Search results for: problem-based learning approach

Authors: Sandra Mitrovic, Gaurav Singh

Abstract:

In many industries, including telecommunications, churn prediction has been a topic of active research. A lot of attention has been drawn on devising the most informative features, and this area of research has gained even more focus with spread of (social) network analytics. The call detail records (CDRs) have been used to construct customer networks and extract potentially useful features. However, to the best of our knowledge, no studies including network features have yet proposed a generic way of representing network information. Instead, ad-hoc and dataset dependent solutions have been suggested. In this work, we build upon a recently presented method (node2vec) to obtain representations for nodes in observed network. The proposed approach is generic and applicable to any network and domain. Unlike node2vec, which assumes a static network, we consider a dynamic and time-evolving network. To account for this, we propose an approach that constructs the feature representation of each node by generating its node2vec representations at different timestamps, concatenating them and finally compressing using an auto-encoder-like method in order to retain reasonably long and informative feature vectors. We test the proposed method on churn prediction task in telco domain. To predict churners at timestamp ts+1, we construct training and testing datasets consisting of feature vectors from time intervals [t1, ts-1] and [t2, ts] respectively, and use traditional supervised classification models like SVM and Logistic Regression. Observed results show the effectiveness of proposed approach as compared to ad-hoc feature selection based approaches and static node2vec.

Keywords: churn prediction, dynamic networks, node2vec, auto-encoders

Procedia PDF Downloads 316

Authors: Guantao Bai

Abstract:

Public space is an indispensable and important component of the urban built environment. How to more accurately evaluate the usage characteristics of public space can help improve its spatial quality. Compared to traditional survey methods, computer vision technology based on deep learning has advantages such as dynamic observation and low cost. This study takes the public space of Shaping Park as an example and, based on deep learning computer vision technology, processes and analyzes the image data of the public space to obtain the spatial usage characteristics and spatiotemporal characteristics of the public space. Research has found that the spontaneous activity time in public spaces is relatively random with a relatively short average activity time, while social activities have a relatively stable activity time with a longer average activity time. Computer vision technology based on deep learning can effectively describe the spatial usage characteristics of the research area, making up for the shortcomings of traditional research methods and providing relevant support for creating a good public space.

Keywords: computer vision, deep learning, public spaces, using features

Procedia PDF Downloads 72

Authors: Sean Gay, Cristina Tat

Abstract:

This presentation will detail how a university in Western Japan has implemented its English for Academic Purposes (EAP) program during the onset of CoViD-19 in the spring semester of 2020. In the spring semester of 2020, after a 2 week delay, all courses within the School of Policy Studies EAP Program at Kwansei Gakuin University were offered in an online asynchronous format. The rationale for this decision was not to disadvantage students who might not have access to devices necessary for taking part in synchronous online lessons. The course coordinators were tasked with consolidating the materials originally designed for face-to-face14 week courses for a 12 week asynchronous online semester and with uploading the modified course materials to Luna, the university’s network, which is a modified version of Blackboard. Based on research to determine the social and academic impacts of this CoViD-19 ERT approach on the students who took part in this EAP program, this presentation explains how future curriculum design and implementation can be managed in a post-CoViD world. There are a wide variety of lessons that were salient. The role of the classroom as a social institution was very prominent; however, awareness of cognitive burdens and strategies to mitigate that burden may be more valuable for teachers. The lessons learned during this period of ERT can help teachers moving forward.

Keywords: asynchronous online learning, emergency remote teaching (ERT), online curriculum design, synchronous online learning

Procedia PDF Downloads 205

Authors: Sara Cumming, Julianne DiSanto, Leah Burton

Abstract:

Homelessness in Canada is a persistent problem. It has been widely argued that the best tactic for eradicating homelessness is to approach social issues from a Housing First perspective—an approach that centers on quickly moving people into permanent and independent housing and then providing them additional support and services as needed. It is recognized that life skills training is both necessary and an effective way to reduce cyclical homelessness; however, there is a scarcity of research on effective ways to teach life skills; this problem was exacerbated in a pandemic context, where in-person delivery was severely restricted or no longer possible. Very little attention has been paid to the diverse cultural needs of clients in a multicultural context and the need to foster cultural knowledge/awareness in individuals to successfully contribute to the cultural safety of communities. This research attempts to fill these gaps in the literature and in practice by employing a community-engaged research (CER) approach. Academic, government, funders, front-line staff, and clients at 15 not-for-profits from across the Greater Toronto Area in Ontario, Canada, collaborated to co-create a virtual, client-centric, equity, diversity, and inclusion (EDI) informed life skill learning management system. We employed a triangulation methodology for this research. An environmental scan was conducted for best practices. Two separate Creative Problem Solving Sessions were held with over 100 front-line workers, managers, and executive directors who work with homeless populations. Quantitative and open-ended surveys were completed by over 200 individuals with experience with homelessness. All sections of this research aimed to discover the areas of skills that individuals need to maintain housing and to ascertain what a more client-driven EDI approach to life skills training should include. This research will showcase which life skills are deemed essential for homeless and precariously housed individuals.

