowledge sharing and co-creating knowledge, according to the student-centered philosophy. Collected data from interviewing showed that the teachers were well aware of changing their teaching methods and make some improvements to balance the educational efficiency and the nature of education. Almost all teachers acknowledge that ICT is helpful to motivate learning enthusiasm. Further, teaching integrated with ICT saves teachers’ time and energy on teaching preparation and promoting effectiveness. Teachers are willing to co-create knowledge with students, though using information is not easy due to the lack of operating skills of the website and ICT. Some teachers are against to co-create knowledge in the informational background since they hold that is not feasible for there being a knowledge gap between teachers and students. Technology would easily mislead teachers and students to the goal of instrumental rationality, which makes pedagogy dysfunctional and inhumane; however, any high quality of teaching should take a dialectical balance between effectiveness and humanity.

Keywords: critical thinking, dialectic between effectiveness and humanity, open knowledge, pedagogy

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Authors: Zena Tredinnick-Kirby, Anna Divinsky, Brendan Berthold, Nicole Cingolani

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Faculty members from The Pennsylvania State University, Zena Tredinnick-Kirby, Ph.D., and Anna Divinsky are at the forefront of an innovative educational approach to improve access in asynchronous online art courses. Their pioneering work weaves virtual reality (VR) technologies to construct a more equitable educational experience for students by transforming their learning and engagement. The significance of their study lies in the need to bridge the digital divide in online art courses, making them more inclusive and interactive for all distance learners. In an era where conventional classroom settings are no longer the sole means of instruction, Tredinnick-Kirby and Divinsky harness the power of instructional technologies to break down geographical barriers by incorporating an interactive VR experience that facilitates community building within an online environment transcending physical constraints. The methodology adopted by Tredinnick-Kirby, and Divinsky is centered around integrating 3D virtual spaces into their art courses. Spatial.io, a virtual world platform, enables students to develop digital avatars and engage in virtual art museums through a free browser-based program or an Oculus headset, where they can interact with other visitors and critique each other’s artwork. The goal is not only to provide students with an engaging and immersive learning experience but also to nourish them with a more profound understanding of the language of art criticism and technology. Furthermore, the study aims to cultivate critical thinking skills among students and foster a collaborative spirit. By leveraging cutting-edge VR technology, students are encouraged to explore the possibilities of their field, experimenting with innovative tools and techniques. This approach not only enriches their learning experience but also prepares them for a dynamic and ever-evolving art landscape in technology and education. One of the fundamental objectives of Tredinnick-Kirby and Divinsky is to remodel how feedback is derived through peer-to-peer art critique. Through the inclusion of 3D virtual spaces into the curriculum, students now have the opportunity to install their final artwork in a virtual gallery space and incorporate peer feedback, enabling students to exhibit their work opening the doors to a collaborative and interactive process. Students can provide constructive suggestions, engage in discussions, and integrate peer commentary into developing their ideas and praxis. This approach not only accelerates the learning process but also promotes a sense of community and growth. In summary, the study conducted by the Penn State faculty members Zena Tredinnick-Kirby, and Anna Divinsky represents innovative use of technology in their courses. By incorporating 3D virtual spaces, they are enriching the learners' experience. Through this inventive pedagogical technique, they nurture critical thinking, collaboration, and the practical application of cutting-edge technology in art. This research holds great promise for the future of online art education, transforming it into a dynamic, inclusive, and interactive experience that transcends the confines of distance learning.

