Search results for: learning method

Authors: Komon Paisal

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The aim of this research was to create collaborative learning activities in the course of Principles of Mathematics for graduate level by investigating the students’ ability in proving the mathematics principles as well as their attitudes towards the activities. The samples composed of 2 main group; lecturers and students. The lecturers consisted of 3 teachers who taught the course of Principles of Mathematics at Rajabhat Suan Sunandha Unicersity in the academic year 2012. The students consisted of 32 students joining the cooperative learning activities in the subject of Principles of Mathematics in the academic year 2012. The research tools included activity plan for cooperative learning, testing on mathematics with the reliability of 0.8067 and the attitude questionnaires reported by the students. The results showed that: 1) the efficiency of the developed cooperative learning activities was 69.76/ 68.57 which was lower than the set criteria at 70/70. 2) The students joining the cooperative learning activities were able to prove the principles of mathematics at the average of 70%. 3) The students joining the cooperative learning activities reported moderate attitude towards the activities.

Keywords: instructional design, pedagogical, teaching strategies, learning strategies

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Authors: Maha Jazouli

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Suicide is one of the most important causes of death in the prison environment, both in Canada and internationally. Rates of attempts of suicide and self-harm have been on the rise in recent years, with hangings being the most frequent method resorted to. The objective of this article is to propose a method to automatically detect in real time suicidal behaviors. We present a gesture recognition system that consists of three modules: model-based movement tracking, feature extraction, and gesture recognition using machine learning algorithms (MLA). Our proposed system gives us satisfactory results. This smart video surveillance system can help assist staff responsible for the safety and health of inmates by alerting them when suicidal behavior is detected, which helps reduce mortality rates and save lives.

Keywords: suicide detection, Kinect azure, RGB-D camera, SVM, machine learning, gesture recognition

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Authors: Abiola A. Sokoya

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Handheld devices are now in use as educational tools for learning in most of the higher institutions, because of the features and functions which can be used in an academic environment. This study examined the usage and the benefits of handheld devices as learning tools. A structured questionnaire was used to collect data, while the data collected was analyzed using simple percentage. It was, however, observed that handheld devices offer numerous functions and application for learning, which could improve academic performance of students. Students are now highly interested in using handheld devices for mobile learning apart from making and receiving calls. The researchers recommended that seminars be organized for students on functions of some common handheld devices that can aid learning for academic purposes. It is also recommended that management of each higher institution should make appropriate policies in-line with the usage of handheld technologies to enhance mobile learning. Government should ensure that appropriate policies and regulations are put in place for the importation of high quality handheld devices into the country, Nigeria being a market place for the technologies. By this, using handheld devices for mobile learning will be enhanced.

Keywords: handheld devices, educational tools, mobile e- learning, usage, benefits

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Authors: Mahmoud Timar, Javad Joukar Borazjani

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A dynamic organization helps the management to overcome both internal and external uncertainties and complexities of the organization with more confidence and efficiency. Regarding this issue, in this paper, the influence of organizational culture factors over organizational learning components, which both of them are considered as important characteristics of a dynamic organization, has been studied in three subsidiary companies (production, consultation and service) of National Iranian Oil Company, and moreover we also tried to identify the most dominant culture in these three subsidiaries. Analysis of 840 received questionnaires by SPSS shows that there is a significant relationship between the components of organizational culture and organizational learning; however the rate of relationship between these two factors was different among the examined companies. By the use of Regression, it has been clarified that in the servicing company the highest relationship is between mission and learning environment, while in production division, there is a significant relationship between adaptability and learning needs satisfaction and however in consulting company the highest relationship is between involvement and applying learning in workplace.

Keywords: denison model, culture, leaning, organizational culture, organizational learning

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Authors: Nguyen J. M., Lucas G., Brunner M., Ruan S., Antonioli D.

