Search results for: learning approaches

Authors: Ramin Shadani

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This study introduces adaptive performance as a key organizational performance dimension and explores the relationship between the dimensions of a learning organization and adaptive performance. A survey was therefore conducted using the dimensions of the Learning Organization Questionnaire (DLOQ), followed by factor analysis and structural equation modeling in order to investigate the dynamics between learning organization practices and adaptive performance. Results confirm that adaptive performance is indeed one important dimension of organizational performance. The study also shows that perceived knowledge and adaptive performance mediate the positive relationship between the practices of a learning organization with perceived financial performance. We extend existing DLOQ research by demonstrating that adaptive performance, as a nonfinancial organizational learning outcome, has a significant impact on financial performance. Our study also provides additional validation of the measures of DLOQ's performance. Indeed, organizations need to take a glance at how the activities of learning and development can provide better overall improvement in performance, especially in enhancing adaptive capability. The study has provided requisite empirical support that activities of learning and development within organizations allow much-improved intangible performance outcomes, especially through adaptive performance.

Keywords: adaptive performance, continuous learning, financial performance, leadership style, organizational learning, organizational performance

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Authors: Rylyne Mande Nchu, Robertson Tengeh, Chux Iwu

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Blended learning is a global phenomenon and is essential to many institutes of learning as an additional method of teaching that complements more traditional methods of learning. In this paper, the lack of practice of a blended learning approach to entrepreneurship education and how it impacts learners' perception of being entrepreneurial. E-learning is in its infancy within the secondary and high school sectors in South Africa. The conceptual framework of the study is based on theoretical aspects of systemic-constructivist learning implemented in an interactive online learning environment in an entrepreneurship education subject. The formative evaluation research was conducted implementing mixed methods of research (quantitative and qualitative) and it comprised a survey of high school learners and informant interviewing with entrepreneurs. Theoretical analysis of literature provides features necessary for creating interactive blended learning environments to be used in entrepreneurship education subject. Findings of the study show that learners do not always objectively evaluate their capacities. Special attention has to be paid to the development of learners’ computer literacy as well as to the activities that would bring online learning to practical training. Needs analysis shows that incorporating blended learning in entrepreneurship education may have a positive perception of entrepreneurship.

Keywords: blended learning, entrepreneurship education, entrepreneurship intention, entrepreneurial skills

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Authors: Kafuko M. Maria, Namisango Fatuma, Byomire Gorretti

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Mobile learning (m-learning) is steadily growing and has undoubtedly derived benefits to learners and tutors in different learning environments. This paper investigates the variation in benefits derived from enhanced classroom learning through use of m-learning platforms in the context of a developing country owing to the fact that it is still in its initial stages. The study focused on how basic technology-enhanced pedagogic innovation like cell phone-based learning is enhancing classroom learning from the learners’ perspective. The paper explicitly indicates the opportunities presented by enhanced learning to a conventional learning environment like a physical classroom. The findings were obtained through a survey of two universities in Uganda in which data was quantitatively collected, analyzed and presented in a three banded diagram depicting the variation in the obtainable benefits. Learners indicated that a smartphone is the most commonly used device. Learners also indicate that straight lectures, student to student plus student to lecturer communication, accessing learning material and assignments are core activities. In a TEL environment support by smartphones, learners indicated that they conveniently achieve the prior activities plus discussions and group work. Learners seemed not attracted to the possibility of using TEL environment to take lectures, as well as make class presentations. The less attractiveness of these two factors may be due to the teacher centered approach commonly applied in the country’s education system.

Keywords: technology enhanced learning, m-learning, classroom learning, perceived benefits

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Authors: Sujit K. Basak, Marguerite Wotto, Paul Bélanger

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This paper presents a conceptual framework on the critical success factors of e-learning implementation in higher education, derived from an in-depth survey of literature review. The aim of this study was achieved by identifying critical success factors that affect for the successful implementation of e-learning. The findings help to articulate issues that are related to e-learning implementation in both formal and non-formal higher education and in this way contribute to the development of programs designed to address the relevant issues.