Keywords: Art, community building, distance learning, virtual reality

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Authors: Khadem Hichem

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With the new technology challenges, dynamics and challenges of the contemporary world, most teachers are struggling to maintain effective and successful teaching /learning environment for learners. Teachers as a key to the success of reforms in the educational setting, they must improve their competencies to teach effectively. Many researchers emphasis on the ongoing professional development of the teacher by enhancing their experiences and encouraging their responsibility for learning, and thus promoting self-reliance, collaboration, and reflection. In short, teachers are considered as learners and they need to learn together. The educational system must support, both conceptually and financially, the teachers’ development as lifelong learners Teachers need opportunities to grow in language proficiency and in knowledge. Changing nature of language and culture in the world, all teachers must have opportunities to update their knowledge and practices. Many researchers in the field of foreign or additional languages indicate that teachers keep side by side of effective instructional practices and they need special support with the challenging task of developing and administering proficiency tests to their students. For significant change to occur, each individual teacher’s needs must be addressed. The teacher must be involved experientially in the process of development, since, by itself, knowledge of how to change does not mean change will be initiated. For improvement to occur, new skills have to be guided, practiced, and reflected upon in collaboration with colleagues. Clearly, teachers are at different places developmentally; therefore, allowances for various entry levels and individual differences need to be built into the professional development structure. Objectives must be meaningful to the participant and teacher improvement must be stated terms of student knowledge, student performance, and motivation. The most successful professional development process acknowledges the student-centered nature of good teaching. This paper highlights the importance of teacher professional development process and institutional supports as way to enhance good teaching and learning environment.

Keywords: teacher professional development, teacher competencies, institutional support, teacher education

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Authors: Olusegun Adeleke Adenuga

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The study examined effect of fishbone creative thinking strategy on problem-solving skills of public teachers in Ogun state, Nigeria. A 2x2x2 factorial design was employed for the study which consisted of 80 participants made up of 40 male and 40 female public teachers randomly selected among public teaching personnel from the two local government area headquarters (Ijebu-ode and Ijebu-Igbo) within Ogun East Senatorial District. Each treatment group received 45minutes instructions and training per week for 8weeks. Data was collected from participants with the use of standardized instrument tagged ‘Problem Solving Inventory’ (PSI) developed by the researchers prior to the training to form a pre-test and immediately after eight weeks of training to form a post-test. One hypothesis was tested; the data obtained was analyzed using Analysis of Covariance (ANCOVA) tested at significance level of 0.05. The result of the data analysis shows that there was a significant effect of the fishbone creative thinking technique on the participants (F (2,99) = 12.410; p <.05). Based on the findings, it is therefore recommended that the report of this study be used to effect organizational change and development of teaching service in Nigeria through teachers’ retraining and capacity building.

Keywords: fishbone, creative thinking strategy, and problem-solving skills, public teachers

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Authors: Meifang Chen

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Background: As China increased its engagement in global health affairs and research, global Health (GH) emerged as a new discipline in China after 2010. Duke Kunshan University (DKU), as a member of the Chinese Consortium of Universities for Global Health, is the first university that experiments “Western-style” liberal arts and sciences (LAS) education pedagogy in GH undergraduate and postgraduate programs in China since 2014. The COVID-19 pandemic has brought significant disruption to education across the world. At the peak of the pandemic, 45 countries in the Europe and Central Asia regions closed their schools, affecting 185 million students. DKU, as many other universities and schools, was unprepared for this sudden abruptness and were forced to build emergency remote learning systems almost immediately. This qualitative study aims to gain a deeper understanding of 1) how Chinese students and parents embrace GH training in the liberal arts and sciences education context, and 2) how the COVID pandemic influences the students’ learning experience as well as affects students and parents’ perceptions of GH-related study and career development in China. Methods: students and parents at DKU were invited and recruited for open-ended, semi-structured interviews during Sept 2021-Mar 2022. Open coding procedures and thematic content analysis were conducted using Nvivo 12 software. Results: A total of 18 students and 36 parents were interviewed. Both students and parents were fond of delivering GH education using the liberal arts and sciences pedagogy. Strengths of LAS included focusing on whole person development, allowing personal enrichment, tailoring curriculum to individual’s interest, providing well-rounded knowledge through interdisciplinary learning, and increasing self-study capacity and adaptability. Limitations of LAS included less time to dive deep into disciplines. There was a significant improvement in independence, creativity, problem solving, and team coordinating capabilities among the students. The impact of the COVID pandemic on GH learning experience included less domestic and abroad fieldwork opportunities, less in-person interactions (especially with foreign students and faculty), less timely support, less lab experience, and coordination challenges due to time-zone difference. The COVID pandemic increased the public’s awareness of the importance of GH and acceptance of GH as a career path. More job and postgraduate program opportunities were expected in near future. However, some parents expressed concerns about GH-related employment opportunities in China. Conclusion: The application of the liberal arts and science education pedagogy in GH training were well-received by the Chinese students and parents. Although global pandemic like COVID disrupted GH learning in many ways, most Chinese students and parents held optimistic attitudes toward GH study and career development.

