Search results for: learning management systems

Authors: Vivek Mahadev, Manoj Kumar, Neelu Mathur, Brahm Dutt Pandey

Abstract:

Perimeter guarding and protection of critical installations require prompt intrusion detection and assessment to take effective countermeasures. Currently, visual and electronic surveillance are the primary methods used for perimeter guarding. These methods can be costly and complicated, requiring careful planning according to the location and terrain. Moreover, these methods often struggle to detect stealthy and camouflaged insurgents. The object of the present work is to devise a surveillance technique using seismic sensors that overcomes the limitations of existing systems. The aim is to improve intrusion detection, assessment, and characterization by utilizing seismic sensors. Most of the similar systems have only two types of intrusion detection capability viz., human or vehicle. In our work we could even categorize further to identify types of intrusion activity such as walking, running, group walking, fence jumping, tunnel digging and vehicular movements. A virtual fence of 60 meters at GCNEP, Bahadurgarh, Haryana, India, was created by installing four underground geophones at a distance of 15 meters each. The signals received from these geophones are then processed to find unique seismic signatures called features. Various feature optimization and selection methodologies, such as LightGBM, Boruta, Random Forest, Logistics, Recursive Feature Elimination, Chi-2 and Pearson Ratio were used to identify the best features for training the machine learning models. The trained models were developed using algorithms such as supervised support vector machine (SVM) classifier, kNN, Decision Tree, Logistic Regression, Naïve Bayes, and Artificial Neural Networks. These models were then used to predict the category of events, employing weighted ensemble voting to analyze and combine their results. The models were trained with 1940 training events and results were evaluated with 831 test events. It was observed that using the weighted ensemble voting increased the efficiency of predictions. In this study we successfully developed and deployed the virtual fence using geophones. Since these sensors are passive, do not radiate any energy and are installed underground, it is impossible for intruders to locate and nullify them. Their flexibility, quick and easy installation, low costs, hidden deployment and unattended surveillance make such systems especially suitable for critical installations and remote facilities with difficult terrain. This work demonstrates the potential of utilizing seismic sensors for creating better perimeter guarding and protection systems using multiple machine learning models in weighted ensemble voting. In this study the virtual fence achieved an intruder detection efficiency of over 97%.

Keywords: geophone, seismic perimeter surveillance, machine learning, weighted ensemble method

Procedia PDF Downloads 64

Authors: Shanxiong Chen, Xu Han, Xiaolong Wang, Hui Ma

Abstract:

Yi is an ethnic group mainly living in mainland China, with its own spoken and written language systems, after development of thousands of years. Ancient Yi is one of the six ancient languages in the world, which keeps a record of the history of the Yi people and offers documents valuable for research into human civilization. Recognition of the characters in ancient Yi helps to transform the documents into an electronic form, making their storage and spreading convenient. Due to historical and regional limitations, research on recognition of ancient characters is still inadequate. Thus, deep learning technology was applied to the recognition of such characters. Five models were developed on the basis of the four-layer convolutional neural network (CNN). Alpha-Beta divergence was taken as a penalty term to re-encode output neurons of the five models. Two fully connected layers fulfilled the compression of the features. Finally, at the softmax layer, the orthographic features of ancient Yi characters were re-evaluated, their probability distributions were obtained, and characters with features of the highest probability were recognized. Tests conducted show that the method has achieved higher precision compared with the traditional CNN model for handwriting recognition of the ancient Yi.

Keywords: recognition, CNN, Yi character, divergence

Procedia PDF Downloads 152

Authors: Thuy T. T. Tran, Hamish Coates, Sophie Arkoudis

Abstract:

Evaluation instruments of teaching are abundant; however, these do not prompt any enhancement in the quality of teaching, not least because these instruments are framed only by teacher-centered conceptions of teaching. There is a need for more sophisticated teaching evaluation measures that focus on student learning and multi-stakeholder involvement. This study aims to develop such an evaluation instrument for Vietnamese higher education. The study uses several kinds of methods. The instrument was initially drafted through in-depth review of research, paying close attention to Vietnamese higher education. Draft evaluation instruments were produced and reviewed by 34 experts. The outcomes of this qualitative and quantitative data reveal an instrument that highlights the value of a multisource student-centered approach, and the rich integration of contextual and cultural traits where Confucian values are emphasized. The validation affirms that evaluating teaching in such way will facilitate the continuous learning growth of all stakeholders involved.