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Deep learning based on convolutional neural networks (CNN) is a very powerful technique for classifying information from an image. We propose a new method, DeepNic, to transform each variable of a tabular dataset into an image where each pixel represents a set of conditions that allow the variable to make an error-free prediction. The contrast of each pixel is proportional to its prediction performance and the color of each pixel corresponds to a sub-family of NICs. NICs are probabilities that depend on the number of inputs to each neuron and the range of coefficients of the inputs. Each variable can therefore be expressed as a function of a matrix of 2 vectors corresponding to an image whose pixels express predictive capabilities. Our objective is to transform each variable of tabular data into images into an image that can be analysed by CNNs, unlike other methods which use all the variables to construct an image. We analyse the NIC information of each variable and express it as a function of the number of neurons and the range of coefficients used. The predictive value and the category of the NIC are expressed by the contrast and the color of the pixel. We have developed a pipeline to implement this technology and have successfully applied it to genomic expressions on an Affymetrix chip.

Keywords: tabular data, deep learning, perfect trees, NICS

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Authors: Shynn Lim, Ching Tan

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The paper presents the PASSION Programme designed by a government school in Singapore, guided by national goals as well as research-based pedagogies that aims to nurture students to become lifelong learners with the strength of character. The design and enactment of the integrated approach to develop in students good character, resilience and social-emotional well-being, future readiness, and active citizenship is guided by a set of principles that amalgamates Biesta’s domains of purposes of education and authentic learning. Data in terms of evidence of students’ learning and students’ feedback were collected, analysed, and suggests that the learning experience benefitted students by boosting their self-confidence, self-directed and collaborative learning skills, as well as empathy.

Keywords: lifelong learning, character and citizenship education, education and career guidance, 21CC, teaching and learning empathy

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Authors: Farshad Badie

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The central focus of this article is on the fact that knowledge is constructed from an interaction between humans’ experiences and over their conceptions of constructed concepts. Logical characterisation of ‘human inductive learning over human’s constructed concepts’ within terminological systems and providing a logical background for theorising over the Human Concept Learning Problem (HCLP) in terminological systems are the main contributions of this research. This research connects with the topics ‘human learning’, ‘epistemology’, ‘cognitive modelling’, ‘knowledge representation’ and ‘ontological reasoning’.

Keywords: human concept learning, concept construction, knowledge construction, terminological systems

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Authors: Ashish Jaiswal, Ashwin Ramesh Babu, Mohammad Zaki Zadeh, Fillia Makedon, Glenn Wylie

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Functional magnetic resonance imaging (fMRI) is a neuroimaging technique that records neural activations in the brain by capturing the blood oxygen level in different regions based on the task performed by a subject. Given fMRI data, the problem of predicting the state of cognitive fatigue in a person has not been investigated to its full extent. This paper proposes tackling this issue as a multi-class classification problem by dividing the state of cognitive fatigue into six different levels, ranging from no-fatigue to extreme fatigue conditions. We built a spatio-temporal model that uses convolutional neural networks (CNN) for spatial feature extraction and a long short-term memory (LSTM) network for temporal modeling of 4D fMRI scans. We also applied a self-supervised method called MoCo (Momentum Contrast) to pre-train our model on a public dataset BOLD5000 and fine-tuned it on our labeled dataset to predict cognitive fatigue. Our novel dataset contains fMRI scans from Traumatic Brain Injury (TBI) patients and healthy controls (HCs) while performing a series of N-back cognitive tasks. This method establishes a state-of-the-art technique to analyze cognitive fatigue from fMRI data and beats previous approaches to solve this problem.

