Search results for: intergenerational technology learning

Authors: Marsha D. Loda

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College enrollment is declining and generation Z, today’s college students, are struggling. Before the pandemic, researchers characterized this generational cohort as unique. Gen Z has been called the most achievement-oriented generation, as they enjoy greater economic status, are more racially and ethnically diverse, and better educated than any other generation. However, they are also the most likely generation to suffer from depression and anxiety. Gen Z has grown up largely with usually well-intentioned but overprotective parents who inadvertently kept them from learning life skills, likely impacting their ability to cope with and to effectively manage challenges. The unprecedented challenges resulting from the pandemic up ended their world and left them emotionally reeling. One of the ramifications of this for higher education is how to reengage current Gen Z students in the classroom. This research presents qualitative findings from 24 single-spaced pages of verbatim comments from college students. Research questions concerned what helps them learn and what they abhor, as well as how to engage them with the university outside of the classroom to aid in retention. Students leave little doubt about what they want to experience in the classroom. In order of mention, students want discussion, to engage with questions, to hear how a topic relates to real life and the real world, to feel connections with the professor and fellow students, and to have an opportunity to give their opinions. They prefer a classroom that involves conversation, with interesting topics and active learning. “professor talks instead of lecturing” “professor builds a connection with the classroom” “I am engaged because it feels like a respectful conversation” Similarly, students are direct about what they dislike in a classroom. In order of frequency, students dislike teachers unenthusiastically reading word or word from notes or presentations, repeating the text without adding examples, or addressing how to apply the information. “All lecture. I can read the book myself” “Not taught how to apply the skill or lesson” “Lectures the entire time. Lesson goes in one ear and out the other.” Pertaining to engagement outside the classroom, Gen Z challenges higher education to step outside the box. They don’t want to just hear from professionals in their field, they want to meet and interact with them. Perhaps because of their dependence on technology and pandemic isolation, they seem to reach out for assistance in forming social bonds. “I believe fun and social events are the best way to connect with students and get them involved. Cookouts, raffles, socials, or networking events would all most likely appeal to many students”. “Events… even if they aren’t directly related to learning. Maybe like movie nights… doing meet ups at restaurants”. Qualitative research suggests strategy. This research is rife with strategic implications to improve learning, increase engagement and reduce drop-out rates among Generation Z higher education students. It also compliments existing research on student engagement. With college enrollment declining by some 1.3 million students over the last two years, this research is both timely and important.

Keywords: college enrollment, generation Z, higher education, pandemic, student engagement

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Authors: John Zanetich

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Due to their positive associations with student learning and retention, certain undergraduate opportunities are designated ‘high-impact.’ High-Impact Practices (HIPs) such as, learning communities, community based projects, research, internships, study abroad and culminating senior experience, share several traits bin common: they demand considerable time and effort, learning occurs outside of the classroom, and they require meaningful interactions between faculty and students, they encourage collaboration with diverse others, and they provide frequent and substantive feedback. As a result of experiential learning in these practices, participation in these practices can be life changing. High impact learning helps individuals locate tacit knowledge, and build mental models that support the accumulation of knowledge. On-going learning from experience and knowledge conversion provides the individual with a way to implicitly organize knowledge and share knowledge over a lifetime. Knowledge conversion is a knowledge management component which focuses on the explication of the tacit knowledge that exists in the minds of students and that knowledge which is embedded in the process and relationships of the classroom educational experience. Knowledge conversion is required when working with tacit knowledge and the demand for a learner to align deeply held beliefs with the cognitive dissonance created by new information. Knowledge conversion and tacit knowledge result from the fact that an individual's way of knowing, that is, their core belief structure, is considered generalized and tacit instead of explicit and specific. As a phenomenon, tacit knowledge is not readily available to the learner for explicit description unless evoked by an external source. The development of knowledge–related capabilities such as Aggressive Development of Tacit Knowledge (ADTK) can be used in experiential educational programs to enhance knowledge, foster behavioral change, improve decision making, and overall performance. ADTK allows the student in HIPs to use their existing knowledge in a way that allows them to evaluate and make any necessary modifications to their core construct of reality in order to amalgamate new information. Based on the Lewin/Schein Change Theory, the learner will reach for tacit knowledge as a stabilizing mechanism when they are challenged by new information that puts them slightly off balance. As in word association drills, the important concept is the first thought. The reactionary outpouring to an experience is the programmed or tacit memory and knowledge of their core belief structure. ADTK is a way to help teachers design their own methods and activities to unfreeze, create new learning, and then refreeze the core constructs upon which future learning in a subject area is built. This paper will explore the use of ADTK as a technique for knowledge conversion in the classroom in general and in HIP programs specifically. It will focus on knowledge conversion in curriculum development and propose the use of one-time educational experiences, multi-session experiences and sequential program experiences focusing on tacit knowledge in educational programs.

