Search results for: self-regulated learning theory

Authors: Patrizia Poscic, Sanja Candrlic, Danijela Jaksic

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The University of Rijeka, Department of Informatics participated in the Stand4Info project, co-financed by the European Union, with the main idea of an alignment of study programs with occupational and qualifications standards in the field of Informatics. A brief overview of our research methodology, goals and deliverables is shown. Our main research and project objectives were: a) development of occupational standards, qualification standards and study programs based on the Croatian Qualifications Framework (CROQF), b) higher education quality improvement in the field of information and communication sciences, c) increasing the employability of students of information and communication technology (ICT) and science, and d) continuously improving competencies of teachers in accordance with the principles of CROQF. CROQF is a reform instrument in the Republic of Croatia for regulating the system of qualifications at all levels through qualifications standards based on learning outcomes and following the needs of the labor market, individuals and society. The central elements of CROQF are learning outcomes - competences acquired by the individual through the learning process and proved afterward. The place of each acquired qualification is set by the level of the learning outcomes belonging to that qualification. The placement of qualifications at respective levels allows the comparison and linking of different qualifications, as well as linking of Croatian qualifications' levels to the levels of the European Qualifications Framework and the levels of the Qualifications framework of the European Higher Education Area. This research has made 3 proposals of occupational standards for undergraduate study level (System Analyst, Developer, ICT Operations Manager), and 2 for graduate (master) level (System Architect, Business Architect). For each occupational standard employers have provided a list of key tasks and associated competencies necessary to perform them. A set of competencies required for each particular job in the workplace was defined and each set of competencies as described in more details by its individual competencies. Based on sets of competencies from occupational standards, sets of learning outcomes were defined and competencies from the occupational standard were linked with learning outcomes. For each learning outcome, as well as for the set of learning outcomes, it was necessary to specify verification method, material, and human resources. The task of the project was to suggest revision and improvement of the existing study programs. It was necessary to analyze existing programs and determine how they meet and fulfill defined learning outcomes. This way, one could see: a) which learning outcomes from the qualifications standards are covered by existing courses, b) which learning outcomes have yet to be covered, c) are they covered by mandatory or elective courses, and d) are some courses unnecessary or redundant. Overall, the main research results are: a) completed proposals of qualification and occupational standards in the field of ICT, b) revised curricula of undergraduate and master study programs in ICT, c) sustainable partnership and association stakeholders network, d) knowledge network - informing the public and stakeholders (teachers, students, and employers) about the importance of CROQF establishment, and e) teachers educated in innovative methods of teaching.

Keywords: study program, qualification standard, occupational standard, higher education, informatics and computer science

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Authors: Kerry Mackereth

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Kimberle Crenshaw’s theory of intersectionality has become immensely influential in the fields of women’s and gender studies. However, intersectionality’s widespread use among feminist scholars and activists has been accompanied by critiques of its reliance upon subject categorization. These critiques are of particular import when connected to Wendy Brown’s characterization of identity politics as static 'wounded attachments'. Together, these critiques show how the gridlock model proposed by intersectionality’s primary metaphor, the traffic accident at the intersection, is useful for identifying discrimination but not for remembering historical injustices or imagining feminist and anti-racist resistance. Through the lens of New Zealand Maori film, focusing upon Once Were Warriors (1994) and Whale Rider (2002), this article examines how wounded histories need not be passively reproduced by contemporaneously oppressed groups. Instead, the metaphor of the traffic intersection should be complemented by the metaphor of the wound. Against Brown’s characterization of wounded attachments as negative, static identities, Gloria Anzaldua’s account of the borderland between the United States and Mexico as “una herida abierta”, an open wound, offers an alternative reading of the wound. Through Anzaldua’s and Hortense Spillers’ political thought, the wound is reconceptualized as not only a site of suffering but also as a regenerative space. The coexistence of deterioration and regeneration at the site of the wound underpins the narrative arc of both Once Were Warriors and Whale Rider. In both films, the respective child protagonists attempt to reconcile the pain of wounded histories with the imagination of cultural regeneration. The metaphor of the wound thus serves as an alternative theoretical resource for mapping experiences of oppression, one that enriches feminist theory by balancing the remembrance of historical grievance with the forging of hopeful political projects.

