Search results for: mobile game based learning

Authors: Daria Druzhinenko- Silhan, Patrick Schmoll

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Childhood obesity is one of the important problem in domain of health care. During two recent decades we are observing a real epidemic of this noninfectious illness. Its consequences are hard: cardio-vascular disease; diabetes; arthrosis etc. (OMS, 2012) Keep Healthy Kids  » study aims to create a new system of accompanying of childhood obesity based on new technologies as mobile applications or serious video-games. We realize a support-study which aims to understand motivations, psychological dynamite and family's impact on weight-loss process in childhood. Sample: 65 children from 7 to 10 years old accompanied by special Care Center in France. Methodology: we proceed by an innovative approach that bases on quantitative and qualitative methods of data collection. We focus our proposal on data collected from medical files. We are also realizing individual assessment (still ongoing) that aims to understand psychological profiles of obese children and their family dynamic. Results: Only 16,9% of children asked for medical accompanying of obesity. We noted that the most important reason to come to the care Center was the fact of mates' scoffs (46,2%°), the second one was the appearance or look (40 %). We found out that the self-image of these children in self-evaluation questionnaire was described mostly as rather good (46,2) or good (28,2%); the most part of children evaluated their well-being as rather good (29,7%) or good (51,4%). In interviews children had tendency to not recall why they came to the Care Center. Discussion : These results permit us to make a hypothesis that children suffering of overweight or obesity are not clearly aware why they must loose weight. It was rather the peer environment that pointed out the problem of overweight for them. So the motivation to loose weight is mostly supported by environment. We suppose that it is a « weak-point » of their motivation and it can be over-come using serious video-games supporting physical activity that can make deviate the motivation from « to loose weight for be looked better by the others » into « have fun and feeling me better ».

Keywords: childhood obesity, motivation, weight-loss, serious video-game

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Authors: Anjum Afrooze

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The curriculum at General Sciences department in Prince Sultan University includes ‘Physical science’ for Computer Science, Information Technology and Business courses. Students are apathetic towards Physical Science and question, as to, ‘How this course is related to their majors?’ English is not a native language for the students and also for many instructors. More than sixty percent of the students come from institutions where English is not the medium of instruction, which makes student learning and academic achievement challenging. After observing the less enthusiastic student cohort for two consecutive semesters, the instructor was keen to find effective strategies to enhance learning and further encourage deep learning by engaging students in different tasks to empower them with necessary skills and motivate them. This study is participatory action research, in which instructor designs effective tasks to engage students in their learning. The study is conducted through two semesters with a total of 200 students. The effectiveness of this approach is studied using questionnaire at the end of each semester and teacher observation. Major outcomes of this study were overall improvement in students attitude towards science learning, enhancement of multiple skills like note taking, problem solving, language proficiency and also fortifying confidence. This process transformed instructor into engaging and reflecting practitioner. Also, these strategies were implemented by other instructors teaching the course and proved effective in opening a path to changes in related areas of the course curriculum. However, refinement in the strategies could be done based on student evaluation and instructors observation.

Keywords: group activity, language proficiency, reasoning skills, science learning

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Authors: Mary Luna Mancao Ninal

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This study aimed to determine the performance of the kindergarten teachers and its relation to pupils’ achievement in different learning areas in the Division of Kabankalan City. Using the standardized assessment and evaluation of the Department of Education secondary data, 100 kinder teachers and 2901 kinder pupils were investigated to determine the performance of the kindergarten teachers based on their Competency–Based Performance Appraisal System for Teachers and the periodic assessment of kinder pupils collected as secondary data. Weighted mean, Pearson–r, chi-square, Analysis of Variance were used in the study. Findings revealed that the kindergarten teacher respondents were 26-31 years old and most of them were female and married; they spent teaching for two years and less and passed the Licensure Examination for Teachers. They were very satisfactory as to instructional competences, school, and home and community involvement, personal, social, and professional characteristics. It also revealed that performance of the kindergarten pupils on their period of assessment shows that they were slightly advanced in their development. It also shows that domain as to performance of the kindergarten pupils were average overall development. Based on the results, it is recommended that Kindergarten teacher must augment their educational qualification and pursue their graduate studies and must develop the total personality of the children for them to achieve high advanced development to become productive individual.