Keywords: tacit knowledge, knowledge management, college programs, experiential learning

Procedia PDF Downloads 262

Authors: Housein Deli, Loui Al-Shrouf, Hammoud Al Joumaa, Mohieddine Jelali

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When forming metallic materials, fluctuations in material properties, process conditions, and wear lead to deviations in the component geometry. Several hundred features sometimes need to be measured, especially in the case of functional and safety-relevant components. These can only be measured offline due to the large number of features and the accuracy requirements. The risk of producing components outside the tolerances is minimized but not eliminated by the statistical evaluation of process capability and control measurements. The inspection intervals are based on the acceptable risk and are at the expense of productivity but remain reactive and, in some cases, considerably delayed. Due to the considerable progress made in the field of condition monitoring and measurement technology, permanently installed sensor systems in combination with machine learning and artificial intelligence, in particular, offer the potential to independently derive forecasts for component geometry and thus eliminate the risk of defective products - actively and preventively. The reliability of forecasts depends on the quality, completeness, and timeliness of the data. Measuring all geometric characteristics is neither sensible nor technically possible. This paper, therefore, uses the example of car seat rail production to discuss the necessary first step of feature selection and reduction by correlation analysis, as otherwise, it would not be possible to forecast components in real-time and inline. Four different car seat rails with an average of 130 features were selected and measured using a coordinate measuring machine (CMM). The run of such measuring programs alone takes up to 20 minutes. In practice, this results in the risk of faulty production of at least 2000 components that have to be sorted or scrapped if the measurement results are negative. Over a period of 2 months, all measurement data (> 200 measurements/ variant) was collected and evaluated using correlation analysis. As part of this study, the number of characteristics to be measured for all 6 car seat rail variants was reduced by over 80%. Specifically, direct correlations for almost 100 characteristics were proven for an average of 125 characteristics for 4 different products. A further 10 features correlate via indirect relationships so that the number of features required for a prediction could be reduced to less than 20. A correlation factor >0.8 was assumed for all correlations.

Keywords: long-term SHM, condition monitoring, machine learning, correlation analysis, component prediction, wear prediction, regressions analysis

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Authors: Ruel A. Welch

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Since the introduction of ServiceNow, the UK’s Science Museum Group’s (SMG) ICT service desk portal. There has not been an analysis of the tools available to SMG staff for just-in-time knowledge acquisition (knowledge management systems) and reporting ICT incidents with a focus on an aspect of professional identity, namely, gender. This study is conducted in the milieu of UK museums, galleries, arts, academic, charitable, and cultural heritage sectors. Numerous authors suggest that males and females experience ICT usage differently. Therefore, it is important for SMG to investigate the apparent disparities so that solutions can be derived to minimize this digital divide if one exists. It is acknowledged at SMG that there are challenges with keeping up with an ever-changing digital landscape. Subsequently, this entails the rapid upskilling of staff and developing an infrastructure that supports just-in-time technological knowledge acquisition and reporting technology-related issues. This problem was addressed by analyzing ServiceNow ICT incident reports and reports from knowledge articles from a six-month period from February to July. This study found a statistically significant relationship between gender and reporting an ICT incident. There is also a significant relationship between gender and the priority level of ICT incidents. Interestingly, there is no statistically significant relationship between gender and reading knowledge articles. Additionally, there is no statistically significant relationship between gender and reporting an ICT incident related to the knowledge article that was read by staff. The knowledge acquired from this study is useful to service desk management practice as it will help to inform the creation of future knowledge articles and ICT incident reporting processes.

Keywords: digital divide, ICT service desk practice, knowledge management systems, workplace learning

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Authors: Meenal Badki

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We address the issue of active feature determination, where the objective is to determine the set of examples on which additional data (such as lab tests) needs to be gathered, given a large number of examples with some features (such as demographics) and some examples with all the features (such as the complete Electronic Health Record). We note that certain features may be more costly, unique, or laborious to gather. Our proposal is a general active learning approach that is independent of classifiers and similarity metrics. It allows us to identify examples that differ from the full data set and obtain all the features for the examples that match. Our comprehensive evaluation shows the efficacy of this approach, which is driven by four authentic clinical tasks.

Keywords: feature determination, classification, active learning, sample-efficiency

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Authors: E. Izsó, M. Bartalné-Berceli, Sz. Gergely, A. Salgó

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The aims of this investigation is to elaborate near-infrared methods for testing and recognition of chemical components and quality in “Pannon wheat” allied (i.e. true to variety or variety identified) milling fractions as well as to develop spectroscopic methods following the milling processes and evaluate the stability of the milling technology by different types of milling products and according to sampling times, respectively. This wheat categories produced under industrial conditions where samples were collected versus sampling time and maximum or minimum yields. The changes of the main chemical components (such as starch, protein, lipid) and physical properties of fractions (particle size) were analysed by dispersive spectrophotometers using visible (VIS) and near-infrared (NIR) regions of the electromagnetic radiation. Close correlation were obtained between the data of spectroscopic measurement techniques processed by various chemometric methods (e.g. principal component analysis (PCA), cluster analysis (CA) and operation condition of milling technology. Its obvious that NIR methods are able to detect the deviation of the yield parameters and differences of the sampling times by a wide variety of fractions, respectively. NIR technology can be used in the sensitive monitoring of milling technology.

