Search results for: older adult learning

Authors: Pratistha Shrestha

Abstract:

Background: Acrochordons (Skin tags) are common benign skin tumors usually occurring on the neck and major flexors of older people. These range in size from 1 mm to 1cm in diameter and are skin-colored or brownish. A possible association with diabetes mellitus has been suggested in previous studies, but the result is not conclusive. Objective: The aim of this study was to find out the association of diabetes mellitus with acrochordons. Material and Methods: One hundred and two patients were selected for the study. Among them, 51 (males–23 and females–28) with acrochordons were taken as cases, and 51 with other dermatologic diseases after matching age and sex were taken as controls. The patients were selected from OPD of the Department of Dermatology and Venereology in Universal College of Medical Sciences–Teaching Hospital (UCMS-TH). Blood glucose levels, including both fasting plasma glucose and 2-hour post-glucose load, were determined for both case and control and compared. Results: Patients with acrochordons had a significantly higher frequency of diabetes than the control group (p < 0.001). A total of 48.5% and 40% of patients with acrochordons having diabetes were obese and overweight, respectively. Conclusion: There is an increased risk of diabetes mellitus in patients with acrochordons. With regard to the importance of early diagnosis of diabetes, it is recommended a high level of suspicion for diabetes mellitus in patients with acrochordons.

Keywords: acrochordons, diabetes mellitus, obesity, skin tags

Procedia PDF Downloads 137

Authors: Adeep Hande, Shubham Agarwal

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This paper presents a study on identifying sexism in online texts using various state-of-the-art deep learning models based on BERT. We experimented with different feature sets and model architectures and evaluated their performance using precision, recall, F1 score, and accuracy metrics. We also explored the use of pseudolabeling technique to improve model performance. Our experiments show that the best-performing models were based on BERT, and their multilingual model achieved an F1 score of 0.83. Furthermore, the use of pseudolabeling significantly improved the performance of the BERT-based models, with the best results achieved using the pseudolabeling technique. Our findings suggest that BERT-based models with pseudolabeling hold great promise for identifying sexism in online texts with high accuracy.

Keywords: large language models, semi-supervised learning, sexism detection, data sparsity

Procedia PDF Downloads 51

Authors: Anna Jeon, Seung-Ho Han, Je-Hun Lee

Abstract:

The aim of this study was to determine the location and distribution pattern of neurovascular structures superior and inferior to the clavicle by detailed dissection. Fifteen adult non-embalmed cadavers with a mean age of 71.5 years were studied. For measurements, the most prominent point of the sternal end of the clavicle (SEC) on anterior view and the most prominent point of the acromial end of the clavicle (AEC) were identified before dissection. A line connecting the SEC and AEC was used as a reference line. The surrounding neurovascular structures were investigated. The supraclavicular nerve was densely distributed at 71.73% on the reference line. Branches of the thoracoacromial artery were located at 76.92%. Branches of subclavian vein were evenly distributed at all sections. The subclavian vein and artery and brachial plexus were located from 31.3% to 57.5%. That area needs caution because major neurovascular structures run underneath the clavicle.

Keywords: clavicle, ORIF, neurovascular structure, anatomical study

Procedia PDF Downloads 143

Authors: Ruby A. L. Espineli

Abstract:

The study assessed the Philippine National Police strategies in the implementation of ‘Peace and Order Agenda for Transformation and Upholding of the Rule-of-Law’ P.A.T.R.O.L Plan 2030. Its operational roadmap presents four perspectives which include resource management, learning and growth, process excellence; and community. Focused group discussion, observation, and distribution of survey questionnaire to selected PNP officers and community members were done to identify and describe the implementation, problems encountered and measures to address the problems of the PNP P.A.T.R.O.L Plan 2030. In resource management, PNP allocates most sufficient funds in providing service firearms, patrol vehicle, and internet connections. In terms of learning and growth, the attitude of PNP officers is relatively higher than their knowledge and skills. Moreover, in terms of process excellence, the PNP use several crime preventions and crime solution strategies to deliver an immediate response to calls of the community. As regards, community perspective, PNP takes effort in establishing partnership with community. It is also interesting to note that PNP officers and community were both undecided on the existence of problems encountered in the implementation of P.A.T.R.O.L Plan 2030. But, they had proactive behavior as they agreed on all the specified measures to address the problems encountered in implementation of PNP P.A.T.R.O.L. Plan 2030. A strategic framework, based on the findings was formulated in this study that could improve and entrench the harmonious working relationship between the PNP and stakeholders in the enhancement of the implementation of PNP P.A.T.R.O.L. Plan 2030.