Keywords: fMRI, brain imaging, deep learning, self-supervised learning, contrastive learning, cognitive fatigue

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Authors: Sudhir Kumar Singh, Debashish Chakravarty

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Slope stability analysis is an important aspect in the field of geotechnical engineering. It is also important from safety, and economic point of view as any slope failure leads to loss of valuable lives and damage to property worth millions. This paper aims at mitigating the risk of slope failure by studying the effect of different joint sets on the stability of mine pit slopes under the influence of various external factors, namely degree of saturation, rainfall intensity, and seismic coefficients. Supervised machine learning approach has been utilized for making accurate and reliable predictions regarding the stability of slopes based on the value of Factor of Safety. Numerous cases have been studied for analyzing the stability of slopes using the popular Finite Element Method, and the data thus obtained has been used as training data for the supervised machine learning models. The input data has been trained on different supervised machine learning models, namely Random Forest, Decision Tree, Support vector Machine, and XGBoost. Distinct test data that is not present in training data has been used for measuring the performance and accuracy of different models. Although all models have performed well on the test dataset but Random Forest stands out from others due to its high accuracy of greater than 95%, thus helping us by providing a valuable tool at our disposition which is neither computationally expensive nor time consuming and in good accordance with the numerical analysis result.

Keywords: finite element method, geotechnical engineering, machine learning, slope stability

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Authors: Vaida Jurgile

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Intercultural learning is one of the approaches taken to understand the cultural diversity of the modern world and to accept changes in cultural identity and otherness and the expression of tolerance. During intercultural learning, students develop their abilities to interact and communicate with their group members. These abilities help to understand social and cultural differences, to form one’s identity, and to give meaning to intercultural learning. Intercultural education recognizes that a true understanding of differences and similarities of another culture is necessary in order to lay the foundations for working together with others, which contributes to the promotion of intercultural dialogue, appreciation of diversity, and cultural exchange. Therefore, it is important to examine the concept of intercultural learning, revealed through students’ learning experiences and understanding of how this learning takes place and what significance this phenomenon has in higher education. At a scientific level, intercultural learning should be explored in order to uncover the influence of cultural identity, i.e., intercultural learning should be seen in a local context. This experience would provide an opportunity to learn from various everyday intercultural learning situations. Intercultural learning can be not only a form of learning but also a tool for building understanding between people of different cultures. The research object of the study is the process of intercultural learning. The aim of the dissertation is to develop a grounded theory of the process of learning in an intercultural study environment, revealing students’ learning experiences. The research strategy chosen in this study is a constructivist grounded theory (GT). GT is an inductive method that seeks to form a theory by applying the systematic collection, synthesis, analysis, and conceptualization of data. The targeted data collection was based on the analysis of data provided by previous research participants, which revealed the need for further research participants. During the research, only students with at least half a year of study experience, i.e., who have completed at least one semester of intercultural studies, were purposefully selected for the research. To select students, snowballing sampling was used. 18 interviews were conducted with students representing 3 different fields of sciences (social sciences, humanities, and technology sciences). In the process of intercultural learning, language expresses and embodies cultural reality and a person’s cultural identity. It is through language that individual experiences are expressed, and the world in which Others exist is perceived. The increased emphasis is placed on the fact that language conveys certain “signs’ of communication and perception with cultural value, enabling the students to identify the Self and the Other. Language becomes an important tool in the process of intercultural communication because it is only through language that learners can communicate, exchange information, and understand each other. Thus, in the process of intercultural learning, language either promotes interpersonal relationships with foreign students or leads to mutual rejection.

Keywords: intercultural learning, grounded theory, students, other

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Authors: Ahmad FAROOQ, Xinfeng Zhang, Fahad Sabah, Raheem Sarwar

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In Traditional Chinese Medicine, tongue diagnosis is a vital inspection tool (TCM). In this study, we explore the potential of machine learning in tongue diagnosis. It begins with the cataloguing of the various classifications and characteristics of the human tongue. We infer 24 kinds of tongues from the material and coating of the tongue, and we identify 21 attributes of the tongue. The next step is to apply machine learning methods to the tongue dataset. We use the Weka machine learning platform to conduct the experiment for performance analysis. The 457 instances of the tongue dataset are used to test the performance of five different machine learning methods, including SVM, Random Forests, Decision Trees, and Naive Bayes. Based on accuracy and Area under the ROC Curve, the Support Vector Machine algorithm was shown to be the most effective for tongue diagnosis (AUC).