Keywords: COVID, global health, liberal arts and sciences pedagogy, China

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Authors: Joelle Thng, Li Fang

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

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

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Authors: Yixiu Liu, Yunzhou Zhang, Jianning Chi, Hao Chu, Rui Zheng, Libo Sun, Guanghao Chen, Fangtong Zhou

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In the last few years, large-scale person re-identification has attracted a lot of attention from video surveillance since it has a potential application prospect in public safety management. However, it is still a challenging job considering the variation in human pose, the changing illumination conditions and the lack of paired samples. Although the accuracy has been significantly improved, the data dependence of the sample training is serious. To tackle this problem, a new strategy is proposed based on bag of visual words (BoVW) model of designing the feature representation which has been widely used in the field of image retrieval. The local features are extracted, and more discriminative feature representation is obtained by cross-view dictionary learning (CDL), then the assignment map is obtained through k-means clustering. Finally, the BoVW histograms are formed which encodes the images with the statistics of the feature classes in the assignment map. Experiments conducted on the CUHK03, Market1501 and MARS datasets show that the proposed method performs favorably against existing approaches.

Keywords: bag of visual words, cross-view dictionary learning, person re-identification, reranking

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Authors: Bikis Muhammed, Sehra Sedigh Sarvestani, Ali R. Hurson, Lasanthi Gamage

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Vehicular traffic events have overly complex spatial correlations and temporal interdependencies and are also influenced by environmental events such as weather conditions. To capture these spatial and temporal interdependencies and make more realistic vehicular traffic predictions, graph neural networks (GNN) based traffic prediction models have been extensively utilized due to their capability of capturing non-Euclidean spatial correlation very effectively. However, most of the already existing GNN-based traffic prediction models have some limitations during learning complex and dynamic spatial and temporal patterns due to the following missing factors. First, most GNN-based traffic prediction models have used static distance or sometimes haversine distance mechanisms between spatially separated traffic observations to estimate spatial correlation. Secondly, most GNN-based traffic prediction models have not incorporated environmental events that have a major impact on the normal traffic states. Finally, most of the GNN-based models did not use an attention mechanism to focus on only important traffic observations. The objective of this paper is to study and make real-time vehicular traffic predictions while incorporating the effect of weather conditions. To fill the previously mentioned gaps, our prediction model uses a real-time driving distance between sensors to build a distance matrix or spatial adjacency matrix and capture spatial correlation. In addition, our prediction model considers the effect of six types of weather conditions and has an attention mechanism in both spatial and temporal data aggregation. Our prediction model efficiently captures the spatial and temporal correlation between traffic events, and it relies on the graph attention network (GAT) and Bidirectional bidirectional long short-term memory (Bi-LSTM) plus attention layers and is called GAT-BILSTMA.

Keywords: deep learning, real time prediction, GAT, Bi-LSTM, attention

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Authors: J. K. Adedeji, M. O. Oyekanmi

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This paper has critically examined the use of Machine Learning procedures in curbing unauthorized access into valuable areas of an organization. The use of passwords, pin codes, user’s identification in recent times has been partially successful in curbing crimes involving identities, hence the need for the design of a system which incorporates biometric characteristics such as DNA and pattern recognition of variations in facial expressions. The facial model used is the OpenCV library which is based on the use of certain physiological features, the Raspberry Pi 3 module is used to compile the OpenCV library, which extracts and stores the detected faces into the datasets directory through the use of camera. The model is trained with 50 epoch run in the database and recognized by the Local Binary Pattern Histogram (LBPH) recognizer contained in the OpenCV. The training algorithm used by the neural network is back propagation coded using python algorithmic language with 200 epoch runs to identify specific resemblance in the exclusive OR (XOR) output neurons. The research however confirmed that physiological parameters are better effective measures to curb crimes relating to identities.