Keywords: homelessness, Housing First, life skills, community engaged research

Procedia PDF Downloads 69

Authors: Saurabh Sharma, Yong Sun, Bruce Vernham

Abstract:

Accurate prediction of NOx emission is a continuous challenge in the field of diesel engine-out emission modeling. Performing experiments for each conditions and scenario cost significant amount of money and man hours, therefore model-based development strategy has been implemented in order to solve that issue. NOx formation is highly dependent on the burn gas temperature and the O₂ concentration inside the cylinder. The current empirical models are developed by calibrating the parameters representing the engine operating conditions with respect to the measured NOx. This makes the prediction of purely empirical models limited to the region where it has been calibrated. An alternative solution to that is presented in this paper, which focus on the utilization of in-cylinder combustion parameters to form a predictive semi-empirical NOx model. The result of this work is shown by developing a fast and predictive NOx model by using the physical parameters and empirical correlation. The model is developed based on the steady state data collected at entire operating region of the engine and the predictive combustion model, which is developed in Gamma Technology (GT)-Power by using Direct Injected (DI)-Pulse combustion object. In this approach, temperature in both burned and unburnt zone is considered during the combustion period i.e. from Intake Valve Closing (IVC) to Exhaust Valve Opening (EVO). Also, the oxygen concentration consumed in burnt zone and trapped fuel mass is also considered while developing the reported model.  Several statistical methods are used to construct the model, including individual machine learning methods and ensemble machine learning methods. A detailed validation of the model on multiple diesel engines is reported in this work. Substantial numbers of cases are tested for different engine configurations over a large span of speed and load points. Different sweeps of operating conditions such as Exhaust Gas Recirculation (EGR), injection timing and Variable Valve Timing (VVT) are also considered for the validation. Model shows a very good predictability and robustness at both sea level and altitude condition with different ambient conditions. The various advantages such as high accuracy and robustness at different operating conditions, low computational time and lower number of data points requires for the calibration establishes the platform where the model-based approach can be used for the engine calibration and development process. Moreover, the focus of this work is towards establishing a framework for the future model development for other various targets such as soot, Combustion Noise Level (CNL), NO₂/NOx ratio etc.

Keywords: diesel engine, machine learning, NOₓ emission, semi-empirical

Procedia PDF Downloads 115

Authors: Akaash Tawade, Manan Khattar, Lucas Spangher, Costas J. Spanos

Abstract:

Many grids are increasing the share of renewable energy in their generation mix, which is causing the energy generation to become less controllable. Buildings, which consume nearly 33% of all energy, are a key target for demand response: i.e., mechanisms for demand to meet supply. Understanding the behavior of office workers is a start towards developing demand response for one sector of building technology. The literature notes that dynamic computational modeling can be predictive of individual action, especially given that occupant behavior is traditionally abstracted from demand forecasting. Recent work founded on Social Cognitive Theory (SCT) has provided a promising conceptual basis for modeling behavior, personal states, and environment using control theoretic principles. Here, an adapted linear dynamical system of latent states and exogenous inputs is proposed to simulate energy demand amongst office workers engaged in a social energy shifting game. The energy shifting competition is implemented in an office in Singapore that is connected to a minigrid of buildings with a consistent 'price signal.' This signal is translated into a 'points signal' by a reinforcement learning (RL) algorithm to influence participant energy use. The dynamic model functions at the intersection of the points signals, baseline energy consumption trends, and SCT behavioral inputs to simulate future outcomes. This study endeavors to analyze how the dynamic model trains an RL agent and, subsequently, the degree of accuracy to which load deferability can be simulated. The results offer a generalizable behavioral model for energy competitions that provides the framework for further research on transfer learning for RL, and more broadly— transactive control.

Keywords: energy demand forecasting, social cognitive behavioral modeling, social game, transfer learning

Procedia PDF Downloads 110

Authors: H. M. Anitha, Anusha N. Rao

Abstract:

The current developments in technology and ideas have given entirely new dimensions to the field of research and education. New delivery methods are proposed which is an added feature to the engineering education. Particularly, more importance is given to new teaching practices such as Information and Communication Technologies (ICT). It is vital to adopt the new ICT methods which lead to the emergence of novel structure and mode of education. The flipped classroom, think pair share and peer instruction are the latest pedagogical methods which give students to learn the course. This involves students to watch video lectures outside the classroom and solve the problems at home. Students are engaged in group discussions in the classroom. These are the active learning methods wherein the students are involved diversely to learn the course. This paper gives a comprehensive study of past and present research which is going on with flipped classroom, thinks pair share activity and peer instruction.

Keywords: flipped classroom, think pair share, peer instruction, active learning

Procedia PDF Downloads 388

Authors: Kumar Vikas

Abstract:

Education is to be anticipated for Human resource development and then national development. However, in most of the developing countries, due to the inadequacy of resources it is almost unattainable to educate all of their citizens through on-campus teaching. Huge amount of money is necessary to establish the infrastructure for on-campus teaching which is out of the reach of the developing countries. In these circumstances, to educate their huge inhabitants the developing countries are to depend on open learning and distance education system. However, a question still stands: can the educators dissimulate knowledge to the learners smoothly through this new system of education? Some recent research shows that the graduates of the open and distance learning institutions in the developing countries are treated as second-grade graduates. This paper aims to identify the challenges or barriers in the development of distance and Open learning system in India and suggest possible alternatives may be followed to overcome the barriers.

