Search results for: institutional learning outcomes

Authors: Maria Florencia Ferrer, Saulo Fabiano Amancio-Vieira

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The use of the blockchain in the public sector is present today and no longer the future of disruptive institutional and technological models. There are still some cultural barriers and resistance to the proper use of its potential. This research aims to present the strengths and weaknesses of using a public-permitted and distributed network in the context of the public sector. Therefore, bibliographical/documentary research was conducted to raise the main aspects of the studied platform, focused on the use of the main demands of the public sector. The platform analyzed was LACChain, which is a global alliance composed of different actors in the blockchain environment, led by the Innovation Laboratory of the Inter-American Development Bank Group (IDB Lab) for the development of the blockchain ecosystem in Latin America and the Caribbean. LACChain provides blockchain infrastructure, which is a distributed ratio technology (DLT). The platform focuses on two main pillars: community and infrastructure. It is organized as a consortium for the management and administration of an infrastructure classified as public, following the ISO typologies (ISO / TC 307). It is, therefore, a network open to any participant who agrees with the established rules, which are limited to being identified and complying with the regulations. As benefits can be listed: public network (open to all), decentralized, low transaction cost, greater publicity of transactions, reduction of corruption in contracts / public acts, in addition to improving transparency for the population in general. It is also noteworthy that the platform is not based on cryptocurrency and is not anonymous; that is, it is possible to be regulated. It is concluded that the use of record platforms, such as LACChain, can contribute to greater security on the part of the public agent in the migration process of their informational applications.

Keywords: blockchain, LACChain, public sector, technological disruptions

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Authors: Peeyush Verma, Anil Kumar, Anju Rawlley, Chanchal Mehra

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India's school-going population is largely served by an educational system that is, in most rural parts, stuck with methods that emphasize rote learning, endless examinations, and monotonous classroom activities. Rural government schools are generally seen as having poor infrastructure, poor support system and low motivation for teaching as well as learning. It was experienced during the survey of this project that there is lesser motivation of rural boys and girls to attend their schools and still less likely chances to study science, tabooed as “difficult”. An experiment was conducted with the help of Rural Knowledge Network Project through Department of Science and Technology, Govt of India in five remote villages of Sehore District in Madhya Pradesh (India) during 2012-2015. These schools are located about 50-70 Km away from Bhopal, the capital of Madhya Pradesh and can distinctively qualify as average rural schools. Three tier methodology was adapted to unfold the experiment. In first tier randomly selected boys and girls from these schools were taken to a daylong visit to the Regional Science Centre located in Bhopal. In second tier, randomly selected half of those who visited earlier were again taken to the Science Centre to make models of Science. And in third tier, all the boys and girls studying science were exposed to video lectures and study material through web. The results have shown an interesting face towards learning science among youths in rural schools through peer learning or incremental learning. The students who had little or no interest in learning science became good learners and queries started pouring in from the neighbourhood village as well as a few parents requested to take their wards in the project to learn science. The paper presented is a case study of the experiment conducted in five rural schools of Sehore District. It reflects upon the methodology of developing awareness and interest among students and finally engaging them in popularising science through peer-to-peer learning using incremental learning elements. The students, who had a poor perception about science initially, had changed their attitude towards learning science during the project period. The results of this case, however, cannot be generalised unless replicated in the same setting elsewhere.

Keywords: popularisation of science, science temper, incremental learning, peer-to-peer learning

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Authors: Ho-Dae Chong, Jong-Kil Kim

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Collaborative research has become more prevalent and important across disciplines because it stimulates innovation and interaction between scholars. Seeing as existing studies relatively disregarded the institutional conditions triggering collaborative research, this work aims to analyze the changing trend in collaborative work patterns among Korean social scientists. The focus of this research is the performance of social scientists who received research grants through the government’s Social Science Korea (SSK) program. Using quantitative statistical methods, collaborative research patterns in a total of 2,354 papers published under the umbrella of the SSK program in peer-reviewed scholarly journals from 2013 to 2016 were examined to identify changing trends and triggering factors in collaborative research. A notable finding is that the share of collaborative research is overwhelmingly higher than that of individual research. In particular, levels of collaborative research surpassed 70%, increasing much quicker compared to other research done in the social sciences. Additionally, the most common composition of collaborative research was for two or three researchers to conduct joint research as coauthors, and this proportion has also increased steadily. Finally, a strong association between international journals and co-authorship patterns was found for the papers published by SSK program researchers from 2013 to 2016. The SSK program can be seen as the driving force behind collaboration between social scientists. Its emphasis on competition through a merit-based financial support system along with a rigorous evaluation process seems to have influenced researchers to cooperate with those who have similar research interests.