Keywords: biometric characters, facial recognition, neural network, OpenCV

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Authors: Sheila S. Silang

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This research seeks to make an impact analysis on multiple intelligence as the basis for differentiated classroom instruction in TLE. It will also address the felt need of how TLE subject could be taught effectively exhausting all the possible means.This study seek the effect of giving different instruction according to the ability of the students in the following objectives: 1. student’s technological skills enhancement, 2. learning potential improvements 3. having better linkage between school and community in a need for soliciting different learning devices and materials for the learner’s academic progress. General Luna, Quezon is composed of twenty seven barangays. There are only two public high schools. We are aware that K-12 curriculum is focused on providing sufficient time for mastery of concepts and skills, develop lifelong learners, and prepare graduates for tertiary education, middle-level skills development, employment, and entrepreneurship. The challenge is with TLE offerring a vast area of specializations, how would Multiple Intelligence play its vital role as basis in classroom instruction in acquiring the requirement of the said curriculum? 1.To what extent do the respondent students manifest the following types of intelligences: Visual-Spatial, Body-Kinesthetic, Musical, Interpersonal, Intrapersonal, Verbal-Linguistic, Logical-Mathematical and Naturalistic. What media should be used appropriate to the student’s learning style? Visual, Printed Words, Sound, Motion, Color or Realia 3. What is the impact of multiple intelligence as basis for differentiated instruction in T.L.E. based on the following student’s ability? Learning Characteristic and Reading Ability and Performance 3. To what extent do the intelligences of the student relate with their academic performance? The following were the findings derived from the study: In consideration of the vast areas of study of TLE, and the importance it plays in the school curriculum coinciding with the expectation of turning students to technologically competent contributing members of the society, either in the field of Technical/Vocational Expertise or Entrepreneurial based competencies, as well as the government’s concern for it, we visualize TLE classroom teachers making use of multiple intelligence as basis for differentiated classroom instruction in teaching the subject .Somehow, multiple intelligence sample such as Linguistic, Logical-Mathematical, Bodily-Kinesthetic, Interpersonal, Intrapersonal, and Spatial abilities that an individual student may have or may not have, can be a basis for a TLE teacher’s instructional method or design.

Keywords: education, multiple, differentiated classroom instruction, impact analysis

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Authors: Madhavi Godavarthy

Abstract:

The globalized world has been witnessing the ubiquity of the English language and has made it mandatory that students be equipped with the required Communication and soft skills. For students and especially for students studying in technical streams, gaining command over the English language is only a part of the bigger challenges they will face in the future. Linguistic capabilities if blended with the right attitude and a positive personality would deliver better results in the present environment of the digitalized world. An English classroom has that ‘space’; a space if utilized well by the teacher can pay rich dividends. The prescribed syllabus for English in the process of adapting itself to the challenges of a more and more technical world has meted out an indifferent treatment in including ‘literary’ material in their curriculum. A debate has always existed regarding the same and diversified opinions have been given. When the student is motivated to reach Literature through intrinsic motivation, it may contribute to his/her personality-development. In the present paper, the element of focus is on the scope and space to motivate students by creating a specific space for herself/himself amidst the schedules of the teaching-learning processes by taking into consideration a few literary excerpts for the purpose.

Keywords: English language, teaching and learning process, reader response theory, intrinsic motivation, literary texts

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Authors: Argyro-Maria Skourmalla

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Today’s reality is characterized by diversity in different levels and aspects of everyday life. Focusing on the aspect of language and communication in Higher Education (HE), the present paper draws on the example of the University of Luxembourg as a multilingual and international setting. The University of Luxembourg, which is located between France, Germany, and Belgium, adopted its new multilingualism policy in 2020, establishing English, French, German, and Luxembourgish as the official languages of the Institution. In addition, with around 10.000 students and staff coming from various countries around the world, linguistic diversity in this university is seen as both a resource and a challenge that calls for an inclusive and multilingual approach. The present paper includes data derived from semi-structured interviews with lecturing staff from different disciplines and an online survey with undergraduate students at the University of Luxembourg. Participants shared their experiences and point of view regarding linguistic diversity in this context. Findings show that linguistic diversity in this university is seen as an asset but comes with challenges, and even though there is progress in the use of multilingual practices, a lot needs to be done towards the recognition of staff and students’ linguistic repertoires for inclusion and education equity.