Keywords: gender theory, historical grievance, intersectionality, New Zealand film, postcolonialism

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Authors: Wiem Gadri

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This study delves into the intriguing properties of Pisot and Salem numbers within the framework of formal Laurent series over finite fields, a domain where these numbers’ spectral charac-teristics, Λm(β) and lm(β), have yet to be fully explored. Utilizing a methodological approach that combines algebraic number theory with the analysis of power series, we extend the foundational work of Erdos, Joo, and Komornik to this new setting. Our research uncovers bounds for lm(β), revealing how these depend on the degree of the minimal polynomial of β and thus offering a novel characterization of Pisot and Salem formal power series. The findings significantly contribute to our understanding of these numbers, highlighting their distribution and properties in the context of formal power series. This investigation not only bridges number theory with formal power series analysis but also sets the stage for further interdisciplinary research in these areas.

Keywords: Pisot numbers, Salem numbers, formal power series, over a finite field

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Authors: Felix Jr. Garde, Eric Augustus Tingatinga

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Most analysis procedures of reinforced concrete (RC) slabs are based on elastic theory. When subjected to large forces, however, slabs deform beyond elastic range and the study of their behavior and performance require nonlinear analysis. This paper presents a numerical model to simulate nonlinear behavior of RC slabs using rigid body-spring discrete element method. The proposed slab model composed of rigid plate elements and nonlinear springs is based on the yield line theory which assumes that the nonlinear behavior of the RC slab subjected to transverse loads is contained in plastic or yield-lines. In this model, the displacement of the slab is completely described by the rigid elements and the deformation energy is concentrated in the flexural springs uniformly distributed at the potential yield lines. The spring parameters are determined from comparison of transverse displacements and stresses developed in the slab obtained using FEM and the proposed model with assumed homogeneous material. Numerical models of typical RC slabs with varying geometry, reinforcement, support conditions, and loading conditions, show reasonable agreement with available experimental data. The model was also shown to be useful in investigating dynamic behavior of slabs.

Keywords: RC slab, nonlinear behavior, yield line theory, rigid body-spring discrete element method

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Authors: D. Kokt, T. F. Dreyer

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The main objective of the study was to design a mentoring programme aimed at developing the soft skills of mentors. The mentors are all employed by a multinational corporation. The company had a mentoring plan in place that did not yield the required results, especially related to the development of soft skills. This prompted the researchers to conduct an extensive literature review followed by a mixed methods approach to ascertain the best practices in developing the soft skills of mentors. The outcomes of the study led to the development of a structured mentoring programme using 25 modules to be completed by mentors. The design incorporated a blended modular approach using both face-to-face teaching and teaching supported by Information Communication Technology (ICT). Blended learning was ideal as the ICT component helped to minimise instructor-mentor physical contact as part of the health measures during the Covid-19 pandemic. The blended learning approach also allowed instructors and mentors an online or offline mode, so that mentors could have more time for creative and cooperative exercises. A range of delivery methodologies were spread out across the different modules to ensure mentor engagement and accelerate mentor development. This included concept development through in-person instructor-led training sessions, concept development through virtual instructor-led training sessions, simulations, case studies, e-learning, role plays, interactive learning using mentoring toolkits, and experiential learning through application. The mentor development journey included formal modular competency assessments. All modules contained post-competency assessment consisting of 10 questions (comprising of a combination of explanatory questions and multiple-choice questions) to ensure understanding and deal with identified competency gaps. The minimum pass mark for all modular competency assessments was 80%. Mentors were allowed to retake the assessment if they scored less than 80% until they demonstrated understanding at the required level.

Keywords: mentor, mentee, soft skills, mentor development, blended learning, modular approach

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Authors: Ilzira A. Minigalieva

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Assessment of cumulative health risks associated with the widely observed combined exposures to two or more metals and their compounds on the organism in industrial or general environment, as well as respective regulatory and technical risk management decision-making have presumably the theoretical and experimental toxicology of mixtures as their reliable scientific basis. Analysis of relevant literature and our own experience proves, however, that there is no full match between these different practices. Moreover, some of the contradictions between them are of a fundamental nature. This unsatisfactory state of things may be explained not only by unavoidable simplifications characteristic of the methodologies of risk assessment and permissible exposure standards setting but also by the extreme intrinsic complexity of the combined toxicity theory, the most essential issues of which are considered and briefly discussed in this paper.