Keywords: community perspectives, learning and growth, process excellence, resource management

Procedia PDF Downloads 214

Authors: Dirson Santos De Campos, Deller James Ferreira, Anderson Cavalcante Gonçalves, Uyara Ferreira Silva

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Rubrics to learning research provide many evaluation criteria and expected performance standards linked to defined student activity for learning and pedagogical objectives. Despite the rubric being used in education at all levels, academic literature on rubrics as a tool to support research in SQL Education is quite rare. There is a large class of SQL queries is syntactically correct, but certainly, not all are semantically correct. Detecting and correcting errors is a recurring problem in SQL education. In this paper, we usthe Rubric Abstract Framework (RAF), which consists of steps, that allows us to map the information to measure student performance guided by didactic objectives defined by the teacher as long as it is contextualized domain modeling by rubric. An empirical study was done that demonstrates how rubrics can mitigate student difficulties in finding logical errors and easing teacher workload in SQL education. Detecting and correcting logical errors is an important skill for students. Researchers have proposed several ways to improve SQL education because understanding this paradigm skills are crucial in software engineering and computer science. The RAF instantiation was using in an empirical study developed during the COVID-19 pandemic in database course. The pandemic transformed face-to-face and remote education, without presential classes. The lab activities were conducted remotely, which hinders the teaching-learning process, in particular for this research, in verifying the evidence or statements of knowledge, skills, and abilities (KSAs) of students. Various research in academia and industry involved databases. The innovation proposed in this paper is the approach used where the results obtained when using rubrics to map logical errors in query formulation have been analyzed with gains obtained by students empirically verified. The research approach can be used in the post-pandemic period in both classroom and distance learning.

Keywords: rubric, logical error, structured query language (SQL), empirical study, SQL education

Procedia PDF Downloads 166

Authors: Kerri Alderson

Abstract:

There is pervasive awareness by post secondary faculty that written feedback on course assignments is inconsistently reviewed by students. In order to support student success and growth, a novel method of providing feedback was sought, and screen casting - short, narrated “movies” of audio visual instructor feedback on students’ scholarly papers - was provided as an alternative to traditional means. An overview of the teaching and learning experience as well as the user-friendly software utilized will be presented. This study covers an overview of this more direct, student-centered medium for providing feedback using technology familiar to post secondary students. Reminiscent of direct personal contact, the personalized video feedback is positively evaluated by students as a formative medium for student growth in scholarly writing.

Keywords: education, pedagogy, screen casting, student feedback, teaching and learning

Procedia PDF Downloads 105

Authors: Mairo Musa Galadima, Phoebe Mshelia

Abstract:

In Nigeria, the national policy of education stipulates that the kindergarten-primary schools and the legislature are to use the three popular Nigerian Languages namely: Hausa, Igbo, and Yoruba. However, the English language seems to be preferred and this calls for this paper. Attempts were made to draw out the challenges faced by learners in understanding English speech sounds and using them to communicate effectively in English; using 5 (five) selected secondary school in Bauchi. It was discovered that challenges abound in the wrong use of stress and intonation, transfer of phonetic features from their first language. Others are inadequately qualified teachers and relevant materials including textbooks. It is recommended that teachers of English should lay more emphasis on the teaching of supra-segmental features and should be encouraged to go for further studies, seminars and refresher courses.

Keywords: stress and intonation, phonetic and challenges, teaching and learning English, secondary schools

Procedia PDF Downloads 331

Authors: Mane Darbinyan, Lusine Hayrapetyan, Elen Matevosyan

Abstract:

Artificial Intelligence in Education (AIED) has been created to help students get ready for the workforce, and over the past 25 years, it has grown significantly, offering a variety of technologies to support academic, institutional, and administrative services. However, this is still challenging, especially considering the labor market's rapid change. While choosing a career, people face various obstacles because they do not take into consideration their own preferences, which might lead to many other problems like shifting jobs, work stress, occupational infirmity, reduced productivity, and manual error. Besides preferences, people should properly evaluate their technical and non-technical skills, as well as their personalities. Professional counseling has become a difficult undertaking for counselors due to the wide range of career choices brought on by changing technological trends. It is necessary to close this gap by utilizing technology that makes sophisticated predictions about a person's career goals based on their personality. Hence, there is a need to create an automated model that would help in decision-making based on user inputs. Improving career guidance can be achieved by embedding machine learning into the career consulting ecosystem. There are various systems of career guidance that work based on the same logic, such as the classification of applicants, matching applications with appropriate departments or jobs, making predictions, and providing suitable recommendations. Methodologies like KNN, Neural Networks, K-means clustering, D-Tree, and many other advanced algorithms are applied in the fields of data and compute some data, which is helpful to predict the right careers. Besides helping users with their career choice, these systems provide numerous opportunities which are very useful while making this hard decision. They help the candidate to recognize where he/she specifically lacks sufficient skills so that the candidate can improve those skills. They are also capable to offer an e-learning platform, taking into account the user's lack of knowledge. Furthermore, users can be provided with details on a particular job, such as the abilities required to excel in that industry.

Keywords: career guidance system, machine learning, career prediction, predictive decision, data mining, technical and non-technical skills

Procedia PDF Downloads 66

Authors: Kholoud H. Al-Zedjali, Abir S. Al-Harrasi, Ali H. Al-Badi

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Recently there has been a dramatic proliferation in the number of social networking sites (SNSs) users; however, little is published about what motivates college students to use SNSs in education. The main goal of this research is to explore the college students’ motives for using SNSs in education. A conceptual framework has therefore been developed to identify the main factors that influence/motivate students to use social networking sites for learning purposes. To achieve the research objectives a quantitative method was used to collect data. A questionnaire has been distributed amongst college students. The results reveal that social influence, perceived enjoyment, institute regulation, perceived usefulness, ranking up-lift, attractiveness, communication tools, free of charge, sharing material and course nature all play an important role in the motivation of college students to use SNSs for learning purposes.

Keywords: Social Networking Sites (SNSs), education, college students, motivations

Procedia PDF Downloads 244

Authors: Rashmi D. G., Aishwarya G., Niharika M. K.