Keywords: barriers, distance education, developing countries, motivation, alternative solutions

Procedia PDF Downloads 250

Authors: Sandra Thompson, Paul Dervan

Abstract:

Ireland’s first Technological University (TU Dublin) was established on 1st January 2019, and its creation is an exciting new milestone in Irish Higher Education. TU Dublin is now Ireland’s biggest University supporting 29,000 students across three campuses with 3,500 staff. The University aspires to create work-ready graduates who are socially responsible, open-minded global thinkers who are ambitious to change the world for the better. As graduates, they will be enterprising and daring in all their endeavors, ready to play their part in transforming the future. Feedback from Irish employers and students coupled with evidence from other authoritative sources such as the World Economic Forum points to a need for greater focus on the development of students’ employability skills as they prepare for today’s work environment. Moreover, with an increased focus on Universal Design for Learning (UDL) and inclusiveness, there is recognition that students are more than a numeric grade value. Robust grading systems have been developed to track a student’s performance around discipline knowledge but there is little or no global consensus on a definition of transversal skills nor on a unified framework to assess transversal skills. Education and industry sectors are often assessing one or two skills, and some are developing their own frameworks to capture the learner’s achievement in this area. Technological University Dublin (TU Dublin) have discovered and implemented a framework to allow students to develop, assess and record their transversal skills using transformative learning theory. The model implemented is an adaptation of Student Transformative Learning Record - STLR which originated in the University of Central Oklahoma (UCO). The purpose of this paper therefore, is to examine the views of students, staff and employers in the context of deploying a Transformative Learning model within the University to assess transversal skills. It will examine the initial impact the transformative learning model is having socially, personally and on the University as an organization. Crucially also, to identify lessons learned from the deployment in order to assist other Universities and Higher Education Institutes who may be considering a focused adoption of Transformative Learning to meet the challenge of preparing students for today’s work environment.

Keywords: assessing transversal skills, higher education, transformative learning, students

Procedia PDF Downloads 130

Authors: Bashaiar Alsanaa

Abstract:

Never has a revolution influenced all aspects of humanity as the communication revolution during the past two decades. This revolution, with all its advances and utilities, swept the world thus becoming an integral part of our lives, hence giving way to emerging applications at the social, economic, political, and educational levels. More specifically, such applications have changed the delivery system through which learning is acquired by students. Interaction with educators, accessibility to content, and creative delivery options are but a few facets of the new learning experience now being offered through the use of technology in the educational field. With different success rates, third world countries have tried to pace themselves with use of educational technology in advanced parts of the world. One such country is the small rich-oil state of Kuwait which has tried to adopt the e-educational model, however, an evaluation of such trial is yet to be done. This study aims to fill the void of research conducted around that topic. The study explores teachers’ acceptance of incorporating communication technologies in higher education in Kuwait. Teachers’ responses to survey questions present an overview of the e-learning experience in this country, and draw a framework through which implications and suggestions for future research can be discussed to better serve the advancement of e-education in developing countries.

Keywords: communication technologies, E-learning, Kuwait, social media

Procedia PDF Downloads 283

Authors: Bashaiar Alsana

Abstract:

Never has a revolution influenced all aspects of humanity as the communication revolution during the past two decades. This revolution, with all its advances and utilities, swept the world thus becoming an integral part of our lives, hence giving way to emerging applications at the social, economic, political, and educational levels. More specifically, such applications have changed the delivery system through which learning is acquired by students. Interaction with educators, accessibility to content, and creative delivery options are but a few facets of the new learning experience now being offered through the use of technology in the educational field. With different success rates, third world countries have tried to pace themselves with use of educational technology in advanced parts of the world. One such country is the small rich-oil state of Kuwait which has tried to adopt the e-educational model, however, an evaluation of such trial is yet to be done. This study aims to fill the void of research conducted around that topic. The study explores teachers’ acceptance of incorporating communication technologies in higher education in Kuwait. Teachers’ responses to survey questions present an overview of the e-learning experience in this country, and draw a framework through which implications and suggestions for future research can be discussed to better serve the advancement of e-education in developing countries.

Keywords: communication technologies, e-learning, Kuwait, social media

Procedia PDF Downloads 262

Authors: Siti Ayu Ningsih

Abstract:

This study aims to find the differences outcomes in learning reading comprehension with text and film as media on Indonesian Language for foreign speaker (BIPA) learning at intermediate level. By using quantitative and qualitative research methods, the respondent of this study is a single respondent from D'Royal Morocco Integrative Islamic School in grade nine from secondary level. Quantitative method used to calculate the learning outcomes that have been given the appropriate action cycle, whereas qualitative method used to translate the findings derived from quantitative methods to be described. The technique used in this study is the observation techniques and testing work. Based on the research, it is known that the use of the text media is more effective than the film for intermediate level of Indonesian Language for foreign speaker learner. This is because, when using film the learner does not have enough time to take note the difficult vocabulary and don't have enough time to look for the meaning of the vocabulary from the dictionary. While the use of media texts shows the better effectiveness because it does not require additional time to take note the difficult words. For the words that are difficult or strange, the learner can immediately find its meaning from the dictionary. The presence of the text is also very helpful for Indonesian Language for foreign speaker learner to find the answers according to the questions more easily. By matching the vocabulary of the question into the text references.

Keywords: Indonesian language for foreign speaker, learning outcome, media, reading comprehension

Procedia PDF Downloads 197

Authors: Benyamin Ahmadnia, Javier Serrano

Abstract:

In this paper we compare two different approaches for translating from Persian to Spanish, as a language pair with scarce parallel corpus. The first approach involves direct transfer using an statistical machine translation system, which is available for this language pair. The second approach involves translation through English, as a pivot language, which has more translation resources and more advanced translation systems available. The results show that, it is possible to achieve better translation quality using English as a pivot language in either approach outperforms direct translation from Persian to Spanish. Our best result is the pivot system which scores higher than direct translation by (1.12) BLEU points.