Keywords: multi stakeholders, quality teaching, student learning, teaching evaluation

Procedia PDF Downloads 290

Authors: Niall J. English

Abstract:

Under- and post-graduate training can benefit from a more active learning style, and most particularly so in engineering. Despite this, outreach to young children in primary and secondary schools is less-developed in terms of its documented effectiveness, especially given new emphasis placed within the third level and advanced research program’s on Education and Public Engagement (EPE). Bearing this in mind, outreach and school visits form the basis to ascertain how active learning, careers stimulus and EPE initiatives for young children can inform the university sector, helping to improve future engineering-teaching standards, and enhancing both quality and practicalities of the teaching-and-learning experience. Indeed, engineering-education EPE/outreach work has been demonstrated to lead to several tangible benefits and improved outcomes, such as greater engagement and interest with science/engineering for school-children, careers awareness, enabling teachers with strong contributions to technical knowledge of engineering subjects, and providing development of general professional skills for engineering, e.g., communication and teamwork. This intervention involved active learning in ‘buzz’ groups for young children of concepts in gas engineering, observing their peer interactions to develop university-level lessons on activity learning. In addition, at the secondary level, careers-outreach efforts have led to statistical determinations of motivations towards engineering education and training, which aids in the redesign of engineering curricula for more active learning.

Keywords: outreach, education and public engagement, careers, peer interactions

Procedia PDF Downloads 107

Authors: Abdullah, Ali, Salamai

Abstract:

Smart healthcare management systems (SHMS) play a vital role in medical centers. SHMS has various risks and threats that affect patient care. So, risk management is the best choice to identify and mitigate these risks. This study proposed a multi-criteria decision-making (MCDM) framework for identifying risks in SHMS and selecting the best project in SHMS to reduce risks. This study used the MCDM method to deal with conflict criteria. There are two MCDM methods: CRiteria Importance Through Intercriteria Correlation (CRITIC) and Additive Ration Assessment (ARAS). The CRITIC approach is used to compute the criteria weights, and the ARAS algorithm is used to select the appropriate projects in SHMS. The neutrosophic set (NS) was applied with MCDM methods to deal with inconsistent data in the evaluation process. The results show the Health Data Informational System project is the best. Sensitivity analysis was conducted to show the stability of the rank. The comparative study was conducted to show the effectiveness of the proposed methodology. The outcomes demonstrate the rank of projects is stable through all scenarios, and the proposed methodology is effective compared with MCDM methods.

Keywords: risk management, portfolio management, smart healthcare, neutrosophic set, MCDM

Procedia PDF Downloads 7

Authors: Jenney Perez Bacalla

Abstract:

The study was conducted to assess the five (5) identified school administrators of the identified secondary schools in terms of professional characteristics, management skills and values patterns in the Division of Leyte Area IV for a proposed enhancement model for school administrators. The study utilized the qualitative method. There were two (2) groups of respondents: the teachers and the school administrators. The teachers perceived the management skills of the school administrators in their technical and conceptual skills and values in planning and organizing work, allocating and using of funds, submitting reports, decision-making, leading people, public relations and community involvement and other value development. It was found out in the study that most of the school administrators’ management skills were very well manifested. Their value patterns were also very well manifested. Most of them had earned master’s degree and with a unit in doctoral and five (5) years and above in service as a school administrator. Most administrators were performing and successfully execute the planning, organizing and utilizing funds and they were able to lead their subordinates. In planning, it shows that administrators studied the future and arrange the plan. Administrators also were able to manage, maintained the good environment wherein individual work together. School administrators were creating an environment conducive to learning. The school administrator is manifesting the desirable practices in school management. In terms of their educational qualifications, they were all qualified. Academic preparation, trainings and maturation were their attributes to the development of managerial skills of the school administrators. They showed competence in the areas of management skills that they were able to carry their functions with utmost responsibility and capability. School administrators in terms of seminars and trainings on administration and supervision were already equipped. It is concluded that the school administrators possessed the necessary skills and work values in administering the school.

Keywords: management skills and values, public secondary schools, qualitative, school administrators

Procedia PDF Downloads 322

Authors: M. Duran Toksari, Berrin Ucarkus

Abstract:

In this paper, we propose two algorithms to optimally solve makespan and total completion time scheduling problems with learning effect and job dependent delivery times in a single machine environment. The delivery time is the extra time to eliminate adverse effect between the main processing and delivery to the customer. In this paper, we introduce the job dependent delivery times for some single machine scheduling problems with position dependent learning effect, which are makespan are total completion. The results with respect to two algorithms proposed for solving of the each problem are compared with LINGO solutions for 50-jobs, 100-jobs and 150-jobs problems. The proposed algorithms can find the same results in shorter time.

Keywords: delivery Times, learning effect, makespan, scheduling, total completion time

Procedia PDF Downloads 459

Authors: Pırıl Tekin, Rızvan Erol

Abstract:

Risk management has become very important and popular in developing countries in recent years. Especially making patient and employee health and safety issues compulsory in the hospitals, raised the number of studies in Turkey. Also risk management become more important for hospital senior management from clinics to the laboratories. Because quality is really important to be chosen for both patients to consult and employees to prefer to work. And also risk management studies can lead to hospital management team about future works and methods. By this point of view, this study is the risk assessment carried out in the biggest dental hospital in the south part of Turkey. This study was conducted as a research case study, covering two different health care place; A Clinic and A Laboratory. It shows that the problems in this dental hospital and how it can solve all.