Keywords: medical imaging, image retrieval, machine learning, tongue

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Authors: Marina Paula Carreira Rolim

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In order to have ELLs take responsibility for their own learning, it is important that they develop skills to work their studies strategically. The less they rely on the instructor as the content provider, the more they become active learners and have a higher sense of self-regulation and confidence in the learning process. This e-poster proposes a new teacher-student relationship that encourages learners to reflect, think critically, and act upon their realities. It also suggests the implementation of different autonomy-supportive teaching tools, such as portfolios, written journals, problem-solving activities, and strategy-based discussions in class. These teaching tools enable ELLs to develop awareness of learning strategies, learning styles, study plans, and available learning resources as means to foster their creative power of learning outside of classroom. In the role of a learning advisor, the teacher is no longer the content provider but a facilitator that introduces skills such as ‘elaborating’, ‘planning’, ‘monitoring’, and ‘evaluating’. The teacher acts as an educator and promotes the use of lifelong metacognitive skills to develop learner autonomy in the ESL/EFL context.

Keywords: autonomy, metacognitive skills, self-regulation, learning strategies, reflection

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Authors: Shuen-Tai Wang, Fang-An Kuo, Chau-Yi Chou, Yu-Bin Fang

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2016 has become the year of the Artificial Intelligence explosion. AI technologies are getting more and more matured that most world well-known tech giants are making large investment to increase the capabilities in AI. Machine learning is the science of getting computers to act without being explicitly programmed, and deep learning is a subset of machine learning that uses deep neural network to train a machine to learn  features directly from data. Deep learning realizes many machine learning applications which expand the field of AI. At the present time, deep learning frameworks have been widely deployed on servers for deep learning applications in both academia and industry. In training deep neural networks, there are many standard processes or algorithms, but the performance of different frameworks might be different. In this paper we evaluate the running performance of two state-of-the-art distributed deep learning frameworks that are running training calculation in parallel over multi GPU and multi nodes in our cloud environment. We evaluate the training performance of the frameworks with ResNet-50 convolutional neural network, and we analyze what factors that result in the performance among both distributed frameworks as well. Through the experimental analysis, we identify the overheads which could be further optimized. The main contribution is that the evaluation results provide further optimization directions in both performance tuning and algorithmic design.

Keywords: artificial intelligence, machine learning, deep learning, convolutional neural networks

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Authors: Radhika Ranjan Roy

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Deployment of machine learning (ML)/deep learning (DL) algorithms for cyberattack detection in operational communications networks (wireless and/or wire-line) is being delayed because of low-performance parameters (e.g., recall, precision, and f₁-score). If datasets become imbalanced, which is the usual case for communications networks, the performance tends to become worse. Complexities in handling reducing dimensions of the feature sets for increasing performance are also a huge problem. Mahalanobis algorithms have been widely applied in scientific research because Mahalanobis distance metric learning is a successful framework. In this paper, we have investigated the Mahalanobis binary classifier algorithm for increasing cyberattack detection performance over communications networks as a proof of concept. We have also found that high-dimensional information in intermediate features that are not utilized as much for classification tasks in ML/DL algorithms are the main contributor to the state-of-the-art of improved performance of the Mahalanobis method, even for imbalanced and sparse datasets. With no feature reduction, MD offers uniform results for precision, recall, and f₁-score for unbalanced and sparse NSL-KDD datasets.

Keywords: Mahalanobis distance, machine learning, deep learning, NS-KDD, local intrinsic dimensionality, chi-square, positive semi-definite, area under the curve

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Authors: Isiya Shinkafi Salihu