Keywords: toxic metals, nanoparticles, typology of combined toxicity, mathematical modeling, health risk assessment and management

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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: Manik Sharma, Ganapathy Krishnamurthi

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The cost of some drugs and medical treatments has risen in recent years, that many patients are having to go without. A classification project could make researchers more efficient. One of the more surprising reasons behind the cost is how long it takes to bring new treatments to market. Despite improvements in technology and science, research and development continues to lag. In fact, finding new treatment takes, on average, more than 10 years and costs hundreds of millions of dollars. If successful, we could dramatically improve the industry's ability to model cellular images according to their relevant biology. In turn, greatly decreasing the cost of treatments and ensure these treatments get to patients faster. This work aims at solving a part of this problem by creating a cellular image classification model which can decipher the genetic perturbations in cell (occurring naturally or artificially). Another interesting question addressed is what makes the deep-learning model decide in a particular fashion, which can further help in demystifying the mechanism of action of certain perturbations and paves a way towards the explainability of the deep-learning model.

Keywords: cellular images, genetic perturbations, deep-learning, explainability

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Authors: Naser Zourikalatehsamad, Seyed Abdorreza Payambarpour, Ibrahim Alwashali, Zahra Abdolkarimi

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The paper aims to evaluate the effect of online advertising on consumer purchase behavior in Malaysian organizations. The paper has potential to extend and refine theory. A survey was distributed among Students of UTM university during the winter 2014 and 160 responses were collected. Regression analysis was used to test the hypothesized relationships of the model. Result shows that the predictors (cost saving factor, convenience factor and customized product or services) have positive impact on intention to continue seeking online advertising.

Keywords: consumer purchase, convenience, customized product, cost saving, customization, flow theory, mass communication, online advertising ads, online advertising measurement, online advertising mechanism, online intelligence system, self-confidence, willingness to purchase

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Authors: Jakob Krause

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Past Financial Crisis has shown that contemporary risk management models provide an unjustified sense of security and fail miserably in situations in which they are needed the most. In this paper, we start from the assumption that risk is a notion that changes over time and therefore past data points only have limited explanatory power for the current situation. Our objective is to derive the optimal amount of representative information by optimizing between the two adverse forces of estimator convergence, incentivizing us to use as much data as possible, and the aforementioned non-representativeness doing the opposite. In this endeavor, the cornerstone assumption of having access to identically distributed random variables is weakened and substituted by the assumption that the law of the data generating process changes over time. Hence, in this paper, we give a quantitative theory on how to perform statistical analysis in non-ergodic systems. As an application, we discuss the impact of a paragraph in the last iteration of proposals by the Basel Committee on Banking Regulation. We start from the premise that the severity of assumptions should correspond to the robustness of the system they describe. Hence, in the formal description of physical systems, the level of assumptions can be much higher. It follows that every concept that is carried over from the natural sciences to economics must be checked for its plausibility in the new surroundings. Most of the probability theory has been developed for the analysis of physical systems and is based on the independent and identically distributed (i.i.d.) assumption. In Economics both parts of the i.i.d. assumption are inappropriate. However, only dependence has, so far, been weakened to a sufficient degree. In this paper, an appropriate class of non-stationary processes is used, and their law is tied to a formal object measuring representativeness. Subsequently, that data set is identified that on average minimizes the estimation error stemming from both, insufficient and non-representative, data. Applications are far reaching in a variety of fields. In the paper itself, we apply the results in order to analyze a paragraph in the Basel 3 framework on banking regulation with severe implications on financial stability. Beyond the realm of finance, other potential applications include the reproducibility crisis in the social sciences (but not in the natural sciences) and modeling limited understanding and learning behavior in economics.