Keywords: near infrared spectroscopy, wheat categories, milling process, monitoring

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Authors: Aya Belal, Ahmed Maher Eltair, Maggie Ahmed Mashaly

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Geopolymer concrete is gaining recognition as a sustainable alternative to conventional Portland Cement concrete due to its environmentally friendly nature, which is a key goal for Smart City initiatives. It has demonstrated its potential as a reliable material for the design of structural elements. However, the production of Geopolymer concrete is hindered by batch-to-batch variations, which presents a significant challenge to the widespread adoption of Geopolymer concrete. To date, Machine learning has had a profound impact on various fields by enabling models to learn from large datasets and predict outputs accurately. This paper proposes an integration between the current drift to Artificial Intelligence and the composition of Geopolymer mixtures to predict their mechanical properties. This study employs Python software to develop machine learning model in specific Decision Trees. The research uses the percentage oxides and the chemical composition of the Alkali Solution along with the curing conditions as the input independent parameters, irrespective of the waste products used in the mixture yielding the compressive strength of the mix as the output parameter. The results showed 90 % agreement of the predicted values to the actual values having the ratio of the Sodium Silicate to the Sodium Hydroxide solution being the dominant parameter in the mixture.

Keywords: decision trees, geopolymer concrete, machine learning, smart cities, sustainability

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Authors: Go Woon Kwak, Siyoung Jun, Soyun Maeng, Haeyoung Lee

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Entry is an education platform used in South Korea, created to help students learn to program, in which they can learn to code while playing. Using the online version of the entry, teachers can easily assign programming homework to the student and the students can make programs simply by linking programming blocks. However, the programs may be made by others, so that the authors of the programs should be identified. In this paper, as the first step toward author identification of entry programs, we present an artificial neural network based classification approach to identify genders of authors of a program written in an entry. A neural network has been trained from labeled training data that we have collected. Our result in progress, although preliminary, shows that the proposed approach could be feasible to be applied to the online version of entry for gender identification of authors. As future work, we will first use a machine learning technique for age identification of entry programs, which would be the second step toward the author identification.

Keywords: artificial intelligence, author identification, deep neural network, gender identification, machine learning

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Authors: Huang Yajing

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Context: Computer-aided language learning (CALL) in China has undergone significant development over the past few decades, with distinct stages marking its evolution. This paper aims to provide a comprehensive review of the practice and research in this field in China, tracing its journey from the early stages of audio-visual education to the current multimedia network integration stage. Research Aim: The study aims to analyze the historical progression of CALL in China, identify key developments in the field, and provide recommendations for enhancing CALL practices in the future. Methodology: The research employs document analysis and literature review to synthesize existing knowledge on CALL in China, drawing on a range of sources to construct a detailed overview of the evolution of CALL practices and research in the country. Findings: The review highlights the significant advancements in CALL in China, showcasing the transition from traditional audio-visual educational approaches to the current integrated multimedia network stage. The study identifies key milestones, technological advancements, and theoretical influences that have shaped CALL practices in China. Theoretical Importance: The evolution of CALL in China reflects not only technological progress but also shifts in educational paradigms and theories. The study underscores the significance of cognitive psychology as a theoretical underpinning for CALL practices, emphasizing the learner's active role in the learning process. Data Collection and Analysis Procedures: Data collection involved extensive review and analysis of documents and literature related to CALL in China. The analysis was carried out systematically to identify trends, developments, and challenges in the field. Questions Addressed: The study addresses the historical development of CALL in China, the impact of technological advancements on teaching practices, the role of cognitive psychology in shaping CALL methodologies, and the future outlook for CALL in the country. Conclusion: The review provides a comprehensive overview of the evolution of CALL in China, highlighting key stages of development and emerging trends. The study concludes by offering recommendations to further enhance CALL practices in the Chinese context.

Keywords: English education, educational technology, computer-aided language teaching, applied linguistics

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Authors: Anna K. Johnson

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Technology can provide endless opportunities for students with special needs. Virtual learning, particularly virtual charter schools in the US, provides opportunities for students with special needs for alternative education besides Brick and Mortar schools. Virtual schools have proven to be successful in the way they are able to provide quality education for their students. Virtual schools, just like Brick and Mortar schools, are not for everybody. This research is designed to look at the effectiveness of online charter schools, so parents can make decisions based on data. This article explains what inclusion is and how inclusion is addressed in the virtual environment. Often, students with special needs have limited options for schooling, and new charter schools provide that alternative education for students who don’t fit in the local brick-and-mortar school.