Abstract:

Purpose: Free recall tasks target cognitive and linguistic processes like episodic memory, lexical access and retrieval. Consequently, the free recall paradigm is suitable for assessing memory deterioration caused by aging; this also depends on linguistic factors, including the use of first and second languages and their relative ability. Hence, the present study aimed to determine if aging has an effect on visual and auditory recall abilities. Method: Twenty young adults (mean age: 25.4±0.99) and older adults (mean age: 63.3±3.51) participated in the study. Participants performed a free recall task under two conditions – related and unrelated and two modalities - visual and auditory where they were instructed to recall as many items as possible with no specific order and time limit. Results: Free recall performance was calculated as the mean number of correctly recalled items. Although younger participants recalled a higher number of items, the performance across conditions and modality was variable. Conclusion: In summary, the findings of the present study revealed an age-related decline in the efficiency of episodic memory, which is crucial to remember recent events.

Keywords: recall, episodic memory, aging, modality

Procedia PDF Downloads 74

Authors: Djamel Fawzi Hadj Sadok, Marrone Silvério Melo Dantas Pedro Henrique Dreyer, Gabriel Fonseca Reis de Souza, Daniel Bezerra, Ricardo Souza, Silvia Lins, Judith Kelner

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A radio base station (RBS), part of the radio access network, is a particular type of equipment that supports the connection between a wide range of cellular user devices and an operator network access infrastructure. Nowadays, most of the RBS maintenance is carried out manually, resulting in a time consuming and costly task. A suitable candidate for RBS maintenance automation is repairing faulty links between devices caused by missing or unplugged connectors. A suitable candidate for RBS maintenance automation is repairing faulty links between devices caused by missing or unplugged connectors. This paper proposes and compares two deep learning solutions to identify attached RJ45 connectors on network ports. We named connector detection, the solution based on object detection, and connector classification, the one based on object classification. With the connector detection, we get an accuracy of 0:934, mean average precision 0:903. Connector classification, get a maximum accuracy of 0:981 and an AUC of 0:989. Although connector detection was outperformed in this study, this should not be viewed as an overall result as connector detection is more flexible for scenarios where there is no precise information about the environment and the possible devices. At the same time, the connector classification requires that information to be well-defined.

Keywords: radio base station, maintenance, classification, detection, deep learning, automation

Procedia PDF Downloads 176

Authors: Azad A. Meerkhan, Alaa Hani Razak, Bayan M. S. Younis

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The efficiency of enzyme-linked immunosorbent assay (ELISA) in sheep infected with Fasciola hepatica was studied. 232 jaundiced sheep among 5208 sheep slaughter in the Duhok abattoir (regardless of the age and gender) between the period of May. 2012 to Oct. 2012 were examined by direct examination (Searching of adult flukes in the bile duct) and by Enzyme-linked immunosorbent assay (ELISA) to detect the prevalence of fascioliasis in the studied population which showed a high observed infection ratio in Sep. 2012 (12.2%) with the high (ELISA) result of infection in May. 2012 (25.36%). Significant differences were found between the two ways in all of the months with the highest difference in May. 2012 and the net deference between the both ways was 6.91%.

Keywords: fascioliasis, Fasciola hepatica, layers, liver fluk, ELISA, direct examination

Procedia PDF Downloads 302

Authors: Stephanie Ducrot, Marie Vernet, Eve Meiss, Yves Chaix

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Learning to read is a key topic of debate today, both in terms of its implications on school failure and illiteracy and regarding what are the best teaching methods to develop. It is estimated today that four to six percent of school-age children suffer from specific developmental disorders that impair learning. The findings from people with dyslexia and typically developing readers suggest that the problems children experience in learning to read are related to the preliteracy skills that they bring with them from kindergarten. Most tools available to professionals are designed for the evaluation of child language problems. In comparison, there are very few tools for assessing the relations between visual skills and the process of learning to read. Recent literature reports that visual-motor skills and visual-spatial attention in preschoolers are important predictors of reading development — the main goal of this study aimed at improving screening for future reading difficulties in preschool children. We used a prospective, longitudinal approach where oculomotor processes (assessed with the DiagLECT test) were measured in pre-readers, and the impact of these skills on future reading development was explored. The dialect test specifically measures the online time taken to name numbers arranged irregularly in horizontal rows (horizontal time, HT), and the time taken to name numbers arranged in vertical columns (vertical time, VT). A total of 131 preschoolers took part in this study. At Time 0 (kindergarten), the mean VT, HT, errors were recorded. One year later, at Time 1, the reading level of the same children was evaluated. Firstly, this study allowed us to provide normative data for a standardized evaluation of the oculomotor skills in 5- and 6-year-old children. The data also revealed that 25% of our sample of preschoolers showed oculomotor impairments (without any clinical complaints). Finally, the results of this study assessed the validity of the DiagLECT test for predicting reading outcomes; the better a child's oculomotor skills are, the better his/her reading abilities will be.

Keywords: vision, attention, oculomotor processes, reading, preschoolers

Procedia PDF Downloads 129

Authors: Azmat Farooq Ahmad Khurram, Sadaf Aslam

Abstract:

This meta-analysis systematically examines the use of artificial intelligence (AI) in instructional methods across diverse educational settings through a thorough analysis of empirical research encompassing various disciplines, educational levels, and regions. This study aims to assess the effects of AI integration on teaching methodologies, classroom dynamics, teachers' roles, and student engagement. Various research methods were used to gather data, including literature reviews, surveys, interviews, and focus group discussions. Findings indicate paradigm shifts in teaching and education, identify emerging trends, practices, and the application of artificial intelligence in learning, and provide educators, policymakers, and stakeholders with guidelines and recommendations for effectively integrating AI in educational contexts. The study concludes by suggesting future research directions and practical considerations for maximizing AI's positive influence on pedagogical practices.

