Search results for: embedded learning support

Authors: Paula Lazarim

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As global mobility thrives, researchers emphasize the urgency of global literacy through training qualified counselors to serve internationally in a culturally competent manner. However, the focus thus far has been on how counselors’ preparation to approach international populations fuses with study abroad experiential learning short-term immersions. Looking for better solutions for cultural competency and skills learning related to international counseling, the author of this manuscript examines international counseling's current status, learning scope and goals, and educational opportunities. A guiding framework grounded on relational pedagogy (Reeves & Le Mare, 2017), relational cultural theory (Jordan, 2017), and intercultural education (Nastasi et al., 2020) is applied with four long-term educational modality projects designed to benefit cultural competence, attitude, relational skills development, and learning an intercultural counseling approach. Suggestions that encourage innovative instruction in counselor education and counseling programs at master and doctoral levels, stimulate self-learning, and educate in intercultural relational competence are linked to strategies for engaging in international counseling based on findings of a literature review and training-projects implementation. Ultimately, the author highlights theoretical and practical implications of suitable training to improve counselors' performance and discusses long-term teaching-learning opportunities that positively impact the international counseling community by sending out internationally culturally competent counselors.

Keywords: international counseling, counselor education, counseling, relational pedagogy, intercultural education, counselors’ training

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Authors: Yanyue Yuan

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In this paper, the author shares the findings of a pilot study that examines students’ creative expressions and their perceptions of creativity when engaged in project-based learning. The study is based on an elective course that the author co-designed and co-taught with a colleague to sixteen grade six and seven students over the spring semester in 2019. Using the Little Prince story as the main prompt, they facilitated students’ original creation of a storytelling concert that integrated script writing, music production, lyrics, songs, and visual design as a result of both individual and collaborative work. The author will share the specific challenges we met during the project, including learning cultures of the school, class management, teachers' and parents’ attitude, process-oriented versus product-oriented mindset, and facilities and logistical resources. The findings of this pilot study will inform the ongoing research initiative of exploring how we can foster creative learning in public schools in the Chinese context. While K-12 schools of China’s public education system are still dominated by exam-oriented and teacher-centered approaches, the author proposes that expression-based learning can be a starting point for promoting students’ creativity and can serve as experimental efforts to initiate incremental changes within the current education framework. The paper will also touch upon insights gained from collaborations between university and K-12 schools.

Keywords: creativity, expression-based learning, K-12, incremental changes

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Authors: Badriah Algarni

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The pedagogy of ‘flipped learning’ is a form of blended instruction which is gaining widespread attention throughout the world. However, there is a lack of research concerning teachers’ professional development (TPD) in teachers who use flipping. The aim of this study was, therefore, to identify teachers’ perspectives on their experience of flipped PD. The study used a qualitative approach. Purposive sampling recruited nineteen teachers who participated in semi-structured, in-depth interviews. Thematic analysis was used to analyse the interview data. Overall, the teachers reported feeling more confident in their knowledge and skills after participating in flipped TPD. The analysis of the interview data revealed five overarching themes:1) increased engagement with the content; 2) better use of resources; 3) a social, collaborative environment; 4) exchange of practices and experiences; and 5) valuable online activities. These findings can encourage educators, policymakers, and trainers to consider flipped TPD as a form of PD to promote the building of teachers’ knowledge and stimulate reflective practices to improve teaching and learning practices.

Keywords: engagement, flipped learning, teachers’ professional development, collaboration

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Authors: Denise Levy, Helen J. Khoury

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Nuclear technology is a controversial issue among a great share of the Brazilian population. Misinformation and common wrong beliefs confuse public’s perceptions and the scientific community is expected to offer a wider perspective on the benefits and risks resulting from ionizing radiation in everyday life. Attentive to the need of new approaches between science and society, the Nuclear Energy Museum, in northeast Brazil, is an initiative created to communicate the growing impact of the beneficial applications of nuclear technology in medicine, industry, agriculture and electric power generation. Providing accessible scientific information, the museum offers a rich learning environment, making use of different educational strategies, such as films, interactive panels and multimedia learning tools, which not only increase the enjoyment of visitors, but also maximize their learning potential. Developed according to modern active learning instructional strategies, multimedia materials are designed to present the increasingly role of nuclear science in modern life, transforming science education into a meaningful learning experience. In year 2016, nine different interactive computer-based activities were developed, presenting curiosities about ionizing radiation in different landmarks around the world, such as radiocarbon dating works in Egypt, nuclear power generation in France and X-radiography of famous paintings in Italy. Feedback surveys have reported a high level of visitors’ satisfaction, proving the high quality experience in learning nuclear science at the museum. The Nuclear Energy Museum is the first and, up to the present time, the only permanent museum in Brazil devoted entirely to nuclear science.