Keywords: risk management, healthcare, dental hospital, quality management

Procedia PDF Downloads 359

Authors: Masud Karim, Md. Solaiman Mia, Saifuddin Md. Tareeq, Md. Hasanuzzaman

Abstract:

Autism Spectrum Disorder (ASD) is a neurodevelopment disorder. Such disorder is found in childhood life. Children with ASD have less capabilities in communication and social skills. Therapies are used to develop communication and social skills. Recently researchers have been trying to use robots in such therapies. In this paper, we have presented social skill learning test cases for children with ASD. Autism conditions are measured in 30 children in a special school. Among them, twelve children are selected who have equal ASD conditions. Then six children participated in training with humans, and another six children participated in training with robots. The learning session continued for one week and three hours each day. We have taken an assessment test before the learning sessions. After completing the learning sessions, we have taken another assessment test. We have found better performances from children who have participated in robotic sessions rather than the children who have participated in human sessions.

Keywords: children with ASD, NAO robot, human-robot interaction, social skills

Procedia PDF Downloads 70

Authors: Kafi Razzaq Ahmed

Abstract:

Speaking fluently in a second language requires vocabulary, grammar, and pronunciation skills. Teaching the English language entails teaching pronunciation. In professional literature, there have been a lot of attempts to integrate technology into improving the pronunciation of learners. The technique is also neglected in Kurdish contexts, Salahaddin University – Erbil included. Thus, the main aim of the research is to point out the efficiency of using video materials for both language teachers and learners within and beyond classroom learning and teaching environments to enhance student's pronunciation. To collect practical data, a research project has been designed. In subsequent research, a posttest will be administered after each lesson to 100 first-year students at Salahaddin University-Erbil English departments. All students will be taught the same material using different methods, one based on video materials and the other based on the traditional approach to teaching pronunciation. Finally, the results of both tests will be analyzed (also knowing the attitudes of both the teachers and the students about both lessons) to indicate the impact of using video in the process of teaching and learning pronunciation.

Keywords: video, pronunciation, teaching, learning

Procedia PDF Downloads 99

Authors: C. J. Rossouw, T. I. van Niekerk

Abstract:

The global manufacturing industry is utilizing the internet and cloud-based services to further explore the anatomy and optimize manufacturing processes in support of the movement into the Fourth Industrial Revolution (4IR). The 4IR from a third world and African perspective is hindered by the fact that many manufacturing systems that were developed in the third industrial revolution are not inherently equipped to utilize the internet and services of the 4IR, hindering the progression of third world manufacturing industries into the 4IR. This research focuses on the development of a non-invasive and cost-effective cyber-physical IoT system that will exploit a machine’s vibration to expose semantic characteristics in the manufacturing process and utilize these results through a real-time cloud-based machine condition monitoring system with the intention to optimize the system. A microcontroller-based IoT sensor was designed to acquire a machine’s mechanical vibration data, process it in real-time, and transmit it to a cloud-based platform via Wi-Fi and the internet. Time-frequency Fourier analysis was applied to the vibration data to form an image representation of the machine’s behaviour. This data was used to train a Convolutional Neural Network (CNN) to learn semantic characteristics in the machine’s behaviour and relate them to a state of operation. The same data was also used to train a Convolutional Autoencoder (CAE) to detect anomalies in the data. Real-time edge-based artificial intelligence was achieved by deploying the CNN and CAE on the sensor to analyse the vibration. A cloud platform was deployed to visualize the vibration data and the results of the CNN and CAE in real-time. The cyber-physical IoT system was deployed on a semi-automated metal granulation machine with a set of trained machine learning models. Using a single sensor, the system was able to accurately visualize three states of the machine’s operation in real-time. The system was also able to detect a variance in the material being granulated. The research demonstrates how non-IoT manufacturing systems can be equipped with edge-based artificial intelligence to establish a remote machine condition monitoring system.

Keywords: IoT, cyber-physical systems, artificial intelligence, manufacturing, vibration analytics, continuous machine condition monitoring

Procedia PDF Downloads 78

Authors: Peter Clutterbuck, Terry Rowlands, Owen Seamons

Abstract:

In this paper we describe one critical research program within a complex, ongoing multi-year project (2010 to 2014 inclusive) with the overall goal to improve the learning outcomes for first year undergraduate commerce/business students within an Information Systems (IS) subject with very large enrolment. The single research program described in this paper is the analysis of student attitudes and decision making in relation to the availability of formative assessment feedback via Web-based real time conferencing and document exchange software (Adobe Connect). The formative assessment feedback between teaching staff and students is in respect of an authentic problem-based, team-completed assignment. The analysis of student attitudes and decision making is investigated via both qualitative (firstly) and quantitative (secondly) application of the Theory of Planned Behavior (TPB) with a two statistically-significant and separate trial samples of the enrolled students. The initial qualitative TPB investigation revealed that perceived self-efficacy, improved time-management, and lecturer-student relationship building were the major factors in shaping an overall favorable student attitude to online feedback, whilst some students expressed valid concerns with perceived control limitations identified within the online feedback protocols. The subsequent quantitative TPB investigation then confirmed that attitude towards usage, subjective norms surrounding usage, and perceived behavioral control of usage were all significant in shaping student intention to use the online feedback protocol, with these three variables explaining 63 percent of the variance in the behavioral intention to use the online feedback protocol. The identification in this research of perceived behavioral control as a significant determinant in student usage of a specific technology component within a virtual learning environment (VLE) suggests that VLEs could now be viewed not as a single, atomic entity, but as a spectrum of technology offerings ranging from the mature and simple (e.g., email, Web downloads) to the cutting-edge and challenging (e.g., Web conferencing and real-time document exchange). That is, that all VLEs should not be considered the same. The results of this research suggest that tertiary students have the technological sophistication to assess a VLE in this more selective manner.