Keywords: artificial intelligence, teaching practices, meta-analysis, teaching-learning

Procedia PDF Downloads 43

Authors: Mane Darbinyan, Lusine Hayrapetyan, Elen Matevosyan

Abstract:

Artificial Intelligence in Education (AIED) has been created to help students get ready for the workforce, and over the past 25 years, it has grown significantly, offering a variety of technologies to support academic, institutional, and administrative services. However, this is still challenging, especially considering the labor market's rapid change. While choosing a career, people face various obstacles because they do not take into consideration their own preferences, which might lead to many other problems like shifting jobs, work stress, occupational infirmity, reduced productivity, and manual error. Besides preferences, people should evaluate properly their technical and non-technical skills, as well as their personalities. Professional counseling has become a difficult undertaking for counselors due to the wide range of career choices brought on by changing technological trends. It is necessary to close this gap by utilizing technology that makes sophisticated predictions about a person's career goals based on their personality. Hence, there is a need to create an automated model that would help in decision-making based on user inputs. Improving career guidance can be achieved by embedding machine learning into the career consulting ecosystem. There are various systems of career guidance that work based on the same logic, such as the classification of applicants, matching applications with appropriate departments or jobs, making predictions, and providing suitable recommendations. Methodologies like KNN, neural networks, K-means clustering, D-Tree, and many other advanced algorithms are applied in the fields of data and compute some data, which is helpful to predict the right careers. Besides helping users with their career choice, these systems provide numerous opportunities which are very useful while making this hard decision. They help the candidate to recognize where he/she specifically lacks sufficient skills so that the candidate can improve those skills. They are also capable of offering an e-learning platform, taking into account the user's lack of knowledge. Furthermore, users can be provided with details on a particular job, such as the abilities required to excel in that industry.

Keywords: career guidance system, machine learning, career prediction, predictive decision, data mining, technical and non-technical skills

Procedia PDF Downloads 53

Authors: Reynante E. Autida, Maria Ana T. Quimbo

Abstract:

The chemistry education curriculum provides an excellent avenue where students learn the principles and concepts in chemistry and at the same time, as a central science, better understand related fields. However, the teaching approach used by teachers affects student learning. Cased-based teaching (CBT) is one of the various forms of inductive method. The teacher starts with specifics then proceeds to the general principles. The students’ role in inductive learning shifts from being passive in the traditional approach to being active in learning. In this paper, the effects of Small-Group Case-Based Teaching (SGCBT) on college chemistry students’ achievement, critical thinking, and attitude toward chemistry including the relationships between each of these variables were determined. A quasi-experimental counterbalanced design with pre-post control group was used to determine the effects of SGCBT on Engineering students of four intact classes (two treatment groups and two control groups) in one of the State Universities in Mindanao. The independent variables are the type of teaching approach (SGCBT versus pure lecture-discussion teaching or PLDT) while the dependent variables are chemistry achievement (exam scores) and scores in critical thinking and chemistry attitude. Both Analysis of Covariance (ANCOVA) and t-tests (within and between groups and gain scores) were used to compare the effects of SGCBT versus PLDT on students’ chemistry achievement, critical thinking, and attitude toward chemistry, while Pearson product-moment correlation coefficients were calculated to determine the relationships between each of the variables. Results show that the use of SGCBT fosters positive attitude toward chemistry and provides some indications as well on improved chemistry achievement of students compared with PLDT. Meanwhile, the effects of PLDT and SGCBT on critical thinking are comparable. Furthermore, correlational analysis and focus group interviews indicate that the use of SGCBT not only supports development of positive attitude towards chemistry but also improves chemistry achievement of students. Implications are provided in view of the recent findings on SGCBT and topics for further research are presented as well.

Keywords: case-based teaching, small-group learning, chemistry cases, chemistry achievement, critical thinking, chemistry attitude

Procedia PDF Downloads 277

Authors: R. Marhenke, M. Martini

Abstract:

The distraction of attentional resources after learning hinders long-term memory consolidation compared to several minutes of post-encoding inactivity in form of wakeful resting. We tested whether an 8-minute period of wakeful resting, compared to performing an adapted version of the d2 test of attention after learning, supports memory retention. Participants encoded and immediately recalled a word list followed by either an 8 minute period of wakeful resting (eyes closed, relaxed) or by performing an adapted version of the d2 test of attention (scanning and selecting specific characters while ignoring others). At the end of the experimental session (after 12-24 min) and again after 7 days, participants were required to complete a surprise free recall test of both word lists. Our results showed no significant difference in memory retention between the experimental conditions. However, we found that participants who completed the first lines of the d2 test in less than the given time limit of 20 seconds and thus had short unfilled intervals before switching to the next test line, remembered more words over the 12-24 minute and over the 7 days retention interval than participants who did not complete the first lines. This interaction occurred only for the first test lines, with the highest temporal proximity to the encoding task and not for later test lines. Differences in retention scores between groups (completed first line vs. did not complete) seem to be widely independent of the general performance in the d2 test. Implications and limitations of these exploratory findings are discussed.