Keywords: critical success factors, e-learning, higher education, life-long learning

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Authors: Siti Rossidatul Munawaroh, Siti Khusnul Khowatim

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This study is determined to find how is the influence of family attention of students in provides guidance of the student learning. The increasing of student’s learning motivation can be increased made up in various ways, one of them are through students social guidance in their relation with the family. The family not only provides the matter and the learning time but also be supervise for the learning time and guide his children to overcome a learning disability. The character of physics subject in their science experiences at junior high schools has demanded that student’s ability is to think symbolically and understand something in a meaningful manner. Therefore, the reinforcement of the physics learning motivation is clearly necessary not only by the school are related, but the family environment and the society. As for the role of family which includes maintenance, parenting, coaching, and educating both of physically and spiritually, this way is expected to give spirit impulsion in studying physics subject in order to increase student learning achievements.

Keywords: physics subject, the influence of family attention, learning motivation, the Student care

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Authors: Xinyu Wang

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In the context of the rapid development of Internet technology and the increasing prevalence of online social media, this study investigates the impact of digital communication on social learning. Through three behavioral experiments, we explore both affective and cognitive social learning in online environments. Experiment 1 manipulates the content of experimental materials and two forms of feedback, emotional valence, sociability, and repetition, to verify whether individuals can achieve online emotional social learning through reinforcement using two social learning strategies. Results reveal that both social learning strategies can assist individuals in affective, social learning through reinforcement, with feedback-based learning strategies outperforming frequency-dependent strategies. Experiment 2 similarly manipulates the content of experimental materials and two forms of feedback to verify whether individuals can achieve online knowledge social learning through reinforcement using two social learning strategies. Results show that similar to online affective social learning, individuals adopt both social learning strategies to achieve cognitive social learning through reinforcement, with feedback-based learning strategies outperforming frequency-dependent strategies. Experiment 3 simultaneously observes online affective and cognitive social learning by manipulating the content of experimental materials and feedback at different levels of social pressure. Results indicate that online affective social learning exhibits different learning effects under different levels of social pressure, whereas online cognitive social learning remains unaffected by social pressure, demonstrating more stable learning effects. Additionally, to explore the sustained effects of online social learning and differences in duration among different types of online social learning, all three experiments incorporate two test time points. Results reveal significant differences in pre-post-test scores for online social learning in Experiments 2 and 3, whereas differences are less apparent in Experiment 1. To accurately measure the sustained effects of online social learning, the researchers conducted a mini-meta-analysis of all effect sizes of online social learning duration. Results indicate that although the overall effect size is small, the effect of online social learning weakens over time.

Keywords: online social learning, affective social learning, cognitive social learning, social learning strategies, social reinforcement, social pressure, duration

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Authors: Selvavinayagan Babiharan

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This research aims to develop a deep learning platform to enhance mathematics education for secondary students in Sri Lanka. The platform will be designed to incorporate interactive and user-friendly features to engage students in active learning and promote their mathematical skills. The proposed platform will be developed using TensorFlow and Keras, two widely used deep learning frameworks. The system will be trained on a large dataset of math problems, which will be collected from Sri Lankan school curricula. The results of this research will contribute to the improvement of mathematics education in Sri Lanka and provide a valuable tool for teachers to enhance the learning experience of their students.