Keywords: coauthorship, collaboration, competition, cooperation, Social Science Korea, policy

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Authors: Nur Azha Putra Abdul Azim, Denise Cheong, S. Nivedita

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Currently, there are no nuclear power reactors among the Association of Southeast Asian Nations (ASEAN) member states (AMS) but there are seven operational nuclear research reactors, and Indonesia is about to construct the region’s first experimental power reactor by the end of the decade. If successful, the experimental power reactor will lay the foundation for the country’s and region’s first nuclear power plant. Despite projecting confidence during the period of nuclear power renaissance in the region in the last decade, none of the AMS has committed to a political decision on the use of nuclear energy and this is largely due to the Fukushima nuclear power accident in 2011. Of the ten AMS, Vietnam, Indonesia and Malaysia have demonstrated the most progress in developing nuclear energy based on the nuclear power infrastructure development assessments made by the International Atomic Energy Agency. Of these three states, Vietnam came closest to building its first nuclear power plant but decided to delay construction further due to safety and security concerns. Meanwhile, Vietnam along with Indonesia and Malaysia continue with their nuclear power infrastructure development and the remaining SEA states, with the exception of Brunei and Singapore, continue to build their expertise and capacity for nuclear power energy. At the current rate of progress, Indonesia is expected to make a national decision on the use of nuclear power by 2023 while Malaysia, the Philippines, and Thailand have included the use of nuclear power in their mid to long-term power development plans. Vietnam remains open to nuclear power but has not placed a timeline. The medium to short-term power development projection in the region suggests that the use of nuclear energy in the region is a matter of 'when' rather than 'if'. In lieu of the prospects for nuclear energy in Southeast Asia (SEA), this presentation will review the literature on ASEAN radiological emergency and preparedness response (EPR) plans and examine ASEAN’s disaster management and emergency framework. Through a combination of institutional mapping and stakeholder analysis methods, which we examine in the context of the international EPR, and nuclear safety and security regimes, we will identify the issues and challenges in developing a regional radiological EPR framework in the SEA. We will conclude with the observation that ASEAN faces serious structural, institutional and governance challenges due to the AMS inherent political structures and history of interstate conflicts, and propose that ASEAN should either enlarge the existing scope of its disaster management and response framework or that its radiological EPR framework should exist as a separate entity.

Keywords: nuclear power, nuclear accident, ASEAN, Southeast Asia

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Authors: Joshua Osondu

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This research explores how Artificial Intelligence (AI) can be utilized as a policy response to address teaching and learning (TL) issues in education in Ghana. The dual (AI and human) instructor model is used as a theoretical framework to examine how AI can be employed to improve teaching and learning processes and to equip learners with the necessary skills in the emerging AI society. A qualitative research design was employed to assess the impact of AI on various TL issues, such as teacher workloads, a lack of qualified educators, low academic performance, unequal access to education and educational resources, a lack of participation in learning, and poor access and participation based on gender, place of origin, and disability. The study concludes that AI can be an effective policy response to TL issues in Ghana, as it has the potential to increase students’ participation in learning, increase access to quality education, reduce teacher workloads, and provide more personalized instruction. The findings of this study are significant for filling in the gaps in AI research in Ghana and other developing countries and for motivating the government and educational institutions to implement AI in TL, as this would ensure quality, access, and participation in education and help Ghana industrialize.

Keywords: artificial intelligence, teacher, learner, students, policy response

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Authors: Christine K. Ormsbee, Jeremy S. Robinson

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Teacher quality is important for United States universities. It impacts student achievement, program and degree progress, and even retention. While course instructors are still the primary designers and deliverers of instruction in U.S. higher education classrooms, students have become better and more vocal consumers of instruction. They are capable of identifying what instructors do that facilitates their learning or, conversely, what instructors do that makes learning more difficult. Instructors can use students as resources as they design and implement their courses. Students have become more aware of their own learning preferences and processes and can articulate those. While it is not necessarily possible or likely that an instructor can address the widely varying differences in learning preferences represented by a large class of students, it is possible for them to employ general instructional supports that help students understand clearly the instructor's study expectations, identify critical content, efficiently commit content to memory, and develop new skills. Those learning supports include reading guides, test study guides, and other instructor-developed tasks that organize learning for students, hold them accountable for the content, and prepare them to use that material in simulated and real situations. When U.S. university teaching and learning support staff work with instructors to help them identify areas of their teaching to improve, a key part of that assistance includes talking to the instructor member's students. Students are asked to explain what the instructor does that helps them learn, what the instructor does that impedes their learning, and what they wish the instructor would do. Not surprisingly, students are very specific in what they see as helpful learning supports for them. Moreover, they also identify impediments to their success, viewing those as the instructor creating unnecessary barriers to learning. A qualitative survey was developed to provide undergraduate students the opportunity to identify instructor behaviors and/or practices that they thought helped students learn and those behaviors and practices that were perceived as hindrances to student success. That information is used to help instructors implement more student-focused learning supports that facilitate student achievement. In this session, data shared from the survey will focus on supportive instructor behaviors identified by undergraduate students in an institution located in the southwest United States and those behaviors that students perceive as creating unnecessary barriers to their academic success.