Keywords: banking regulation, non-ergodicity, risk management, semimartingale modeling

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Authors: Revoti Prasad Bora, Nikita Katyal, Saurabh Yadav

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Pre-processing plays an important role in various image processing applications. Most of the time due to the similar nature of images, a particular pre-processing or a set of pre-processing steps are sufficient to produce the desired results. However, in the education domain, there is a wide variety of images in various aspects like images with line-based diagrams, chemical formulas, mathematical equations, etc. Hence a single pre-processing or a set of pre-processing steps may not yield good results. Therefore, a Deep Learning based approach for dynamically selecting a relevant pre-processing technique for each image is proposed. The proposed method works as a classifier to detect hidden patterns in the images and predicts the relevant pre-processing technique needed for the image. This approach experimented for an image similarity matching problem but it can be adapted to other use cases too. Experimental results showed significant improvement in average similarity ranking with the proposed method as opposed to static pre-processing techniques.

Keywords: deep-learning, classification, pre-processing, computer vision, image processing, educational data mining

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Authors: Mario Gianni, Manuel A. Ruiz Garcia, Fiora Pirri

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In this work, we present a Bayesian non-parametric approach to model the motion control of ATVs. The motion control model is based on a Dirichlet Process-Gaussian Process (DP-GP) mixture model. The DP-GP mixture model provides a flexible representation of patterns of control manoeuvres along trajectories of different lengths and discretizations. The model also estimates the number of patterns, sufficient for modeling the dynamics of the ATV.

Keywords: Dirichlet processes, gaussian mixture models, learning motion patterns, tracked robots for urban search and rescue

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Authors: Willy Mbenza, Sho Kenjiro

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Increasing efforts are directed towards a better understanding and foreknowledge of extreme precipitation likelihood, given the adverse effects associated with their occurrence. This knowledge plays a crucial role in long-term planning and the formulation of effective emergency response. However, predicting extreme events reliably presents a challenge to conventional empirical/statistics due to the involvement of numerous variables spanning different time and space scales. In the recent time, Machine Learning has emerged as a promising tool for predicting the dynamics of extreme precipitation. ML techniques enables the consideration of both local and regional physical variables that have a strong influence on the likelihood of extreme precipitation. These variables encompasses factors such as air temperature, soil moisture, specific humidity, aerosol concentration, among others. In this study, we develop an ML model that incorporates both local and regional variables while establishing a robust relationship between physical variables and precipitation during the downscaling process. Furthermore, the model provides valuable information on the frequency and duration of a given intensity of precipitation.

Keywords: machine learning (ML), predictions, rainfall events, regional variables

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Authors: Houda Zouar, Hanane Sarnou

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In the 21st, century the concept of learners' autonomy is crucial. The concept of self-regulated learning has come forward as a result of enabling learners to direct their learning with autonomy towards academic goals achievement. Academic self-regulation is defined as the process by which learners systematically plan, monitor and asses their learning to achieve their academic established goals. In the field of English as a foreign language, teachers emphasise the role of learners’ autonomy to foster the process of English language learning. Consequently, academic self-regulation is considered as a vehicle to enhance autonomy among English language learners. However, not all learners can be equally self-regulators if not well assisted, mainly those novice pupils of basic education. For this matter, understanding the role of teachers in fostering academic self- regulation must be among the preliminary objectives in searching and developing this area. The present research work targets the role of the Algerian middle school teachers in enhancing academic self-regulation and teaching pupils how to learn, besides their role as models in the trajectory of teaching their pupils to become self-regulators. Despite the considerable endeavours in the field of educational setting on Self-Regulated Learning, the literature of the Algerian context indicates confined endeavours to undertake and divulge this notion. To go deeper into this study, a mixed method approach was employed to confirm our hypothesis. For data collection, teachers were observed and addressed by a questionnaire on their role in enhancing academic self- regulation among their pupils. The result of the research indicates that the attempts of middle school Algerian teachers are implicit and limited. This study emphasises the need to prepare English language teachers with the necessary skills to promote autonomous and self-regulator English learners.