Keywords: nuclear technology, multimedia learning tools, science museum, society and education

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Authors: Karen Hong

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Smart tactile textiles are a series of textile-based products that incorporates smart embedded technology to be utilized as tactile therapeutic applications for 2 main groups of target users. The first group of users will be children with sensory processing disorder who are suffering from tactile sensory dysfunction. Children with tactile sensory issues may have difficulty tolerating the sensations generated from the touch of certain textures on the fabrics. A series of smart tactile textiles, collectively known as ‘Tactile Toys’ are developed as tactile therapy play objects, exposing children to different types of touch sensations within textiles, enabling them to enjoy tactile experiences together with interactive play which will help them to overcome fear of certain touch sensations. The second group of users will be the elderly or geriatric patients who are suffering from deteriorating sense of touch. One of the common consequences of aging is suffering from deteriorating sense of touch and a decline in motoric function. With the focus in stimulating the sense of touch for this particular group of end users, another series of smart tactile textiles, collectively known as ‘Tactile Aids’ are developed also as tactile therapy. This range of products can help to maintain touch sensitivity and at the same time allowing the elderly to enjoy interactive play to practice their hand-eye coordination and enhancing their motor skills. These smart tactile textile products are being designed and tested out by the end users and have proofed their efficacy as tactile therapy enabling the users to lead a better quality of life.

Keywords: smart textiles, embedded technology, tactile therapy, tactile aids, tactile toys

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Authors: Saliha Ozcan

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Technology has become an integral part of our lives, aiding individuals in accessing higher order competencies, such as global awareness, creativity, collaborative problem solving, and self-directed learning. Students need to acquire these competencies, often referred to as 21st century skills, in order to adapt to a fast changing world. Today, an ever-increasing number of schools are exploring how engagement through telecollaboration can support language learning and promote 21st century skill development in classrooms. However, little is known regarding how telecollaboration may influence the way students acquire 21st century skills. In this paper, we aim to shed light to the potential implications of telecollaborative practices in acquisition of 21st century skills. In our context, telecollaboration, which might be carried out in a variety of settings both synchronously or asynchronously, is considered as the process of communicating and working together with other people or groups from different locations through online digital tools or offline activities to co-produce a desired work output. The study presented here will describe and analyse the implementation of a telecollaborative project between two high school classes, one in Spain and the other in Sweden. The students in these classes were asked to carry out some joint activities, including creating an online platform, aimed at raising awareness of the situation of the Syrian refugees. We conduct a qualitative study in order to explore how language, culture, communication, and technology merge into the co-construction of knowledge, as well as supporting the attainment of the 21st century skills needed for network-mediated communication. To this end, we collected a significant amount of audio-visual data, including video recordings of classroom interaction and external Skype meetings. By analysing this data, we verify whether the initial pedagogical design and intended objectives of the telecollaborative project coincide with what emerges from the actual implementation of the tasks. Our findings indicate that, as well as planned activities, unplanned classroom interactions may lead to acquisition of certain 21st century skills, such as collaborative problem solving and self-directed learning. This work is part of a wider project (KONECT, EDU2013-43932-P; Spanish Ministry of Economy and Finance), which aims to explore innovative, cross-competency based teaching that can address the current gaps between today’s educational practices and the needs of informed citizens in tomorrow’s interconnected, globalised world.

Keywords: 21st century skills, telecollaboration, language learning, network mediated communication

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Authors: Maria Georgiou

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This study examined whether there was a statistically significant difference between pretest and posttest achievement scores for students who received multimedia-based instructions in science. The paired samples t-test was used to address the research question and to establish whether there was a significant difference between pretest and posttest scores that may have occurred based on the students’ learning experience with multimedia technology. Findings indicated that there was a significant difference in students’ achievement scores before and after a multimedia-based instruction. Students’ achievement scores were increased by approximately two points, after students received multimedia-based instruction. On a paired samples t-test, a high level of significance was found, p = 0.000. Opportunities to learn with multimedia are more likely to result in sustained improvements in student achievement and a deeper understanding of science content. Multimedia can make learning more active and student-centered and activate student motivation.

Keywords: constructivist learning, hyperstudio, multimedia, multimedia-based instruction

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Authors: Shurui Bai, Biyun Huang, Khe Foon Hew

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Gamification is defined as the use of game design elements in non-game contexts. The primary purpose of using gamification in an educational context is to engage students in school activities such that their likelihood of completion is increased. But how actually effective is gamification in improving student learning? In order to answer this question, this paper provides a systematic review of prior research studies on gamification in K-12 and university contexts limited to computer science discipline. Unlike other published gamification review works, we specifically analyzed comparison-based studies in quasi-experiment, historical control, and randomization rather than studies with mere anecdotal or phenomenological results. The main purpose for this is to discuss possible causal effects of gamified practices on student performance, behavior change, and perceptual skills following an integrative model. Implications for practice are discussed, along with several suggestions for future research studies.