Keywords: effective teaching, pedagogy, student engagement, instructional design

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Authors: Muhammad Fajar Suardi, Fathimatufzzahra, Dela Isnaini Sendra

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Learning is an activity that has been used to do, especially for a student or academics. But a handful of people have not been using and maximizing their brains work and some also do not know a good brain work time in capturing the lessons, so that knowledge is absorbed is also less than the maximum. Indonesia Memory Sports Council (IMSC) is an institution which is engaged in the performance of the brain and the development of effective learning methods by using several techniques that can be used in considering the lessons and knowledge to grasp well, including: loci method, substitution method, and chain method. This study aims to determine the techniques and benefits of using the method given in learning and memorization by applying memory techniques taught by Indonesia Memory Sports Council (IMSC) to students and the difference if not using this method. This research uses quantitative research with survey method addressed to students of Indonesian Memory Sports Council (IMSC). The results of this study indicate that learn, understand and remember the lesson using the techniques of memory which is taught in Indonesia Memory Sport Council is very effective and faster to absorb the lesson than learning without using the techniques of memory, and this affects the academic achievement of students in each educational institution.

Keywords: chain method, Indonesia memory sports council, loci method, substitution method

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Authors: Kimberley Kennedy

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The major findings of this study discuss the importance of understanding and applying Systems thinking concepts to ensure an effective Project-Based Learning environment. A pilot project study of a major pedagogical change was conducted over a five year period with the goal to give students real world, hands-on learning experiences and the opportunity to apply what they had learned over the past two years of their business program. The first two weeks of the fifteen week semester utilized teaching methods of lectures, guest speakers and design thinking workshops to prepare students for the project work. For the remaining thirteen weeks of the semester, the students worked with actual business owners and clients on projects and challenges. The first three years of the five year study focused on student feedback to ensure a quality learning experience and continuous improvement process was developed. The final two years of the study, examined the conceptual understanding and perception of learning and teaching by faculty using Project-Based Learning pedagogy as compared to lectures and more traditional teaching methods was performed. Relevant literature was reviewed and data collected from program faculty participants who completed pre-and post-semester interviews and surveys over a two year period. Systems thinking concepts were applied to better understand the challenges for faculty using Project-Based Learning pedagogy as compared to more traditional teaching methods. Factors such as instructor and student fatigue, motivation, quality of work and enthusiasm were explored to better understand how to provide faculty with effective support and resources when using Project-Based Learning pedagogy as the main teaching method. This study provides value by presenting generalizable, foundational knowledge by offering suggestions for practical solutions to assure student and teacher engagement in Project-Based Learning courses.

Keywords: continuous improvement, project-based learning, systems thinking, teacher engagement

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Authors: Karen V. Lee

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The background and significance of this study involves research about a music teacher discovering how language development and learning can help her overcome harmful and lasting consequences from sexual violence. Education about intervention resources from language development that helps her cope with consequences influencing her career as teacher. Basic methodology involves the qualitative method of research as theoretical framework where the author is drawn into a deep storied reflection about political issues surrounding teachers who need to overcome social, psychological, and health risk behaviors from violence. Sub-themes involve available education from learning resources to ensure teachers receive social, emotional, physical, spiritual, and intervention resources that evoke visceral, emotional responses from the audience. Major findings share how language development and learning provide helpful resources to victims of violence. It is hoped the research dramatizes an episodic yet incomplete story that highlights the circumstances surrounding the protagonist’s life. In conclusion, the research has a reflexive storied framework that embraces harmful and lasting consequences from sexual violence. The reflexive story of the sensory experience critically seeks verisimilitude by evoking lifelike and believable feelings from others. Thus, the scholarly importance of using language development and learning for intervention resources can provide transformative aspects that contribute to social change. Overall, the circumstance surrounding the story about sexual violence is not uncommon in society. Language development and learning supports the moral mission to help teachers overcome sexual violence that socially impacts their professional lives as victims.

Keywords: intervention, language development and learning, sexual violence, story

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Authors: Elena Puica

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This paper aims to investigate the impact of Supply Chain Management (SCM) on the environment by applying a Machine Learning model while pointing out the efficiency of the technology used. The Machine Learning model was used to derive the efficiency and optimization of technology used in SCM and the environmental impact of SCM processes. The model applied is a predictive classification model and was trained firstly to determine which stage of the SCM has more outputs and secondly to demonstrate the efficiency of using advanced technology in SCM instead of recuring to traditional SCM. The outputs are the emissions generated in the environment, the consumption from different steps in the life cycle, the resulting pollutants/wastes emitted, and all the releases to air, land, and water. This manuscript presents an innovative approach to applying advanced technology in SCM and simultaneously studies the efficiency of technology and the SCM's impact on the environment. Identifying the conceptual relationships between SCM practices and their impact on the environment is a new contribution to the research. The authors can take a forward step in developing recent studies in SCM and its effects on the environment by applying technology.

Keywords: machine-learning model in SCM, SCM processes, SCM and the environmental impact, technology in SCM

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Authors: Cristina Vatamanu, Doina Cosovan, Dragos Gavrilut, Henri Luchian

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In the past few years, the amount of malicious software increased exponentially and, therefore, machine learning algorithms became instrumental in identifying clean and malware files through semi-automated classification. When working with very large datasets, the major challenge is to reach both a very high malware detection rate and a very low false positive rate. Another challenge is to minimize the time needed for the machine learning algorithm to do so. This paper presents a comparative study between different machine learning techniques such as linear classifiers, ensembles, decision trees or various hybrids thereof. The training dataset consists of approximately 2 million clean files and 200.000 infected files, which is a realistic quantitative mixture. The paper investigates the above mentioned methods with respect to both their performance (detection rate and false positive rate) and their practicability.