Keywords: special education, virtual school, online, inclusion

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Authors: A. Schuchter, M. Promegger

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The outbreak of the COVID-19 pandemic has shown us that online education is so much more than just a cool feature for teachers – it is an essential part of modern teaching. In online math teaching, it is common to use tools to share screens, compute and calculate mathematical examples, while the students can watch the process. On the other hand, flipped classroom models are on the rise, with their focus on how students can gather knowledge by watching videos and on the teacher’s use of technological tools for information transfer. This paper proposes a co-educational teaching approach for coding and engineering subjects with the help of drone-building to spark interest in technology and create a platform for knowledge transfer. The project combines aspects from mathematics (matrices, vectors, shaders, trigonometry), physics (force, pressure and rotation) and coding (computational thinking, block-based programming, JavaScript and Python) and makes use of collaborative-shared 3D Modeling with clara.io, where students create mathematics knowhow. The instructor follows a problem-based learning approach and encourages their students to find solutions in their own time and in their own way, which will help them develop new skills intuitively and boost logically structured thinking. The collaborative aspect of working in groups will help the students develop communication skills as well as structural and computational thinking. Students are not just listeners as in traditional classroom settings, but play an active part in creating content together by compiling a Handbook of Knowledge (called “open book”) with examples and solutions. Before students start calculating, they have to write down all their ideas and working steps in full sentences so other students can easily follow their train of thought. Therefore, students will learn to formulate goals, solve problems, and create a ready-to use product with the help of “reverse engineering”, cross-referencing and creative thinking. The work on drones gives the students the opportunity to create a real-life application with a practical purpose, while going through all stages of product development.

Keywords: flipped classroom, co-creational education, coding, making, drones, co-education, ARCS-model, problem-based learning

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Authors: Abdullah Mukhtar, Shehroz Mukhtar, Amina Mukhtar, Choudhry Shahid, Hafiz Raza Razzaq, Saif Ur Rahman

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The aim of this study is to find out the negative and positive impacts of social media platforms on the attitude toward learning and the educational environment of the student community. Social Media platforms have become a source of collaboration with one another throughout the globe, making it a small world. This study performs a focalized investigation of the adverse and constructive factors that have a strong impact not only on psychological adjustments but also on the academic performance of peers. This study is quantitative research adopting a random sampling method in which the participants were the students at the university. The researcher distributed 1000 questionnaires among the university students from different departments and asked them to fill in the data on the Lickert Scale. The participants are from the age group of 18-24 years. The study applies user and gratification theory in order to examine the behavior of students practicing social media in their academic and personal lives. The findings of the study reveal that the use of social media platforms in the Pakistani context has less positive impact as compared to negative impacts on the behavior of students towards learning. The research suggests that usage of online social media platforms should be taught to students; awareness must the created among the users of social media by means of seminars, workshops and by media itself to overcome the negative impacts of social media, leading towards sustainable education in Pakistan.

Keywords: social media, positive impacts, negative impacts, sustainable education, learning behaviour

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Authors: Kwaku Damoah

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This paper presents a methodology and software application (App) designed to empower users in accessing, retrieving, and comparatively exploring data within the hierarchical network framework of the Government Finance Statistics (GFS) system. It explores the ease of navigating the GFS system and identifies the gaps filled by the new methodology and App. The GFS, embodies a complex Hierarchical Network Classification (HNC) structure, encapsulating institutional units, revenues, expenses, assets, liabilities, and economic activities. Navigating this structure demands specialized knowledge, experience, and skill, posing a significant challenge for effective analytics and fiscal policy decision-making. Many professionals encounter difficulties deciphering these classifications, hindering confident utilization of the system. This accessibility barrier obstructs a vast number of professionals, students, policymakers, and the public from leveraging the abundant data and information within the GFS. Leveraging R programming language, Data Science Analytics and Machine Learning, an efficient methodology enabling users to access, navigate, and conduct exploratory comparisons was developed. The machine learning Fiscal Analytics App (FLOWZZ) democratizes access to advanced analytics through its user-friendly interface, breaking down expertise barriers.

Keywords: data science, data wrangling, drilldown analytics, government finance statistics, hierarchical network classification, machine learning, web application.

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Authors: Upeksha Jayasuriya

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The sudden transition from onsite to online teaching/learning due to the COVID-19 pandemic called for a need to incorporate feasible as well as effective methods of online teaching in most developing countries like Sri Lanka. The English as a Second Language (ESL) classroom faces specific challenges in this adaptation, and teaching writing can be identified as the most challenging task compared to teaching the other three skills. This study was therefore carried out to explore the challenges of teaching writing online and to provide effective means of overcoming them while taking into consideration the attitudes of students and teachers with regard to learning/teaching English writing via online platforms. A survey questionnaire was distributed (electronically) among 60 students from the University of Colombo, the University of Kelaniya, and The Open University in order to find out the challenges faced by students, while in-depth interviews were conducted with 12 lecturers from the mentioned universities. The findings reveal that the inability to observe students’ writing and to receive real-time feedback discourage students from engaging in writing activities when taught online. It was also discovered that both students and teachers increasingly prefer Google Slides over other platforms such as Padlet, Linoit, and Jam Board as it boosts learner autonomy and student-teacher interaction, which in turn allows real-time formative feedback, observation of student work, and assessment. Accordingly, it can be recommended that teaching writing online can be better facilitated by using interactive platforms such as Google Slides, for it promotes active learning and student engagement in the ESL class.