Keywords: computer science, gamification, learning performance, systematic review

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Authors: Naziema B. Jappie

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The objective of this study is to examine the relationship between college readiness characteristics and learning outcome assessment scores. About this, it is important to examine the first-year retention and success rate. In order to undertake this study, it will be necessary to look at proficiency levels on general and domain-specific knowledge and skills reflected on national benchmark test scores (NBT), in-college interventions and course-taking patterns. Preliminary results based on data from more than 1000 students suggest that there is a positive association between NBT scores and students’ 1st-year college GPA and their retention status. For example, 63% of students with a proficient level of math skills in the NBT had the highest level of GPA at the end of 1st-year of college in comparison to 56% of those who started with a primary or intermediate level, respectively. The retention rates among those with proficiency levels were also higher than those with basic or intermediate levels (98% vs. 93% and 88%, respectively). By the end of 3rd year in college, students with intermediate or proficient entering NBT math skills had 7% and 8% of dropout rate, compared to 14% for those started at primary level; a greater percentage of students qualified by the end of 3rd-year qualified among proficient students than that among intermediate or basic level students (50% vs. 44% and 27% respectively). The findings of this study added knowledge to the field in South Africa and are expected to help stakeholders and policymakers to better understand college learning and challenges for students with disadvantaged backgrounds and provide empirical evidence in support of related practices and policies.

Keywords: assessment, data analysis, performance, proficiency, policy, student success

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Authors: Pachawo Bisani, Goodall Nyirenda

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The Malawi National Antiretroviral Therapy (NART) Electronic Medical Record (EMR) system was designed and developed with guidance from the Ministry of Health through the Department of HIV and AIDS (DHA) with the aim of supporting the management of HIV patient data and reporting in high prevalence ART clinics. As of 2021, the system has been scaled up to over 206 facilities across the country. The system is integrated with the clinical decision support system (CDSS) to assist healthcare providers in making a decision about an individual patient at a particular point in time. Despite NART EMR undergoing several evaluations and assessments, little has been done to evaluate the clinical decision support system in the NART EMR system. Hence, the study aimed to evaluate the use of CDSS in the NART EMR system in Malawi. The study adopted a mixed-method approach, and data was collected through interviews, observations, and questionnaires. The study has revealed that the CDSS tools were integrated into the ART clinic workflow, making it easy for the user to use it. The study has also revealed challenges in system reliability and information accuracy. Despite the challenges, the study further revealed that the system is effective and efficient, and overall, users are satisfied with the system. The study recommends that the implementers focus more on the logic behind the clinical decision-support intervention in order to address some of the concerns and enhance the accuracy of the information supplied. The study further suggests consulting the system's actual users throughout implementation.

Keywords: clinical decision support system, electronic medical record system, usability, antiretroviral therapy

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Authors: Gayathri Nagarajan, L. D. Dhinesh Babu

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Health care is one of the prominent industries that generate voluminous data thereby finding the need of machine learning techniques with big data solutions for efficient processing and prediction. Missing data, incomplete data, real time streaming data, sensitive data, privacy, heterogeneity are few of the common challenges to be addressed for efficient processing and mining of health care data. In comparison with other applications, accuracy and fast processing are of higher importance for health care applications as they are related to the human life directly. Though there are many machine learning techniques and big data solutions used for efficient processing and prediction in health care data, different techniques and different frameworks are proved to be effective for different applications largely depending on the characteristics of the datasets. In this paper, we present a framework that uses ensemble machine learning technique gradient boosted trees for data classification in health care big data. The framework is built on Spark platform which is fast in comparison with other traditional frameworks. Unlike other works that focus on a single technique, our work presents a comparison of six different machine learning techniques along with gradient boosted trees on datasets of different characteristics. Five benchmark health care datasets are considered for experimentation, and the results of different machine learning techniques are discussed in comparison with gradient boosted trees. The metric chosen for comparison is misclassification error rate and the run time of the algorithms. The goal of this paper is to i) Compare the performance of gradient boosted trees with other machine learning techniques in Spark platform specifically for health care big data and ii) Discuss the results from the experiments conducted on datasets of different characteristics thereby drawing inference and conclusion. The experimental results show that the accuracy is largely dependent on the characteristics of the datasets for other machine learning techniques whereas gradient boosting trees yields reasonably stable results in terms of accuracy without largely depending on the dataset characteristics.