Keywords: formative assessment feedback, virtual learning environment, theory of planned behavior, perceived behavioral control

Procedia PDF Downloads 384

Authors: Natalie Frandsen

Abstract:

Pursuing post-secondary education is a milestone for many Canadian youths. This transition involves many changes and opportunities for growth. However, this may also be a period where challenges arise. Perhaps not surprisingly, mental health challenges for post-secondary students are common. This poses difficulties for students and instructors. Common mental-health-related symptoms (e.g., low motivation, fatigue, inability to concentrate) can affect academic performance, and instructors may need to provide accommodations for these students without the necessary expertise. ‘Distance education’ has been growing and gaining momentum in Canada for three decades. As a consequence of the COVID-19 pandemic, post-secondary institutions have been required to deliver courses using ‘remote’ methods (i.e., various online delivery modalities). The learning challenges and subsequent academic performance issues experienced by students with mental-health-related disabilities studying online are not well understood. However, we can postulate potential factors drawing from learning theories, the relationship between mental-health-related symptoms and academic performance, and learning design. Identifying barriers and opportunities to academic performance is an essential step in ensuring that students with mental-health-related disabilities are able to achieve their academic goals. Completing post-secondary education provides graduates with more employment opportunities. It is imperative that our post-secondary institutions take a holistic view of learning by providing learning and mental health support while reducing structural barriers. Health-promoting universities and colleges infuse health into their daily operations and academic mandates. Acknowledged in this Charter is the notion that all sectors must take an active role in favour of health, social justice, and equity for all. Drawing from mental health promotion and Universal Design for Learning (UDL) frameworks, relevant adult learning concepts, and critical digital pedagogy, considerations for mental-health-promoting, online learning community development will be summarized. The education sector has the opportunity to create and foster equitable and mental health-promoting learning environments. This is of particular importance during a global pandemic when the mental health of students is being disproportionately impacted.

Keywords: academic performance, community, mental health promotion, online learning

Procedia PDF Downloads 120

Authors: Fariha Asif

Abstract:

The Saudi EFL learners face a number of problems in EFL learning, anxiety is the most potent one among those. It means that its resolution can lead to better language skills in Saudi students. That’s why, the study is carried out and is considered to be of interest to the Saudi language learners, educators and the policy makers because of the potentially negative impact that anxiety has on English language learning. The purpose of the study is to explore the factors that cause language anxiety in the Saudi EFL learners while learning speaking skills and the influence it casts on communication in the target language. The investigation of the anxiety-producing factors that arise while learning to communicate in the target language will hopefully broaden the insight into the issue of language anxiety and will help language teachers in making the classroom environment less stressful. The study seeks to answer the questions such as what are the psycholinguistic factors that cause language anxiety among ESL/EFL learners in learning and speaking English Language, especially in the context of the Saudi students. What are the socio-cultural factors that cause language anxiety among Saudi EFL learners in learning and speaking English Language? How is anxiety manifested in the language learning of the Saudi EFL learners? And which strategies can be used to successfully cope with language anxiety? The scope of the study is limited to the college and university English Teachers and subject specialists (males and females) in public sectors colleges and universities in Saudi Arabia. Some of the key findings of the study are:, Anxiety plays an important role in English as foreign language learning for the Saudi EFL learners. Some teachers believe that anxiety bears negatives effects for the learners, while some others think that anxiety serves a positive outcome for the learners by giving them an extra bit of motivation to do their best in English language learning. Language teachers seem to have consensus that L1 interference is one of the major factors that cause anxiety among the Saudi EFL learners. Most of the Saudi EFL learners are found to have fear of making mistakes. They don’t take initiative and opt to keep quiet and don’t respond fearing that they would make mistakes and this would ruin their image in front of their peers. Discouraging classroom environment is also counted as one of the major anxiety causing factors. The teachers, who don’t encourage learners positively, make them anxious and they start avoiding class participation. It is also found that English language teachers have their important role to minimize the negative effects of anxiety in the classes. The teachers’ positive encouragement can do wonders in this regard. A positive, motivating and encouraging class environment is essential to produce desired results in English language learning for the Saudi EFL learners.