Keywords: statistical machine translation, direct translation approach, pivot language translation approach, parallel corpus

Procedia PDF Downloads 488

Authors: Adnan Alhazmi

Abstract:

Background: UDL can be understood as a framework that holds the potential to elaborate the alternatives and platforms for the students with intellectual disabilities within general education settings and aims at offering flexible pathways that can support all the students in gaining a mastering over the goals of learning. This system of learning addresses the problem of the variability of the learner by delineating the diverse ways in which the individuals can understand, conceive, express and deal with the information. Goal: The aim of the proposed research is to examine the impact of the implementation of UDL in teaching practices for the students with intellectual disabilities in Saudi Arabian schools. Method: This research has used a combination of quantitative and qualitative designs. Survey questionnaires were used to gather the data for under this analytical descriptive method. The application of the qualitative interpretive approach was applied with the help of the interview to gather a detailed understanding on the aim of the research. For this purpose, the semi-structured interviews were conducted. Thus, the primary data will be gathered with the help of survey and interview to examine the impact of universal design learning implementation on teaching practices for intellectually disabled students in Saudi Arabian schools. The survey was conducted to examine the prevailing teaching practices for the students with intellectual disabilities in Saudi Arabia and evaluate if the teaching experience influences the current practices or not. The surveys were distributed to 50 teachers who teach the students with intellectual disabilities. However, the interviews were conducted to explore barriers of implementing UDL in Saudi Arabia and provide suggested guideline for the implementation of UDL in Saudi Arabia. The interviews, therefore, were with 10 teachers teaching the same subject. Findings: A key findings highlighted in this study revealed that the UDL framework serves as a crucial guide for teachers within inclusive settings to undertake meaningful planning for the individuals with intellectual disabilities so that they are able to access, participate, and grow within the general education curriculum. Other findings of the study highlighted the need to prepare the educators and all faculty members to understand the purpose and need for inclusion, the UDL framework so that better information about academic and social expectations for individuals with intellectual disabilities can be delivered. Conclusion: On the basis of the preliminary study undertaken on the subject of research, it could be suggested that UDL can serve to be an effective support for undertaking a meaningful inclusion of students with intellectual disability (ID) in general educational settings. It holds the potential role of working as an institutional design framework that could be used for designing curriculum for students with intellectual disabilities.

Keywords: intellectual disability, inclusion, universal design for learning, teaching practice

Procedia PDF Downloads 140

Authors: Chia Wei Lim, Ning Yan

Abstract:

The subject of reactor design, dealing with the transformation of chemical feedstocks into more valuable products, constitutes the central idea of chemical engineering. Despite its importance, the way it is taught to chemical engineering undergraduates has stayed virtually the same over the past several decades, even as the chemical industry increasingly leans towards the use of software for the design and daily monitoring of chemical plants. As such, there has been a widening learning gap as chemical engineering graduates transition from university to the industry since they are not exposed to effective platforms that relate the fundamental concepts taught during lectures to industrial applications. While the success of technology enhanced learning (TEL) has been demonstrated in various chemical engineering subjects, TELs in the teaching of reactor design appears to focus on the simulation of reactor processes, as opposed to arguably more important ideas such as the selection and optimization of reactor configuration for different types of reactions. This presents an opportunity for us to utilize the readily available easy-to-use MATLAB App platform to create an educational tool to aid the learning of fundamental concepts of reactor design and to link these concepts to the industrial context. Here, interactive software for the learning of reactor design has been developed to narrow the learning gap experienced by chemical engineering undergraduates. Dubbed the ReactorDesign App, it enables students to design reactors involving complex design equations for industrial applications without being overly focused on the tedious mathematical steps. With the aid of extensive visualization features, the concepts covered during lectures are explicitly utilized, allowing students to understand how these fundamental concepts are applied in the industrial context and equipping them for their careers. In addition, the software leverages the easily accessible MATLAB App platform to encourage self-directed learning. It is useful for reinforcing concepts taught, complementing homework assignments, and aiding exam revision. Accordingly, students are able to identify any lapses in understanding and clarify them accordingly. In terms of the topics covered, the app incorporates the design of different types of isothermal and non-isothermal reactors, in line with the lecture content and industrial relevance. The main features include the design of single reactors, such as batch reactors (BR), continuously stirred tank reactors (CSTR), plug flow reactors (PFR), and recycle reactors (RR), as well as multiple reactors consisting of any combination of ideal reactors. A version of the app, together with some guiding questions to aid explorative learning, was released to the undergraduates taking the reactor design module. A survey was conducted to assess its effectiveness, and an overwhelmingly positive response was received, with 89% of the respondents agreeing or strongly agreeing that the app has “helped [them] with understanding the unit” and 87% of the respondents agreeing or strongly agreeing that the app “offers learning flexibility”, compared to the conventional lecture-tutorial learning framework. In conclusion, the interactive ReactorDesign App has been developed to encourage self-directed explorative learning of the subject and demonstrate the industrial applications of the taught design concepts.

Keywords: explorative learning, reactor design, self-directed learning, technology enhanced learning

Procedia PDF Downloads 95

Authors: Diego Aguirre, Olac Fuentes

Abstract:

In this paper, we present a taxonomy of weight initialization schemes used in deep learning. We survey the most representative techniques in each class and compare them in terms of overhead cost, convergence rate, and applicability. We also introduce a new weight initialization scheme. In this technique, we perform an initial feedforward pass through the network using an initialization mini-batch. Using statistics obtained from this pass, we initialize the weights of the network, so the following properties are met: 1) weight matrices are orthogonal; 2) ReLU layers produce a predetermined number of non-zero activations; 3) the output produced by each internal layer has a unit variance; 4) weights in the last layer are chosen to minimize the error in the initial mini-batch. We evaluate our method on three popular architectures, and a faster converge rates are achieved on the MNIST, CIFAR-10/100, and ImageNet datasets when compared to state-of-the-art initialization techniques.