Keywords: big data analytics, ensemble machine learning, gradient boosted trees, Spark platform

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Authors: Andreas D. Jansson

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The availability of inexpensive, yet competent hardware allows for increased level of automation and self-optimization in the context of Industry 4.0. However, such agents require high quality information about their surroundings along with a robust strategy for collision avoidance, as they may cause expensive damage to equipment or other agents otherwise. Manually defining a strategy to cover all possibilities is both time-consuming and counter-productive given the capabilities of modern hardware. This paper explores the idea of a model-free self-optimizing obstacle avoidance strategy for multiple autonomous agents in a simulated dynamic environment using the Q-learning algorithm.

Keywords: autonomous vehicles, industry 4.0, multi-agent system, obstacle avoidance, Q-learning, simulation

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Authors: Stela Doncheva

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Postpartum distress, encompassing depressive symptoms, obsessions, and anxiety, remains a subject of significant scientific interest due to its prevalence among individuals giving birth. This critical and transformative period presents a multitude of factors that impact women's health. On the one hand, variables such as social support, satisfaction in romantic relationships, shared newborn care, and birth satisfaction directly affect the mental well-being of new mothers. On the other hand, the interplay of hormonal changes, personality characteristics, emotional difficulties, and the profound life adjustments experienced by mothers can profoundly influence their self-esteem and overall physical and emotional well-being. This paper extensively explores the factors of alexithymia, social support, partners' support, and birth satisfaction to gain deeper insights into their impact on postpartum distress. Utilizing a qualitative survey consisting of six self-reflective questionnaires, this study collects valuable data regarding the individual postpartum experiences of Bulgarian mothers. The primary objective is to enrich our understanding of the complex factors involved in the development of postpartum distress during this crucial period. The results shed light on the intricate nature of the problem and highlight the significant influence of bio-psycho-social elements. By contributing to the existing knowledge in the field, this research provides valuable implications for the development of interventions and support systems tailored to the unique needs of mothers in the postpartum period. Ultimately, this study aims to improve the overall well-being of new mothers and promote optimal maternal health during the postpartum journey.

Keywords: maternal mental health, postpartum distress, postpartum depression, postnatal mothers

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Authors: Ratun Rahman, Rafid Islam, Akin Ahmed, Kamrul Hasan, Hasan Mahmud

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Malware is becoming more prevalent, and several threat categories have risen dramatically in recent years. This paper provides a bird's-eye view of the world of malware analysis. The efficiency of five different machine learning methods (Naive Bayes, K-Nearest Neighbor, Decision Tree, Random Forest, and TensorFlow Decision Forest) combined with features picked from the retrieval of Android permissions to categorize applications as harmful or benign is investigated in this study. The test set consists of 1,168 samples (among these android applications, 602 are malware and 566 are benign applications), each consisting of 948 features (permissions). Using the permission-based dataset, the machine learning algorithms then produce accuracy rates above 80%, except the Naive Bayes Algorithm with 65% accuracy. Of the considered algorithms TensorFlow Decision Forest performed the best with an accuracy of 90%.

Keywords: android malware detection, machine learning, malware, malware analysis

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Authors: Elisa Monteiro, Kiiko Ikegami

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The inclusion of children with diverse learning needs and/or disabilities in regular classrooms has been identified as crucial to the provision of educational equity and quality for all students. In this, teachers play an essential role, as they have a strong impact on student attainment. Whilst the adoption of inclusive practice is increasing, with potential benefits for the teaching profession, there is also a rise in the level of its challenges in Macao as many more students with learning disabilities are now being included in general education classes. Consequently, there has been a significant focus on teacher professional development to ensure that teachers are adequately prepared to teach in inclusive classrooms that give access to diverse students. Major changes in teacher education will need to take place to include more inclusive education content and to equip teachers with the necessary skills in the area of inclusive practice. This paper draws on data from in-depth interviews with 20 teachers to examine teachers’ views of support, challenges, and barriers to inclusive practices at the school and classroom levels. Thematic analysis was utilised to determine major themes within the data. Several themes emerged and serve to illustrate the identified barriers and the potential value of effective teacher education. Suggestions for increased professional development opportunities for inclusive education specific to higher education institutions are presented and the implications for practice and teacher education are discussed.

Keywords: inclusion, inclusive practice, teacher education, higher education

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Authors: Neha Singh, Shristi Singh