Keywords: factors, psychology, speaking, EFL

Procedia PDF Downloads 446

Authors: Krishang Surapaneni

Abstract:

The goal of this project is to determine how to predict important aspects of options, including the ask price. We want to compare different machine learning models to learn the best model and the best hyperparameters for that model for this purpose and data set. Option pricing is a relatively new field, and it can be very complicated and intimidating, especially to inexperienced people, so we want to create a machine learning model that can predict important aspects of an option stock, which can aid in future research. We tested multiple different models and experimented with hyperparameter tuning, trying to find some of the best parameters for a machine-learning model. We tested three different models: a Random Forest Regressor, a linear regressor, and an MLP (multi-layer perceptron) regressor. The most important feature in this experiment is the ask price; this is what we were trying to predict. In the field of stock pricing prediction, there is a large potential for error, so we are unable to determine the accuracy of the models based on if they predict the pricing perfectly. Due to this factor, we determined the accuracy of the model by finding the average percentage difference between the predicted and actual values. We tested the accuracy of the machine learning models by comparing the actual results in the testing data and the predictions made by the models. The linear regression model performed worst, with an average percentage error of 17.46%. The MLP regressor had an average percentage error of 11.45%, and the random forest regressor had an average percentage error of 7.42%

Keywords: finance, linear regression model, machine learning model, neural network, stock price

Procedia PDF Downloads 64

Authors: Dulanjali Ranasinghe, Isuru Supasan, Kaushalya Premachandra, Ranjan Dissanayake, Ajith Rajapaksha, Eustace Fernando

Abstract:

Proteomics studies of organisms are considered to be significantly information-rich compared to their genomic counterparts because proteomes of organisms represent the expressed state of all proteins of an organism at a given time. In modern top-down and bottom-up proteomics workflows, the primary analysis methods employed are gel–based methods such as two-dimensional (2D) electrophoresis and mass spectrometry based methods. Machine learning (ML) and artificial intelligence (AI) have been used increasingly in modern biological data analyses. In particular, the fields of genomics, DNA sequencing, and bioinformatics have seen an incremental trend in the usage of ML and AI techniques in recent years. The use of aforesaid techniques in the field of proteomics studies is only beginning to be materialised now. Although there is a wealth of information available in the scientific literature pertaining to proteomics workflows, no comprehensive review addresses various aspects of the combined use of proteomics and machine learning. The objective of this review is to provide a comprehensive outlook on the application of machine learning into the known proteomics workflows in order to extract more meaningful information that could be useful in a plethora of applications such as medicine, agriculture, and biotechnology.

Keywords: proteomics, machine learning, gel-based proteomics, mass spectrometry

Procedia PDF Downloads 137

Authors: Katarzyna Olcoń, Rose M. Pulliam, Dorie J. Gilbert

Abstract:

This article examines the impact of learning about the history of racial oppression on U.S. university students who participated in a Ghana study abroad which involved visiting the former slave dungeons. Relying on ethnographic observations, individual interviews, and written journals of 27 students (predominantly White and Latino/a and social work majors), we identified four themes: (1) the suffering and resilience of African and African descent people; (2) ‘it’s still happening today’; (3) ‘you don’t learn about that in school’; and (4) remembrance, equity, and healing.

Keywords: racial oppression, anti-racism pedagogy, student learning, social work education, study abroad

Procedia PDF Downloads 107

Authors: Raghuveer Kaur, Kartikay Sharma, Ashu Khanna

Abstract:

Earnings management has been present from times immemorial. The recent downfall of giant enterprises like Enron, Satyam and WorldCom has brought a lot of focus on the study and detection of earnings management. The present study is an attempt to study earnings management in one of the fastest emerging economy - India. The study makes an attempt to understand earnings management in different sectors of the economy. The paper first tests a hypothesis to check whether different sectors of India are engaged in earnings management or not. In the later section the paper aims to study the level of earnings management in 6 popular sectors of India: IT&BPO, Retail, Telecom, Biotech, Hotels and coffee. To measure earnings management two popular techniques of detecting earnings management has been employed: Modified Jones Model and Beniesh M Score. A total of 332 companies were studied. Publicly available data from Capitaline database has been used. The paper also classifies the top and bottom five performers on the basis of sales turnover in each sector and identifies whether they manage their earnings or not.

Keywords: earnings management, India, modified Jones model, Beneish M score

Procedia PDF Downloads 499

Authors: Qura-tul-aain Khair

Abstract:

Purpose- The purpose of this paper is to empirically examining the strength of association of responsive market orientation and proactive market orientation with new product performance and exploring the possible moderating role of organizational learning based on contingency theory. Design/methodology/approach- Data for this study was collected from FMCG manufacturing industry and services industry, where customers are in contact frequently and responses are recorded on continuous basis. Sample was collected through convenience sampling. The data collected from different marketing department and sales personnel were analysed using SPSS 16 version. Findings- The paper finds that responsive market orientation is more strongly associated with new product performance. The moderator, organizational learning, plays it significant role on the relationship between responsive market orientation and new product performance. Research limitations/implications- this paper has taken sample from just FMCG industry and service industry, more work can be done regarding how different-markets require different market orientation behaviours. Originality/value- This paper will be useful for foreign business looking for investing and expanding in Pakistan, they can find opportunity to get sustained competitive advantage through exploring the proactive side of market orientation and importance of organizational learning.