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Open education resources (OER) are open learning materials in different formats, course content and context to support learning globally. This study investigated the level of awareness of Hospitality and Tourism OER among students in the Department of Tourism and Hotel Management in a University. Specifically, it investigated students’ awareness, use and accessibility of OER in learning. The research design method used was the quantitative approach, using an online questionnaire. The thesis research shows that respondents frequently use OER but with little knowledge of the content and context of the material. Most of the respondents’ have little knowledge about the concept even though they use it. Information and communication technologies are tools for information gathering, social networking and knowledge sharing and transfer. OER are open education materials accessible online such as curriculum, maps, course materials, and videos that users create, adapt, reuse for learning and research. Few of the respondents that used OER in learning faced some challenges such as high cost of data, poor connectivity and lack of proper guidance. The results suggest a lack of awareness of OER among students in the faculty of tourism and the need for support from the teachers in the utilization of OER. The thesis also reveals that some of the international students are accessing the internet as beginners in their studies which require guidance. The research, however, recommends that further studies should be conducted to other faculties.

Keywords: creative commons, open education resources, open licenses, information and communication technology

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Authors: Chih-Chun Wu

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Learning information and communication technologies (ICT) helps people survive in current society. For the internet generation also referred as digital natives, learning new technology is like breathing; however, for the elder generations also called digital immigrants, including parents and grandparents, learning new technology could be challenged and frustrated. While majority research focused on the effects of elders’ ICT learning, less attention was paid to the help that the elders got from their other family members while learning ICT. This study utilized the anonymous questionnaire to survey 3,749 undergraduates and demonstrated that families are great places for intergenerational technology learning to be carried out. Results from this study confirmed that in the family, the younger generation both helped set up technology products and educated the elder ones needed technology knowledge and skills. The family elder members in this study applied to those who lived under the same roof with relative relations. Results from this study revealed that 2,331 (62.2%) and 2,656 (70.8%) undergraduates revealed that they helped their family elder members set up and taught them how to use LINE respectively. In addition, 1,481 (49.1%) undergraduates helped their family elder members set up, and 2,222 (59.3%) taught them. When it came to Apps, 2,527 (67.4%) helped their family elder members download them, and 2,876 (76.7%) taught how to use them. As for search engine, 2,317 (61.8%) undergraduates taught their family elders. Furthermore, 3,118 (83.2%), 2,639 (70.4%) and 2,004 (53.7%) undergraduates illustrated that they taught their family elder members smartphones, computers and tablets respectively. Meanwhile, only 904 (24.2%) undergraduates taught their family elders how to make a doctor appointment online. This study suggests to making good use of intergenerational technology learning in the family, since it increases family elders’ technology capital, and thus strengthens our country’s human capital and competitiveness.

Keywords: intergenerational technology learning, adult technology learning, family technology learning, ICT learning

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Authors: Allen A. Espinosa, Larkins A. Trinidad

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The present study investigated collegiate students’ problem solving strategies and misconceptions in solving stoichiometric problems and later on formulate a teaching framework from the result of the study. The study found out that the most prominent strategies among students are the mole method and the proportionality method, which are both algorithmic by nature. Misconception was also noted as some students rely on Avogadro’s number in converting between moles. It is suggested therefore that the teaching of stoichiometry should not be confined to demonstration. Students should be involved in the process of thinking of ways to solve the problem.

Keywords: stoichiometry, Svogadro’s number, mole method, proportionality method

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Authors: Bella Llego

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This study aims to investigate the motivating and de-motivating factors that affect the learning ability of students attending the English Learning Center in Thailand. The subjects of this research were 20 students from the Hana Semiconductor Co., Limited. The data were collected by using questionnaire and analyzed using the SPSS program for the percentage, mean and standard deviation. The research results show that the main motivating factor in learning English at Hana Semiconductor Co., Ltd. is that it would help the employees to communicate with foreign customers and managers. Other reasons include the need to read and write e-mails, and reports in English, as well as to increase overall general knowledge. The main de-motivating factor is that there is a lot of vocabulary to remember when learning English. Another de-motivating factor is that when homework is given, the students have no time to complete the tasks required of them at the end of the working day.