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Accidents involving motor vehicles are more likely to cause serious injuries and fatalities. It also has a host of other perpetual issues, such as the regular loss of life and goods in accidents. To solve these issues, appropriate measures must be implemented, such as establishing an autonomous incident detection system that makes use of machine learning and artificial intelligence. In order to reduce traffic accidents, this article examines the overview of artificial intelligence and machine learning in autonomous event detection systems. The paper explores the major issues, prospective solutions, and use of artificial intelligence and machine learning in road transportation systems for minimising traffic accidents. There is a lot of discussion on additional, fresh, and developing approaches that less frequent accidents in the transportation industry. The study structured the following subtopics specifically: traffic management using machine learning and artificial intelligence and an incident detector with these two technologies. The internet of vehicles and vehicle ad hoc networks, as well as the use of wireless communication technologies like 5G wireless networks and the use of machine learning and artificial intelligence for the planning of road transportation systems, are elaborated. In addition, safety is the primary concern of road transportation. Route optimization, cargo volume forecasting, predictive fleet maintenance, real-time vehicle tracking, and traffic management, according to the review's key conclusions, are essential for ensuring the safety of road transportation networks. In addition to highlighting research trends, unanswered problems, and key research conclusions, the study also discusses the difficulties in applying artificial intelligence to road transport systems. Planning and managing the road transportation system might use the work as a resource.

Keywords: artificial intelligence, machine learning, incident detector, road transport systems, traffic management, automatic incident detection, deep learning

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Authors: Aloysius Hardoko, Susilo

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The root cause of the problem after the environmental damage due to coal mining activities defined as the province of East Kalimantan corridor masterplan economic activity accelerated the expansion of Indonesia's economic development (MP3EI) is the behavior of adults. Adult behavior can be changed through knowledge management and attitude. Based on the root of the problem, the objective of the research is to apply knowledge management and attitude based on holistic approach in learning andragogy as an effort to solve environmental problems after coal mining activities. Research methods to achieve the objective of using quantitative research with pretest postes group design. Knowledge management and attitudes based on a holistic approach in adult learning are applied through initial learning activities, core and case-based cover of environmental damage. The research instrument is a description of the case of environmental damage. The data analysis uses t-test to see the effect of knowledge management attitude based on holistic approach before and after adult learning. Location and sample of representative research of adults as many as 20 people in Kutai Kertanegara District, one of the districts in East Kalimantan province, which suffered the worst environmental damage. The conclusion of the research result is the application of knowledge management and attitude in adult learning influence to adult knowledge and attitude to overcome environmental problem post-coal mining activity.

Keywords: knowledge management and attitude, holistic approach, andragogy learning, environmental Issue

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Authors: Chanaphop Vannaolarn, Weena Eiamprapai

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Thai noblewomen and lady-in-waiting in the era of King Rama V stayed only inside the palace. King Rama V decided to build Dusit Palace in 1897 and another palace called Suan Sunandha in 1900 after his royal visit to Europe. This palace became the residence for noblewomen in the court until the change of political system in 1932. The study about noblewomen in the palace can educate people about how our nation was affected by western civilization in terms of architecture, food, outfit and recreations. It is a way to develop the modern society by studying the great historical value of the past. A learning center about noblewomen will not only provide knowledge but also create bond and patriotic feeling among Thais.

Keywords: noblewomen, palace, management, learning center

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Authors: Fenni Sim

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Background: The application of systemic family therapy approaches to community health cases have not gathered traction. In National Kidney Foundation, Singapore, the belief is that community support has great potential in helping End Stage Renal Failure (ESRF) patients manage the demands of their treatment regime, whether Hemodialysis (HD) or Peritoneal Dialysis(PD) and sustain them on the treatment. However, the current community support does not include family interventions and is largely nursing based. Although nursing support is well provided to patients, and their family members in issues related to treatment and compliance, complex family issues and dynamics arising from caregiver strain or pre-dialysis relationship strain might deter efforts in managing the challenges of the treatment. Objective: The objective of the study is to understand the potential scope of work provided by a social worker who is trained in systemic family therapy and the effects of these interventions. Methodology: 3 families on HD and 3 families on PD who have been receiving family intervention for the past 6 months would be chosen for the study. A qualitative interview would be conducted to review the effectiveness for the family. Scales such as SCORE-15, PHQ-9, and Zarit Burden were used to measure family functioning, depression, and caregiver’s burden for the families. Results: The research is still in preliminary phase. Conclusion: The study highlights the importance of family intervention for families with multiple stressors on different treatment modalities who might have different needs and challenges. Nursing support needs to be complemented with family-based support to manage complex family issues in order to achieve better health outcomes and improved family coping.

Keywords: complementing nursing support, end stage renal failure, healthcare, systemic approaches

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Authors: Rita Gill Singh, Alex Chun Koon, Cindy Sing Bik Ngai, Joanna Wen Ying Ho, Mei Li Khong, Enoch Chan, Terrence Lau

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Although humour is viewed as a beneficial element in teaching, there has been little attempt to systematize humour in teaching, possibly because it is difficult to teach someone to be humorous. This study integrated planned humour pedagogical approach into teaching and learning activities and examined the effect of systematically planned humour on students’ engagement and learning in different courses. Specifically, appropriate types of humour (i.e. analogy, absurdity and wordplay) and incorporation methods and frequency were systematically integrated into the lessons of courses at some higher education institutions in Hong Kong. The results showed that the planned humour pedagogical approach increased student engagement, as well as enhanced learning and motivation while reducing students’ stress. The pedagogical implications of this study will be useful for researchers, practitioners, and educators.