Keywords: linguistic diversity, higher education, Luxembourg, multilingual practices, teaching, learning

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Authors: Mohammad Abu-Shaira, Weishi Shi

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Adaptive learning, a commonly employed solution to drift, involves updating predictive models online during their operation to react to concept drifts, thereby serving as a critical component and natural extension for online learning systems that learn incrementally from each example. This paper introduces LSTM-SCCM “Long Short-Term Memory Stream Cruise Control Method”, a drift adaptation-as-a-service framework for online learning. LSTM-SCCM automates drift adaptation through prompt detection, drift magnitude quantification, dynamic hyperparameter tuning, performing shortterm optimization and model recalibration for immediate adjustments, and, when necessary, conducting long-term model recalibration to ensure deeper enhancements in model performance. LSTM-SCCM is incorporated into a suite of cutting-edge online regression models, assessing their performance across various types of concept drift using diverse datasets with varying characteristics. The findings demonstrate that LSTM-SCCM represents a notable advancement in both model performance and efficacy in handling concept drift occurrences. LSTM-SCCM stands out as the sole framework adept at effectively tackling concept drifts within regression scenarios. Its proactive approach to drift adaptation distinguishes it from conventional reactive methods, which typically rely on retraining after significant degradation to model performance caused by drifts. Additionally, LSTM-SCCM employs an in-memory approach combined with the Self-Adjusting Memory (SAM) architecture to enhance real-time processing and adaptability. The framework incorporates variable thresholding techniques and does not assume any particular data distribution, making it an ideal choice for managing high-dimensional datasets and efficiently handling large-scale data. Our experiments, which include abrupt, incremental, and gradual drifts across both low- and high-dimensional datasets with varying noise levels, and applied to four state-of-the-art online regression models, demonstrate that LSTM-SCCM is versatile and effective, rendering it a valuable solution for online regression models to address concept drift.

Keywords: automated drift detection and adaptation, concept drift, hyperparameters optimization, online and adaptive learning, regression

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Authors: Sun Zhe, Ruggero Micheletto

Abstract:

The research of neural network is very important for the development of advanced next generation intelligent devices and the medical treatment. The most important part of the neural network research is the learning. The process of learning in our brain is essentially several adjustment processes of connection strength between neurons. It is very difficult to figure out how this mechanism works in the complex network and how the connection strength influences brain functions. For this reason, we made a model with only two coupled neurons and studied the influence of connection strength between them. To emulate the neuronal activity of realistic neurons, we prefer to use the Izhikevich neuron model. This model can simulate the neuron variables accurately and it’s simplicity is very suitable to implement on computers. In this research, the parameter ρ is used to estimate the correlation coefficient between spike train of two coupling neurons.We think the results is very important for figuring out the mechanism between synchronization of coupling neurons and synaptic plasticity. The result also presented the importance of the spike frequency adaptation in complex systems.

Keywords: neural networks, noise, stochastic processes, coupled neurons, correlation coefficient, synchronization, pacemaker, synaptic plasticity

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Authors: Sneha Thakur, Sanjeev Karmakar

Abstract:

This paper proposed hybrid Particle Swarm Optimization (PSO) – Long-Short Term Memory (LSTM) model for groundwater level prediction. The evaluation of the performance is realized using the parameters: root mean square error (RMSE) and mean absolute error (MAE). Ground water level forecasting will be very effective for planning water harvesting. Proper calculation of water level forecasting can overcome the problem of drought and flood to some extent. The objective of this work is to develop a ground water level forecasting model using deep learning technique integrated with optimization technique PSO by applying 29 years data of Chhattisgarh state, In-dia. It is important to find the precise forecasting in case of ground water level so that various water resource planning and water harvesting can be managed effectively.

Keywords: long short-term memory, particle swarm optimization, prediction, deep learning, groundwater level

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