Keywords: organizational learning, proactive market orientation, responsive market orientation, new product performance

Procedia PDF Downloads 363

Authors: S. Vijayakumar, S. B. Rathna Kumar, Navnath D Jagadale

Abstract:

Learning and teaching are the challenges ahead in the education of the students with hearing impairment using sign language (SHISL). Either the students or teachers face difficulties in the process of learning/teaching. Communication is one of the main barriers while teaching SHISL. Further, the courses of study or the subjects are limited to SHISL at least in countries like India. Students with hearing impairment mainly opt for sign language as a communication mode. Subjects like physics, chemistry, advanced mathematics etc. are not available in the curriculum for the SHISL since their content and ideas are complex. In India, exemption for language papers is being given for the students with hearing impairment. It may give opportunity to them to secure secondary/ higher secondary qualifications. It is a known fact that students with hearing impairment are facing difficulty in their future carrier. They secure neither a higher study nor a good employment opportunity. Vocational training in various trades will land them in few jobs with few bucks in pocket. However, not all of them are blessed with higher positions in government or private sectors in competitive fields or where the technical knowledge is required. E learning with sign language instructions can be used for teaching languages and science subjects. Computer Based Instruction (CBI), Computer Based Training (CBT), and Computer Assisted Instruction (CAI) are now part-and-parcel of Modern Education. It will also include signed video clip corresponding to the topic. Learning language subjects will improve the understanding of concepts in different subjects. Learning other science subjects like their hearing counterparts will enable the SHISL to go higher in studies and increase their height to pluck a fruit of the tree of employment.

Keywords: students with hearing impairment using sign language, hearing impairment, language subjects, science subjects, e-learning

Procedia PDF Downloads 388

Authors: Narupot Putwattana

Abstract:

Changes in global situation such as environmental and economic crisis brought the new perspective for science education called integrative biology. STEM has been increasingly mentioned for several educational researches as the approach which combines the concept in Science (S), Technology (T), Engineering (E) and Mathematics (M) to apply in teaching and learning process so as to strengthen the 21st-century skills such as creativity and critical thinking. Recent studies demonstrated STEM as the pedagogy which described the engineering process along with the science classroom activities. So far, pedagogical contents for STEM explaining the content in biology have been scarce. A qualitative literature review was conducted so as to gather the articles based on electronic databases (google scholar). STEM education, engineering design, teaching and learning of biology were used as main keywords to find out researches involving with the application of STEM in biology teaching and learning process. All articles were analyzed to obtain appropriate teaching and learning model that unify the core concept of biology. The synthesized model comprised of engineering design, inquiry-based learning, biological prototype and biologically-inspired design (BID). STEM content and context integration were used as the theoretical framework to create the integrative biology instructional model for STEM education. Several disciplines contents such as biology, engineering, and technology were regarded for inquiry-based learning to build biological prototype. Direct and indirect integrations were used to provide the knowledge into the biology related STEM strategy. Meanwhile, engineering design and BID showed the occupational context for engineer and biologist. Technological and mathematical aspects were required to be inspected in terms of co-teaching method. Lastly, other variables such as critical thinking and problem-solving skills should be more considered in the further researches.

Keywords: biomimicry, engineering approach, STEM education, teaching and learning model

Procedia PDF Downloads 231

Authors: Laura Mion

Abstract:

Concepts of quality assurance and management are now part of the organizational culture of the Universities. Quality Assurance (QA) systems are, in large part, provided for by national regulatory dictates or supranational indications (such as, for example, at European level are, the ESG Guidelines "European Standard Guidelines"), but their specific definition, in terms of guiding principles, requirements and methodologies, are often delegated to the national evaluation agencies or to the autonomy of individual universities. For this reason, the experiences of implementation of QA systems in different countries and in different universities is an interesting source of information to understand how quality in universities is understood, pursued and verified. The literature often deals with the treatment of the experiences of implementation of QA systems in the individual areas in which the University's activity is carried out - teaching, research, third mission - but only rarely considers quality systems with a systemic and integrated approach, which allows to correlate subjects, actions, and performance in a virtuous circuit of continuous improvement. In particular, it is interesting to understand how to relate the results and uses of the QA in the triple distinction of university activities, identifying how one can cause the performance of the other as a function of an integrated whole and not as an exploit of specific activities or processes conceived in an abstractly atomistic way. The aim of the research is, therefore, to investigate which experiences of "integrated" QA systems are present on the international scene: starting from the experience of European countries that have long shared the Bologna Process for the creation of a European space for Higher Education (EHEA), but also considering experiences from emerging countries that use QA processes to develop their higher education systems to keep them up to date with international levels. The concept of "integration", in this research, is understood in a double meaning: i) between the different areas of activity, in particular between the didactic and research areas, and possibly with the so-called "third mission" "ii) the functional integration between those involved in quality assessment and management and the governance of the University. The paper will present the results of a systematic review conducted according with a method of an integrative review aimed at identifying best practices of quality assurance systems, in individual countries or individual universities, with a high level of integration. The analysis of the material thus obtained has made it possible to grasp common and transversal elements of QA system integration practices or particularly interesting elements and strengths of these experiences that can, therefore, be considered as winning aspects in a QA practice. The paper will present the method of analysis carried out, and the characteristics of the experiences identified, of which the structural elements will be highlighted (level of integration, areas considered, organizational levels included, etc.) and the elements for which these experiences can be considered as best practices.