Keywords: ensembles, false positives, feature selection, one side class algorithm

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Authors: Amy M. Kwon

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Support vector machine (SVM) is a well-known algorithm in machine learning due to its superior performance, and it also functions well in multiple-instance (MI) problems. Our study proposes a schematic algorithm to select instances based on Hausdorff distance, which can be adapted to SVMs as input vectors under the MI setting. Based on experiments on five benchmark datasets, our strategy for adapting representation outperformed in comparison with original approach. In addition, task execution times (TETs) were reduced by more than 80% based on MissSVM. Hence, it is noteworthy to consider this representation adaptation to SVMs under MI-setting.

Keywords: support vector machine, Margin, Hausdorff distance, representation selection, multiple-instance learning, machine learning

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Authors: Huynh Tan Hoi

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Considered as one of the hardest languages in the world, Japanese is still the language that many young people choose to learn. Today, with the development of technology, learning foreign languages in general and Japanese language, in particular, is not an impossible barrier. Learning materials are not only from paper books, songs but also through software programs of smartphones or computers. Especially, students who begin to explore effective skills to study this language need to access modern technologies to improve their learning much better. When using the software, some students may feel embarrassed and challenged, but everything would go smoothly after a few days. After completing the course, students will get more knowledge, achieve a higher knowledge such as N2 or N1 Japanese Language Proficiency Test Certificate. In this research paper, 35 students who are studying at Ho Chi Minh City FPT University were asked to complete the questionnaire at the beginning of July up to August of 2018. Through this research, we realize that with the guidance of lecturers, the necessity of using modern software and some effective methods are indispensable in term of improving quality of teaching and learning process.

Keywords: higher knowledge, Japanese, methods, software, students

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Authors: Zahra Kazemi Saleh, Bénédicte Poulin-Charronnat, Annie Vinter

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This study examines the effects of aging on visual statistical learning, using eye-tracking techniques to investigate this cognitive phenomenon. Visual statistical learning is a fundamental brain function that enables the automatic and implicit recognition, processing, and internalization of environmental patterns over time. Some previous research has suggested the robustness of this learning mechanism throughout the aging process, underscoring its importance in the context of education and rehabilitation for the elderly. The study included three distinct groups of participants, including 21 young adults (Mage: 19.73), 20 young-old adults (Mage: 67.22), and 17 old-old adults (Mage: 79.34). Participants were exposed to a series of 12 arbitrary black shapes organized into 6 pairs, each with different spatial configurations and orientations (horizontal, vertical, and oblique). These pairs were not explicitly revealed to the participants, who were instructed to passively observe 144 grids presented sequentially on the screen for a total duration of 7 min. In the subsequent test phase, participants performed a two-alternative forced-choice task in which they had to identify the most familiar pair from 48 trials, each consisting of a base pair and a non-base pair. Behavioral analysis using t-tests revealed notable findings. The mean score for the first group was significantly above chance, indicating the presence of visual statistical learning. Similarly, the second group also performed significantly above chance, confirming the persistence of visual statistical learning in young-old adults. Conversely, the third group, consisting of old-old adults, showed a mean score that was not significantly above chance. This lack of statistical learning in the old-old adult group suggests a decline in this cognitive ability with age. Preliminary eye-tracking results showed a decrease in the number and duration of fixations during the exposure phase for all groups. The main difference was that older participants focused more often on empty cases than younger participants, likely due to a decline in the ability to ignore irrelevant information, resulting in a decrease in statistical learning performance.

Keywords: aging, eye tracking, implicit learning, visual statistical learning

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Authors: Hasti Ebrahimi

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This study sheds light on the challenges and difficulties caused by the Iranian clerical system’s intervention in the country’s school education during the COVID-19 pandemic, when schools remained closed for almost two years. The pandemic brought Iranian elementary school education to a standstill for almost 6 months before the country developed a nationwide learning platform – a customized television network. While the initiative seemed to have been welcomed by the majority of Iranian parents, it resented some of the more traditional strata of the society, including the influential Friday Prayer Leaders who found the televised version of the elementary education ‘less spiritual’ and ‘more ‘material’ or science-based. That prompted the Iranian Channel of Education, the specialized television network that had been chosen to serve as a nationally televised school during the pandemic, to try to redefine much of its online elementary school educational content within the religious ideology of the Islamic Republic of Iran. As a result, young clergies appeared on the television screen as preachers of Islamic morality, religious themes and even sociology, history, and arts. The present research delves into the consequences of such an intervention, how it might have impacted the infrastructure of Iranian elementary education and whether or not the new ideology-infused curricula would withstand the opposition of students and mainstream teachers. The main methodology used in this study is Critical Discourse Analysis with a cognitive approach. It systematically finds and analyzes the alternative ideological structures of discourse in the Iranian Channel of Education from September 2021 to July 2022, when the clergy ‘teachers’ replaced ‘regular’ history and arts teachers on the television screen for the first time. It has aimed to assess how the various uses of the alternative ideological discourse in elementary school content have influenced the processes of learning: the acquisition of knowledge, beliefs, opinions, attitudes, abilities, and other cognitive and emotional changes, which are the goals of institutional education. This study has been an effort aimed at understanding and perhaps clarifying the relationships between the traditional textual structures and processing on the one hand and socio-cultural contexts created by the clergy teachers on the other. This analysis shows how the clerical portion of elementary education on the Channel of Education that seemed to have dominated the entire televised teaching and learning process faded away as the pandemic was contained and mainstream classes were restored. It nevertheless reflects the deep ideological rifts between the clerical approach to school education and the mainstream teaching process in Iranian schools. The semantic macrostructures of social content in the current Iranian elementary school education, this study suggests, have remained intact despite the temporary ideological intervention of the ruling clerical elite in their formulation and presentation. Finally, using thematic and schematic frameworks, the essay suggests that the ‘clerical’ social content taught on the Channel of Education during the pandemic cannot have been accepted cognitively by the channel’s target audience, including students and mainstream teachers.