Keywords: ESL, teaching writing, online teaching, active learning, student engagement

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Authors: Ayşe Çoban, Orhan Çoban, Murat Birekul

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In this study, the effects of radio frequency identification system on the retailing sector were theoretically analysed. The technology of Radio Frequency Identification (RFID) is a method enabling to identify the objects individually and automatically, using radio frequency. RFID generally consists of a tag and reader. RFID tags can be programmed to receive, store, and send the information of object such as Electronic Product Code (EPC). Having read the tags placed on product by the reader, the information associated with the management of supply chain can be automatically recorded and replaced. Recently, RFID technology used in many areas has particularly important effects on the businesses that are active in the retailing sector. The most important disadvantage of this technology is that the cost of installation and operation is higher compared to its alternatives. However, it provides important advantages to the business enterprises in the application process. At present, it is especially adopted by the large sized enterprises and with chain stores in the international areas. The application results point out that RFID technology provides business enterprises with the important competitive advantage.

Keywords: RFID, retailing sector, RFID technologies, electronic product code

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Authors: Dante Jose R. Amisola, Glenford M. Prospero

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'Driving What’s Next' is a strong campaign of the new administration of De La Salle Lipa in promoting social innovation in quality education. The new leadership directs social innovation in quality education in the institutional directions and initiatives to address real-world challenges with real-world solutions. This research under study aims to qualify the commitment of the institution to extend the Lasallian quality human and Christian education to all, as expressed in the Institution’s new mission-vision statement. The Classic Grounded Theory methodology is employed in the process of generating concepts in reference to the documents, a series of meetings, focus group discussions and other related activities that account for the conceptualization and formulation of the new mission-vision along with the new education innovation framework. Notably, Driving What’s Next is the emergent theory that encapsulates the commitment of giving quality human and Christian education to all. It directs the new leadership in driving social innovation in quality education initiatives. Correspondingly, Driving What’s Next is continually resolved through four interrelated strategies also termed as the institution's four strategic directions, namely: (1) driving social innovation in quality education, (2) embracing our shared humanity and championing social inclusion and justice initiatives, (3) creating sustainable futures and (4) engaging diverse stakeholders in our shared mission. Significantly, the four strategic directions capture and integrate the 17 UN sustainable development goals, making the innovative curriculum locally and globally relevant. To conclude, the main concern of the new administration and how it is continually resolved, provide meaningful and fun learning experiences and promote a new way of learning in the light of the 21^st century skills among the members of the academic community including stakeholders and extended communities at large, which are defined as: learning together and by association (collaboration), learning through engagement (communication), learning by design (creativity) and learning with social impact (critical thinking).

Keywords: DLSL four strategic directions , DLSL Lipa mission-vision, driving what's next, social innovation in quality education

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Authors: Nguyen Thu Ha, Vu Viet Phuong, Do Thi Tieu Yen, Nguyen Thi Thanh Ha

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This semi-experimental research investigated the correlation between 42 English as a foreign language (EFL) sophomores' self-regulated learning strategies (SRL) use and their reading comprehension in the Vietnamese context. The analysis from TOEIC reading tests with SPSS 25.0 indicated that there are substantial differences between the post-test reading scores between the experimental group and the control group; therefore, SRL impacts the reading comprehension of EFL participants. Contrary to the alternative hypothesis, teaching learners SRL approaches had a statistically significant influence on reading comprehension. The findings may aid educators in teaching reading comprehension as an essential skill and in using SRL to improve reading comprehension and achievement and enhance reading comprehension aids for language students and instructors. They should equip educators with a variety of instructional strategies which assist academics in preparing learners for lifetime language study and independence. Moreover, the results might encourage educators, administrators, and policymakers to capitalize on the effects of teaching SRL strategies by providing EFL teachers with preparation programs and experiences that help them improve their teaching methods and strategies, especially when teaching reading comprehension.

Keywords: correlation, reading proficiency, self-regulated learning strategies, SRL, TOEIC reading comprehension

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Authors: M. Devaki, K. B. Jayanthi

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The identification of water bodies from satellite images has recently received a great deal of attention. Different methods have been developed to distinguish water bodies from various satellite images that vary in terms of time and space. Urban water identification issues body manifests in numerous applications with a great deal of certainty. There has been a sharp rise in the usage of satellite images to map natural resources, including urban water bodies and forests, during the past several years. This is because water and forest resources depend on each other so heavily that ongoing monitoring of both is essential to their sustainable management. The relevant elements from satellite pictures have been chosen using a variety of techniques, including machine learning. Then, a convolution neural network (CNN) architecture is created that can identify a superpixel as either one of two classes, one that includes water or doesn't from input data in a complex metropolitan scene. The deep learning technique, CNN, has advanced tremendously in a variety of visual-related tasks. CNN can improve classification performance by reducing the spectral-spatial regularities of the input data and extracting deep features hierarchically from raw pictures. Calculate the water body using the satellite image's resolution. Experimental results demonstrate that the suggested method outperformed conventional approaches in terms of water extraction accuracy from remote-sensing images, with an average overall accuracy of 97%.