Keywords: higher education, pedagogy, humour, student engagement, learning, motivation

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Authors: Newton Muhury, Armando A. Apan, Tek Maraseni

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This study modelled the relationships between vegetation response and available water below the soil surface using the Terra’s Moderate Resolution Imaging Spectroradiometer (MODIS) generated Normalised Difference Vegetation Index (NDVI) and soil water content (SWC) data. The Soil & Water Assessment Tool (SWAT) interface known as ArcSWAT was used in ArcGIS for the groundwater analysis. The SWAT model was calibrated and validated in SWAT-CUP software using 10 years (2001-2010) of monthly streamflow data. The average Nash-Sutcliffe Efficiency during the calibration and validation was 0.54 and 0.51, respectively, indicating that the model performances were good. Twenty years (2001-2020) of monthly MODIS NDVI data for three different types of vegetation (forest, shrub, and grass) and soil water content for 43 sub-basins were analysed using the WEKA, machine learning tool with a selection of two supervised machine learning algorithms, i.e., support vector machine (SVM) and random forest (RF). The modelling results show that different types of vegetation response and soil water content vary in the dry and wet season. For example, the model generated high positive relationships (r=0.76, 0.73, and 0.81) between the measured and predicted NDVI values of all vegetation in the study area against the groundwater flow (GW), soil water content (SWC), and the combination of these two variables, respectively, during the dry season. However, these relationships were reduced by 36.8% (r=0.48) and 13.6% (r=0.63) against GW and SWC, respectively, in the wet season. On the other hand, the model predicted a moderate positive relationship (r=0.63) between shrub vegetation type and soil water content during the dry season, which was reduced by 31.7% (r=0.43) during the wet season. Our models also predicted that vegetation in the top location (upper part) of the sub-basin is highly responsive to GW and SWC (r=0.78, and 0.70) during the dry season. The results of this study indicate the study region is suitable for seasonal crop production in dry season. Moreover, the results predicted that the growth of vegetation in the top-point location is highly dependent on groundwater flow in both dry and wet seasons, and any instability or long-term drought can negatively affect these floodplain vegetation communities. This study has enriched our knowledge of vegetation responses to groundwater in each season, which will facilitate better floodplain vegetation management.

Keywords: ArcSWAT, machine learning, floodplain vegetation, MODIS NDVI, groundwater

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Authors: Miraç Savaş Turhan, Ali Danışman

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New institutional theorists in organization theory have used institutional logics perspective to explain the contradictory practices in modern western societies. Accordingly, distinct institutional logics are embedded in central institutions such as the market, state, democracy, family, and religion. Individual and organizational actors and their practices are restricted and guided by institutional logics in a particular field. Through this perspective, actors are assumed to have a situated, embedded, boundedly intentional, and adaptive role against the structure in social, cultural and political context. Since the early 1990's, increasing number of studies has attempted to explain the role of actors in creating, maintaining, and changing institutions. Yet, most of these studies have focused on organizational field-level actors, ignoring the role that can be played by individual actors within organizations. As a result, we have much information about what organizational field level actors can do, but relatively little knowledge about the ability of organizational change agents within organization in relation to institutional orders. This study is an attempt to find out how the ability of individual actors who attempt to change their organization is constrained and shaped by institutional logics dominating the field. We examine this issue in a private school in the Turkish Education field. We first describe dominating institutional logics in the Turkish Education field. Then we conducted in-depth interviews and content analysis in the school. The early results indicate that attempts and actions of organizational change agents are remarkably directed and shaped by the dominating institutional logics in the Turkish Education field.

Keywords: Institutional logics, individual actors, organizational change, organizational change agent

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Authors: Katejarinporn Chaiya, Jarumon Nookong, Nutthapat Kaewrattanapat

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The purposes of this research were to develop and find users’ satisfaction after using the Decision Support System for Examination Selection. This research presents the design of information systems. In order to find the necessary examination of the statistics. Based on the examination of the candidate and then taking the easy difficulty setting statistics applied to the test. In addition, research has also made performance appraisals from experts and user satisfaction. By results of analysis showed that the performance appraisals from experts on the system as a whole and at a good level. mean was 3.44 and S.D. was 0.55 and user satisfaction per system as a whole and the good level mean was 3.37 and S.D. was 0.42 can conclude that effective systems are in a good level. Work has been completed in accordance with the scope of work. The website used developing this project is PHP, MySQL.5.0.45 for database.