Keywords: Algeria, English as a foreign language, middle school, self-regulation, Teachers' role

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Authors: Shaheeb Abdul Azeez, Siong-Choy Chong

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Background: Talent retention is increasingly becoming a major challenge for many industries due to the high turnover rate. Public higher learning institutions in the Maldives have a similar situation with the turnover of their employees'. This paper is to identify whether Human Resource Management (HRM) practices have any impact on employee retention in public higher learning institutions in the Maldives. Purpose: This paper aims to identify the influence of HRM practices on employee retention in public higher learning institutions in the Maldives. A total of 15 variables used in this study; 11 HRM practices as independent variables (leadership, rewards, salary, employee participation, compensation, training and development, career development, recognition, appraisal system and supervisor support); job satisfaction and motivation as mediating variables; demographic profile as moderating variable and employee retention as dependent variable. Design/Methodology/Approach: A structured self-administered questionnaire was used for data collection. A total of 300 respondents were selected as the study sample, representing the academic and administrative from public higher learning institutions using a stratified random sampling method. AMOS was used to test the hypotheses constructed. Findings: The results suggest that there is no direct effect between the independent variable and dependent variable. Also, the study concludes that no moderate effects of demographic profile between independent and dependent variables. However, the mediating effects of job satisfaction and motivation in the relationship between HRM practices and employee retention were significant. Salary had a significant influence on job satisfaction, whilst both compensation and recognition have significant influence on motivation. Job satisfaction and motivation were also found to significantly influence employee retention. Research Limitations: The study consists of many variables more time consuming for the respondents to answer the questionnaire. The study is focussed only on public higher learning institutions in the Maldives due to no participation from the private sector higher learning institutions. Therefore, the researcher is unable to identify the actual situation of the higher learning industry in the Maldives. Originality/Value: To our best knowledge, no study has been conducted using the same framework throughout the world. This study is the initial study conducted in the Maldives in this study area and can be used as a baseline for future researches. But there are few types of research conducted on the same subject throughout the world. Some of them concluded with positive findings while others with negative findings. Also, they have used 4 to 7 HRM practices as their study framework.

Keywords: human resource management practices, employee retention, motivation, job satisfaction

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Authors: Mary Deyo, Zmara Harrison

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This study reports the outcomes of an 8-week experiential learning program for 6 adults with Intellectual and Developmental Disabilities (IDD) at a day habilitation program. The intervention foci for this program include executive function, language learning in the domains of expressive, receptive, and pragmatic language, and quality of life. The interprofessional collaboration aimed at supporting adults with IDD to reach person-centered, functional goals across skill domains is critical. This study is a significant addition to the speech-language pathology literature in that it examines a therapy method that potentially meets this need while targeting domains within the speech-language pathology scope of practice. Communication therapy was provided during highly valued and meaningful hands-on learning experiences, referred to as the Garden Club, which incorporated all aspects of planting and caring for a garden as well as related journaling, sensory, cooking, art, and technology-based activities. Direct care staff and an undergraduate research assistant were trained by SLP to be impactful language guides during their interactions with participants in the Garden Club. SLP also provided direct therapy and modeling during Garden Club. Research methods used in this study included a mixed methods analysis of a literature review, a quasi-experimental implementation of communication therapy in the context of experiential learning activities, Quality of Life participant surveys, quantitative pre- post- data collection and linear mixed model analysis, qualitative data collection with qualitative content analysis and coding for themes. Outcomes indicated overall positive changes in expressive vocabulary, following multi-step directions, sequencing, problem-solving, planning, skills for building and maintaining meaningful social relationships, and participant perception of the Garden Project’s impact on their own quality of life. Implementation of this project also highlighted supports and barriers that must be taken into consideration when planning similar projects. Overall findings support the use of experiential learning projects in day habilitation programs for adults with IDD, as well as additional research to deepen understanding of best practices, supports, and barriers for implementation of experiential learning with this population. This research provides an important contribution to research in the fields of speech-language pathology and other professions serving adults with IDD by describing an interprofessional experiential learning program with positive outcomes for executive function, language learning, and quality of life.