Keywords: deep learning, image classification, supervised learning, weight initialization

Procedia PDF Downloads 137

Authors: Saiakhil Chilaka

Abstract:

Juvenile recidivism presents a significant challenge to the criminal justice system, impacting both the individuals involved and broader societal safety. This study aims to identify the key factors influencing recidivism and successful rehabilitation outcomes by utilizing a dataset of over 25,000 individuals from the NIJ Recidivism Challenge. We employed machine learning techniques, particularly Random Forest Classification, combined with SHAP (SHapley Additive exPlanations) for model interpretability. Our findings indicate that supervision risk score, percent days employed, and education level are critical factors affecting recidivism, with higher levels of supervision, successful employment, and education contributing to lower recidivism rates. Conversely, Gang Affiliation emerged as a significant risk factor for reoffending. The model achieved an accuracy of 68.8%, highlighting its utility in identifying high-risk individuals and informing targeted interventions. These results suggest that a comprehensive approach involving personalized supervision, vocational training, educational support, and anti-gang initiatives can significantly reduce recidivism and enhance rehabilitation outcomes for juveniles, providing critical insights for policymakers and juvenile justice practitioners.

Keywords: juvenile, justice system, data analysis, SHAP

Procedia PDF Downloads 26

Authors: Nitza Davidovitch, Yael Yossel-Eisenbach

Abstract:

The purpose of the study was to inquire whether there was a change in the shaping of undergraduate students’ digitally-oriented study pattern in the pre-Covid (2016-2017) versus post-Covid period (2022-2023), as affected by three factors: social background characteristics, high school, and academic background characteristics. These two-time points were cauterized by dramatic changes in teaching and learning at institutions of higher education. The data were collected via cross-sectional surveys at two-time points, in the 2016-2017 academic school year (N=443) and in the 2022-2023 school year (N=326). The questionnaire was distributed on social media and it includes questions on demographic background characteristics, previous studies in high school and present academic studies, and questions on learning and reading habits. Method of analysis: A. Statistical descriptive analysis, B. Mean comparison tests were conducted to analyze the variations in the mean score for the digitally-oriented learning pattern variable at two-time points (pre- and post-Covid) in relation to each of the independent variables. C. Analysis of variance was performed to test the main effects and the interactions. D. Applying linear regression, the research aimed to examine the combined effect of the independent variables on shaping students' digitally-oriented learning habits. The analysis includes four models. In all four models, the dependent variable is students’ perception of digitally oriented learning. The first model included social background variables; the second model included scholastic background as well. In the third model, the academic background variables were added, and the fourth model includes all the independent variables together with the variable of period (pre- and post-COVID). E. Factor analysis confirms using the principal component method with varimax rotation; the variables were constructed by a weighted mean of all the relevant statements merged to form a single variable denoting a shared content world. The research findings indicate a significant rise in students’ perceptions of digitally-oriented learning in the post-COVID period. From a gender perspective, the impact of COVID on shaping a digital learning pattern was much more significant for female students. The socioeconomic status perspective is eliminated when controlling for the period, and the student’s job is affected - more than all other variables. It may be assumed that the student’s work pattern mediates effects related to the convenience offered by digital learning regarding distance and time. The significant effect of scholastic background on shaping students’ digital learning patterns remained stable, even when controlling for all explanatory variables. The advantage that universities had over colleges in shaping a digital learning pattern in the pre-COVID period dissipated. Therefore, it can be said that after COVID, there was a change in how colleges shape students’ digital learning patterns in such a way that no institutional differences are evident with regard to shaping the digital learning pattern. The study shows that period has a significant independent effect on shaping students’ digital learning patterns when controlling for the explanatory variables.

Keywords: learning pattern, COVID, socioeconomic status, digital learning

Procedia PDF Downloads 64

Authors: Ulriikka Savela-Huovinen, Hanni Muukkonen, Auli Toom

Abstract:

The development of workplace as a learning environment has been emphasized in research field of workplace learning. The prior literature on sensory performance emphasized the individual’s competences as assessor, while the competences in the collaborative interactional and knowledge creation practices as workplace learning method are not often mentioned. In the present study aims to find out what kinds of competences and contexts are central when assessor conducts food sensory evaluation in authentic professional context. The aim was to answer the following questions: first, what kinds of competences does sensory evaluation require according to assessors? And second, what kinds of contexts for sensory evaluation do assessors report? Altogether thirteen assessors from three Finnish food companies were interviewed by using semi-structural thematic interviews to map practices and development intentions as well as to explicate already established practices. The qualitative data were analyzed by following the principles of abductive and inductive content analysis. Analysis phases were combined and their results were considered together as a cross-analysis. When evaluated independently required competences were perception, knowledge of specific domains and methods and cognitive skills e.g. memory. Altogether, 42% of analysis units described individual evaluation contexts, 53% of analysis units described collaborative interactional contexts, and 5% of analysis units described collaborative knowledge creation contexts. Related to collaboration, analysis reviewed learning, sharing and reviewing both external and in-house consumer feedback, developing methods to moderate small-panel evaluation and developing product vocabulary collectively between the assessors. Knowledge creation contexts individualized from daily practices especially in cases product defects were sought and discussed. The study findings contribute to the explanation that sensory assessors learn extensively from one another in the collaborative interactional and knowledge creation context. Assessors learning and abilities to work collaboratively in the interactional and knowledge creation contexts need to be ensured in the development of the expertise.