Keywords: quality assurance, university, integration, country

Procedia PDF Downloads 71

Authors: Nico Rosamilia

Abstract:

The study evaluates the importance of non-financial disclosure practices for regulators, investors, businesses, and markets. It aims to create a sector-specific set of indicators for environmental, social, and governance (ESG) performances alternative to the ratings of the agencies. The existing literature extensively studies the implementation of ESG rating systems. Conversely, this study has a twofold outcome. Firstly, it should generalize incentive systems and governance policies for ESG and sustainable principles. Therefore, it should contribute to the EU Sustainable Finance Disclosure Regulation. Secondly, it concerns the market and the investors by highlighting successful sustainable investing. Indeed, the study contemplates the effect of ESG adoption practices on corporate value. The research explores the asset pricing angle in order to shed light on the fragmented argument on the finance of ESG. Investors may be misguided about the positive or negative effects of ESG on performances. The paper proposes a different method to evaluate ESG performances. By comparing the results of a traditional econometric approach (Lasso) with a machine learning algorithm (Random Forest), the study establishes a set of indicators for ESG performance. Therefore, the research also empirically contributes to the theoretical strands of literature regarding model selection and variable importance in a finance framework. The algorithms will spit out sector-specific indicators. This set of indicators defines an alternative to the compounded scores of ESG rating agencies and avoids the possible offsetting effect of scores. With this approach, the paper defines a sector-specific set of indicators to standardize ESG disclosure. Additionally, it tries to shed light on the absence of a clear understanding of the direction of the ESG effect on corporate value (the problem of endogeneity).

Keywords: ESG ratings, non-financial information, value of firms, sustainable finance

Procedia PDF Downloads 67

Authors: Bitewulign Mekonnen

Abstract:

Context: This scientific paper focuses on the use of near-infrared (NIR) spectroscopy to determine glucose concentration in aqueous solutions accurately and rapidly. The study compares six different machine learning methods for predicting glucose concentration and also explores the development of a deep learning model for classifying NIR spectra. The objective is to optimize the detection model and improve the accuracy of glucose prediction. This research is important because it provides a comprehensive analysis of various machine-learning techniques for estimating aqueous glucose concentrations. Research Aim: The aim of this study is to compare and evaluate different machine-learning methods for predicting glucose concentration from NIR spectra. Additionally, the study aims to develop and assess a deep-learning model for classifying NIR spectra. Methodology: The research methodology involves the use of machine learning and deep learning techniques. Six machine learning regression models, including support vector machine regression, partial least squares regression, extra tree regression, random forest regression, extreme gradient boosting, and principal component analysis-neural network, are employed to predict glucose concentration. The NIR spectra data is randomly divided into train and test sets, and the process is repeated ten times to increase generalization ability. In addition, a convolutional neural network is developed for classifying NIR spectra. Findings: The study reveals that the SVMR, ETR, and PCA-NN models exhibit excellent performance in predicting glucose concentration, with correlation coefficients (R) > 0.99 and determination coefficients (R²)> 0.985. The deep learning model achieves high macro-averaging scores for precision, recall, and F1-measure. These findings demonstrate the effectiveness of machine learning and deep learning methods in optimizing the detection model and improving glucose prediction accuracy. Theoretical Importance: This research contributes to the field by providing a comprehensive analysis of various machine-learning techniques for estimating glucose concentrations from NIR spectra. It also explores the use of deep learning for the classification of indistinguishable NIR spectra. The findings highlight the potential of machine learning and deep learning in enhancing the prediction accuracy of glucose-relevant features. Data Collection and Analysis Procedures: The NIR spectra and corresponding references for glucose concentration are measured in increments of 20 mg/dl. The data is randomly divided into train and test sets, and the models are evaluated using regression analysis and classification metrics. The performance of each model is assessed based on correlation coefficients, determination coefficients, precision, recall, and F1-measure. Question Addressed: The study addresses the question of whether machine learning and deep learning methods can optimize the detection model and improve the accuracy of glucose prediction from NIR spectra. Conclusion: The research demonstrates that machine learning and deep learning methods can effectively predict glucose concentration from NIR spectra. The SVMR, ETR, and PCA-NN models exhibit superior performance, while the deep learning model achieves high classification scores. These findings suggest that machine learning and deep learning techniques can be used to improve the prediction accuracy of glucose-relevant features. Further research is needed to explore their clinical utility in analyzing complex matrices, such as blood glucose levels.