Keywords: information technology, education, machine learning, mathematics

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Authors: Nesengani Elelwani Clinton

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This paper presents reflective learning as an opportunity commonly available and used for food waste learning in a food processing company in the transition to sustainable and just food systems. In addressing how employees learn about food waste during food processing, the opportunities available for food waste learning were investigated. Reflective learning appeared to be the most used approach to learning about food waste. In the case of food waste learning, reflective learning was a response after employees wasted a substantial amount of food, where process controllers and team leaders would highlight the issue to employees who wasted food and explain how food waste could be reduced. This showed that learning about food waste is not proactive, and there continues to be a lack of structured learning around food waste. Several challenges were highlighted around reflective learning about food waste. Some of the challenges included understanding the language, lack of interest from employees, set times to reach production targets, and working pressures. These challenges were reported to be hindering factors in understanding food waste learning, which is not structured. A need was identified for proactive learning through structured methods. This is because it was discovered that in the plant, where food processing activities happen, the signage and posters that are there are directly related to other sustainability issues such as food safety and health. This indicated that there are low levels of awareness about food waste. Therefore, this paper argues that food waste learning should be proactive. The proactive learning approach should include structured learning materials around food waste during food processing. In the structuring of the learning materials, individual trainers should be multilingual. This will make it possible for those who do not understand English to understand in their own language. And lastly, there should be signage and posters in the food processing plant around food waste. This will bring more awareness around food waste, and employees' behaviour can be influenced by the posters and signage in the food processing plant. Thus, will enable a transition to a just and sustainable food system.

Keywords: sustainable and just food systems, food waste, food waste learning, reflective learning approach

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Authors: Pauline Logue

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In recent decades, the Irish Department of Education and Skills has pro-actively promoted student-center learning methodologies. Similarly, the National Forum for the Enhancement of Teaching and Learning has advocated such strategies, aligning them with student success. These developments have informed the author’s professional practice as a teacher educator. This qualitative student-perspective study focuses on a review of one pilot initiative in the academic year 2020-2021, namely, the implementation of universal design for learning strategies within teacher education, employing student-centered learning strategies. Findings included: that student-centered strategies enhanced student performance and success overall, with some minor evidence of student resistance. It was concluded that a dialogical review with student teachers on prior learning experiences (from intellectual and affective perspectives) and learning environments (physical, virtual, and emotional) could facilitate greater student ownership of learning. It is recommended to more formally structure such a dialogical review in a future delivery.

Keywords: professional practice, student-centered learning, teacher education, universal design for learning

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Authors: P. Kooche Baghy, S. Eskandari, E.javanmard

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Neural network has been used as a predictive means of cold rolling force in this dissertation. Thus, imposed average force on rollers as a mere input and five pertaining parameters to its as a outputs are regarded. According to our study, feed-forward multilayer perceptron network has been selected. Besides, Bayesian algorithm based on the feed-forward back propagation method has been selected due to noisy data. Further, 470 out of 585 all tests were used for network learning and others (115 tests) were considered as assessment criteria. Eventually, by 30 times running the MATLAB software, mean error was obtained 3.84 percent as a criteria of network learning. As a consequence, this the mentioned error on par with other approaches such as numerical and empirical methods is acceptable admittedly.

Keywords: artificial neural network, Bayesian, cold rolling, force evaluation

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Authors: Cristian Crespo

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Conditional cash transfers (CCTs) have been targeted towards the poor. Thus, their targeting assessments check whether these schemes have been allocated to low-income households or individuals. However, CCTs have more than one goal and target group. An additional goal of CCTs is to increase school enrolment. Hence, students at risk of dropping out of school also are a target group. This paper analyses whether one of the most common targeting mechanisms of CCTs, a proxy means test (PMT), is suitable to identify the poor and future school dropouts. The PMT is compared with alternative approaches that use the outputs of a predictive model of school dropout. This model was built using machine learning algorithms and rich administrative datasets from Chile. The paper shows that using machine learning outputs in conjunction with the PMT increases targeting effectiveness by identifying more students who are either poor or future dropouts. This joint targeting approach increases effectiveness in different scenarios except when the social valuation of the two target groups largely differs. In these cases, the most likely optimal approach is to solely adopt the targeting mechanism designed to find the highly valued group.