Keywords: televised elementary school learning, Covid 19, critical discourse analysis, Iranian clerical ideology

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Authors: Abdelghani Boudiaf

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The profusion of studies relating to the concept of organizational learning shows the importance that has been given to this concept in the management sciences. A few years ago, companies leaned towards ISO 9001 certification; this requires the implementation of the quality management system (QMS). In order for this objective to be achieved, companies must have a set of skills, which pushes them to develop learning through continuous training. The results of empirical research have shown that implementation of the QMS in the company promotes the development of learning. It should also be noted that several types of learning are developed in this sense. Given the nature of skills development is normative in the context of the quality demarche, companies are obliged to qualify and improve the skills of their human resources. Continuous training is the keystone to develop the necessary learning. To carry out continuous training, companies need to be able to identify their real needs by developing training plans based on well-defined engineering. The training process goes obviously through several stages. Initially, training has a general aspect, that is to say, it focuses on topics and actions of a general nature. Subsequently, this is done in a more targeted and more precise way to accompany the evolution of the QMS and also to make the changes decided each time (change of working method, change of practices, change of objectives, change of mentality, etc.). To answer our problematic we opted for the method of qualitative research. It should be noted that the case study method crosses several data collection techniques to explain and understand a phenomenon. Three cases of companies were studied as part of this research work using different data collection techniques related to this method.

Keywords: changing mentalities, continuing training, organizational learning, quality management system, skills development

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Authors: Maria Hopkins

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Research on student engagement is founded on a desire to improve the quality of online instruction in both course design and delivery. A high level of student engagement is associated with a wide range of educational practices including purposeful student-faculty contact, peer to peer contact, active and collaborative learning, and positive factors such as student satisfaction, persistence, achievement, and learning. By encouraging student engagement, institutions of higher education can have a positive impact on student success that leads to retention and degree completion. The current research presents the results of an online student engagement survey which support faculty teaching practices to maximize the learning experience for online students. The ‘Indicators of Engaged Learning Online’ provide a framework that measures level of student engagement. Social constructivism and collaborative learning form the theoretical basis of the framework. Social constructivist pedagogy acknowledges the social nature of knowledge and its creation in the minds of individual learners. Some important themes that flow from social constructivism involve the importance of collaboration among instructors and students, active learning vs passive consumption of information, a learning environment that is learner and learning centered, which promotes multiple perspectives, and the use of social tools in the online environment to construct knowledge. The results of the survey indicated themes that emphasized the importance of: Interaction among peers and faculty (collaboration); Timely feedback on assignment/assessments; Faculty participation and visibility; Relevance and real-world application (in terms of assignments, activities, and assessments); and Motivation/interest (the need for faculty to motivate students especially those that may not have an interest in the coursework per se). The qualitative aspect of this student engagement study revealed what instructors did well that made students feel engaged in the course, but also what instructors did not do well, which could inform recommendations to faculty when expectations for teaching a course are reviewed. Furthermore, this research provides evidence for the connection between higher student engagement and persistence and retention in online programs, which supports our rationale for encouraging student engagement, especially in the online environment because attrition rates are higher than in the face-to-face environment.

Keywords: instructional design, learning effectiveness, online learning, student engagement