Keywords: performance, kindergarten teacher, learning areas, professional, pupil

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Authors: Samer Abu Ghazaleh, Jawdat Gousous

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

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

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Authors: P. L. Cheng, I. N. Umar

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Online discussion forum is a popular e-learning technique that allows participants to interact and construct knowledge. This study aims to examine the levels of participation, categories of participants and the structure of their interactions in a forum. A convenience sampling of one course coordinator and 23 graduate students was selected in this study. The forums’ log file and the Social Network Analysis software were used in this study. The analysis reveals 610 activities (including viewing forum’s topic, viewing discussion thread, posting a new thread, replying to other participants’ post, updating an existing thread and deleting a post) performed by them in this forum, with an average of 3.83 threads posted. Also, this forum consists of five at-risk participants, six bridging participants, four isolated participants and five leaders of information. In addition, the network density value is 0.15 and there exist five reciprocal interactions in this forum. The closeness value varied between 28 and 68 while the eigen vector centrality value varied between 0.008 and 0.39. The finding indicates that the participants tend to listen more rather than express their opinions in the forum. It was also revealed that those who actively provide supports in the discussion forum were not the same people who received the most responses from their peers. This study found that cliques do not exist in the forum and the participants are not selective to whom they response to, rather, it was based on the content of the posts made by their peers. Based upon the findings, further analysis with different method and population, larger sample size and a longer time frame are recommended.

Keywords: e-learning, learning management system, online forum, social network analysis

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Authors: Razali Bin Abidin

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This paper presents the development of a portable water jet cutter for soft materials such as meat. Twelve geometries of nozzles were simulated using finite element method. Water pressure was set to 1500 lb/in². Through the simulation, highest average water output speed was 133.04 m/s. The nozzle was fabricated from Al - alloy 5052 with the Factor of Safety~ 3. This indicates that the nozzle made of Al-alloy 5052 is capable of performing the cutting process without any fracture. Preliminary design of mobile water jet hand tool is presented at the end of this paper.

Keywords: water jet, finite element, Al-alloy 5052, nozzle geometry

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Authors: N. Didiş Körhasan, D. Kaltakçı Gürel

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

Keywords: pedagogy, physics, physics education, science education

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Authors: Xhevrie Mamaqi

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Organization capacity learning is a process referring to the sum total of individual and collective learning through training programs, experience and experimentation, among others. Today, in-business ongoing training is one of the most important strategies for human capital development and it is crucial to sustain and improve workers’ knowledge and skills. Many organizations, firms and business are adopting a strategy of continuous learning, encouraging employees to learn new skills continually to be innovative and to try new processes and work in order to achieve a competitive advantage and superior business results. This paper uses the Resource Based View and Capacities (RBV) approach to construct a hypothetical relationships model between training and business results. The test of the model is applied on transversal data. A sample of 266 business of Spanish sector service has been selected. A Structural Equation Model (SEM) is used to estimate the relationship between ongoing training, represented by two latent dimension denominated Human and Social Capital resources and economic business results. The coefficients estimated have shown the efficient of some training aspects explaining the variation in business results.

Keywords: business results, human and social capital resources, training, RBV theory, SEM

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Authors: Dian Hartiningsih, Miranda Diponegoro, Evita Eddie Singgih

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

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

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Authors: Parthiban Srinivasan

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With recent advances in computational power and access to enough data in biosciences, artificial intelligence methods are increasingly being used in drug discovery research. These methods are essentially a series of advanced statistics based exercises that review the past to indicate the likely future. Our goal is to develop a model that accurately predicts biological activity and toxicity parameters for novel compounds. We have compiled a robust library of over 150,000 chemical compounds with different pharmacological properties from literature and public domain databases. The compounds are stored in simplified molecular-input line-entry system (SMILES), a commonly used text encoding for organic molecules. We utilize an automated process to generate an array of numerical descriptors (features) for each molecule. Redundant and irrelevant descriptors are eliminated iteratively. Our prediction engine is based on a portfolio of machine learning algorithms. We found Random Forest algorithm to be a better choice for this analysis. We captured non-linear relationship in the data and formed a prediction model with reasonable accuracy by averaging across a large number of randomized decision trees. Our next step is to apply deep neural network (DNN) algorithm to predict the biological activity and toxicity properties. We expect the DNN algorithm to give better results and improve the accuracy of the prediction. This presentation will review all these prominent machine learning and deep learning methods, our implementation protocols and discuss these techniques for their usefulness in biomedical and health informatics.