Keywords: long-term memory, retroactive interference, attention, forgetting

Procedia PDF Downloads 113

Authors: Meiying Liao, Poya Huang

Abstract:

The aesthetic domain is one of the six major domains in the Taiwanese preschool curriculum, encompassing visual arts, music, and dramatic play. Its primary objective is to cultivate children’s abilities in exploration and awareness, expression and creation, and response and appreciation. The purpose of this study was to explore the effects of hosting a vocal music concert on aesthetic inspiration and learning among preschoolers in a preschool setting. The primary research method employed was a case study focusing on a private preschool in Northern Taiwan that organized a school-wide event featuring two vocalists. The concert repertoires included children’s songs, folk songs, and arias performed in Mandarin, Hakka, English, German, and Italian. In addition to professional performances, preschool teachers actively participated by presenting a children’s song. A total of 5 classes, comprising approximately 150 preschoolers, along with 16 teachers and staff, participated in the event. Data collection methods included observation, interviews, and documents. Results indicated that both teachers and children thoroughly enjoyed the concert, with high levels of acceptance when the program was appropriately designed and hosted. Teachers reported that post-concert discussions with children revealed the latter’s ability to recall people, events, and elements observed during the performance, expressing their impressions of the most memorable segments. The concert effectively achieved the goals of the aesthetic domain, particularly in fostering response and appreciation. It also inspired preschoolers’ interest in music. Many teachers noted an increased desire for performance among preschoolers after exposure to the concert, with children imitating the performers and their expressions. Remarkably, one class extended this experience by incorporating it into the curriculum, autonomously organizing a high-quality concert in the music learning center. Parents also reported that preschoolers enthusiastically shared their concert experiences at home. In conclusion, despite being a single event, the positive responses from preschoolers towards the music performance suggest a meaningful impact. These experiences extended into the curriculum, as firsthand exposure to performances allowed teachers to deepen related topics, fostering a habit of autonomous learning in the designated learning centers.

Keywords: concert, early childhood music education, aesthetic education, music develpment

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Authors: Olga C. Rodrigue

Abstract:

Long-term care and skilled nursing facilities experience ebbs and flows of nursing staffing, a problem compounded by the perception of the facilities as undesirable workplaces and competition for staff from other healthcare entities. Travel nurses are contracted to fill staffing needs due to increased admissions, increased and unexpected attrition of nurses, or facility expansion of services. Prior to beginning the contracted assignment, the travel nurse must meet industry, company, and regulatory requirements (The Joint Commission and CMS) for skills and knowledge. Travel nurses, however, inconsistently receive the pre-assignment orientation needed to work at the contracted facility, if any information is given at all. When performance expectations are not met, travel nurses may subsequently choose to leave the position without completing the terms of the contract, and some facilities may choose to terminate the contract prior to the expected end date. The overarching goal of the Doctor of Nursing Practice evidence-based practice improvement project is to provide travel nurses with the basic and necessary information to prepare them to begin a long-term and skilled nursing assignment. The project involves the identification of travel nurse learning needs through a survey and the development and provision of web-based learning modules to address those needs prior to arrival for a long-term and skilled nursing assignment.

Keywords: nurse staffing, travel nurse, travel staff, contract staff, contracted assignment, long-term care, skilled nursing, onboarding, orientation, staff development, supplemental staff

Procedia PDF Downloads 149

Authors: M. L. W. P. De Silva, R. A. C. Rabel, N. Smith, L. McIntyre, T. J Parkinson, K. A. N. Wijayawardhane

Abstract:

Curricular integration is an important concept in medical education for developing students’ ability to create connections between different medical disciplines. Problem-Based Learning (PBL) is one of the vehicles through which such integration can be achieved. During the recent review of the veterinary curriculum at the University of Peradeniya, a series of courses in Integrative Veterinary Science (IVS) were introduced, in which PBL was the primary teaching methodology. The objectives of this study were to evaluate students’ opinions on PBL as a teaching method: it should be noted that, within the context of secondary and tertiary education in Sri Lanka, this would be an entirely novel learning experience for the students. Opinions were sought at the conclusion of IVS sessions where students of semesters 2, 4, 6, and 7 (of an 8-semester program) were exposed to a two, 2-hour PBL-based case scenario. The PBL-based case scenario in semesters 2, 4, and 7 were delivered using material previously developed by an experienced PBL practitioner, whilst material for semester 6 was prepared de novo by a less experienced practitioner. Each student (semesters 2: n=38, 4: n=37, 6: n=55, and 7: n=40) completed a questionnaire which asked whether: (i) the course had improved their critical thinking skills; (ii) the learning environment was sufficiently comfortable to express/share student’s opinion; (iii) there was sufficient facilitator guidance; (iv) the online study environment enhanced learning; and (v) the students were overall satisfied with the PBL approach and IVS concept. Responses were given on a 5-point Likert-scale (strongly agree (SA), agree (A), neutral (N), disagree (D), and strongly disagree (SD)). SA and A responses were summed to provide an overall ‘satisfactory’ response. Results were subjected to frequency-distribution statistical analysis. A total of 88.5% of students gave SA+A scores to their overall satisfaction. The proportion of SA+A scores differed between different semesters, such that 95% of semester 2, 4, and 7 students gave SA+A scores, whereas only 69% of semester 6 students did so for their respective sessions. Overall, 96% of the students gave SA+A scores to the question relating to the improvement of critical thinking skills: semester 6 students’ scores were marginally, but not significantly, lower (91% SA+A) than those in other semesters. The difference of scores between semester 6 and the other semesters may be attributed to the different PBL-material used and/or the different experience levels of the practitioners that developed the study material. The use of PBL as a means of teaching IVS curriculum-integration courses was well-received by the students in terms of their overall satisfaction and their perceptions of improved critical thinking skills. Importantly, this was achieved in the face of a methodology that was entirely novel to the students. Finally, the delivery of the PBL medium was readily mastered by the practitioner to whom it was also a novel methodology.