Keywords: water body, Deep learning, satellite images, convolution neural network

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Authors: Simone Leonardi, Luca Ardito

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Micro-influencers are effective elements in the marketing strategies of companies and institutions because of their capability to create an hyper-engaged audience around a specific topic of interest. In recent years, many scientific approaches and commercial tools have handled the task of detecting this type of social media users. These strategies adopt solutions ranging from rule based machine learning models to deep neural networks and graph analysis on text, images, and account information. This work compares the existing solutions and proposes an ensemble method to generalize them with different input data and social media platforms. The deployed solution combines deep learning models on unstructured data with statistical machine learning models on structured data. We retrieve both social media accounts information and multimedia posts on Twitter and Instagram. These data are mapped into feature vectors for an eXtreme Gradient Boosting (XGBoost) classifier. Sixty different topics have been analyzed to build a rule based gold standard dataset and to compare the performances of our approach against baseline classifiers. We prove the effectiveness of our work by comparing the accuracy, precision, recall, and f1 score of our model with different configurations and architectures. We obtained an accuracy of 0.91 with our best performing model.

Keywords: deep learning, gradient boosting, image processing, micro-influencers, NLP, social media

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Authors: Zahara Abdulhussan Al-Awadai

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Currently, serious games play a significant role in education, sparking an increasing interest in using games for purposes beyond mere entertainment. In this research, we investigate the main requirements and aspects of designing and developing effective serious games for learning and developing a conceptual model to describe the structure of serious games with a focus on both aspects of serious games. The main contributions of this approach are to facilitate the design and development of serious games in a flexible and easy-to-use way and also to support the cooperative work between the multidisciplinary developer team.

Keywords: game development, game design, requirements, serious games, serious game model.

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Authors: Mohammed Amraouy, Mostafa Bellafkih, Abdellah Bennane, Aziza Benomar

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Distance education has become popular due to their ability to provide learning from almost anywhere and anytime. COVID-19 forced educational institutions to urgently introduce distance education to ensure pedagogical continuity, so all stakeholders were invited to adapt to this new paradigm. In order to identify strengths and weaknesses, the research focuses on the need to create an effective mechanism for evaluating distance education. The aims of this research were to explore and evaluate the use of digital media in general and official platforms in particular in distance education practices. To this end, we have developed and validated a questionnaire before administering it to a sample of 431 teachers in Morocco. Teachers reported lower knowledge and skills in the didactic use of ICT in the distance education process. In addition, although age and educative experience of the teachers continue to modulate the level of instrumental skills. Therefore, resources (digital resources and infrastructure) and the teachers’ ICT training present serious limitations, which require a training more focused on the distance educational paradigm and educational environments that allow teachers to create educational activities able to promote and facilitate the distance learning process.

Keywords: distance education, e-learning, teachers’ perceptions, assessment

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Authors: Zahid Shafait, Jiayu Huang

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Purpose: This study is based on a trait-based theory of emotional intelligence. This study intends to explore the enabling effect of organizational climate, i.e., affiliation, innovation, and fairness, on the emotional intelligence of teachers in Chinese higher education institutes. This study, additionally, intends to investigate the direct impact of teachers’ emotional intelligence on their learning outcomes, i.e., cognitive, social, self-growth outcomes and satisfaction with the university experience. Design/methodology/approach: This study utilized quantitative research techniques to scrutinize the data. Moreover, partial least squares structural equation modeling, i.e., PLS-SEM, was used to assess the hypothetical relationships to conclude their statistical significance. Findings: Results confirmed the supposed associations, i.e., the organizational climate has an enabling effect on emotional intelligence. Likewise, emotional intelligence was concluded to have a direct and positive association with learning outcomes in higher education. Practical implications: This study has investigated abandoned research that is enabling the effects of organizational climate on teachers’ emotional intelligence in Chinese higher education. Organizational climate enables emotionally intelligent teachers to learn efficiently and, at the same time, augments their satisfaction and productivity within an institution. Originality/value: This study investigated the enabling effects of organizational climate on teachers’ emotional intelligence in Chinese higher education that is original in investigated country and sector.

Keywords: organizational climate, emotional intelligence, learning outcomes, higher education

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Authors: A. Georgiou, A. Galani, A. Karatza, G. E. Bampasidis

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Augmented Reality (AR) technology has become integral in enhancing visitor experiences at Greece's UNESCO World Heritage Sites. This research meticulously investigates various facets of AR applications/games associated with these revered sites. The cultural heritage represents the identity of each nation in the world. Technology can breathe life into this identity. Through Augmented Reality (AR), individuals can travel back in time, visit places they cannot access in real life, discover the history of these places, and live unique experiences. The study examines the objectives and intended goals behind the development and deployment of each augmented reality application/game pertaining to the UNESCO World Heritage Sites in Greece. It thoroughly analyzes the scenarios presented within these AR games/applications, examining how historical narratives, interactive elements, and cultural context are incorporated to engage users. Furthermore, the research identifies and assesses the technological platforms utilized for the development and implementation of these AR experiences, encompassing mobile devices, AR headsets, or specific software frameworks. It classifies and examines the types of augmented reality employed within these applications/games, including marker-based, markerless, location-based, or immersive AR experiences. Evaluation of the benefits accrued by visitors engaging with these AR applications/games, such as enhanced learning experiences, improved cultural understanding, and heightened engagement with the heritage sites, forms a crucial aspect of this study. Additionally, the research scrutinizes potential drawbacks or limitations associated with the AR applications/games, considering technological barriers, user accessibility issues, or constraints affecting user experience. By thoroughly investigating these pivotal aspects, this research aims to provide a comprehensive overview and analysis of the landscape of augmented reality applications/games linked to the UNESCO World Heritage Sites in Greece. The findings seek to contribute nuanced insights into the effectiveness, challenges, and opportunities associated with leveraging AR technology for heritage site preservation, visitor engagement, and cultural enrichment.