Keywords: deep learning, drug discovery, health informatics, machine learning, toxicity prediction

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Authors: Liwen Hou

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The booming mobile business has been penetrating the taxi industry worldwide with P2P (peer to peer) taxi services, as an emerging business model, transforming the industry. Parallel with other mobile businesses, member recommendations and online reviews are believed to be very effective with regard to acquiring new users for P2P taxi services. Based on an empirical dataset of the taxi industry in China, this study aims to reveal which factors influence users’ recommendations and review-writing behaviors. Differing from the existing literature, this paper takes the taxi driver’s perspective into consideration and hence selects a group of variables related to the drivers. We built two models to reflect the factors that influence the number of recommendations and reviews posted on the platform (i.e., the app). Our models show that all factors, except the driver’s score, significantly influence the recommendation behavior. Likewise, only one factor, passengers’ bad reviews, is insignificant in generating more drivers’ reviews. In the conclusion, we summarize the findings and limitations of the research.

Keywords: online recommendation, P2P taxi service, review-writing, word of mouth

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Authors: J. H. Low, S. H. Hew, C. O. Wong

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This paper proposes an innovative approach to represent the pictogram Chinese characters. The advantage of this representation is using an extraordinary to represent the pictogram Chinese character. This extraordinary representation is created accordingly to the original pictogram Chinese characters revolution. The purpose of this innovative creation is to assistant the learner learning Chinese as second language (SCL) in Chinese language learning specifically on memorize Chinese characters. Commonly, the SCL will give up and frustrate easily while memorize the Chinese characters by rote. So, our innovative representation is able to help on memorize the Chinese character by the help of visually storytelling. This innovative representation enhances the Chinese language learning experience of SCL.

Keywords: Chinese e-learning, innovative Chinese character representation, knowledge management, language learning

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Authors: Somtop Keawchuer

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The objectives of this research are to compare the satisfaction of students, towards the happiness learning, sorted by their personal profiles, and to figure out the factors that affect the students’ happiness learning. This paper used survey method to collect data from 362 students. The survey was mainly conducted in the Faculty of Management Science, Suan Sunandha Rajabhat University, including 3,443 students. The statistics used for interpreting the results included the frequencies, percentages, standard deviations and One-way ANOVA. The findings revealed that the students are aware and satisfaction that all the factors in 3 categories (knowledge, skill and attitude) influence the happiness learning at the highest levels. The comparison of the satisfaction levels of the students toward their happiness learning leads to the results that the students with different genders, ages, years of study, and majors of the study have the similar satisfaction at the high level.

Keywords: happiness, learning satisfaction, students, Faculty of Management Science

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Authors: Faiza Abdul Latip

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One of the ultimate goals of any nation is to produce competitive manpower and this includes Philippines. Inclination in the field of Mathematics has a significant role in achieving this goal. However, Mathematics, as considered by most people, is the most difficult subject matter along with its topics to learn. This could be manifested from the low performance of students in national and international assessments. Educators have been widely using learning style models in identifying the way students learn. Moreover, it could be the frontline in knowing the difficulties held by each learner in a particular topic specifically concepts pertaining to fractions. However, as what many educators observed, students show difficulties in doing mathematical tasks and in great degree in dealing with fractions most specifically in the district of Datu Odin Sinsuat, Maguindanao. This study focused on the Datu Odin Sinsuat district grade six pupils’ learning styles along with their achievements and difficulties in learning concepts on fractions. Five hundred thirty-two pupils from ten different public elementary schools of the Datu Odin Sinsuat districts were purposively used as the respondents of the study. A descriptive research using the survey method was employed in this study. Quantitative analysis on the pupils’ learning styles on the Kolb’s Learning Style Inventory (KLSI) and scores on the mathematics diagnostic test on fraction concepts were made using this method. The simple frequency and percentage counts were used to analyze the pupils’ learning styles and their achievements on fractions. To determine the pupils’ difficulties in fractions, the index of difficulty on every item was determined. Lastly, the Kruskal-Wallis Test was used in determining the significant difference in the pupils’ achievements on fractions classified by their learning styles. This test was set at 0.05 level of significance. The minimum H-Value of 7.82 was used to determine the significance of the test. The results revealed that the pupils of Datu Odin Sinsuat districts learn fractions in varied ways as they are of different learning styles. However, their achievements in fractions are low regardless of their learning styles. Difficulties in learning fractions were found most in the area of Estimation, Comparing/Ordering, and Division Interpretation of Fractions. Most of the pupils find it very difficult to use fraction as a measure, compare or arrange series of fractions and use the concept of fraction as a quotient.