Keywords: experiential learning, adults, intellectual and developmental disabilities, expressive language, receptive language, pragmatic language, executive function, communication therapy, day habilitation, interprofessionalism, quality of life

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Authors: Meera Rajeev Kumar

Abstract:

An overall social, emotional, and cultural development in a child is what a parent expects. There is no point in comparing the generations of 70’s or 80’s with that of the children of today as the trends are changing drastically. Technology has enabled them to become smart as well as over smart in one way or the other. Children today are quite ignorant of today’s values or ethics and are imbibing different cultures around them and ultimately confused on what to follow. The researcher has gained experience in transmitting or imparting the traditional culture through performing arts. It is understood that the children undergo a transformation from what they knew to what the truth is, through learning and experience. Through performing arts, the child develops an emotional, quick learning, abundant creativity, and ultimately self-realisation on what is right and wrong. The child also gains good organising skills, good decision making skills, therefore summing up to a holistic development. The sample study is 50, and a random sampling technique is adopted to differentiate between a normal child and a child learning an art. The study is conducted in Tamil Nadu, in India.

Keywords: creativity, cultural, emotional, empower

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Authors: Chandrakala Varatharajoo, Adelina Binti Asmawi, Nabeel Abdallah Mohammad Abedalaziz

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This study investigated the impact of inflectional and derivational morphemic analysis awareness on ESL secondary school students’ vocabulary learning strategy. The quasi-experimental study was conducted with 106 low proficiency secondary school students in two experimental groups (inflectional and derivational) and one control group. The students’ vocabulary acquisition was assessed through two measures: Morphemic Analysis Test and Vocabulary- Morphemic Test in the pretest and posttest before and after an intervention programme. Results of ANCOVA revealed that both the experimental groups achieved a significant score in Morphemic Analysis Test and Vocabulary-Morphemic Test. However, the inflectional group obtained a fairly higher score than the derivational group. Thus, the results indicated that ESL low proficiency secondary school students performed better on inflectional morphemic awareness as compared to derivatives. The results also showed that the awareness of inflectional morphology contributed more on the vocabulary acquisition. Importantly, learning inflectional morphology can help ESL low proficiency secondary school students to develop both morphemic awareness and vocabulary gain. Theoretically, these findings show that not all morphemes are equally useful to students for their language development. Practically, these findings indicate that morphological instruction should at least be included in remediation and instructional efforts with struggling learners across all grade levels, allowing them to focus on meaning within the word before they attempt the text in large for better comprehension. Also, by methodologically, by conducting individualized intervention and assessment this study provided fresh empirical evidence to support the existing literature on morphemic analysis awareness and vocabulary learning strategy. Thus, a major pedagogical implication of the study is that morphemic analysis awareness strategy is a definite boon for ESL secondary school students in learning English vocabulary.

Keywords: ESL, instruction, morphemic analysis, vocabulary

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Authors: Elisabeth Desiana Mayasari, Laurensia Aptik Evanjeli, Brigitta Erlita Tri Anggadewi

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The condition of the COVID-19 pandemic demands adaptation in various aspects of human life, including in the field of education. Teachers are expected to do distance learning or Learning From Home (LFH). The teacher said that he experienced stress, anxiety, feeling depressed, and afraid based on the interview. Learning adaptations and pandemic situations can impact the mental health of teachers, so the purpose of this study is to determine the mental health of teachers while teaching online. This research was conducted with a quantitative approach using a survey method. The subjects in this study were 330 elementary school teachers under the auspices of a foundation in Yogyakarta. Teachers' mental health was measured using the Indonesian version of The Mental Health Inventory (MHI-38), which has a reliability of 0.888. The results showed that the teachers generally had a good mental health condition marked by a lower negative aspect score than the positive aspect. In addition, the overall mental health aspect shows that some teachers have better mental health when compared to the average score, as well as higher positive aspect scores in all sub-aspects.