Keywords: augmented reality, AR applications, UNESCO sites, cultural heritage, Greece, visitor engagement, historical narratives

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Authors: Nashrawan Naser Taha, Andrew M. Cox

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In a multi-cultural learning context, where ties are weak and dynamic, combining qualitative with quantitative research methods may be more effective. Such a combination may also allow us to answer different types of question, such as about people’s perception of the network. In this study the use of observation, interviews and photos were explored as ways of enhancing data from social network questionnaires. Integrating all of these methods was found to enhance the quality of data collected and its accuracy, also providing a richer story of the network dynamics and the factors that shaped these changes over time.

Keywords: mixed methods, social network analysis, multi-cultural learning, social network dynamics

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Authors: Md Yeasin, Ranjit Kumar Paul

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In recent years, recommendation systems have become indispensable tools for agricultural system. The accurate and timely recommendations can significantly impact crop yield and overall productivity. Causal inference modeling aims to establish cause-and-effect relationships by identifying the impact of variables or factors on outcomes, enabling more accurate and reliable recommendations. New advancements in causal inference models have been found in the literature. With the advent of the modern era, deep learning and machine learning models have emerged as efficient tools for modeling. This study proposed an innovative approach to enhance recommendation systems-based machine learning based casual inference model. By considering the causal effect and opportunity cost of covariates, the proposed system can provide more reliable and actionable recommendations for cereal farmers. To validate the effectiveness of the proposed approach, experiments are conducted using cereal cultivation data of eastern India. Comparative evaluations are performed against existing correlation-based recommendation systems, demonstrating the superiority of the advanced causal inference modeling approach in terms of recommendation accuracy and impact on crop yield. Overall, it empowers farmers with personalized recommendations tailored to their specific circumstances, leading to optimized decision-making and increased crop productivity.

Keywords: agriculture, casual inference, machine learning, recommendation system

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Authors: Jonathan D. Moore, Mark G. Reith, David S. Long

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Serious games (SGs) have been shown to be an effective teaching tool in many contexts. Because of the success of SGs, several design frameworks have been created to expedite the process of making original serious games to teach specific learning objectives (LOs). Even with these frameworks, the time required to create a custom SG from conception to implementation can range from months to years. Furthermore, it is even more difficult to design a game framework that allows an instructor to create customized game variants supporting multiple LOs within the same field. This paper proposes a refactoring methodology to apply the theoretical principles from well-established design frameworks to a pre-existing serious game. The expected result is a generalized game that can be quickly customized to teach LOs not originally targeted by the game. This methodology begins by describing the general components in a game, then uses a combination of two SG design frameworks to extract the teaching elements present in the game. The identified teaching elements are then used as the theoretical basis to determine the range of LOs that can be taught by the game. This paper evaluates the proposed methodology by presenting a case study of refactoring the serious game Battlespace Next (BSN) to teach joint military capabilities. The range of LOs that can be taught by the generalized BSN are identified, and examples of creating custom LOs are given. Survey results from users of the generalized game are also provided. Lastly, the expected impact of this work is discussed and a road map for future work and evaluation is presented.

Keywords: serious games, learning objectives, game design, learning theory, game framework

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Authors: Alejandra Torres-Landa López

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Introduction: Can architecture students be creative in spaces conformed by an educational infrastructure build with paradigms of the past?, this question and others related are answered in this paper as it presents the PhD research: An anthropic conflict in Mexican Higher Education Institutes, problems and challenges of the educational infrastructure in teaching and learning History of Architecture. This research was finished in 2013 and is one of the first studies conducted nationwide in Mexico that analysis the educational infrastructure impact in learning architecture; its objective was to identify which elements of the educational infrastructure of Mexican Higher Education Institutes where architects are formed, hinder or contribute to the teaching and learning of History of Architecture; how and why it happens. The methodology: A mixed methodology was used combining quantitative and qualitative analysis. Different resources and strategies for data collection were used, such as questionnaires for students and teachers, interviews to architecture research experts, direct observations in Architecture classes, among others; the data collected was analyses using SPSS and MAXQDA. The veracity of the quantitative data was supported by the Cronbach’s Alpha Coefficient, obtaining a 0.86, figure that gives the data enough support. All the above enabled to certify the anthropic conflict in which Mexican Universities are. Major findings of the study: Although some of findings were probably not unknown, they haven’t been systematized and analyzed with the depth to which it’s done in this research. So, it can be said, that the educational infrastructure of most of the Higher Education Institutes studied, is a barrier to the educational process, some of the reasons are: the little morphological variation of space, the inadequate control of lighting, noise, temperature, equipment and furniture, the poor or none accessibility for disable people; as well as the absence, obsolescence and / or insufficiency of information technologies are some of the issues that generate an anthropic conflict understanding it as the trouble that teachers and students have to relate between them, in order to achieve significant learning). It is clear that most of the educational infrastructure of Mexican Higher Education Institutes is anchored to paradigms of the past; it seems that they respond to the previous era of industrialization. The results confirm that the educational infrastructure of Mexican Higher Education Institutes where architects are formed, is perceived as a "closed container" of people and data; infrastructure that becomes a barrier to teaching and learning process. Conclusion: The research results show it's time to change the paradigm in which we conceive the educational infrastructure, it’s time to stop seen it just only as classrooms, workshops, laboratories and libraries, as it must be seen from a constructive, urban, architectural and human point of view, taking into account their different dimensions: physical, technological, documental, social, among others; so the educational infrastructure can become a set of elements that organize and create spaces where ideas and thoughts can be shared; to be a social catalyst where people can interact between each other and with the space itself.