Keywords: difficulties in fraction, fraction, Kolb's model, learning styles

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Authors: Zhidong Zhang

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This study established a mixed method model in assessing statistics learning with Bayesian network models. There are three variants in exploratory sequential designs. There are three linked steps in one of the designs: qualitative data collection and analysis, quantitative measure, instrument, intervention, and quantitative data collection analysis. The study used a scoring model of analysis of variance (ANOVA) as a content domain. The research study is to examine students’ learning in both semantic and performance aspects at fine grain level. The ANOVA score model, y = α+ βx1 + γx1+ ε, as a cognitive task to collect data during the student learning process. When the learning processes were decomposed into multiple steps in both semantic and performance aspects, a hierarchical Bayesian network was established. This is a theory-driven process. The hierarchical structure was gained based on qualitative cognitive analysis. The data from students’ ANOVA score model learning was used to give evidence to the hierarchical Bayesian network model from the evidential variables. Finally, the assessment results of students’ ANOVA score model learning were reported. Briefly, this was a mixed method research design applied to statistics learning assessment. The mixed methods designs expanded more possibilities for researchers to establish advanced quantitative models initially with a theory-driven qualitative mode.

Keywords: exploratory sequential design, ANOVA score model, Bayesian network model, mixed methods research design, cognitive analysis

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Authors: M. Zezou

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This paper focuses on the design of a Massive Open Online Course (MOOC) about Content Language Integrated Learning (CLIL) and more specifically about how teachers can use CLIL as an educational approach incorporating technology in their teaching as well. All the four weeks of the MOOC will be presented and a step-by-step analysis of each lesson will be offered. Additionally, the paper includes detailed lesson plans about CLIL lessons with proposed CLIL activities and games in which technology plays a central part. The MOOC is structured based on certain criteria, in order to ensure success, as well as a positive experience that the learners need to have after completing this MOOC. It addresses to all language teachers who would like to implement CLIL into their teaching. In other words, it presents the methodology that needs to be followed so as to successfully carry out a CLIL lesson and achieve the learning objectives set at the beginning of the course. Firstly, in this paper, it is very important to give the definitions of MOOCs and LMOOCs, as well as to explore the difference between a structure-based MOOC (xMOOC) and a connectivist MOOC (cMOOC) and present the criteria of a successful MOOC. Moreover, the notion of CLIL will be explored, as it is necessary to fully understand this concept before moving on to the design of the MOOC. Onwards, the four weeks of the MOOC will be introduced as well as lesson plans will be presented: The type of the activities, the aims of each activity and the methodology that teachers have to follow. Emphasis will be placed on the role of technology in foreign language learning and on the ways in which we can involve technology in teaching a foreign language. Final remarks will be made and a summary of the main points will be offered at the end.

Keywords: CLIL, cMOOC, lesson plan, LMOOC, MOOC criteria, MOOC, technology, xMOOC

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Authors: Haifeng Wang, Haili Zhang

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Most movie recommendation systems have been developed for customers to find items of interest. This work introduces a predictive model usable by small and medium-sized enterprises (SMEs) who are in need of a data-based and analytical approach to stock proper movies for local audiences and retain more customers. We used classification models to extract features from thousands of customers’ demographic, behavioral and social information to predict their movie genre preference. In the implementation, a Gaussian kernel support vector machine (SVM) classification model and a logistic regression model were established to extract features from sample data and their test error-in-sample were compared. Comparison of error-out-sample was also made under different Vapnik–Chervonenkis (VC) dimensions in the machine learning algorithm to find and prevent overfitting. Gaussian kernel SVM prediction model can correctly predict movie genre preferences in 85% of positive cases. The accuracy of the algorithm increased to 93% with a smaller VC dimension and less overfitting. These findings advance our understanding of how to use machine learning approach to predict customers’ preferences with a small data set and design prediction tools for these enterprises.