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Authors: Mashaal Hooda

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The rationale for conducting this action research was to increase students' Academic Achievement (AA) contexts of studying/researching by employing the Goal Setting intervention (GS). The purposive sample consisted of 10 female undergraduate students at a university in Dubai. The intervention was introduced through workshop classes conducted online. The pre-intervention consisted of discussions concentrating on participants' research contexts amidst a pandemic. The GS moderators were implemented in the class, followed by scaffolding and mentoring interactions and self-reflective accounts of students' actions and feelings of using the intervention to better plan and structure their dissertation tasks. The research incorporated a Mixed Methods Methodology (MMM). Quantitative data collection took place through surveys, while qualitative data were collected using semi-structured interviews. Triangulation of the emergent themes showed a positive increase in students achievable GS, self-regulatory study skills, feedback-seeking behaviours, research organisation and synthesis, self-reflection and Academic Resilient (AR) attitudes amalgamate to enhance students' AA outcomes. Though, students' intrinsic motivational levels to study and research observed minor changes only. Nonetheless, the pebble in the shoe was removed as students AA contexts improved in undertaking better actionable steps for their research. Therefore, the GS intervention enabled students to set, balance, and achieve academic goals while catering to their academic anxieties, mental health concerns, and adaptability to the e-learning platforms amidst the COVID-19 pandemic. Despite the wide-scale changes the pandemic brought to the teaching and learning communities, the GS intervention served as a targeted intervention to help students maintain their achievement contexts in a goal-oriented way.

Keywords: academic achievement, acadeic resilience, COVID-19, goal setting

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Authors: Y. L. Chang, Y. H. Huang

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This study designed a mobile guide system that integrates the design principles of guidance and interpretation with augmented reality (AR) as an auxiliary tool for National Taiwan Science Education Center guidance and explored the learning performance of participants who were divided into two visiting groups: AR-guided mode and non-guided mode (without carrying any auxiliary devices). The study included 96 college students as participants and employed a quasi-experimental research design. This study evaluated the learning performance of education center students aided with different guided modes, including their flow experience, activity involvement, learning effects, as well as their attitude and acceptance of using the guide systems. The results showed that (a) the AR guide promoted visitors’ flow experience; (b) the AR-guidance activity involvement and flow experience having a significant positive effect; (c) most of the visitors of mobile guide system with AR elicited a positive response and acceptance attitude. These results confirm the necessity of human–computer–context interaction. Future research can continue exploring the advantages of enhanced learning effectiveness, activity involvement, and flow experience through application of the results of this study.

Keywords: augmented reality, mobile guide system, informal learning, flow experience, activity involvement

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Authors: Andrea Treviño Gavito, Diego Klabjan, Sanjiv J. Shah

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Echocardiograms serve as pivotal resources for clinicians in diagnosing cardiac conditions, offering non-invasive insights into a heart’s structure and function. When echocardiographic studies are conducted, no standardized labeling of the acquired views is performed. Employing machine learning algorithms for automated echocardiogram view detection has emerged as a promising solution to enhance efficiency in echocardiogram use for diagnosis. However, existing approaches predominantly rely on supervised learning, necessitating labor-intensive expert labeling. In this paper, we introduce a fully unsupervised echocardiographic view detection framework that leverages convolutional autoencoders to obtain lower dimensional representations and the K-means algorithm for clustering them into view-related groups. Our approach focuses on discriminative patches from echocardiographic frames. Additionally, we propose a trainable inverse average layer to optimize decoding of average operations. By integrating both public and proprietary datasets, we obtain a marked improvement in model performance when compared to utilizing a proprietary dataset alone. Our experiments show boosts of 15.5% in accuracy and 9.0% in the F-1 score for frame-based clustering, and 25.9% in accuracy and 19.8% in the F-1 score for view-based clustering. Our research highlights the potential of unsupervised learning methodologies and the utilization of open-sourced data in addressing the complexities of echocardiogram interpretation, paving the way for more accurate and efficient cardiac diagnoses.

Keywords: artificial intelligence, echocardiographic view detection, echocardiography, machine learning, self-supervised representation learning, unsupervised learning

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Authors: Csilla Paksi-Petró

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The Hungarian national public administration training system providing continuous, lifelong further training to some ten thousand executives in public administration was launched in 2014, adding skills and competency development to the previous training solutions, which had a mainly legal and professional approach. The executive training system is being continuously developed since tackling the existing qualitative, and quantitative challenges calls for the introduction of novel, innovative solutions. With a gap-filling character, this study presents, in brief, the last eight years of system of executive training in public administration, supported by the outcomes of the author's empirical research, makes suggestions for the possible directions of its further development. Through this article, the reader may obtain an overview of the current Hungarian civil service further training system, its institution system, the method of its application, its target groups, its results, and its development prospects. By reading the article, the reader will get acquainted with the good practices of the Hungarian civil service further training system.

Keywords: coaching, e-learning, executive development, further-training

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Authors: Julius Onyancha, Valentina Plekhanova

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One of the significant issues facing web users is the amount of noise in web data which hinders the process of finding useful information in relation to their dynamic interests. Current research works consider noise as any data that does not form part of the main web page and propose noise web data reduction tools which mainly focus on eliminating noise in relation to the content and layout of web data. This paper argues that not all data that form part of the main web page is of a user interest and not all noise data is actually noise to a given user. Therefore, learning of noise web data allocated to the user requests ensures not only reduction of noisiness level in a web user profile, but also a decrease in the loss of useful information hence improves the quality of a web user profile. Noise Web Data Learning (NWDL) tool/algorithm capable of learning noise web data in web user profile is proposed. The proposed work considers elimination of noise data in relation to dynamic user interest. In order to validate the performance of the proposed work, an experimental design setup is presented. The results obtained are compared with the current algorithms applied in noise web data reduction process. The experimental results show that the proposed work considers the dynamic change of user interest prior to elimination of noise data. The proposed work contributes towards improving the quality of a web user profile by reducing the amount of useful information eliminated as noise.

