Search results for: traditional learning

Authors: Wong Seng Yue

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Game dynamics and game mechanics are the two main components that used in gamification to engage and encourage students to learn. The advantages of gamified classroom are engaging students, increasing students interest, preserving students focus and remain a positive behaviour. However, the empirical studies on gamification are still at early stage, especially the effectiveness of various gamification components have not been evaluated. Thus, this study is aimed to conduct a user experience (UX) evaluation on gamified classroom through Prezi, which focused on learning experience, gaming experience, adaptivity, and gameplay experience. This study is a further study extended from the previous exploratory study to explore more on UX of gamified classroom via Prezi by interview. A focus group study, which involves 22 students from a foundation course has been conducted for the study. Besides the empirical data from the previous study, this focus group study has significantly found that 90.9% respondents show their positive perceptions on gaming experience via Prezi. They are interested, feel fresh, good, and highly motivated of the contents of Prezi. 95.5% participants have had a positive learning experience from the gamified classroom via Prezi, which can engage them, made them concentrate on learning and easy to remember what they have learned if compared to the traditional classroom slides. The adaptivity of the gamified classroom also high due to its zooming user interface, narrative, rewards and engagement features. This study has uncovered on how far the impact of gamification components in the classroom, especially UX that implemented in gamified classroom.

Keywords: user experience (UX), gamification, gamified classroom, Prezi

Procedia PDF Downloads 198

Authors: PB Venkataraman

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Most of the real-life problems are ill-structured. They do not have a single solution but many competing solutions. The solution paths are non-linear and ambiguous, and the problem definition itself is many times a challenge. Students of professional education learn to solve such problems through internships. The current pandemic situation has constrained on-site internship opportunities; thus the students have no option but to pursue this learning online. This research assessed the learning gain of four undergraduate students in engineering as they undertook an online internship in an organisation over a period of eight weeks. A clinical interview at the end of the internship provided the primary data to assess the team’s problem-solving skills using a tested rubric. In addition to this, change in their learning attitudes were assessed through a pre-post study using a repurposed CLASS instrument for Electrical Engineering. Analysis of CLASS data indicated a shift in the sophistication of their learning attitude. A learning engagement survey adopting a 6-point Likert scale showed active participation and motivation in learning. We hope this new research will stimulate educators to exploit online internships even beyond the time of pandemic as more and more business operations are transforming into virtual.

Keywords: ill-structured problems, learning attitudes, internship, assessment, student engagement

Procedia PDF Downloads 194

Authors: Christodoulou Christos, Politis Anastasios

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A large majority of users favoured to wireless LAN connection since it was so simple to use. A wireless network can be the target of numerous attacks. Class hijacking is a well-known attack that is fairly simple to execute and has significant repercussions on users. The statistical flow analysis based on machine learning (ML) techniques is a promising categorization methodology. In a given dataset, which in the context of this paper is a collection of components representing frames belonging to various flows, machine learning (ML) can offer a technique for identifying and characterizing structural patterns. It is possible to classify individual packets using these patterns. It is possible to identify fraudulent conduct, such as class hijacking, and take necessary action as a result. In this study, we explore a way to use machine learning approaches to thwart this attack.

Keywords: wireless lan, quality of service, machine learning, class hijacking, EDCA remapping

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Authors: Pieter Conradie, M. Marina Moller

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Web 2.0 Internet-based technologies have intruded all aspects of human life. Presently, this phenomenon is especially evident in the educational context, with increased disruptive Web 2.0 technology infusions dramatically changing educational practice. The most prominent of these Web 2.0 intrusions can be identified as Massive Open Online Courses (Coursera, EdX), video and photo sharing sites (Youtube, Flickr, Instagram), and Web 2.0 online tools utilize to create Personal Learning Environments (PLEs) (Symbaloo (aggregator), Delicious (social bookmarking), PBWorks (collaboration), Google+ (social networks), Wordspress (blogs), Wikispaces (wiki)). These Web 2.0 technologies have supported the realignment from a teacher-based pedagogy (didactic presentation) to a learner-based pedagogy (problem-based learning, project-based learning, blended learning), allowing greater learner autonomy. No longer is the educator the source of knowledge. Instead the educator has become the facilitator and mediator of the learner, involved in developing learner competencies to support life-long learning (continuous learning) in the 21st century. In this study, the self-regulated learning skills of thirty first-year university learners were explored by utilizing the Online Self-regulated Learning Questionnaire. Implementing an action research method, an intervention was affected towards improving the self-regulation skill set of the participants. Statistical significant results were obtained with increased self-regulated learning proficiency, positively impacting learner performance. Goal setting, time management, environment structuring, help seeking, task (learning) strategies and self-evaluation skills were confirmed as determinants of improved learner success.