Keywords: assessor, collaboration, competences, contexts, learning and practices, sensory evaluation

Procedia PDF Downloads 238

Authors: Azzah Alghamdi

Abstract:

The Interactive White Boards (IWBs) as one of the innovative educational technologies have been extensively investigated in advanced countries such as the UK, US, and Australia. However, there is a significant lack of research studies, which mainly examine the use of IWBs in Saudi Arabia. Therefore, this study aims to investigate the attitudes of primary teachers towards using IWBs in both the teaching and learning processes. Moreover, it aims to investigate if there is any significant difference between male teachers and females regarding their attitudes towards using this technology. This study concentrated on teachers in primary schools, which participated in Tatweer project in the city of Jeddah, in Saudi Arabia. Mixed methods approach was employed in this study using a designed questionnaire, classroom observations, and a semi-structured interview. 587 teachers (286 men and 301 women) from Tatweer primary schools were completed the questionnaire as well as twenty teachers were interviewed including seven female teachers were observed in their classrooms. The findings of this study indicated that approximately 11% of the teachers within the sample (n=587) had negative attitudes towards the use of IWBs in the teaching and learning processes. However, the majority of them nearly 89% agreed about the benefits of using IWBs in their classrooms. Additionally, all the twenty teachers who were interviewed (including the seven observed female teachers) had positive attitudes towards the use of these technologies. Moreover, 87% of male teachers and 91% of female teachers who completed the questionnaire accepted the usefulness of using IWBs in improving their teaching and students' learning. Thus, this indicates that there was no significant difference between male and female teachers in Tatweer primary schools in terms of their views about using these innovative technologies in their lessons. The findings of the current study will help the Ministry of Education to improve the policies of using IWBs in Saudi Arabia. Indeed, examining teachers’ attitudes towards IWBs is a very important issue because they are the main users in classrooms. Hence, their views should be considered to addressing the powers and boundaries of using IWBs. Moreover, students will feel comfortable to use IWBs if their teachers accept and use them well.

Keywords: IWBs, Saudi teachers’ views, Tatweer schools, teachers' gender

Procedia PDF Downloads 228

Authors: Hossein Gitinavard, Mohammad Hossein Fazel Zarandi

Abstract:

In the last decades, concerns about the environmental issues lead to professional and academic efforts on green supplier selection problems. In this sake, one of the main issues in evaluating the green supplier selection problems, which could increase the uncertainty, is the preferences of the experts' judgments about the candidate green suppliers. Therefore, preparing an expert system to evaluate the problem based on the historical data and the experts' knowledge can be sensible. This study provides an expert evaluation system to assess the candidate green suppliers under selected criteria in a multi-period approach. In addition, a ranking approach under interval-valued hesitant fuzzy set (IVHFS) environment is proposed to select the most appropriate green supplier in planning horizon. In the proposed ranking approach, the IVHFS and the last aggregation approach are considered to margin the errors and to prevent data loss, respectively. Hence, a comparative analysis is provided based on an illustrative example to show the feasibility of the proposed approach.

Keywords: green supplier selection, expert system, ranking approach, interval-valued hesitant fuzzy setting

Procedia PDF Downloads 329

Authors: Meng-Tzu Cheng, Louisa Rosenheck, Chen-Yen Lin, Eric Klopfer

Abstract:

The purpose of the research is to explore some of the ways in which gameplay data can be analyzed to yield results that feedback into the learning ecosystem. Back-end data for all users as they played an MMOG, The Radix Endeavor, was collected, and this study reports the analyses on a specific genetics quest by using the data mining techniques, including the decision tree method. In the study, different reasons for quest failure between participants who eventually succeeded and who never succeeded were revealed. Regarding the in-game tools use, trait examiner was a key tool in the quest completion process. Subsequently, the results of decision tree showed that a lack of trait examiner usage can be made up with additional Punnett square uses, displaying multiple pathways to success in this quest. The methods of analysis used in this study and the resulting usage patterns indicate some useful ways that gameplay data can provide insights in two main areas. The first is for game designers to know how players are interacting with and learning from their game. The second is for players themselves as well as their teachers to get information on how they are progressing through the game, and to provide help they may need based on strategies and misconceptions identified in the data.

Keywords: MMOG, decision tree, genetics, gaming-learning interaction

Procedia PDF Downloads 358

Authors: Sarolta Lipóczi, Ildikó Szabó

Abstract:

The use of ICT in European Schools has increased over the last decade but there is still room for improvement. Also interactive technology is often used below its technical and pedagogical potentials. The pedagogical potential of interactive technology in classrooms has not yet reached classrooms in different countries and in a substantial way. To develop these materials cooperation between educational researchers and teachers from different backgrounds is necessary. INTACT project brings together experts from science education, mathematics education, social science education and foreign language education – with a focus on bilingual education – and teachers in secondary and primary schools to develop a variety of pedagogically qualitative interactive teaching and learning resources. Because of the backgrounds of the consortium members INTACT project focuses on the areas of science, mathematics and social sciences. To combine these two features (science/math and foreign language) the project focuses on bilingual education. A big issue supported by ‘interactiveness’ is social and collaborative learning. The easy way to communicate and collaborate offered by web 2.0 tools, mobile devices connected to the learning material allows students to work and learn together. There will be a wide range of possibilities for school co-operations at regional, national and also international level that allows students to communicate and cooperate with other students beyond the classroom boarders while using these interactive teaching materials. Opening up the learning scenario enhance the social, civic and cultural competences of the students by advocating their social skills and improving their cultural appreciation for other nations in Europe. To enable teachers to use the materials in indented ways descriptions of successful learning scenarios (i.e. using design patterns) will be provided as well. These materials and description will be made available to teachers by teacher trainings, teacher journals, booklets and online materials. The resources can also be used in different settings including the use of a projector and a touchpad or other technical interactive devices for the input i.e. mobile phones. Kecskemét College as a partner of INTACT project has developed two teaching and learning resources in the area of foreign language teaching. This article introduces these resources as well.

Keywords: bilingual educational settings, international cooperation, interactive teaching and learning resources, work across culture

Procedia PDF Downloads 397

Authors: Hsin-Yu Lee, Ming-Zhong Li, Wen-Hsi Chiu, Su-Fen Cheng, Shwu-Wen Lin

Abstract:

Background: The use of medical terminology is essential to professional nurses on clinical practice. However, most nursing students consider traditional lecture-based teaching of medical terminology as boring and overly conceptual and lack motivation to learn. It is thus an issue to be discussed on how to enhance nursing students’ self-directed learning and improve learning outcomes of medical terminology. Digital game-based learning is a learner-centered way of learning. Past literature showed that the most common game-based learning for language education has been immersive games and teaching games. Thus, this study selected role-playing games (RPG) and digital puzzle games for observation and comparison. It is interesting to explore whether digital game-based learning has positive impact on nursing students’ learning of medical terminology and whether students can adapt well on this type of learning. Results can be used to provide references for institutes and teachers on teaching medical terminology. These instructions give you guidelines for preparing papers for the conference. Use this document as a template if you are using Microsoft Word. Otherwise, use this document as an instruction set. The electronic file of your paper will be formatted further at WASET. Define all symbols used in the abstract. Do not cite references in the abstract. Do not delete the blank line immediately above the abstract; it sets the footnote at the bottom of this column. Page margins are 1,78 cm top and down; 1,65 cm left and right. Each column width is 8,89 cm and the separation between the columns is 0,51 cm. Objective: The purpose of this research is to explore respectively the impact of RPG and puzzle game on nursing students’ self-directed learning and technology acceptance. The study further discusses whether different game types bring about different influences on students’ self-directed learning and technology acceptance. Methods: A quasi-experimental design was adopted in this study so that repeated measures between two groups could be conveniently conducted. 103 nursing students from a nursing college in Northern Taiwan participated in the study. For three weeks of experiment, the experiment group (n=52) received “traditional teaching + RPG” while the control group (n=51) received “traditional teaching + puzzle games”. Results: 1. On self-directed learning: For each game type, there were significant differences for the delayed tests of both groups as compared to the pre and post-tests of each group. However, there were no significant differences between the two game types. 2. On technology acceptance: For the experiment group, after the intervention of RPG, there were no significant differences concerning technology acceptance. For the control group, after the intervention of puzzle games, there were significant differences regarding technology acceptance. Pearson-correlation coefficient and path analysis conducted on the results of the two groups revealed that the dimension were highly correlated and reached statistical significance. Yet, the comparison of technology acceptance between the two game types did not reach statistical significance. Conclusion and Recommend: This study found that through using different digital games on learning, nursing students have effectively improved their self-directed learning. Students’ technology acceptances were also high for the two different digital game types and each dimension was significantly correlated. The results of the experimental group showed that through the scenarios of RPG, students had a deeper understanding of medical terminology, which reached the ‘Understand’ dimension of Bloom’s taxonomy. The results of the control group indicated that digital puzzle games could help students memorize and review medical terminology, which reached the ‘Remember’ dimension of Bloom’s taxonomy. The findings suggest that teachers of medical terminology could use digital games to assist their teaching according to their goals on cognitive learning. Adequate use of those games could help improve students’ self-directed learning and further enhance their learning outcome on medical terminology.

Keywords: digital game-based learning, medical terminology, nursing education, self-directed learning, technology acceptance model

Procedia PDF Downloads 168

Authors: Mehwish Asghar

Abstract:

Breast Cancer (BC) is a common type of cancer among women. Its screening is usually performed using different imaging modalities such as magnetic resonance imaging, mammogram, X-ray, CT, etc. Among these modalities’ mammogram is considered a powerful tool for diagnosis and screening of breast cancer. Sophisticated machine learning approaches have shown promising results in complementing human diagnosis. Generally, machine learning methods can be divided into two major classes: one is Radiomics analysis (RA), where image features are extracted manually; and the other one is the concept of convolutional neural networks (CNN), in which the computer learns to recognize image features on its own. This research aims to improve the incidence of early detection, thus reducing the mortality rate caused by breast cancer through the latest advancements in computer science, in general, and machine learning, in particular. It has also been aimed to ease the burden of doctors by improving and automating the process of breast cancer detection. This research is related to a relative analysis of different techniques for the implementation of different models for detecting and classifying breast cancer. The main goal of this research is to provide a detailed view of results and performances between different techniques. The purpose of this paper is to explore the potential of a convolutional neural network (CNN) w.r.t feature extractor and as a classifier. Also, in this research, it has been aimed to add the module of Radiomics for comparison of its results with deep learning techniques.