Keywords: web log data, web user profile, user interest, noise web data learning, machine learning

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Authors: Konstantinos Perifanos, Eirini Florou, Dionysis Goutsos

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This paper presents and benchmarks a number of end-to-end Deep Learning based models for metaphor detection in Greek. We combine Convolutional Neural Networks and Recurrent Neural Networks with representation learning to bear on the metaphor detection problem for the Greek language. The models presented achieve exceptional accuracy scores, significantly improving the previous state-of-the-art results, which had already achieved accuracy 0.82. Furthermore, no special preprocessing, feature engineering or linguistic knowledge is used in this work. The methods presented achieve accuracy of 0.92 and F-score 0.92 with Convolutional Neural Networks (CNNs) and bidirectional Long Short Term Memory networks (LSTMs). Comparable results of 0.91 accuracy and 0.91 F-score are also achieved with bidirectional Gated Recurrent Units (GRUs) and Convolutional Recurrent Neural Nets (CRNNs). The models are trained and evaluated only on the basis of training tuples, the related sentences and their labels. The outcome is a state-of-the-art collection of metaphor detection models, trained on limited labelled resources, which can be extended to other languages and similar tasks.

Keywords: metaphor detection, deep learning, representation learning, embeddings

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Authors: Degale Desta, Cheng Jian

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The most important factor in identifying a person is their face. Even identical twins have their own distinct faces. As a result, identification and face recognition are needed to tell one person from another. A face recognition system is a verification tool used to establish a person's identity using biometrics. Nowadays, face recognition is a common technique used in a variety of applications, including home security systems, criminal identification, and phone unlock systems. This system is more secure because it only requires a facial image instead of other dependencies like a key or card. Face detection and face identification are the two phases that typically make up a human recognition system.The idea behind designing and creating a face recognition system using deep learning with Azure ML Python's OpenCV is explained in this paper. Face recognition is a task that can be accomplished using deep learning, and given the accuracy of this method, it appears to be a suitable approach. To show how accurate the suggested face recognition system is, experimental results are given in 98.46% accuracy using Fast-RCNN Performance of algorithms under different training conditions.

Keywords: deep learning, face recognition, identification, fast-RCNN

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Authors: Anne N. Heirman, Lisette van der Molen, Richard Dirven, Gyorgi B. Halmos, Michiel W.M. van den Brekel

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Background: Due to the rising incidence of oropharyngeal squamous cell cancer (OPSCC), many patients are challenged with choosing between transoral(robotic) surgery and radiotherapy, with equal survival and oncological outcomes. Also, functional outcomes are of little difference over the years. With this study, the wants and needs of patients and caregivers are identified to develop a comprehensible patient decision aid (PDA). Methods: The development of this PDA is based on the International Patient Decision Aid Standards criteria. In phase 1, relevant literature was reviewed and compared to current counseling papers. We interviewed ten post-treatment patients and ten doctors from four head and neck centers in the Netherlands, which were transcribed verbatim and analyzed. With these results, the first draft of the PDA was developed. Phase 2 beholds testing the first draft for comprehensibility and usability. Phase 3 beholds testing for feasibility. After this phase, the final version of the PDA was developed. Results: All doctors and patients agreed a PDA was needed. Phase 1 showed that 50% of patients felt well-informed after standard care and 35% missed information about treatment possibilities. Side effects and functional outcomes were rated as the most important for decision-making. With this information, the first version was developed. Doctors and patients stated (phase 2) that they were satisfied with the comprehensibility and usability, but there was too much text. The PDA underwent text reduction revisions and got more graphics. After revisions, all doctors found the PDA feasible and would contribute to regular counseling. Patients were satisfied with the results and wished they would have seen it before their treatment. Conclusion: Decision-making for OPSCC should focus on differences in side-effects and functional outcomes. Patients and doctors found the PDA to be of great value. Future research will explore the benefits of the PDA in clinical practice.

Keywords: head-and-neck oncology, oropharyngeal cancer, patient decision aid, development, shared decision making

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Authors: Diriba Gemechu, Lamessa Abebe