Keywords: andragogy, online self-regulated learning questionnaire, self-regulated learning, web 2.0

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Authors: Heny Hartono, Cecilia Titiek Murniati

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The pandemic has given teachers and students no other choice but having full online learning. In such an emergency situation as the time of the covid-19 pandemic, the application of LMS (Learner Management System) in higher education is the most reasonable solution for students and teachers. In fact, the online learning requires all elements of a higher education systems, including the human resources, infrastructure, and supporting systems such as the application, server, and stable internet connection. The readiness of the higher education institution in preparing the online system may secure those who are involved in the online learning process. It may also result in students’ self-efficacy in online learning. This research aimed to investigate how students perceive their self-efficacy in online English learning, especially in speaking classes which is considered as a productive language skill. This research collects qualitative data with narrative inquiry involving 25 students of speaking classes as the respondents. The results of this study show that students perceive their self-efficacy in speaking online classes as not very high.

Keywords: self-efficacy, online learning, speaking class, college students, e-learning

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Authors: Jianhua Wang, Ying Zhou, Xi Zhang

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To establish the influential mechanism of learning engagement on interpreter’s performance, the present study submitted a questionnaire to a sample of 927 English major students with 804 valid ones and used the structural equation model as the basis for empirical analysis and statistical inference on the sample data. In order to explore the mechanism for interpreting learning engagement on student interpreters’ performance, a path model of interpreting processes with three variables of ‘input-environment-output’ was constructed. The results showed that the effect of each ‘environment’ variable on interpreting ability was different from and greater than the ‘input’ variable, and learning engagement was the greatest influencing factor. At the same time, peer interaction on interpreting performance has significant influence. Results suggest that it is crucial to provide effective guidance for optimizing learning engagement and interpreting teaching research by both improving the environmental support and building the platform of peer interaction, beginning with learning engagement.

Keywords: learning engagement, interpreting performance, interpreter training, English major students

Procedia PDF Downloads 188

Authors: Valerie Triggs, Michele Sorensen

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As two university professors in postsecondary faculties of social work and education, we have observed that students often recognize the importance of learning facts about colonization but have difficulty grappling with how they themselves might be implicated in reconciliation or how they might respond to these facts in meaningful ways. The detachment observed between students and factual information results in the initiation of a research study centered around an approach to teaching the course. This involved transitioning its pedagogical format to embrace a/r/tographic methods of teaching, learning, and inquiry. By taking seriously the arguments of various Indigenous scholars for learning from the land and by working alongside traditional Indigenous knowledge, we chose to engage a speculative approach to course design and teaching, which actually used the land as one of the course texts. We incorporated art practices that involved connecting bodies with land as well as using land materials in various creative and aesthetic projects while being informed by Medicine Keepers, Indigenous and settler artists, and knowledge-keeper helpers. In this study, we share some of the unanticipated themes that arose when students began to allow land and artmaking, both aesthetically and intuitively, through both joy and sorrow, to affect a reimagining and repositioning of selves and relations. We found that time and engagement with land and art began to build more empathic understanding and foster personal and professional practices grounded in respect, relevance, reciprocity, and responsibility.

Keywords: reconciliation, decolonization, artmaking, respect

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Authors: Vincenzo Capalbo, Gianpaolo Ghiani, Emanuele Manni

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Global e-commerce sales have reached unprecedented levels in the past few years. As this trend is only predicted to go up as we continue into the ’20s, new challenges will be faced by companies when planning and controlling e-commerce logistics. In this paper, we survey the related literature on Optimization and Machine Learning as well as on combined methodologies. We also identify the distinctive features of next-generation planning algorithms - namely scalability, model-and-run features and learning capabilities - that will be fundamental to cope with the scale and complexity of logistics in the next decade.