Keywords: de-motivating, English learning center, motivating, student communicate

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Authors: Sokkhey Phauk, Takeo Okazaki

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The challenging task in educational institutions is to maximize the high performance of students and minimize the failure rate of poor-performing students. An effective method to leverage this task is to know student learning patterns with highly influencing factors and get an early prediction of student learning outcomes at the timely stage for setting up policies for improvement. Educational data mining (EDM) is an emerging disciplinary field of data mining, statistics, and machine learning concerned with extracting useful knowledge and information for the sake of improvement and development in the education environment. The study is of this work is to propose techniques in EDM and integrate it into a web-based system for predicting poor-performing students. A comparative study of prediction models is conducted. Subsequently, high performing models are developed to get higher performance. The hybrid random forest (Hybrid RF) produces the most successful classification. For the context of intervention and improving the learning outcomes, a feature selection method MICHI, which is the combination of mutual information (MI) and chi-square (CHI) algorithms based on the ranked feature scores, is introduced to select a dominant feature set that improves the performance of prediction and uses the obtained dominant set as information for intervention. By using the proposed techniques of EDM, an academic performance prediction system (APPS) is subsequently developed for educational stockholders to get an early prediction of student learning outcomes for timely intervention. Experimental outcomes and evaluation surveys report the effectiveness and usefulness of the developed system. The system is used to help educational stakeholders and related individuals for intervening and improving student performance.

Keywords: academic performance prediction system, educational data mining, dominant factors, feature selection method, prediction model, student performance

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Authors: Leandro Marcos Alves Vaz

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The teaching of physics in Brazilian public schools emphasizes strongly the theoretical aspects of this science, showing its philosophical and mathematical basis, but neglecting its experimental character. Perhaps the lack of science laboratories explains this practice. In this work, we present a method of teaching physics using the computer. As alternatives to real experiments, we have the trials through simulators, many of which are free software available on the internet. In order to develop a study on the use of simulators in teaching, knowing the impossibility of simulations on all topics in a given subject, we combined these programs with phenomenological and/or experimental texts in order to mitigate this limitation. This study proposes the use of simulators and the debate using phenomenological/experimental texts on electrostatic theme in groups of the 3rd year of EJA (Adult and Youth Education) in order to verify the advantages of this methodology. Some benefits of the hybridization of the traditional method with the tools used were: Greater motivation of the students in learning, development of experimental notions, proactive socialization to learning, greater easiness to understand some concepts and the creation of collaborative activities that can reduce timidity of part of the students.

Keywords: experimentation, learning physical, simulators, youth and adult

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Authors: S. Rawashdi, D. Bshouty

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This paper aimed at discussing how to urge middle and high school Arab students in Israel to be aware of the importance of and investing in learning mathematics. In the first phase of the study, three questionnaires were passed to two nine-grade classes, one on Awareness, one on Awakeness and one on Learning. One of the two classes was an outstanding class from a public school (PUBS) of 31 students, and the other a heterogeneous class from a private school (PRIS) with 31 students. The Learning questionnaire which was administrated to the Awareness and Awareness topics was passed to PRIS and the Awareness and Awareness Questionnaires were passed to the PUBS class After two months we passed the post-questionnaire to both classes to validate the long-term impact of the study. The findings of the study show that awakeness and awareness processes have an effect on the math learning process, on its context in students' daily lives and their growing interest in learning math.

Keywords: awakeness, awareness, learning mathematics, pupils

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Authors: Okoh Charity N.

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This study investigated the predictive power of preschoolers’ involvement in indoor and outdoor learning activities on their social learning skills in Niger state, Nigeria. Two research questions and two null hypotheses guided the study. Correlational research design was employed in the study. The population of the study consisted of 8,568 Nursery III preschoolers across the 549 preschools in the five Local Education Authorities in Niger State. A sample of 390 preschoolers drawn through multistage sampling procedure. Two instruments; Preschoolers’ Learning Activities Rating Scale (PLARS) and Preschoolers’ Social Learning Skills Rating Scale (PSLSRS) developed by the researcher were used for data collection. The reliability coefficients obtained for the PLARS and PSLSRS were 0.83 and 0.82, respectively. Data collected were analyzed using simple linear regression. Results showed that 37% of preschoolers’ social learning skills are predicted by their involvement in indoor learning activities, which is statistically significant (p < 0.05). It also shows that 11% of preschoolers’ social learning skills are predicted by their involvement in outdoor learning activities, which is statistically significant (p < 0.05). Therefore, it was recommended among others, that government and school administrators should employ qualified teachers who will stand as role models for preschoolers’ social skills development and provide indoor and outdoor activities and materials for preschoolers in schools.