Keywords: secision support system, examination, PHP, information systems

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Authors: Eti Gilad, Shosh Millet

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In light of the technological development and its introduction into the field of education, an online course was designed in parallel to the 'conventional' course for teaching the ''Qualitative Research Methods''. This course aimed to characterize learning-teaching processes in a 'Qualitative Research Methods' course studied in two different frameworks. Moreover its objective was to explore the difference between the culture of a physical learning environment and that of online learning. The research monitored four learner groups, a total of 72 students, for two years, two groups from the two course frameworks each year. The courses were obligatory for M.Ed. students at an academic college of education and were given by one female-lecturer. The research was conducted in the qualitative method as a case study in order to attain insights about occurrences in the actual contexts and sites in which they transpire. The research tools were open-ended questionnaire and reflections in the form of vignettes (meaningful short pictures) to all students as well as an interview with the lecturer. The tools facilitated not only triangulation but also collecting data consisting of voices and pictures of teaching and learning. The most prominent findings are: differences between the two courses in the change features of the learning environment culture for the acquisition of contents and qualitative research tools. They were manifested by teaching methods, illustration aids, lecturer's profile and students' profile.

Keywords: face to face course, online course, qualitative research, vignettes

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Authors: Norfishah Mat Rabi, Rosma Osman, Norziana Mat Rabi

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It is difficult for autistic children to mix with and be around with other people. Language difficulties are a problem that affects their social life. A lack of knowledge and ability in language are factors that greatly influence their behavior, and their ability to communicate and interact. Autistic children need to be assisted to improve their language abilities through the use of suitable learning resources. This study is conducted to identify weather graphic animation resources can help autistic children learn and use transitive verbs more effectively. The study was conducted in a rural secondary school in Penang, Malaysia. The research subject comprised of three autistic students ranging in age from 14 years to 16 years. The 14-year-old student is placed in A Class and two 16-year-old students placed in B Class. The class placement of the subjects is based on the diagnostic test results conducted by the teacher and not based on age. Data collection is done through observation and interviews for the duration of five weeks; with the researcher allocating 30 minutes for every learning activity carried out. The research finding shows that the subjects learn transitive verbs better using graphic animation compared to static pictures. It is hoped that this study will give a new perspective towards the learning processes of autistic children.

Keywords: graphic animation, autistic children, language learning, teaching

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Authors: Yiqiao Yin

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Many scholars and educators have dedicated their lives in K12 education system and there has been an exploding amount of attention to implement technical foundations for Artificial Intelligence Education for high school and precollege level students. This paper focuses on the development and use of resources to support K-12 education in Artificial Intelligence (AI). The author and his team have more than three years of experience coaching students from pre-college level age from 15 to 18. This paper is a culmination of the experience and proposed online tools, software demos, and structured activities for high school students. The paper also addresses a portfolio of AI concepts as well as the expected learning outcomes. All resources are provided with online videos and Github repositories for immediate use.

Keywords: K12 education, AI4ALL, pre-college education, pre-college AI

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Authors: Ramy Shaaban

Abstract:

The purpose of this study was to examine the difference in clinical reasoning skills of students when using virtual audiology cases with and without collaborative assistance from major learning approaches important to clinical reasoning skills and computer-based learning models: Situated Learning Theory, Social Development Theory, Scaffolding, and Collaborative Learning. A quasi-experimental design was conducted at two United States universities to examine whether there is a significant difference in clinical reasoning skills between three treatment groups using IUP Audiosim software. Two computer-based audiology case simulations were developed, and participants were randomly placed into the three groups: no collaboration, virtual collaboration, and live collaboration. The clinical reasoning data were analyzed using One-Way ANOVA and Tukey posthoc analyses. The results show that there was a significant difference in clinical reasoning skills between the three treatment groups. The score obtained by the no collaboration group was significantly less than the scores obtained by the virtual and live collaboration groups. Collaboration, whether virtual or in person, has a positive effect on students’ clinical reasoning. These results with audiology students indicate that combining collaboration models with scaffolding and embedding situated learning and social development theories into the design of future virtual patients has the potential to improve students’ clinical reasoning skills.