Keywords: e-commerce, hardware acceleration, logistics, machine learning, mixed integer programming, optimization

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Authors: Chinaza Uleanya, Martin Duma, Bongani Gamede

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The study investigated learning challenges experienced by students in universities situated in developing sub-Saharan African countries using selected universities in South Africa and Nigeria. Questionnaires were administered to 2,335 randomly selected students from selected universities in South Africa and Nigeria. The outcome of the study shows that six common learning challenges are visible in developing sub-Sahara African universities. The causes of these learning challenges cut across the failure in responsibilities of the various stakeholders in the field of education and the effects are monumental both to the students and society. This paper suggests recommendations to university administrators, education policy makers and implementers on the need to take education more seriously, to review and implement appropriate policies, and to ensure provision of quality education through the supply of adequate amenities and other motivating factors.

Keywords: learning, challenges, learning challenges, access with success, participatory access

Procedia PDF Downloads 284

Authors: Atakan Aral Ormancı, Tuğçe Arslantaş, Murat Özcü

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This study presents the design and implementation of an experimental chassis-level system for various control applications. Specifically, the height level of the chassis is controlled using proportional integrated derivative, fuzzy logic, and deep learning control methods. Real-time data obtained from height and pressure sensors installed in a 6x2 truck chassis, in combination with pulse-width modulation signal values, are utilized during the tests. A prototype pneumatic system of a 6x2 truck is added to the setup, which enables the Smart Pneumatic Actuators to function as if they were in a real-world setting. To obtain real-time signal data from height sensors, an Arduino Nano is utilized, while a Raspberry Pi processes the data using Matlab/Simulink and provides the correct output signals to control the Smart Pneumatic Actuator in the truck chassis. The objective of this research is to optimize the time it takes for the chassis to level down and up under various loads. To achieve this, proportional integrated derivative control, fuzzy logic control, and deep learning techniques are applied to the system. The results show that the deep learning method is superior in optimizing time for a non-linear system. Fuzzy logic control with a triangular membership function as the rule base achieves better outcomes than proportional integrated derivative control. Traditional proportional integrated derivative control improves the time it takes to level the chassis down and up compared to an uncontrolled system. The findings highlight the superiority of deep learning techniques in optimizing the time for a non-linear system, and the potential of fuzzy logic control. The proposed approach and the experimental results provide a valuable contribution to the field of control, automation, and systems engineering.

Keywords: automotive, chassis level control, control systems, pneumatic system control

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Authors: Haitham Taha

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The cognitive flexibility of 27 asthmatic children with learning difficulties was tested by using the Wisconsin card sorting test (WCST) and compared to the performances of 30 non-asthmatic children who have persistence learning difficulties also. The results revealed that the asthmatic group had poor performance through all the WCST psychometric parameters and especially the preservative errors one. The results were discussed in light of the postulation that poor executive functions and specifically poor cognitive flexibility are in the basis of the learning difficulties of asthmatic children with learning difficulties. Neurophysiologic framework was suggested for explaining the etiology of poor executive functions and cognitive flexibility among children with moderate into severe asthma.

Keywords: asthma, learning disabilities, executive functions, cognitive flexibility, WCST

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Authors: Sana Mohammad Jafar, Hossaini Seyahi Zohreh

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Infections and food intoxication caused by microbial contamination of food is of major issues in different countries, and diseases caused by the consumption of contaminated food included a large percentage of the country's health problems. Since traditional cheese for cultural reasons, good taste and smell in many parts of the area still has the important place in people's food basket, transmission of pathogenic bacteria could be at risk human health through the consumption of this food. In this study selected randomly 100 samples of 250 grams of traditional cheeses supplied in the city Behbahan market and adjacent to the ice was transferred to the laboratory and microbiological tests were performed immediately. According to the results, from 100 samples tested traditional cheese, 94 samples (94% of samples) were contaminated with coliforms, which of this number 75 samples (75% of samples) the contamination rate was higher than the limit (more than 100 cfu/g). Of the total samples, 36 samples (36% of samples) were contaminated with fecal coliform which of this number 30 samples (30% of samples) were contaminated with Escherichia.coli bacteria. Based on the results of agglutination test,no samples was found positive as pathogenic Escherichia.coli.