Keywords: educational infrastructure, impact of space in learning architecture outcomes, learning environments, teaching architecture, learning architecture

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Authors: Kalbende Krunal Ramesh

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The Carbon Capture and Storage Technology (CCS) provides a veritable platform to bridge the gap between the seemingly irreconcilable twin global challenges of ensuring a secure, reliable and diversified energy supply and mitigating climate change by reducing atmospheric emissions of carbon dioxide. Making its proper regulatory policy and making it flexible for the government and private company by law to regulate, also exploring the opportunity in this sector is the main aim of this paper. India's total annual emissions was 1725 Mt CO2 in 2011, which comprises of 6% of total global emission. It is very important to control the greenhouse gas emission for the environment protection. This paper discusses the various regulatory policy and technology adopted by some of the countries for successful using CCS technology. The brief geology of sedimentary basins in India is studied, ranging from the category I to category IV and deep water and potential for mature technology in CCS is reviewed. Areas not suitable for CO2 storage using presently mature technologies were over viewed. CSS and Clean development mechanism was developed for India, considering the various aspects from research and development, project appraisal, approval and validation, implementation, monitoring and verification, carbon credit issued, cap and trade system and its storage potential. The opportunities in oil and gas operations, power sector, transport sector is discussed briefly.

Keywords: carbon credit issued, cap and trade system, carbon capture and storage technology, greenhouse gas

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Authors: Evy Latifah, Eko Widaryanto, M. Dawam Maghfoer, Arifin

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Tomato (Lycopersicon esculentum Mill.) is potential vegetables to develop, because it has high economic value and has the potential to be exported. There is a decrease in tomato productivity due to unfavorable growth conditions such as bacterial wilt, fusarium wilt, high humidity, high temperature and inappropriate production technology. Grafting technology is one alternative technology. In addition to being able to control the disease in the soil, grafting is also able to increase the growth and yield of production. Besides, it is also necessary to know the economic benefits if using grafting technology. A promising eggplant rootstock for tomato grafting is Solanum torvum. S. torvum is selected as a rootstock with high compatibility. The purpose of this research is to know the effect of grafting several varieties of tomatoes with Solanum torvum as a rootstock. The experiment was conducted in Agricultural Extension Center Pare. Experimental Garden of Pare Kediri sub-district from July to early December 2016. The materials used were tomato Cervo varieties, Karina, Timoty, and Solanum torvum. Economic analysis, growth, and yield including plant height, number of leaves, percentage of disease and tomato production were used as performance measures. The study showed that grafting tomato Timoty scion with Solanum torvum as rootstock had higher production. Financially, grafting tomato Timoty and Cervo scion had higher profit about. 28,6% and 16,3% compared to Timoty and Cervo variety treatment without grafting.

Keywords: grafting technology, economic analysis, growth, yield of tomato, Solanum torvum

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Authors: K. L. Wong, I. N. Umar

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Online forum is part of a Learning Management System (LMS) environment in which students share opinions. This study attempts to investigate the perceptions of students towards online forum and their patterns of listening behaviour during the forum interaction. The students’ perceptions were measured using a questionnaire, in which seven dimensions were used including online experience, benefits of forum participation, cost of participation, perceived ease of use, usefulness, attitude and intention. Meanwhile, their patterns of listening behaviours were obtained using the log file extracted from the LMS. A total of 25 postgraduate students undertaking a course were involved in this study, and their activities in the forum session were recorded by the LMS and used as a log file. The results from the questionnaire analysis indicated that the students perceived that the forum is easy to use, useful, and bring benefits to them. Also, they showed positive attitude towards online forum, and they have the intention to use it in future. Based on the log data, the participants were also divided into six clusters of listening behaviour, in which they are different in terms of temporality, breadth, depth and speaking level. The findings were compared to previous clusters grouping and future recommendations are also discussed.

Keywords: e-learning, learning management system, listening behavior, online forum

Procedia PDF Downloads 433