Keywords: critical thinking skills, integration, problem based learning, veterinary education

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Authors: Fatemeh Moosavi, Tumelo Franck Nkoshwane

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Peter Drucker the renowned management guru once said, “The best way to predict the future is to create it.” Mr. Drucker is also the man who placed human capital as the most vital resource of any institution. As such any institution bent on creating a better future, requires a competent human capital, one that is able to execute with efficiency and effectiveness the objective a society aspires to. Technology today is accelerating the rate at which many societies transition to knowledge based societies. In this accelerated paradigm, it is imperative that those in leadership establish a platform capable of sustaining the planned future; intellectual capital. The capitalist economy going into the future will not just be sustained by dollars and cents, but by individuals who possess the creativity to enterprise, innovate and create wealth from ideas. This calls for cities of the future, to have this premise at the heart of their future plan, if the objective of designing sustainable and liveable future cities will be realised. The knowledge economy, now transitioning to the creative economy, requires cities of the future to be ‘gardens’ of inspiration, to be places where knowledge, creativity, and innovation can thrive as these instruments are becoming critical assets for creating wealth in the new economic system. Developing nations must accept that learning is a lifelong process that requires keeping abreast with change and should invest in teaching people how to keep learning. The need to continuously update one’s knowledge, turn these cities into vibrant societies, where new ideas create knowledge and in turn enriches the quality of life of the residents. Cities of the future must have as one of their objectives, the ability to motivate their citizens to learn, share knowledge, evaluate the knowledge and use it to create wealth for a just society. The five functional factors suggested by Kevin Lynch;-vitality, meaning/sense, adaptability, access, control, and monitoring should form the basis on which policy makers and urban designers base their plans for future cities. The authors of this paper believe that developing nations “creative economy clusters”, cities where creative industries drive the need for constant new knowledge creating sustainable learning creative cities. Obviously the form, shape and size of these districts should be cognisant of the environmental, cultural and economic characteristics of each locale. Gaborone city in the republic of Botswana is presented as the case study for this paper.

Keywords: learning city, sustainable creative city, creative industry, good city form

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Authors: Albert K. Chong, Jasim Ahmed Ali Al-Baghdadi, Peter B. Milburn

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Precise capture of plantar 3D surface of the foot at the loading gait phases on rigid substrate was found to be valuable for the assessment of the physiology, health and problems of the feet. Photogrammetry, a precision 3D spatial data capture technique is suitable for this type of dynamic application. In this research, the technique is utilised to study of the effect on the plantar deformation for having a strip of kinesiology tape on the plantar surface while going through the loading phase of gait. For this pilot study, one healthy adult male subject was recruited under the USQ University human research ethics guidelines for this preliminary study. The 3D plantar deformation data of both with and without applying the tape were analysed. The results and analyses are presented together with the detail of the findings.

Keywords: gait, human plantar, plantar loading, photogrammetry, kinesiology tape

Procedia PDF Downloads 477

Authors: Yifan Fan, Xudong Luo, Pingping Lin

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An essential task in the field of artificial intelligence is to allow computers to interact with people through natural language. Therefore, researches such as virtual assistants and dialogue systems have received widespread attention from industry and academia. The response generation plays a crucial role in dialogue systems, so to push forward the research on this topic, this paper surveys various methods for response generation. We sort out these methods into three categories. First one includes finite state machine methods, framework methods, and instance methods. The second contains full-text indexing methods, ontology methods, vast knowledge base method, and some other methods. The third covers retrieval methods and generative methods. We also discuss some hybrid methods based knowledge and deep learning. We compare their disadvantages and advantages and point out in which ways these studies can be improved further. Our discussion covers some studies published in leading conferences such as IJCAI and AAAI in recent years.

Keywords: deep learning, generative, knowledge, response generation, retrieval

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Authors: Ciaran Friel, Jerry Suls, Patrick Robles, Frank Vicari, Joan Duer-Hefele, Karina W. Davidson