Keywords: determination, traditional cheese, Behbahan, Escherichia coli

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Authors: Harun Bozna

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MOOC (massive open online course) is a groundbreaking education platform and a current buzzword in higher education. Although MOOCs offer many appreciated learning experiences to learners from various universities and institutions, they have considerably higher dropout rates than traditional education. Only about 10% of the learners who enroll in MOOCs actually complete the course. In this case, perceptions of participants and a comprehensive analysis of MOOCs have become an essential part of the research in this area. This study aims to explore the MOOCs in detail for better understanding its content, purpose and primarily drop out issues. The researcher conducted an online questionnaire to get perceptions of graduate students on their learning experiences in MOOCs and arranged a semi- structured oral interview with some participants. The participants are Turkish graduate level students doing their MA and Ph.D. in various programs. The findings show that participants are more likely to drop out courses due to lack of time and lack of pressure.

Keywords: distance education, MOOCs, drop out, perception of graduate students

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Authors: Dante J. Dorantes-González, Aldrin Balsa-Yepes

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Existing learning techniques such as problem-based learning, project-based learning, or case study learning are learning techniques that focus mainly on technical details, but give no specific guidelines on learner’s experience and emotional learning aspects such as arousal salience and valence, being emotional states important factors affecting engagement and retention. Some approaches involving emotion in educational settings, such as social and emotional learning, lack neuroscientific rigorousness and use of specific neurobiological mechanisms. On the other hand, neurobiology approaches lack educational applicability. And educational approaches mainly focus on cognitive aspects and disregard conditioning learning. First, authors start explaining the reasons why it is hard to learn thoughtfully, then they use the method of neurobiological mapping to track the main limbic system functions, such as the reward circuit, and its relations with perception, memories, motivations, sympathetic and parasympathetic reactions, and sensations, as well as the brain cortex. The authors conclude explaining the major finding: The mechanisms of nonconscious learning and the triggers that guarantee long-term memory potentiation. Afterward, the educational framework for practical application and the instructors’ guidelines are established. An implementation example in engineering education is given, namely, the study of tuned-mass dampers for earthquake oscillations attenuation in skyscrapers. This work represents an original learning technique based on nonconscious learning mechanisms to enhance long-term memories that complement existing cognitive learning methods.

Keywords: emotion, emotion-enhanced memory, learning technique, STEM

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Authors: Wentian Shi, Daming Shi, Maysam Orouskhani, Feng Tian

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Whereas currently the most prevalent deep learning methods require a large amount of data for training, few-shot learning tries to learn a model from limited data without extensive retraining. In this paper, we present a loss function based on triplet loss for solving few-shot problem using metric based learning. Instead of setting the margin distance in triplet loss as a constant number empirically, we propose an adaptive margin distance strategy to obtain the appropriate margin distance automatically. We implement the strategy in the deep siamese network for deep metric embedding, by utilizing an optimization approach by penalizing the worst case and rewarding the best. Our experiments on image recognition and co-segmentation model demonstrate that using our proposed triplet loss with adaptive margin distance can significantly improve the performance.

Keywords: few-shot learning, triplet network, adaptive margin, deep learning

Procedia PDF Downloads 157

Authors: Sheldon McCall, Miao Yu, Liyun Gong, Shigang Yue, Stefanos Kollias

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Falls are a significant health concern for older adults globally, and prompt identification is critical to providing necessary healthcare support. Our study proposes a new fall detection method using computer vision based on modern deep learning techniques. Our approach involves training a trans- former model on a large 2D pose dataset for general action recognition, followed by transfer learning. Specifically, we freeze the first few layers of the trained transformer model and train only the last two layers for fall detection. Our experimental results demonstrate that our proposed method outperforms both classical machine learning and deep learning approaches in fall/non-fall classification. Overall, our study suggests that our proposed methodology could be a valuable tool for identifying falls.