Keywords: mental health, teacher, COVID-19 pandemic, MHI-38

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Authors: Asifa Amara, Prachi Singh, Kanishka, Debargho Pathak, Akshat Kumar, Jayakumar Eravelly

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Today's generation is totally dependent on technology that uses data as its fuel. The present study is all about innovations and developments in data science and gives an idea about how efficiently to use the data provided. This study will help to understand the core concepts of data science. The concept of artificial intelligence was introduced by Alan Turing in which the main principle was to create an artificial system that can run independently of human-given programs and can function with the help of analyzing data to understand the requirements of the users. Data science comprises business understanding, analyzing data, ethical concerns, understanding programming languages, various fields and sources of data, skills, etc. The usage of data science has evolved over the years. In this review article, we have covered a part of data science, i.e., machine learning. Machine learning uses data science for its work. Machines learn through their experience, which helps them to do any work more efficiently. This article includes a comparative study image between human understanding and machine understanding, advantages, applications, and real-time examples of machine learning. Data science is an important game changer in the life of human beings. Since the advent of data science, we have found its benefits and how it leads to a better understanding of people, and how it cherishes individual needs. It has improved business strategies, services provided by them, forecasting, the ability to attend sustainable developments, etc. This study also focuses on a better understanding of data science which will help us to create a better world.

Keywords: data science, machine learning, data analytics, artificial intelligence

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Authors: Manik Konch

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Actions are generally evaluated from moral point of view. Either the action is praised or condemned, but in all cases it involves the agent who performs it. The agent is held morally responsible for bringing out an action. This paper is an attempt to explore the Aristotle’s notion of action and its relation with moral development in response to modern philosophical moral psychology. Particularly, the distinction between voluntary, involuntary, and non-voluntary action in the Nicomachean Ethics with some basic problems from the perspective of moral psychology: the role of choice, moral responsibility, desire, and akrasia for an action. How to do a morally right action? Is there any role of virtue, character to do a moral action? These problems are analyzed and interpreted in order to show that the Aristotelian theory of action significantly contributes to the philosophical study of moral psychology. In this connection, the paper juxtaposes Aristotle’s theory of action with response from David Charles, John R. Searle’s, and Alfred Mele theorization of action in the mechanism of human moral behaviours. To achieve this addressed problem, we consider, how the recent moral philosophical moral psychology research can shed light on Aristotle's ethics by focusing on theory of action. In this connection, we argue that the desire is the only responsible for the akratic action. According to Aristotle, desire is primary source of action and it is the starting point of action and also the endpoint of an action. Therefore we are trying to see how desire can make a person incontinent and motivate to do such irrational actions. Is there any causes which we can say such actions are right or wrong? To measure an action we have need to see the consequences such act. Thus, we discuss the relationship between akrasia and action from the perspective of contemporary moral psychologists and philosophers whose are currently working on it.

Keywords: action, desire, moral psychology, Aristotle

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Authors: C. Manjula, Lilly Florence

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Software technology is developing rapidly which leads to the growth of various industries. Now-a-days, software-based applications have been adopted widely for business purposes. For any software industry, development of reliable software is becoming a challenging task because a faulty software module may be harmful for the growth of industry and business. Hence there is a need to develop techniques which can be used for early prediction of software defects. Due to complexities in manual prediction, automated software defect prediction techniques have been introduced. These techniques are based on the pattern learning from the previous software versions and finding the defects in the current version. These techniques have attracted researchers due to their significant impact on industrial growth by identifying the bugs in software. Based on this, several researches have been carried out but achieving desirable defect prediction performance is still a challenging task. To address this issue, here we present a machine learning based hybrid technique for software defect prediction. First of all, Genetic Algorithm (GA) is presented where an improved fitness function is used for better optimization of features in data sets. Later, these features are processed through Decision Tree (DT) classification model. Finally, an experimental study is presented where results from the proposed GA-DT based hybrid approach is compared with those from the DT classification technique. The results show that the proposed hybrid approach achieves better classification accuracy.