Keywords: computational social science, movie preference, machine learning, SVM

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Authors: Jean Marie Tshimula, Atsushi Togashi

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We develop a data-science approach for providing an interactive visualization and predictive models to find insights into the projects' historical data in order for stakeholders understand some unseen opportunities in the African market that might escape them behind the online project portfolio of the African Development Bank. This machine learning-based web application identifies the market trend of the fastest growing economies across the continent as well skyrocketing sectors which have a significant impact on the future of business in Africa. Owing to this, the approach is tailored to predict where the investment needs are the most required. Moreover, we create a corpus that includes the descriptions of over more than 1,200 projects that approximately cover 14 sectors designed for some of 53 African countries. Then, we sift out this large amount of semi-structured data for extracting tiny details susceptible to contain some directions to follow. In the light of the foregoing, we have applied the combination of Latent Dirichlet Allocation and Random Forests at the level of the analysis module of our methodology to highlight the most relevant topics that investors may focus on for investing in Africa.

Keywords: machine learning, topic modeling, natural language processing, big data

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Authors: Ying Li, Yan Li

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A new algorithm for single hidden layer feedforward neural networks (SLFN), Orthogonal Basis Extreme Learning (OBEL) algorithm, is proposed and the algorithm derivation is given in the paper. The algorithm can decide both the NNs parameters and the neuron number of hidden layer(s) during training while providing extreme fast learning speed. It will provide a practical way to develop NNs. The simulation results of function approximation showed that the algorithm is effective and feasible with good accuracy and adaptability.

Keywords: neural network, orthogonal basis extreme learning, function approximation

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Authors: Dawei Cai

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In this paper, we present an autonomous guidance service by combining the position information from NFC and the orientation information from a 6 axis acceleration and terrestrial magnetism sensor. We developed an algorithm to calculate the device orientation based on the data from acceleration and terrestrial magnetism sensor. If visitors want to know some explanation about an exhibit in front of him, what he has to do is just lift up his mobile device. The identification program will automatically identify the status based on the information from NFC and MEMS, and start playing explanation content for him. This service may be convenient for old people or disables or children.

Keywords: NFC, ubiquitous computing, guide sysem, MEMS

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Authors: Sun-Young Jang, Sung-Ah Kim, Dongyoun Shin

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The Intelligent transportation system is essential to build smarter cities. Machine learning based transportation prediction could be highly promising approach by delivering invisible aspect visible. In this context, this research aims to make a prototype model that predicts transportation network by using big data and machine learning technology. In detail, among urban transportation systems this research chooses bus system.  The research problem that existing headway model cannot response dynamic transportation conditions. Thus, bus delay problem is often occurred. To overcome this problem, a prediction model is presented to fine patterns of bus delay by using a machine learning implementing the following data sets; traffics, weathers, and bus statues. This research presents a flexible headway model to predict bus delay and analyze the result. The prototyping model is composed by real-time data of buses. The data are gathered through public data portals and real time Application Program Interface (API) by the government. These data are fundamental resources to organize interval pattern models of bus operations as traffic environment factors (road speeds, station conditions, weathers, and bus information of operating in real-time). The prototyping model is designed by the machine learning tool (RapidMiner Studio) and conducted tests for bus delays prediction. This research presents experiments to increase prediction accuracy for bus headway by analyzing the urban big data. The big data analysis is important to predict the future and to find correlations by processing huge amount of data. Therefore, based on the analysis method, this research represents an effective use of the machine learning and urban big data to understand urban dynamics.

Keywords: big data, machine learning, smart city, social cost, transportation network

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Authors: Ibrahim Laro ABUBAKAR

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The study examined the Availability and Utilization of E-Learning Technologies in Teaching of Human Kinetics and Health Education courses in Nigerian Universities, specifically, Universities in Kwara State. Two purposes were formulated to guide the study from which two research questions and two hypotheses were raised. The descriptive research design was used in the research. Three Hundred respondents (100 Lecturers and 200 Students) made up the population for the study. There was no sampling, as the population of the study was not much. A structured questionnaire tagged ‘Availability and Utilization of E-Learning Technologies in Teaching and Learning Questionnaire’ (AUETTLQ) was used for data collection. The questionnaire was subjected to face and content validation, and it was equally pilot tested. The validation yielded a reliability coefficient of 0.78. The data collected from the study were statistically analyzed using frequencies and percentage count for personal data of the respondents, mean and standard deviation to answer the research questions. The null hypotheses were tested at 0.05 level of significance using the independent t-test. One among other findings of this study showed that lecturers and Student are aware of synchronous e-learning technologies in teaching and learning of Human Kinetics and Health Education but often utilize the synchronous e-learning technologies. It was recommended among others that lecturers and Students should be sensitized through seminars and workshops on the need to maximally utilize available e-learning technologies in teaching and learning of Human Kinetics and Health Education courses in Universities.