Keywords: healthcare, fall detection, transformer, transfer learning

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Authors: Hamza Zidoum

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This paper investigates the impact of human genetic variation on the function of human proteins using machine-learning algorithms. Single-Nucleotide Polymorphism represents the most common form of human genome variation. We focus on the single amino-acid polymorphism located in the coding region as they can affect the protein function leading to pathologic phenotypic change. We use several supervised Machine Learning methods to identify structural properties correlated with increased risk of the missense mutation being damaging. SVM associated with Principal Component Analysis give the best performance.

Keywords: single-nucleotide polymorphism, machine learning, feature selection, SVM

Procedia PDF Downloads 366

Authors: Ntokozo C. Mthembu

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The notion of sustainable chemistry has become significant in the discourse for a global post-colonial era, including South Africa, especially when it comes to access to the general health system and related policies in relation to disease or ease of human life. In view of the stubborn vestiges of coloniality in the daily lives of indigenous African people in general, the fundamentals of present Western medical and traditional medicine systems and related policies in the democratic era were examined in this study. The situation of traditional healers in relation to current policy was also reviewed. The advent of democracy in South Africa brought about a variety of development opportunities and limitations, particularly with respect to indigenous African knowledge systems such as traditional medicine. There were high hopes that the limitations of previous narrow cultural perspectives would be rectified in the democratic era through development interventions, but some sections of society, such as traditional healers, remain marginalised. The Afrocentric perspective was explored in dissecting government interventions related to traditional medicine. This article highlights that multiple medical systems should be adopted and that health policies should be aligned in order to guarantee mutual respect and to address the remnants of colonialism in South Africa, Africa and the broader global community.

Keywords: traditional healing system, healers, pluralist healthcare system, post-colonial era

Procedia PDF Downloads 139

Authors: Salwa Aftab, Sehrish Riaz

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The objective of this study was to check the impact of grade sensitivity on learning motivation and academic performance of students and to remove the degree of difference that exists among students regarding the cause of their learning motivation and also to gain knowledge about this matter since it has not been adequately researched. Data collection was primarily done through the academic sector of Pakistan and was depended upon the responses given by students solely. A sample size of 208 university students was selected. Both paper and online surveys were used to collect data from respondents. The results of the study revealed that grade sensitivity has a positive relationship with the learning motivation of students and their academic performance. These findings were carried out through systematic correlation and regression analysis.

Keywords: academic performance, correlation, grade sensitivity, learning motivation, regression

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Authors: Rafia Rafique, Arifa Khadim

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This research investigates the moderating role of job satisfaction between organizational learning and work performance among nurses. Correlation research design was used. Non-probability purposive sampling technique was utilized to recruit a sample of 110 nurses from public hospitals situated in the city of Lahore. The construct of organizational learning was measured using subscale of Integrated Scale for Measuring Organizational Learning. Job satisfaction was measured with the help of Job Satisfaction Survey. Performance of employees (task performance, contextual performance and counterproductive work behavior) was assessed by Individual Work Performance Questionnaire. Job satisfaction negatively moderates the relationship between organizational learning and counterproductive work behavior. Education has a significant positive relationship with organizational learning. Age, current hospital experience, marital satisfaction and salary of the nurses have positive relationship while number of children has significant negative relationship with counterproductive work behavior. These outcomes can be insightful in understanding the dynamics involved in work performance. Based on the result of this study relevant solutions can be proposed to improve the work performance of nurses.

Keywords: counterproductive work behavior, nurses, organizational learning, work performance

Procedia PDF Downloads 426

Authors: Jatuphum Ketchatturat

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Value-added assessment has been used for developing the model of monitoring and evaluation of student's learning achievement. The steps of model development consist of 1) study and analyisis of the school and the district report system of student achievement and progress, 2) collecting the data of student achievement to develop the value added indicator, 3) developing the system of value-added assessment by participatory action research approach, 4) putting the system of value-added assessment into the educational district of secondary school, 5) determining the quality of the developed system of value-added assessment. The components of the developed model consist of 1) the database of value-added assessment of student's learning achievement, 2) the process of monitoring and evaluation the student's learning achievement, and 3) the reporting system of value-added assessment of student's learning achievement.