Keywords: conditional cash transfers, machine learning, poverty, proxy means tests, school dropout prediction, targeting

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Authors: Khoi A. Nguyen, Rodney A. Stewart, Hong Zhang

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‘Water-related energy’ is energy use which is directly or indirectly influenced by changes to water use. Informatics applying a range of mathematical, statistical and rule-based approaches can be used to reveal important information on demand from the available data provided at second, minute or hourly intervals. This study aims to combine these two concepts to improve the current water end use disaggregation problem through applying a wide range of most advanced pattern recognition techniques to analyse the concurrent high-resolution water-energy consumption data. The obtained results have shown that recognition accuracies of all end-uses have significantly increased, especially for mechanised categories, including clothes washer, dishwasher and evaporative air cooler where over 95% of events were correctly classified.

Keywords: deep learning network, smart metering, water end use, water-energy data

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Authors: Dongkwon Han, Sangho Kim, Sunil Kwon

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Unconventional gas resources have dramatically changed the future energy landscape. Unlike conventional gas resources, the key challenges in unconventional gas have been the requirement that applies to advanced approaches for production forecasting due to uncertainty and complexity of fluid flow. In this study, artificial neural network (ANN) model which integrates machine learning and data-driven approach was developed to predict productivity in shale gas. The database of 129 wells of Eagle Ford shale basin used for testing and training of the ANN model. The Input data related to hydraulic fracturing, well completion and productivity of shale gas were selected and the output data is a cumulative production. The performance of the ANN using all data sets, clustering and variables importance (VI) models were compared in the mean absolute percentage error (MAPE). ANN model using all data sets, clustering, and VI were obtained as 44.22%, 10.08% (cluster 1), 5.26% (cluster 2), 6.35%(cluster 3), and 32.23% (ANN VI), 23.19% (SVM VI), respectively. The results showed that the pre-trained ANN model provides more accurate results than the ANN model using all data sets.

Keywords: unconventional gas, artificial neural network, machine learning, clustering, variables importance

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Authors: Md. Mizanoor Rahman, Md. Zakir Hossain Talukder, M. Mahruf C. Shohel, Prithvi Shrestha

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In Bangladesh, classroom practice and English Learning (EL) competencies acquired both by the teacher and learner in primary and secondary schools are still very weak. Therefore, English is the most commonly failed examination subject at the school level; in addition, there are severe problems in communicative English by the Bangladeshi nationals– this has been characterized as a constraint to economic development. Job applicants and employees often lack English language skills necessary to work effectively. As a result; both government and its international development partners such as DFID, UNESCO, and CIDA have been very active to uplift the quality of the English language learning and implementing projects with innovative approaches. Recently; the economy has been increasing and in line with this, the technology has been deployed in English learning to improve reading, writing, speaking and listening skills. Young Bangladeshi creative, from a variety of backgrounds including film, animation, photography, and digital media are being trained to develop ideas for English Language Teaching (ELT) media. They are being motivated to develop a wide range of ideas for low cost English learning media products. English Language education policy in Bangladesh supports communicative language teaching practices and accordingly, actors have been influencing curriculum, textbook, deployment of technology and assessment changes supporting communicative ELT. The various projects are also being implemented to reform the curriculum, revise the textbook and adjust the assessment mechanism so that the country can increase in proficiency in communicative English among the population. At present; the numbers of teachers, students and adult learners classified at higher levels of proficiency because of deployment of technology and motivation for learning and using English among school population of Bangladesh. The current paper discusses the various interventions in Bangladesh with appropriate media to improve the competencies of the ELT among population.

Keywords: English learning, technology, education, psychological sciences

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Authors: Baoliang Xu

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The future of education should focus on creating meaningful learning for learners. Play is a basic form and an important means of carrying out kindergarten educational activities, which promotes the creation and development of meaningful learning and is of great importance in the harmonious physical and mental development of young children. Through literature research and case studies, this paper finds that: meaningful learning has the characteristics of contextuality, interaction and constructiveness; teachers should pay great attention to the guidance of children's games, fully respect children's autonomy and create a prepared game environment; children's meaningful learning exists in games and hidden in things that interest them, and "the generation of questions The "generation of questions" fuels the depth of children's meaningful learning, and teachers' professional support helps children's meaningful learning to develop continuously. In short, teachers' guidance of young children's play should be emphasized to effectively provide scaffolding instruction to promote meaningful learning in a holistic manner.