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Physical activity guidelines focus on increasing moderate intensity activity for older adults, but adherence to recommendations remains low. This is despite the fact that scientific evidence supports that any increase in physical activity is positively correlated with health benefits. Behavior change techniques (BCTs) have demonstrated effectiveness in reducing sedentary behavior and promoting physical activity. This pilot study uses a Personalized Trials (N-of-1) design to evaluate the efficacy of using four BCTs to promote an increase in low-intensity physical activity (2,000 steps of walking per day) in adults aged 45-75 years old. The 4 BCTs tested were goal setting, action planning, feedback, and self-monitoring. BCTs were tested in random order and delivered by text message prompts requiring participant response. The study recruited health system employees in the target age range, without mobility restrictions and demonstrating interest in increasing their daily activity by a minimum of 2,000 steps per day for a minimum of five days per week. Participants were sent a Fitbit Charge 4 fitness tracker with an established study account and password. Participants were recommended to wear the Fitbit device 24/7, but were required to wear it for a minimum of ten hours per day. Baseline physical activity was measured by the Fitbit for two weeks. Participants then engaged with a clinical research coordinator to review comprehension of the text message content and required actions for each of the BCTs to be tested. Participants then selected a consistent daily time in which they would receive their text message prompt. In the 8 week intervention phase of the study, participants received each of the four BCTs, in random order, for a two week period. Text message prompts were delivered daily at a time selected by the participant. All prompts required an interactive response from participants and may have included recording their detailed plan for walking or daily step goal (action planning, goal setting). Additionally, participants may have been directed to a study dashboard to view their step counts or compare themselves with peers (self-monitoring, feedback). At the end of each two week testing interval, participants were asked to complete the Self-Efficacy for Walking Scale (SEW_Dur), a validated measure that assesses the participant’s confidence in walking incremental distances and a survey measuring their satisfaction with the individual BCT that they tested. At the end of their trial, participants received a personalized summary of their step data in response to each individual BCT. Analysis will examine the novel individual-level heterogeneity of treatment effect made possible by N-of-1 design, and pool results across participants to efficiently estimate the overall efficacy of the selected behavioral change techniques in increasing low-intensity walking by 2,000 steps, 5 days per week. Self-efficacy will be explored as the likely mechanism of action prompting behavior change. This study will inform the providers and demonstrate the feasibility of N-of-1 study design to effectively promote physical activity as a component of healthy aging.

Keywords: aging, exercise, habit, walking

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Authors: Laura Sapranaviciute-Zabazlajeva, Abdonas Tamosiunas, Dalia Luksiene, Dalia Virviciute

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The cardiovascular diseases (CVD) is the leading cause of death in the EU, especially in the middle aged and elderly population. Psychological wellbeing (PWB) has been linked with better cardiovascular health and survival in the elderly. The aim of the study is to evaluate associations between CVD risk and PWB in middle-aged and elderly population. 10,940 middle aged and older Lithuanians of age 45-74 years, were invited to participate in the study. A study sample was a random and stratified by gender and age. In 2006-2008 7,087 responders participated in the survey, so the response rate was 64.8%. A follow-up study was conducted from 2006 till 2015. New CVD cases and deaths from CVD were evaluated using the Kaunas population-based CVD register and death register of Kaunas. Study results revealed that good PWB predicts longer life in female participants (Log Rank = 13.7, p < 0.001). In the fully adjusted model for socio-demographic, social and CVD risk factors, hazard ratio for CVD mortality risk was lower amongst women with good PWB (HR = 0.28, 95% CI 0.11-0.72), but not significantly for men. Our study concludes, that lower CVD mortality rates is being associated with better PWB in female aged 45-74 years.

Keywords: psychological well-being, cardiovascular disease, elderly, survival

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Authors: Ozlem Kaya

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21st-century learners are energetic and tech-savvy, and the skills and the knowledge required in this century are complex and challenging. Therefore, teachers need to find new ways to appeal to the needs and interests of their students and meet the demands of the 21st century at the same time. One way to do so in English language learning has been to incorporate various technology tools into classroom practices. Although teachers think these practices are effective and their students enjoy them, students may have different perceptions. To find out what students think about the use of technology tools in terms of developing 21st-century skills and knowledge, this study was conducted at Anadolu University School of Foreign Languages. A questionnaire was administered to 40 students at elementary level. Afterward, semi-structured interviews were held with 8 students to provide deeper insight into their perceptions. The details of the findings of the study will be presented and discussed during the presentation.

Keywords: 21st century skills, technology tools, perception, English Language Learning

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Authors: Sylvie Studente

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Despite the increase in international students migrating to the UK, the transition from home environment to a host institution abroad can be overwhelming for many students due to acculturative stressors. These stressors are reported to peak within the first six months of transitioning into study abroad which has determinantal impacts for Higher Education Institutions. These impacts include; increased drop-out rates and overall decreases in academic performance. Research suggests that belongingness can negate acculturative stressors through providing opportunities for students to form necessary social connections. In response to this universities have focussed on utilising technology to create learning communities with the most commonly deployed being social media, blogs, and discussion forums. Despite these attempts, the application of technology in supporting international students is still ambiguous. With the reported growing popularity of mobile devices among students and accelerations in learning technology owing to the COVID-19 pandemic, the potential is recognised to address this challenge via the use of chatbot technology. Whilst traditionally, chatbots were deployed as conversational agents in business domains, they have since been applied to the field of education. Within this emerging area of research, a gap exists in addressing the educational value of chatbots over and above the traditional service orientation categorisation. The proposed study seeks to extend upon current understandings by investigating the challenges faced by international students in studying abroad and exploring the potential of chatbots as a solution to assist students’ acculturation. There has been growing interest in the application of chatbot technology to education accelerated by the shift to online learning during the COVID-19 pandemic. Although interest in educational chatbots has surged, there is a lack of consistency in the research area in terms of guidance on the design to support international students in HE. This gap is widened when considering the additional challenge of supporting multicultural international students with diverse. Diversification in education is rising due to increases in migration trends for international study. As global opportunities for education increase, so does the need for multiculturally inclusive learning support.