Keywords: awareness, utilization, E-Learning, technologies, human kinetics synchronous

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Authors: Krishang Surapaneni

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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

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Authors: Eylem Tas

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This empirical study aims to explore the development of students' entrepreneurial skills through problem-based learning within the context of university-industry collaborations (UICs) in curriculum co-design and co-delivery (CDD). The research question guiding this study is: "How do problem-based learning and university-industry collaborations influence the development of students' entrepreneurial skills in the context of curriculum co-design and co-delivery?” To address this question, the study was conducted in a big city in Germany and involved interviews with stakeholders from various industries, including the private sector, government agencies (govt), and non-governmental organizations (NGOs). These stakeholders had established collaborative partnerships with the targeted university for projects encompassing entrepreneurial development aspects in CDD. The study sought to gain insights into the intricacies and subtleties of UIC dynamics and their impact on fostering entrepreneurial skills. Qualitative content analysis, based on Mayring's guidelines, was employed to analyze the interview transcriptions. Through an iterative process of manual coding, 442 codes were generated, resulting in two main sections: "the role of problem-based learning and UIC in fostering entrepreneurship" and "challenges and requirements of problem-based learning within UIC for systematical entrepreneurship development.” The chosen experimental approach of semi-structured interviews was justified by its capacity to provide in-depth perspectives and rich data from stakeholders with firsthand experience in UICs in CDD. By enlisting participants with diverse backgrounds, industries, and company sizes, the study ensured a comprehensive and heterogeneous sample, enhancing the credibility of the findings. The first section of the analysis delved into problem-based learning and entrepreneurial self-confidence to gain a deeper understanding of UIC dynamics from an industry standpoint. It explored factors influencing problem-based learning, alignment of students' learning styles and preferences with the experiential learning approach, specific activities and strategies, and the role of mentorship from industry professionals in fostering entrepreneurial self-confidence. The second section focused on various interactions within UICs, including communication, knowledge exchange, and collaboration. It identified key elements, patterns, and dynamics of interaction, highlighting challenges and limitations. Additionally, the section emphasized success stories and notable outcomes related to UICs' positive impact on students' entrepreneurial journeys. Overall, this research contributes valuable insights into the dynamics of UICs and their role in fostering students' entrepreneurial skills. UICs face challenges in communication and establishing a common language. Transparency, adaptability, and regular communication are vital for successful collaboration. Realistic expectation management and clearly defined frameworks are crucial. Responsible data handling requires data assurance and confidentiality agreements, emphasizing the importance of trust-based relationships when dealing with data sharing and handling issues. The identified key factors and challenges provide a foundation for universities and industrial partners to develop more effective UIC strategies for enhancing students' entrepreneurial capabilities and preparing them for success in today's digital age labor market. The study underscores the significance of collaborative learning and transparent communication in UICs for entrepreneurial development in CDD.

Keywords: collaborative learning, curriculum co-design and co-delivery, entrepreneurial skills, problem-based learning, university-industry collaborations

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Authors: Sirilak Areerachakul, Nat Ployong, Supayothin Na Songkla

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This research’s objective is to select the model with most accurate value by using Neural Network Technique as a way to filter potential students who enroll in IT course by electronic learning at Suan Suanadha Rajabhat University. It is designed to help students selecting the appropriate courses by themselves. The result showed that the most accurate model was 100 Folds Cross-validation which had 73.58% points of accuracy.