Keywords: meaningful learning, young childhood, game, case study

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Authors: Alison Power

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Games-based learning aims to enhance students’ engagement with and enjoyment of learning opportunities using games-related principles to create a fun yet productive learning environment. Motivating students to learn in an online setting can be particularly challenging, so a cross-Faculty synchronous online session provided students with the opportunity to engage with ‘GAMING’: an interactive, flexible and scalable e-resource for students to work synchronously in groups to complete a series of e-tivities designed to enhance their skills of leadership, collaboration and negotiation. Findings from a post-session online survey found the majority of students had a positive learning experience, finding 'GAMING' to be an innovative and engaging e-resource which motivated their group to learn.

Keywords: collaboration, games-based learning, groupwork, synchronous online learning, teamwork

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Authors: Omar Alzeley, Sergey Utev

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Minimizing a constrained multivariate function is the fundamental of Machine learning, and these algorithms are at the core of data mining and data visualization techniques. The decision function that maps input points to output points is based on the result of optimization. This optimization is the central of learning theory. One approach to complex systems where the dynamics of the system is inferred by a statistical analysis of the fluctuations in time of some associated observable is time series analysis. The purpose of this paper is a mathematical transition from the autoregressive model of classical time series to the matrix formalization of quantum theory. Firstly, we have proposed a quantum time series model (QTS). Although Hamiltonian technique becomes an established tool to detect a deterministic chaos, other approaches emerge. The quantum probabilistic technique is used to motivate the construction of our QTS model. The QTS model resembles the quantum dynamic model which was applied to financial data. Secondly, various statistical methods, including machine learning algorithms such as the Kalman filter algorithm, are applied to estimate and analyses the unknown parameters of the model. Finally, simulation techniques such as Markov chain Monte Carlo have been used to support our investigations. The proposed model has been examined by using real and simulated data. We establish the relation between quantum statistical machine and quantum time series via random matrix theory. It is interesting to note that the primary focus of the application of QTS in the field of quantum chaos was to find a model that explain chaotic behaviour. Maybe this model will reveal another insight into quantum chaos.

Keywords: machine learning, simulation techniques, quantum probability, tensor product, time series

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Authors: Ye Wang, Ickjai Lee

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Due to the widespread of mobile sensing, there is a strong need to handle trails of moving objects, trajectories. This paper proposes three visual analytic approaches for higher order information of trajectory data sets based on the higher order Voronoi diagram data structure. Proposed approaches reveal geometrical information, topological, and directional information. Experimental results demonstrate the applicability and usefulness of proposed three approaches.

Keywords: visual analytics, higher order information, trajectory datasets, spatio-temporal data

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Authors: Mimi Mohaffyza Mohamad, Yee Mei Heong, Nurfirdawati Muhammad Hanafi, Tee Tze Kiong

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This study is conducted to investigate the disparity of between learning styles and cognitive abilities specifically in Vocational Education. Felder and Silverman Learning Styles Model (FSLSM) was applied to measure the students’ learning styles while the content in Building Construction Subject consists; knowledge, skills and problem solving were taken into account in constructing the elements of cognitive abilities. There are four dimension of learning styles proposed by Felder and Silverman intended to capture student learning preferences with regards to processing either active or reflective, perception based on sensing or intuitive, input of information used visual or verbal and understanding information represent with sequential or global learner. The study discovered that students are tending to be visual learners and each type of learner having significant difference whereas cognitive abilities. The finding may help teachers to facilitate students more effectively and to boost the student’s cognitive abilities.