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The aim of this study was to examine the effect of cooperative learning method on student’s academic achievement and on the achievement level over a usual method in teaching different topics of mathematics. The study also examines the perceptions of students towards cooperative learning. Cooperative learning is the instructional strategy in which pairs or small groups of students with different levels of ability work together to accomplish a shared goal. The aim of this cooperation is for students to maximize their own and each other learning, with members striving for joint benefit. The teacher’s role changes from wise on the wise to guide on the side. Cooperative learning due to its influential aspects is the most prevalent teaching-learning technique in the modern world. Therefore the study was conducted in order to examine the effect of cooperative learning on the academic achievement of grade 9 students in Mathematics in case of Mettu secondary school. Two sample sections are randomly selected by which one section served randomly as an experimental and the other as a comparison group. Data gathering instruments are achievement tests and questionnaires. A treatment of STAD method of cooperative learning was provided to the experimental group while the usual method is used in the comparison group. The experiment lasted for one semester. To determine the effect of cooperative learning on the student’s academic achievement, the significance of difference between the scores of groups at 0.05 levels was tested by applying t test. The effect size was calculated to see the strength of the treatment. The student’s perceptions about the method were tested by percentiles of the questionnaires. During data analysis, each group was divided into high and low achievers on basis of their previous Mathematics result. Data analysis revealed that both the experimental and comparison groups were almost equal in Mathematics at the beginning of the experiment. The experimental group out scored significantly than comparison group on posttest. Additionally, the comparison of mean posttest scores of high achievers indicates significant difference between the two groups. The same is true for low achiever students of both groups on posttest. Hence, the result of the study indicates the effectiveness of the method for Mathematics topics as compared to usual method of teaching.

Keywords: academic achievement, comparison group, cooperative learning, experimental group

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Authors: Kazumoto Tanaka

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It is well known that sport skill learning is facilitated by video observation of players’ actions in sports. The optimal viewpoint for the observation of actions depends on sport scenes. On the other hand, it is impossible to change viewpoint for the observation in general, because most videos are filmed from fixed points. The study has tackled the problem and focused on karate match as a first step. The study developed a method for observing karate player’s actions from any point of view by using 3D-CG model (i.e. virtual player) obtained from video images, and verified the effectiveness of the method on karate match.

Keywords: computer graphics, karate training, learning by observation, motion capture, virtual player

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Authors: Budoor Al Abid

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Educational systems are increasingly provided as open online services, providing guidance and support for individual learners. To adapt the learning systems, a proper evaluation must be made. This paper builds the evaluation model Fuzzy C Means Adaptive System (FCMAS) based on data mining techniques to assess the difficulty of the questions. The following steps are implemented; first using a dataset from an online international learning system called (slepemapy.cz) the dataset contains over 1300000 records with 9 features for students, questions and answers information with feedback evaluation. Next, a normalization process as preprocessing step was applied. Then FCM clustering algorithms are used to adaptive the difficulty of the questions. The result is three cluster labeled data depending on the higher Wight (easy, Intermediate, difficult). The FCM algorithm gives a label to all the questions one by one. Then Random Forest (RF) Classifier model is constructed on the clustered dataset uses 70% of the dataset for training and 30% for testing; the result of the model is a 99.9% accuracy rate. This approach improves the Adaptive E-learning system because it depends on the student behavior and gives accurate results in the evaluation process more than the evaluation system that depends on feedback only.

Keywords: machine learning, adaptive, fuzzy logic, data mining

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Authors: Reiko Yamamoto

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This paper reports on how synchrony occurs between children and their teacher, and what prevents or facilitates synchrony. The aim of the experiment conducted in this study was to precisely analyze their movements and synchrony and reveal the process of synchrony in a real-world classroom. Specifically, the experiment was conducted for around 20 minutes during an English as a foreign language (EFL) lesson. The participants were 11 fourth-grade school children and their classroom teacher in a public elementary school in Japan. Previous researchers assert that synchrony causes the state of flow in a class. For checking the level of flow, Short Flow State Scale (SFSS) was adopted. The experimental procedure had four steps: 1) The teacher read aloud the first half of an English storybook to the children. Both the teacher and the children were at their own desks. 2) The children were subjected to an SFSS check. 3) The teacher read aloud the remaining half of the storybook to the children. She made the children remove their desks before reading. 4) The children were again subjected to an SFSS check. The movements of all participants were recorded with a video camera. From the movement analysis, it was found that the children synchronized better with the teacher in Step 3 than in Step 1, and that the teacher’s movement became free and outstanding without a desk. This implies that the desk acted as a barrier between the children and the teacher. Removal of this barrier resulted in the children’s reactions becoming synchronized with those of the teacher. The SFSS results proved that the children experienced more flow without a barrier than with a barrier. Apparently, synchrony is what caused flow or social emotions in the classroom. The main conclusion is that synchrony leads to cognitive outcomes such as children’s academic performance in EFL learning.

Keywords: engagement in a class, English as a foreign language (EFL) learning, interactional synchrony, social emotions

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Authors: Donghee Noh, Seonhyeong Kim, Junhwan Choi, Heegon Kim, Sooho Jung, Keunho Park

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In this paper, we describe an image post-processing method to enhance the performance of the parcel segmentation method using deep learning-based aerial images conducted in previous studies. The study results were evaluated using a confusion matrix, IoU, Precision, Recall, and F1-Score. In the case of the confusion matrix, it was observed that the false positive value, which is the result of misclassification, was greatly reduced as a result of image post-processing. The average IoU was 0.9688 in the image post-processing, which is higher than the deep learning result of 0.8362, and the F1-Score was also 0.9822 in the image post-processing, which was higher than the deep learning result of 0.8850. As a result of the experiment, it was found that the proposed technique positively complements the deep learning results in segmenting the parcel of interest.

Keywords: aerial image, image process, machine vision, open field smart farm, segmentation

Procedia PDF Downloads 74