Keywords: artificial neural network, classification, students, e-learning

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Authors: Pailin Klinkesorn

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The research aimed to study the use of learning strategies for Japanese language among college students with different learning achievements who study Japanese as a foreign language in the Higher Education’s level. The survey was conducted by using a questionnaire adapted from Strategy Inventory for language Learning or SILL (Oxford, 1990), consisting of two parts: questions about personal data and questions about the use of learning strategies for Japanese language. The samples of college students in the Japanese language program were purposively selected from Suansunandha Rajabhat University. The data from the questionnaire was statistically analyzed by using mean scores and one-way ANOVA. The results showed that Social Strategies was used by the greatest number of college students, whereas Memory Strategies was used by the least number of students. The students in different levels used various strategies, including Memory Strategies, Cognitive Strategies, Metacognitive Strategies and Social Strategies, at the significance level of 0.05. In addition, the students with different learning achievements also used different strategies at the significance level of 0.05. Further studies can explore learning strategies of other groups of Japanese learners, such as university students or company employees. Moreover, learning strategies for language skills, including listening, speaking, reading and writing, can be analyzed for better understanding of learners’ characteristics and for teaching applications.

Keywords: language learning strategies, achievement, Japanese, college students

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Authors: Thrivikraman Aswathi, S. Advaith

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As there can be cases where the use of real data is somehow limited, such as when it is hard to get access to a large volume of real data, we need to go for synthetic data generation. This produces high-quality synthetic data while maintaining the statistical properties of a specific dataset. In the present work, a generative adversarial network (GAN) is trained to produce multivariate time series (MTS) data since the MTS is now being gathered more often in various real-world systems. Furthermore, the GAN-generated MTS data is fed into a transformer-based deep learning architecture that carries out the data categorization into predefined classes. Further, the model is evaluated across various distinct domains by generating corresponding MTS data.

Keywords: GAN, transformer, classification, multivariate time series

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Authors: Eunji Choi, Borang Park, Youngjae Choi, Jinwoo Moon

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In this study, a predictive model for estimating the metabolism (MET) of human body was developed for the optimal control of indoor thermal environment. Human body images for indoor activities and human body joint coordinated values were collected as data sets, which are used in predictive model. A deep learning algorithm was used in an initial model, and its number of hidden layers and hidden neurons were optimized. Lastly, the model prediction performance was analyzed after the model being trained through collected data. In conclusion, the possibility of MET prediction was confirmed, and the direction of the future study was proposed as developing various data and the predictive model.

Keywords: deep learning, indoor quality, metabolism, predictive model

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Authors: Javad Sarvestan, Zdenek Svoboda

Abstract:

Force-time (F-T) curvature characteristics are globally referenced as the main indicators of athletic jump performance. Nevertheless, to the best of authors’ knowledge, no investigation tried to deeply study the relationship between F-T curve variables and real-game jump performance among elite volleyball players. To this end, this study was designated to investigate the association between F-T curve variables, including movement timings, force, velocity, power, rate of force development (RFD), modified reactive strength index (RSImod), and net impulse with spike jump height during real-game circumstances. Twelve young elite volleyball players performed 3 countermovement jump (CMJ) and 3 spike jump in real-game circumstances with 1-minute rest intervals to prevent fatigue. Shapiro-Wilk statistical test illustrated the normality of data distribution, and Pearson’s product correlation test portrayed a significant correlation between CMJ height and peak RFD (0.85), average RFD (r=0.81), RSImod (r=0.88) and concentric net impulse (r=0.98), and also significant correlation between spike jump height and peak RFD (0.73), average RFD (r=0.80), RSImod (r=0.62) and concentric net impulse (r=0.71). Multiple regression analysis also reported that these factors have a strong contribution in predicting of CMJ (98%) and spike jump (77%) heights. Outcomes of this study confirm that the RFD, concentric net impulse, and RSImod values could precisely monitor and track the volleyball attackers’ explosive strength, muscular stretch-shortening cycle function efficiency, and ultimate spike jump height. To this effect, volleyball coaches and trainers are advised to have an in-depth focus on their athletes’ progression or the impacts of strength trainings by observing and chasing the F-T curve variables such as RFD, net impulse, and RSImod.

Keywords: net impulse, reactive strength index, rate of force development, stretch-shortening cycle

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Authors: Han Nguyen

Abstract:

The objective of this study is to investigate the impact of culture on advertising appeals in mobile phone industry via social media channel in UK, Brazil and India. Content analysis on Samsung and Nokia commercials in YouTube is conducted. The result indicates that the advertising appeals are both congruent and incongruent with cultural dimensions in UK, Brazil and India. The result suggests that Hofstede and value paradoxes might be the tools to predict the relationship between cultural values and advertising appeals.

Keywords: mobile phone advertising, international advertising, social media advertising.

Procedia PDF Downloads 499