Keywords: learning styles, cognitive abilities, dimension of learning styles, learning preferences

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Authors: Noawanit Songkram

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This paper is a report on the findings of a study conducted on e–learning system in virtual learning environment to develop problem solving ability and team learning for learners in higher education. The methodology of this study was R&D research. The subjects were 18 undergraduate students in Faculty of Education, Chulalongkorn University in the academic year of 2013. The research instruments were a problem solving ability assessment, a team learning evaluation form, and an attitude questionnaire. The data was statistically analyzed using mean, standard deviation, one way repeated measure ANOVA and t–test. The research findings discovered the e –learning system in virtual learning environment to develop problem solving ability and team learning for learners in higher education consisted of five components:(1) online collaborative tools, (2) active learning activities, (3) creative thinking, (4) knowledge sharing process, (5) evaluation and nine processes which were (1) preparing in group working, (2) identifying interested topic, (3) analysing interested topic, (4) collecting data, (5) concluding idea (6) proposing idea, (7) creating workings, (8) workings evaluation, (9) sharing knowledge from empirical experience.

Keywords: e-learning system, problem solving ability, team leaning, virtual learning environment

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Authors: Samira Karimi-Mansoub, Rahem Abri

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Currently, users expect high quality and personalized information from search results. To satisfy user’s needs, personalized approaches to web search have been proposed. These approaches can provide the most appropriate answer for user’s needs by using user context and incorporating information about query provided by combining search technologies. To carry out personalized web search, there is a need to make different techniques on whole of user search process. There are the number of possible deployment of personalized approaches such as personalized web search, personalized recommendation, personalized summarization and filtering systems and etc. but the common feature of all approaches in various domains is that user modeling is utilized to provide personalized information from the Web. So the most important work in personalized approaches is user model mining. User modeling applications and technologies can be used in various domains depending on how the user collected information may be extracted. In addition to, the used techniques to create user model is also different in each of these applications. Since in the previous studies, there was not a complete survey in this field, our purpose is to present a survey on applications and techniques of user modeling from the viewpoint of improvement in search results by considering the existing literature and researches.

Keywords: filtering systems, personalized web search, user modeling, user search behavior

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Authors: Amira Khelil, Habib Affes

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The XXIst century is characterized by promoting teamwork as one of the main drivers of firms` performance. Collective competence is becoming crucial in developing and maintaining a firm’s competitive advantage, as well as its contributions to organizational innovation. In other words, the improvement of collective competence for a firm is no longer a choice, but rather an obligation. Learning capabilities of a firm in the context of knowledge management are assumed to be the main drivers of collective competence. Although there are some efforts to consider these concepts together; they are mostly discussed separately in the management theory. Thus, this paper aims to offer a holistic approach for development collective competence on the basis of Knowledge Management and Organizational Learning Capabilities. A theoretical model that defines a relationship between knowledge management, organizational learning and collective competence is presented at the end of this paper.

Keywords: collective competence, exploitation learning, exploration learning, knowledge management, organizational learning capabilities

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Authors: Mamochana, A. Ramatea, Fumane, P. Khanare