Keywords: machine learning, signal processing, near-infrared spectroscopy, support vector machine, neural network

Procedia PDF Downloads 71

Authors: Shan-Ken Chien

Abstract:

This research aims to share the application of the Music and Narrative Curriculum developed through a college community service-learning course to a special education classroom in a local secondary school. The development of the Music and Narrative Curriculum stems from the music appreciation courses that the author has taught at the university. The curriculum structure consists of three instructional phases, each with three core literacy. This study will show the implementation of an eighteen-week general music education course, including classroom training on the university campus and four intervention music lessons in a special education classroom. Students who participated in the Music and Narrative Curriculum came from two different parts. One is twenty-five college students enrolling in Music Literacy and Community Service-Learning, and the other one is nine junior high school students with intellectual disabilities (ID) in a special education classroom. This study measures two parts. One is the effectiveness of the Music and Narrative Curriculum in applying four interventions in music lessons in a special education classroom, and the other is measuring college students' service-learning experiences and growth outcomes.

Keywords: college service-learning, general music education, music literacy, narrative skills, students with special needs

Procedia PDF Downloads 62

Authors: Eda Kocakaya, Sebahat Seker, Dogan Argun

Abstract:

The aim of this study is to determine the process of information technologies and the connections between concepts in accounting management services in Turkey. The objective of this study is to determine the adaptation and evaluation process of information technologies and the connections between concepts and differences in accounting management services in Turkey. The situation and determination of the IT applications of Accounting Management were studied. The applications of • Billing • Order Processing • Accounts Receivable/Payable Management • Contract Management • Bank Account Management Were discussed in this study. The IT applications were demonstrated and realized in actual accounting services. The sectoral representative's companies were selected, and the IT application was searched by bibliometric analysis.

Keywords: management, accounting, information technologies, adaptation

Procedia PDF Downloads 298

Authors: Tharwat N. Hijjawi

Abstract:

Learning oral skills in an Arabic speaking environment is challenging. A blended course (material, activities, and individual/ group work tasks …) was implemented in a module of level B1 for undergraduate students of French as a foreign language in order to increase their opportunities to practice listening and speaking skills. This research investigates the influence of this modality on enhancing active learning and examines the effectiveness of provided strategies. Moreover, it aims at discovering how it allows teacher to flip the traditional classroom and create a learner-centered framework. Which approaches were integrated to motivate students and urge them to search, analyze, criticize, create and accomplish projects? What was the perception of students? This paper is based on the qualitative findings of a questionnaire and a focus group interview with learners. Despite the doubled time and effort both “teacher” and “student” needed, results revealed that the NTIC allowed a shift into a learning paradigm where learners were the “chiefs” of the process. Tasks and collaborative projects required higher intellectual capacities from them. Learners appreciated this experience and developed new life-long learning competencies at many levels: social, affective, ethical and cognitive. To conclude, they defined themselves as motivated young researchers, motivators and critical thinkers.

Keywords: active learning, critical thinking, inverted classroom, learning paradigm, problem-based

Procedia PDF Downloads 257

Authors: Efleda Preclaro Tolentino

Abstract:

Research indicates that an educator’s belief system is reflected in the way they structure the learning environment. Their values and belief system have the potential to positively impact school readiness through an understanding of children’s development and the creation of a stable, motivating environment. Based on the premise that the social environment influences the development of social skills, knowledge construct, and shared values of young children, this study examined verbal and nonverbal exchanges between early childhood teachers and their preschool students within the context of remote learning. Using the qualitative method of data collection, the study determined the nature of interactions between preschoolers and their teachers within a remote learning environment at a preschool in Southeast Asia that utilized the Mother Tongue-based Multilingual Education (MTBMLE) Approach. From the lens of sociocultural theory, the study investigated preschoolers’ use of literacies to convey meaning and to interact within a remote learning environment. Using a Strengths Perspective, the study revealed the creativity and resourcefulness of preschoolers in expressing themselves through trans-literacies that were made possible by the use of online mode of learning within cultural and subcultural norms. The study likewise examined how social skills acquired by young children were transmitted (verbally or nonverbally) in their interactions with peers during Zoom meetings. By examining the dynamics of social exchanges between teachers and children, the findings of the study underscore the importance of providing support for preschool students as they apply acquired values and shared practices within a remote learning environment. The potential of distance learning in the early years will be explored, specifically in supporting young children’s language and literacy development. At the same time, the study examines the role of teachers as cultivators of trans-literacies. The teachers’ skillful use of technology in facilitating young children’s learning, as well as in supporting interactions with families, will be examined. The findings of this study will explore the potential of distance learning in early childhood education to establish continuity in learning, supporting young children’s social and emotional transitions, and nurturing trans-literacies that transcend prevailing definitions of learning contexts. The implications of teachers and parents working collaboratively to support student learning will be examined. The importance of preparing teachers to be resourceful, adaptable, and innovative to ensure that learning takes place across a variety of modes and settings will be discussed.

Keywords: transliteracy, preschoolers, remote learning, strengths perspective

Procedia PDF Downloads 73

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

Abstract:

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

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

Procedia PDF Downloads 297

Authors: Joshua Osondu

Abstract:

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

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

Procedia PDF Downloads 75