Keywords: breast cancer (BC), machine learning (ML), convolutional neural network (CNN), radionics, magnetic resonance imaging, artificial intelligence

Procedia PDF Downloads 228

Authors: Hasti Ebrahimi

Abstract:

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

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

Procedia PDF Downloads 55

Authors: Saurabh Kumar

Abstract:

In the fiercely competitive landscape of e-commerce, understanding and mitigating customer churn has become paramount for sustainable business growth. This paper presents a thorough investigation into the application of machine learning techniques for churn prediction in e-commerce, aiming to provide actionable insights for businesses seeking to enhance customer retention strategies. We conduct a comparative study of various machine learning algorithms, including traditional statistical methods and ensemble techniques, leveraging a rich dataset sourced from Kaggle. Through rigorous evaluation, we assess the predictive performance, interpretability, and scalability of each method, elucidating their respective strengths and limitations in capturing the intricate dynamics of customer churn. We identified the XGBoost classifier to be the best performing. Our findings not only offer practical guidelines for selecting suitable modeling approaches but also contribute to the broader understanding of customer behavior in the e-commerce domain. Ultimately, this research equips businesses with the knowledge and tools necessary to proactively identify and address churn, thereby fostering long-term customer relationships and sustaining competitive advantage.

Keywords: customer churn, e-commerce, machine learning techniques, predictive performance, sustainable business growth

Procedia PDF Downloads 33

Authors: Terence Soule, Tami Al Ghamdi

Abstract:

To study how to transfer knowledge from multiple source problems to the target problem, we modeled the Transfer Learning (TL) process using Genetic Algorithms as the model solver. TL is the process that aims to transfer learned data from one problem to another problem. The TL process aims to help Machine Learning (ML) algorithms find a solution to the problems. The Genetic Algorithms (GA) give researchers access to information that we have about how the old problem is solved. In this paper, we have five different source problems, and we transfer the knowledge to the target problem. We studied different scenarios of the target problem. The results showed combined knowledge from multiple source problems improves the GA performance. Also, the process of combining knowledge from several problems results in promoting diversity of the transferred population.

Keywords: transfer learning, genetic algorithm, evolutionary computation, source and target

Procedia PDF Downloads 142

Authors: Husain A. Murad, Ali A. Dashti, Ali Al-Kandari

Abstract:

The outbreak of Coronavirus during the Spring semester of 2020 brought new challenges for the teaching of vocational mass communication courses at universities in Kuwait. Using the Media Richness Theory (MRT), this study examines the response of 252 university students on mass communication programs. A questionnaire regarding their perceptions and preferences concerning modes of instruction on vocational courses online, focusing on the four factors of MRT: immediacy of feedback, capacity to include personal focus, conveyance of multiple cues, and variety of language. The outcomes show that immediacy of feedback predicted all criterion variables: suitability of distance learning (DL) for teaching vocational courses, sentiments of students toward DL, perceptions of easiness of evaluation of DL coursework, and the possibility of retaking DL courses. Capacity to include personal focus was another positive predictor of the criterion variables. It predicted students’ sentiments toward DL and the possibility of retaking DL courses. The outcomes are discussed in relation to implications for using DL, as well as constructing an agenda for DL research.

Keywords: distance learning, media richness theory, traditional learning, vocational media courses

Procedia PDF Downloads 77

Authors: Katherine Karayianis

Abstract:

Children with Attention Deficit Hyperactivity Disorder (ADHD) have trouble learning in traditional classrooms. These children miss out on important developmental opportunities in school, which leads to challenges starting in early childhood, and these problems persist throughout their adult lives. Despite receiving supplemental support in school, children with ADHD still perform below their non-ADHD peers. Thus, there is a great need to find better ways of facilitating learning in children with ADHD. Evidence has shown that children with ADHD learn best through interactive engagement, but this is not always possible in schools, given classroom restraints and the large student-to-teacher ratio. Redesigning classrooms may not be feasible, so informal learning opportunities provide a possible alternative. One popular informal learning opportunity is educational TV shows like Sesame Street. These types of educational shows can teach children foundational skills taught in pre-K and early elementary school. One downside to these shows is the lack of interactive dialogue between the TV characters and the child viewers. Pseudo-interaction is often deployed, but the benefits are limited if the characters can neither understand nor contingently respond to the child. AI technology has become extremely advanced and is now popular in many electronic devices that both children and adults have access to. AI has been successfully used to create interactive dialogue in children’s educational TV shows, and results show that this enhances children’s learning and engagement, especially when children perceive the character as a reliable teacher. It is likely that children with ADHD, whose minds may otherwise wander, may especially benefit from this type of interactive technology, possibly to a greater extent depending on their perception of the animated dialogic agent. To investigate this issue, I have begun examining the moderating role of inattention among children’s learning from an educational TV show with different types of dialogic interactions. Preliminary results have shown that when character interactions are neither immediate nor accurate, children who are more easily distracted will have greater difficulty learning from the show, but contingent interactions with a TV character seem to buffer these negative effects of distractibility by keeping the child engaged. To extend this line of work, the moderating role of the child’s perception of the dialogic agent as a reliable teacher will be examined in the association between children’s attention and the type of dialogic interaction in the TV show. As such, the current study will investigate this moderated moderation.

Keywords: attention, dialogic TV, informal learning, educational TV, perception of teacher

Procedia PDF Downloads 86