Keywords: clinical reasoning, virtual patients, collaborative learning, scaffolding

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Authors: V. Saccà, A. Sarica, F. Novellino, S. Barone, T. Tallarico, E. Filippelli, A. Granata, P. Valentino, A. Quattrone

Abstract:

The work aim was to evaluate how well Random Forest (RF) and Support Vector Machine (SVM) algorithms could support the early diagnosis of Multiple Sclerosis (MS) from resting-state functional connectivity data. In particular, we wanted to explore the ability in distinguishing between controls and patients of mean signals extracted from ICA components corresponding to 15 well-known networks. Eighteen patients with early-MS (mean-age 37.42±8.11, 9 females) were recruited according to McDonald and Polman, and matched for demographic variables with 19 healthy controls (mean-age 37.55±14.76, 10 females). MRI was acquired by a 3T scanner with 8-channel head coil: (a)whole-brain T1-weighted; (b)conventional T2-weighted; (c)resting-state functional MRI (rsFMRI), 200 volumes. Estimated total lesion load (ml) and number of lesions were calculated using LST-toolbox from the corrected T1 and FLAIR. All rsFMRIs were pre-processed using tools from the FMRIB's Software Library as follows: (1) discarding of the first 5 volumes to remove T1 equilibrium effects, (2) skull-stripping of images, (3) motion and slice-time correction, (4) denoising with high-pass temporal filter (128s), (5) spatial smoothing with a Gaussian kernel of FWHM 8mm. No statistical significant differences (t-test, p < 0.05) were found between the two groups in the mean Euclidian distance and the mean Euler angle. WM and CSF signal together with 6 motion parameters were regressed out from the time series. We applied an independent component analysis (ICA) with the GIFT-toolbox using the Infomax approach with number of components=21. Fifteen mean components were visually identified by two experts. The resulting z-score maps were thresholded and binarized to extract the mean signal of the 15 networks for each subject. Statistical and machine learning analysis were then conducted on this dataset composed of 37 rows (subjects) and 15 features (mean signal in the network) with R language. The dataset was randomly splitted into training (75%) and test sets and two different classifiers were trained: RF and RBF-SVM. We used the intrinsic feature selection of RF, based on the Gini index, and recursive feature elimination (rfe) for the SVM, to obtain a rank of the most predictive variables. Thus, we built two new classifiers only on the most important features and we evaluated the accuracies (with and without feature selection) on test-set. The classifiers, trained on all the features, showed very poor accuracies on training (RF:58.62%, SVM:65.52%) and test sets (RF:62.5%, SVM:50%). Interestingly, when feature selection by RF and rfe-SVM were performed, the most important variable was the sensori-motor network I in both cases. Indeed, with only this network, RF and SVM classifiers reached an accuracy of 87.5% on test-set. More interestingly, the only misclassified patient resulted to have the lowest value of lesion volume. We showed that, with two different classification algorithms and feature selection approaches, the best discriminant network between controls and early MS, was the sensori-motor I. Similar importance values were obtained for the sensori-motor II, cerebellum and working memory networks. These findings, in according to the early manifestation of motor/sensorial deficits in MS, could represent an encouraging step toward the translation to the clinical diagnosis and prognosis.

Keywords: feature selection, machine learning, multiple sclerosis, random forest, support vector machine

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Authors: Aya M. Aboudesouky

Abstract:

Covid-19 has changed and affected the whole world dramatically in a new way that the entire world, even scientists, have not imagined before. The educational institutions around the world have been fighting since Covid-19 hit the world last December to keep the educational process unchanged for all students. E-learning was a must for almost all US universities during the pandemic. It was specifically more challenging to use online case-based learning instead of regular classes among nursing students who take practical education. This study aims to examine the difference in performance and satisfaction between nursing students taking traditional education and those who take virtual case-based education during their practical study. This study enrolls 40 last-year nursing undergraduates from a mid-sized university in Western Pennsylvania. The study uses a convenient sample. Students will be divided into two groups; a control group that is exposed to traditional teaching strategy and a treatment group that is exposed to a case-based teaching strategy. The module designed for this study is a total parenteral nutrition (TPN) module that will be taught for one month. The treatment group (n=20) utilizes the virtual simulation of the CBL method, while the control group (n=20) uses the traditional lecture-based teaching method. Student evaluations are collected after a month by using the survey to attain the students’ learning satisfaction and self-evaluation of the course. The post-test is used to assess the end of the course performance.

Keywords: virtual case-based learning, traditional education, nursing education, Covid-19 crisis, online practical education

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Authors: Xin Chen

Abstract:

Pre-industrial old-world human cultural diversity and societal complexity exhibits remarkable geographic regularities. Along the latitudinal axis from the equator to the arctic, a descending trend of human ethno-cultural diversity is found to be in coincidence with a descending trend of biological diversity. Along the same latitudinal axis, the pre-industrial human societal complexity shows to peak at the intermediate latitude. It is postulated that human cultural diversity and societal complexity are strongly influenced by collective learning, and that collective learning is positively related to human population size, social interactions, and environmental challenges. Under such postulations the relationship between collective learning and important geographical-environmental factors, including climate and biodiversity/bio-productivity is examined. A hypothesis of intermediate bio-productivity is formulated to account for those latitudinal patterns of pre-industrial human societal complexity.

Keywords: cultural diversity, soetal complexity, latitudinal patterns, biodiversity, bio-productivity, collective learning

Procedia PDF Downloads 67