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Enabling the learning environment is a significant and adaptive technique necessary to navigate learners’ educational challenges. However, research has indicated that quality provision of education in the environments that are enabling, especially to learners with visual impairments (LVIs, hereafter) in rural schools, remain an ongoing challenge globally. Hence, LVIs often have a lower level of academic performance as compared to their peers. To balance this gap and fulfill learners'fundamentalhuman rights¬ of receiving an equal quality education, appropriate measures and structures that make enabling learning environment a better place to learn must be better understood. This paper, therefore, intends to find possible means that rural schools of Lesotho can employ to make the learning environment for LVIs enabling. The present study aims to determine suitable assets that can be drawn to make the learning environment for LVIs enabling. The study is also informed by the transformative paradigm and situated within a qualitative research approach. Data were generated through focus group discussions with twelve teachers who were purposefully selected from two rural primary schools in Lesotho. The generated data were then analyzed thematically using Braun and Clarke's six-phase framework. The findings of the study indicated that participating teachers do have an understanding that rural schools boast of assets (existing and hidden) that have a positive influence in responding to the special educational needs of LVIs. However, the participants also admitted that although their schools boast of assets, they still experience limited knowledge about the use of the existing assets and thus, realized a need for improved collaboration, involvement of the existing assets, and enhancement of academic resources to make LVIs’ learning environment enabling. The findings of this study highlight the significance of the effective use of assets. Additionally, coincides with literature that shows recognizing and tapping into the existing assets enable learning for LVIs. In conclusion, the participants in the current study indicated that for LVIs’ learning environment to be enabling, there has to be sufficient use of the existing assets. The researchers, therefore, recommend that the appropriate use of assets is good, but may not be sufficient if the existing assets are not adequately managed. Hence,VILs experience a vicious cycle of vulnerability. It was thus, recommended that adequate use of assets and teachers' engagement as active assets should always be considered to make the learning environment a better place for LVIs to learan in the future

Keywords: assets, enabling learning environment, rural schools, learners with visual impairments

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Authors: Beilei Xu, Wencheng Wu, Lei Lin, Rachel Melnyk, Ahmed Ghazi

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In operating rooms, excessive cognitive stress can impede the performance of a surgeon, while low engagement can lead to unavoidable mistakes due to complacency. As a consequence, there is a strong desire in the surgical community to be able to monitor and quantify the cognitive stress of a surgeon while performing surgical procedures. Quantitative cognitiveload-based feedback can also provide valuable insights during surgical training to optimize training efficiency and effectiveness. Various physiological measures have been evaluated for quantifying cognitive stress for different mental challenges. In this paper, we present a study using the cognitive stress measured by the task evoked pupillary response extracted from the time series eye-tracking measurements to predict task difficulties in a virtual reality based robotic surgery training environment. In particular, we proposed a differential-task-difficulty scale, utilized a comprehensive feature extraction approach, and implemented a multitask learning framework and compared the regression accuracy between the conventional single-task-based and three multitask approaches across subjects.

Keywords: surgical metric, task evoked pupillary response, multitask learning, TSFresh

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Authors: Mari A. Virtanen, Elina Haavisto, Eeva Liikanen, Maria Kääriäinen

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Ubiquitous learning and the use of ubiquitous learning environments herald a new era in higher education. Ubiquitous environments fuse together authentic learning situations and digital learning spaces where students can seamlessly immerse themselves into the learning process. Definitions of ubiquitous learning are wide and vary in the previous literature and learning environments are not systemically described. The aim of this scoping review was to identify the criteria and the use of ubiquitous learning environments in higher education contexts. The objective was to provide a clear scope and a wide view for this research area. The original studies were collected from nine electronic databases. Seven publications in total were defined as eligible and included in the final review. An inductive content analysis was used for the data analysis. The reviewed publications described the use of ubiquitous learning environments (ULE) in higher education. Components, contents and outcomes varied between studies, but there were also many similarities. In these studies, the concept of ubiquitousness was defined as context-awareness, embeddedness, content-personalization, location-based, interactivity and flexibility and these were supported by using smart devices, wireless networks and sensing technologies. Contents varied between studies and were customized to specific uses. Measured outcomes in these studies were focused on multiple aspects as learning effectiveness, cost-effectiveness, satisfaction, and usefulness. This study provides a clear scope for ULE used in higher education. It also raises the need for transparent development and publication processes, and for practical implications of ubiquitous learning environments.