Keywords: chatbots, education, international students, acculturation

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Authors: Annette Cosgrove, Carina Ginty, Tony Hall, Cornelia Connolly

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The objectives of this research study is to examine the impact of professional development in Technology Enhanced Learning (TEL) and the digitization of learning in teaching communities across multiple higher education sites in the ATU (Atlantic Technological University *) ( 2020-2025), including the proposal of an evidence-based digital teaching model for use in a future pandemic. The research strategy undertaken for this study is a multi-site study using mixed methods. Qualitative & quantitative methods are being used in the study to collect data. A pilot study was carried out initially, feedback was collected and the research instrument was edited to reflect this feedback before being administered. The purpose of the staff questionnaire is to evaluate the impact of professional development in the area of TEL, and to capture the practitioner's views on the perceived impact on their teaching practice in the higher education sector across ATU (West of Ireland – 5 Higher education locations ). The phenomenon being explored is ‘ the impact of professional development in the area of technology-enhanced learning and on teaching practice in a higher education institution. The research methodology chosen for this study is an Action based Research Study. The researcher has chosen this approach as it is a prime strategy for developing educational theory and enhancing educational practice. This study includes quantitative and qualitative methods to elicit data that will quantify the impact that continuous professional development in the area of digital teaching practice and technologies has on the practitioner’s teaching practice in higher education. The research instruments/data collection tools for this study include a lecturer survey with a targeted TEL Practice group ( Pre and post covid experience) and semi-structured interviews with lecturers. This research is currently being conducted across the ATU multi-site campus and targeting Higher education lecturers that have completed formal CPD in the area of digital teaching. ATU, a West of Ireland university, is the focus of the study. The research questionnaire has been deployed, with 75 respondents to date across the ATU - the primary questionnaire and semi-formal interviews are ongoing currently – the purpose being to evaluate the impact of formal professional development in the area of TEL and its perceived impact on the practitioners teaching practice in the area of digital teaching and learning. This paper will present initial findings, reflections and data from this ongoing research study.

Keywords: TEL, technology, digital, education

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Authors: Monica Racha, Siva Chandrasekaran, Alex Stojcevski

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The engineering programs focus on promoting students' personal and professional development by ensuring that students acquire technical and professional competencies during four-year studies. The traditional engineering laboratory provides an opportunity for students to "practice by doing," and laboratory facilities aid them in obtaining insight and understanding of their discipline. Due to rapid technological advancements and the current COVID-19 outbreak, the traditional labs were transforming into virtual learning environments. Aim: To better understand the limitations of the physical laboratory, this research study aims to use a Machine Learning (ML) algorithm that interfaces with the Augmented Reality HoloLens and predicts the image behavior to classify and detect the electronic components. The automated electronic components error classification and detection automatically detect and classify the position of all components on a breadboard by using the ML algorithm. This research will assist first-year undergraduate engineering students in conducting laboratory practices without any supervision. With the help of HoloLens, and ML algorithm, students will reduce component placement error on a breadboard and increase the efficiency of simple laboratory practices virtually. Method: The images of breadboards, resistors, capacitors, transistors, and other electrical components will be collected using HoloLens 2 and stored in a database. The collected image dataset will then be used for training a machine learning model. The raw images will be cleaned, processed, and labeled to facilitate further analysis of components error classification and detection. For instance, when students conduct laboratory experiments, the HoloLens captures images of students placing different components on a breadboard. The images are forwarded to the server for detection in the background. A hybrid Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) algorithm will be used to train the dataset for object recognition and classification. The convolution layer extracts image features, which are then classified using Support Vector Machine (SVM). By adequately labeling the training data and classifying, the model will predict, categorize, and assess students in placing components correctly. As a result, the data acquired through HoloLens includes images of students assembling electronic components. It constantly checks to see if students appropriately position components in the breadboard and connect the components to function. When students misplace any components, the HoloLens predicts the error before the user places the components in the incorrect proportion and fosters students to correct their mistakes. This hybrid Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) algorithm automating electronic component error classification and detection approach eliminates component connection problems and minimizes the risk of component damage. Conclusion: These augmented reality smart glasses powered by machine learning provide a wide range of benefits to supervisors, professionals, and students. It helps customize the learning experience, which is particularly beneficial in large classes with limited time. It determines the accuracy with which machine learning algorithms can forecast whether students are making the correct decisions and completing their laboratory tasks.

Keywords: augmented reality, machine learning, object recognition, virtual laboratories

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Authors: Mayank Raj, V. G. Narendra

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Ever since the DARPA challenge on autonomous vehicles in 2005, there has been a lot of buzz about ‘Autonomous Vehicles’ amongst the major tech giants such as Google, Uber, and Tesla. Numerous approaches have been adopted to solve this problem, which can have a long-lasting impact on mankind. In this paper, we have used Deep Learning techniques and TensorFlow framework with the goal of building a neural network model to predict (speed, acceleration, steering angle, and brake) features needed for navigation of autonomous vehicles. The Deep Neural Network has been trained on images and sensor data obtained from the comma.ai dataset. A heatmap was used to check for correlation among the features, and finally, four important features were selected. This was a multivariate regression problem. The final model had five convolutional layers, followed by five dense layers. Finally, the calculated values were tested against the labeled data, where the mean squared error was used as a performance metric.

Keywords: autonomous vehicles, deep learning, computer vision, artificial intelligence

Procedia PDF Downloads 139