Keywords: preschooler, social learning, indoor activities, outdoor activities

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Authors: Mostafa ‘Neo’ Mohsenvand, Mohammad Rasool Izadi, Pattie Maes

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EEG-based biometrics (user identification) has been explored on small datasets of no more than 157 subjects. Here we show that the accuracy of modern supervised methods falls rapidly as the number of users increases to a few thousand. Moreover, supervised methods require a large amount of labeled data for training which limits their applications in real-world scenarios where acquiring data for training should not take more than a few minutes. We show that using contrastive learning for pre-training, it is possible to maintain high accuracy on a dataset of 2130 subjects while only using a fraction of labels. We compare 5 different self-supervised tasks for pre-training of the encoder where our proposed method achieves the accuracy of 96.4%, improving the baseline supervised models by 22.75% and the competing self-supervised model by 3.93%. We also study the effects of the length of the signal and the number of channels on the accuracy of the user-identification models. Our results reveal that signals from temporal and frontal channels contain more identifying features compared to other channels.

Keywords: brainprint, contrastive learning, electroencephalo-gram, self-supervised learning, user identification

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Authors: Lin Li, Farshad Amini

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The flipped classroom has been introduced to promote collaborative learning and higher-order learning objectives. In contrast to the traditional classroom, the flipped classroom has students watch prerecorded lecture videos before coming to class and then “class becomes the place to work through problems, advance concepts, and engage in collaborative learning”. In this paper, the active flipped learning combines flipped classroom with active learning that is to establish an active flipped learning (AFL) model, aiming to promote active learning, stress deep learning, encourage student engagement and highlight data-driven personalized learning. Because students have watched the lecture prior to class, contact hours can be devoted to problem-solving and gain a deeper understanding of the subject matter. The instructor is able to provide students with a wide range of learner-centered opportunities in class for greater mentoring and collaboration, increasing the possibility to engage students. Currently, little is known about the extent to which AFL improves engineering students’ performance. This paper presents the preliminary study on the core course of sophomore students in Engineering Mechanics. A series of survey and interviews have been conducted to compare students’ learning engagement, empowerment, self-efficacy, and satisfaction with the AFL. It was found that the AFL model taking advantage of advanced technology is a convenient and professional avenue for engineering students to strengthen their academic confidence and self-efficacy in the Engineering Mechanics by actively participating in learning and fostering their deep understanding of engineering statics and dynamics

Keywords: active learning, engineering mechanics, flipped classroom, performance

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Authors: Elleuch Imen

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In this paper, it propose a new approach for learning Arabic as a foreign language via audio-visual translation, particularly subtitling. The approach consists of developing video sequences appropriate to different levels of learning (from A1 to C2) containing conversations, quizzes, games and others. Each video aims to achieve a specific objective, such as the correct pronunciation of Arabic words, the correct syntactic structuring of Arabic sentences, the recognition of the morphological characteristics of terms and the semantic understanding of statements. The subtitled videos obtained can be incorporated into different Arabic second language learning tools such as Moocs, websites, platforms, etc.

Keywords: arabic foreign language, learning, audio-visuel translation, subtitled videos

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Authors: Suratno

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Metacognition thinking skills should be developed early on in learning. The aim of research builds metacognition thinking skills through collaborative learning with self-evaluation. Approach to action research study involving 32 middle school students in Jember Indonesia. Indicators metacognition skills consist of planning, information management strategies, comprehension monitoring, and debugging strategies. Data were analyzed by t test and analysis of instructional videos. Results of the study here were significant differences in metacognition skills before and after the implementation of collaborative learning with self-evaluation. Analysis instructional video showing the difference artifacts of student learning activities to learning before and after implementation of collaborative learning with self-evaluation. Self-evaluation makes students familiar practice thinking skills metacognition.