Keywords: higher education, learning environment, scoping review, ubiquitous learning, u-learning

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Authors: A. Meydanlioglu, F. Arikan

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In recent years, thanks to the development of information and communication technologies, the computer and internet have been used widely in higher education. Internet-based education is impacting traditional higher education as online components increasingly become integrated into face-to-face (FTF) courses. The goal of combined internet-based and traditional education is to take full advantage of the benefits of each platform in order to provide an educational opportunity that can promote student learning better than can either platform alone. Research results show that the use of hybrid learning is more effective than online or FTF models in higher education. Due to the potential benefits, an increasing number of institutions are interested in developing hybrid courses, programs, and degrees. Future research should evaluate the effectiveness of hybrid learning. This paper is designed to determine the impact of hybrid learning on higher education.

Keywords: e-learning, higher education, hybrid learning, online education

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Authors: Aleksandra Ristic

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The Coronavirus Disease – 2019 hit Europe in February 2020, and infections took place in four waves. It left consequences and demanded changes for the future. More than half of European countries responded quickly by declaring a state of emergency and introducing various containment measures that have had a major impact on individuals’ lives in recent years. Closing public lives was largely achieved by limited access and/or closing public institutions and services, including the closure of educational institutions. Teaching in classrooms converted to distance learning. In the research, we used a quantitative study to analyze various factors of distance learning that influenced pupils in different segments: teachers’ availability, family support, entire online conference learning, successful distance learning, time for themselves, reliable sources, teachers’ feedback, successful distance learning, online participation classes, motivation and teachers’ communication and theoretical review of the importance of digital skills, e-learning Index, World comparison of e-learning in the past, digital education plans for the field of Europe. We have gathered recommendations and distance learning solutions to improve the learning process by strengthening teachers and creating more tiered strategies for setting and achieving learning goals by the children.

Keywords: availability, digital skills, distance learning, resources

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Authors: Mingxi Xiao

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Children’s experiences in the early years build and shape the brain. The early years learning environment plays a significantly important role in children’s development. A well-constructed environment will facilitate children’s physical and mental well-being. This case study used an early learning centre in Australia called SDN Hurstville as an example, describing the learning environment in the centre, as well as analyzing the functions of the affordances. In addition, this report talks about the sustainability of learning in the centre, and how the environment supports cultural diversity and indigenous learning. The early years for children are significant. Different elements in the early childhood centre should work together to help children develop better. This case study found that the natural environment and the artificial environment are both critical to children; only when they work together can children have better development in physical and mental well-being and have a sense of belonging when playing and learning in the centre.

Keywords: early childhood center, early childhood education, learning environment, Australia

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Authors: Sannikumar Patel, Brian Nolan, Markus Hofmann, Philip Owende, Kunjan Patel

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Sentiment analysis and opinion mining have become emerging topics of research in recent years but most of the work is focused on data in the English language. A comprehensive research and analysis are essential which considers multiple languages, machine translation techniques, and different classifiers. This paper presents, a comparative analysis of different approaches for multilingual sentiment analysis. These approaches are divided into two parts: one using classification of text without language translation and second using the translation of testing data to a target language, such as English, before classification. The presented research and results are useful for understanding whether machine translation should be used for multilingual sentiment analysis or building language specific sentiment classification systems is a better approach. The effects of language translation techniques, features, and accuracy of various classifiers for multilingual sentiment analysis is also discussed in this study.

Keywords: cross-language analysis, machine learning, machine translation, sentiment analysis

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Authors: Nabil Shawkat, Jamil Saquer

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Social media has accelerated our ability to engage with others and eliminated many communication barriers. On the other hand, the widespread use of social media resulted in an increase in online hate speech. This has drastic impacts on vulnerable individuals and societies. Therefore, it is critical to detect hate speech to prevent innocent users and vulnerable communities from becoming victims of hate speech. We investigate the performance of different deep learning and machine learning algorithms on three different datasets. Our results show that the BERT model gives the best performance among all the models by achieving an F1-score of 90.6% on one of the datasets and F1-scores of 89.7% and 88.2% on the other two datasets.

Keywords: hate speech, machine learning, deep learning, abusive words, social media, text classification

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