Keywords: learning achievement, monitoring and evaluation, value-added assessment

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Authors: Vishnu Pratap Singh Kirar, Madhuri Saxena

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Advancement in sequence data generation technologies is churning out voluminous omics data and posing a massive challenge to annotate the biological functional features. With so much data available, the use of machine learning methods and tools to make novel inferences has become obvious. Machine learning methods have been successfully applied to a lot of disciplines, including computational biology and bioinformatics. Researchers in computational biology are interested to develop novel machine learning frameworks to classify the huge amounts of biological data. In this proposal, it plan to employ novel machine learning approaches to aid the understanding of how apparently innocuous mutations (in intergenic DNA and at synonymous sites) cause diseases. We are also interested in discovering novel functional sites in the genome and mutations in which can affect a phenotype of interest.

Keywords: genome wide association studies (GWAS), next generation sequencing (NGS), deep learning, omics

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Authors: Shazi Shah Jabeen, Ajay Jesse Thomas

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The study is aimed at understanding the learning trends of students who opt for online language courses and to assess the effectiveness of the same. Multiple factors including use of the latest available technology and the skills that are trained by these online methods have been assessed. An attempt has been made to answer how each of the various language skills is trained online and how effective the online methods are compared to the classroom methods when students interact with peers and instructor. A mixed method research design was followed for collecting information for the study where a survey by means of a questionnaire and in-depth interviews with a number of respondents were undertaken across the various institutes and study centers located in the United Arab Emirates. The questionnaire contained 19 questions which included 7 sub-questions. The study revealed that the students find learning with an instructor to be a lot more effective than learning alone in an online environment. They prefer classroom environment more than the online setting for language learning.

Keywords: effectiveness, language, online learning, skills

Procedia PDF Downloads 581

Authors: Arun Prasad Jaganathan

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In today's dynamic industrial world, traditional task allocation methods often fall short in adapting to evolving operational conditions. This paper introduces an AI-enabled task assistance and management system designed to overcome the limitations of conventional approaches. By using artificial intelligence (AI) and machine learning (ML), the system intelligently interprets user instructions, analyzes tasks, and allocates resources based on real-time data and environmental factors. Additionally, geolocation tracking enables proactive identification of potential delays, ensuring timely interventions. With its transparent reporting mechanisms, the system provides stakeholders with clear insights into task progress, fostering accountability and informed decision-making. The paper presents a comprehensive overview of the system architecture, algorithm, and implementation, highlighting its potential to revolutionize task management across diverse industries.

Keywords: artificial intelligence, machine learning, task allocation, operational efficiency, resource optimization

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Authors: Samer Abu Ghazaleh, Jawdat Gousous

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E-learning in general started in Jordan around ten years ago in universities and at different departments and colleges. This paper will investigate the possibility to apply e-learning in architecture department at University of Jordan. As known architecture departments in general depend greatly in its syllabus upon design courses and studios, which consists nearly one third of its total credit hours. A survey has been conducted for architectural students at the University of Jordan and several conclusions have been reached irrespective of age, gender and nationality of the students, where the main problem was the way of the communication between the tutor and the student.

Keywords: cellular telephone, design courses, e-learning, internet

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Authors: N. Didiş Körhasan, D. Kaltakçı Gürel

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Many students have difficulty in learning physics from elementary to university level. In addition, students' expectancy, attitude, and motivation may be influenced negatively with their experience (failure) and prejudice about physics learning. For this reason, physics educators, who are also physics teachers, search for the best ways to make students' learning of physics easier by considering cognitive, affective, and psychomotor issues in learning. This research critically discusses the history of physics education, fundamental pedagogical approaches, and models to teach physics, and transformation of physics education with recent research.