Keywords: metacognition, collaborative, evaluation, thinking skills

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Authors: Stephanie K. Douglas, Gordon R. Haley

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Organizations face increasing disruptions, changes, and uncertainties through the rapid shifts in the economy and business environment. A capacity for resilience is necessary for organizations to survive and thrive in such adverse conditions. Learning is an essential component of an organization's capability for building resilience. Strategic human resource management is a principal component of learning and organizational resilience. To achieve organizational resilience, human resource management strategies must support individual knowledge, skills, and ability development through organizational learning. This study aimed to contribute to the comprehensive knowledge of the relationship between strategic human resource management and organizational learning to build organizational resilience. The organizational learning dimensions of knowledge acquisition, knowledge distribution, knowledge interpretation, and organizational memory can be fostered through human resource management strategies and then aggregated to the organizational level to build resilience.

Keywords: human resource development, human resource management, organizational learning, organizational resilience

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Authors: Horng-Jyh Chen, Yi-Fang Chen, Chien-Liang Lin

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In this paper, the authors try to investigate the determinants of behavioral intention of the blended e-learning course for senior students at the Active Ageing University in Taiwan. Due to lower proficiency in the use of computers and less experience on learning styles of the blended e-learning course for senior students will be expected quite different from those for most young students. After more than five weeks course for two years the questionnaire survey is executed to collect data for statistical analysis in order to understand the determinants of the behavioral intention for senior students. The object of this study is at one of the Active Ageing University in Taiwan total of 84 senior students in the blended e-learning for the ceramics teaching course. The research results show that only the perceived usefulness of the blended e-learning course has significant positive relationship with the behavioral intention.

Keywords: Active Aging University, blended e-learning, ceramics teaching course, behavioral intention

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Authors: Anandkumar S. Purohit

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Introduction: Amblyopia is a serious condition resulting in monocular impairment of vision. Although traditional treatment improves vision, we attempted the results of perceptual learning in this study. Methods: The prospective cohort study included all patients with amblyopia who were subjected to perceptual learning. The presenting data on vision, stereopsis, and contrast sensitivity were documented in a pretested online format, and the pre‑ and post‑treatment information was compared using descriptive, cross‑tabulation, and comparative methods on SPSS 22. Results: The cohort consisted of 47 patients (23 females and 24 males) with a mean age of 14.11 ± 7.13 years. A significant improvement was detected in visual acuity after the PL sessions, and the median follow‑up period was 17 days. Stereopsis improved significantly in all age groups. Conclusion: PL with hand-eye coordination is an effective method for managing amblyopia. This approach can improve vision in all age groups.

Keywords: amblyopia, perceptual learning, hand-eye coordination, visual acuity, stereopsis, contrast sensitivity, ophthalmology

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Authors: Raminder Kaur

Abstract:

This paper considers the emerging area of integrating Virtual Reality (VR) technologies into the teaching of Visual Anthropology, Research Methods, and the Anthropology of Contemporary India in the University of Sussex. If deployed in a critical and self-reflexive manner, there are several advantages to VR-based immersive learning: (i) Based on data available for British schools, it has been noted that ‘Learning through experience can boost knowledge retention by up to 75%’. (ii) It can tutor students to learn with and from virtual worlds, devising new collaborative methods where suited. (iii) It can foster inclusive learning by aiding students with SEN and disabilities who may not be able to explore such areas in the physical world. (iv) It can inspire and instill confidence in students with anxieties about approaching new subjects, realms, or regions. (v) It augments our provision of ‘smart classrooms’ synchronised to the kinds of emerging immersive learning environments that students come from in schools.

Keywords: virtual reality, anthropology, immersive learning, university

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