Keywords: pedagogy, physics, physics education, science education

Procedia PDF Downloads 253

Authors: Thomas Turner

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Due to the Covid-19 pandemic alternative ways of delivering dental education were required. As a result, many institutions moved teaching online. The impact of this is poorly understood. Is online problem-based learning (PBL) and case-based learning (CBL) effective and is it suitable in the post-pandemic era? PBL and CBL are both types of interactive, group-based learning which are growing in popularity within many dental schools. PBL was first introduced in the 1960’s and can be defined as learning which occurs from collaborative work to resolve a problem. Whereas CBL encourages learning from clinical cases, encourages application of knowledge and helps prepare learners for clinical practice. To evaluate the use of online PBL and CBL. A literature search was conducted using the CINAHL, Embase, PubMed and Web of Science databases. Literature was also identified from reference lists. Studies were only included from dental education. Seven suitable studies were identified. One of the studies found a high learner and facilitator satisfaction rate with online CBL. Interestingly one study found learners preferred CBL over PBL within an online format. A study also found, that within the context of distance learning, learners preferred a hybrid curriculum including PBL over a traditional approach. A further study pointed to the limitations of PBL within an online format, such as reduced interaction, potentially hindering the development of communication skills and the increased time and technology support required. An audience response system was also developed for use within CBL and had a high satisfaction rate. Interestingly one study found achievement of learning outcomes was correlated with the number of student and staff inputs within an online format. Whereas another study found the quantity of learner interactions were important to group performance, however the quantity of facilitator interactions was not. This review identified generally favourable evidence for the benefits of online PBL and CBL. However, there is limited high quality evidence evaluating these teaching methods within dental education and there appears to be limited evidence comparing online and faceto-face versions of these sessions. The importance of the quantity of learner interactions is evident, however the importance of the quantity of facilitator interactions appears to be questionable. An element to this may be down to the quality of interactions, rather than just quantity. Limitations of online learning regarding technological issues and time required for a session are also highlighted, however as learners and facilitators get familiar with online formats, these may become less of an issue. It is also important learners are encouraged to interact and communicate during these sessions, to allow for the development of communication skills. Interestingly CBL appeared to be preferred to PBL in an online format. This may reflect the simpler nature of CBL, however further research is required to explore this finding. Online CBL and PBL appear promising, however further research is required before online formats of these sessions are widely adopted in the post-pandemic era.

Keywords: case-based learning, online, problem-based learning, remote, virtual

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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: Dian Hartiningsih, Miranda Diponegoro, Evita Eddie Singgih

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In facing the 21st century, children need to be prepared in reaching their optimum development level which encompasses all aspect of growth and to achieve the learning goals which include not only knowledge and skill, but also disposition and feeling. Teachers as the forefront of education need to be equipped with the understanding and skill of a learning method which can prepare the children to face this 21st century challenge. Project approach is an approach which utilizes active learning which is beneficial for the children. Subject to this research are kindergarten teachers at Dwi Matra Kindergarten and Kirana Preschool. This research is a quantitative research using before and after study design. The result suggest that through preliminary training program on learning with project approach, the kindergarten teachers ability to explain project approach including understanding, benefit and stages of project approach have increased significantly, the teachers ability to design learning with project approach have also improved significantly. The result of learning design that the teachers had made shows a remarkable result for the first stage of the project approach; however the second and third design result was not as optimal. Challenges faced in the research will be elaborated further in the research discussion.

Keywords: project approach, teacher training, learning method, kindergarten

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Authors: Subramaniam Chandran, A. Geetha

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This paper addresses three issues: how to prepare instructional design for imparting English language skill from inter-disciplinary self-learning material; how the disadvantaged students are benefited from such kind of language skill imparted through m-learning; and how do the m-learners perform better than the other learners. This paper examines these issues through an experimental study conducted among the distance learners enrolled in preparatory program for bachelor’s degree. This program is designed for the disadvantage learners especially for the school drop-outs to qualify to pursue graduate program through distant education. It also explains how mobile learning helps them to enhance their capacity in learning despite their rural background and other disadvantages. In India nearly half of the students enrolled in schools do not complete their study. The pursuance of higher education is very low when compared with developed countries. This study finds a significant increase in their learning capacity and mobile learning seems to be a viable alternative where conventional system could not reach the disadvantaged learners. Improving the English language skill is one of the reasons for such kind of performance. Exercises framed from the relevant self-learning material for enhancing English language skill not only improves language skill but also widens the subject-knowledge. This paper explains these issues out of the study conducted among the disadvantaged learners.

Keywords: English language skill, disadvantaged learners, distance education, m-learning

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