Keywords: decision tree, genetic algorithm, machine learning, software defect prediction

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Authors: Daniela Velichová

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Plenty of ideas on how to adopt active learning methods in education are available nowadays. Mathematics is a subject where the active involvement of students is required in particular in order to achieve desirable results regarding sustainable knowledge and deep understanding. The present article is based on the outcomes of an Erasmus+ project DrIVE-MATH, that was aimed at developing a novel and integrated framework to teach maths classes in engineering courses at the university level. It is fundamental for students from the early years of their academic life to have agile minds. They must be prepared to adapt to their future working environments, where enterprises’ views are always evolving, where all collaborate in teams, and relations between peers are thought for the well-being of the whole - workers and company profit. This reality imposes new requirements on higher education in terms of adaptation of different pedagogical methods, such as project-based and active-learning methods used within the course curricula. Active learning methodologies are regarded as an effective way to prepare students to meet the challenges posed by enterprises and to help them in building critical thinking, analytic reasoning, and insight to the solved complex problems from different perspectives. Fostering learning-by-doing activities in the pedagogical process can help students to achieve learning independence, as they could acquire deeper conceptual understanding by experimenting with the abstract concept in a more interesting, useful, and meaningful way. Clear information about learning outcomes and goals might help students to take more responsibility for their learning results. Active learning methods implemented by the project team members in their teaching practice, eduScrum and Jigsaw in particular, proved to provide better scientific and soft skills support to students than classical teaching methods. EduScrum method enables teachers to generate a working environment that stimulates students' working habits and self-initiative as they become aware of their responsibilities within the team, their own acquired knowledge, and their abilities to solve problems independently, though in collaboration with other team members. This method enhances collaborative learning, as students are working in teams towards a common goal - knowledge acquisition, while they are interacting with each other and evaluated individually. Teams consisting of 4-5 students work together on a list of problems - sprint; each member is responsible for solving one of them, while the group leader – a master, is responsible for the whole team. A similar principle is behind the Jigsaw technique, where the classroom activity makes students dependent on each other to succeed. Students are divided into groups, and assignments are split into pieces, which need to be assembled by the whole group to complete the (Jigsaw) puzzle. In this paper, analysis of students’ perceptions concerning the achievement of deeper conceptual understanding in mathematics and the development of soft skills, such as self-motivation, critical thinking, flexibility, leadership, responsibility, teamwork, negotiation, and conflict management, is presented. Some new challenges are discussed as brought by introducing active learning methods in the basic mathematics courses. A few examples of sprints developed and used in teaching basic maths courses at technical universities are presented in addition.

Keywords: active learning methods, collaborative learning, conceptual understanding, eduScrum, Jigsaw, soft skills

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Authors: Khalid Yousuf Ahmed

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At the beginning of growth period, East Asian countries achieved impressive economic growth for the decades. They transformed from agricultural economy toward industrialization and contributed to dynamic structural transformation. The achievements were driven by government-led development policies that implemented effective innovation policy to boost technological capability of local firms. Recently, most Sub-Saharan African have been showing sustainable growth. Exceptionally, Ethiopia has been recording double-digit growth for a decade. Hence, Ethiopia has claimed to follow the footstep of East Asia development model. The study is going to examine whether Ethiopia can replicate innovation and economic growth model of East Asia by using Japan, Taiwan, South Korea and China as a case to illustrate their model of growth. This research will be based on empirical data gathering and extended theory of national innovation system and economic growth theory. Moreover, the methodology is based on Knowledge Assessment Methodology (KAM) and also employing cross-countries regression analysis. The results explained that there is a significant relationship between innovation indicators and economic growth in East Asian countries while the relationship is non-existing for Ethiopia except implementing similar policies and achieving similar growth trend. Therefore, Ethiopia needs to introduce inclusive policies that give priority to improving human capital and invest on the knowledge-based economy to replicate East Asian Model.

Keywords: economic growth, FDI, endogenous growth theory, East Asia model

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Authors: Lorena Blasco-Arcas, Francesca Pucciarelli

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Business contexts have become globalised and digitalised, which requires that managers develop a strong sense of cross-cultural intelligence while working in geographically distant teams by means of digital technologies. How to better equip future managers on these kinds of skills has been put forward as a critical issue in Business Schools. In pursuing these goals, higher education is shifting from a passive lecture approach, to more active and experiential learning approaches that are more suitable to learn skills. For example, through the use of case studies, proposing plausible business problem to be solved by students (or teams of students), these institutions have focused for long in fostering learning by doing. Though, case studies are no longer enough as a tool to promote active teamwork and experiential learning. Moreover, digital advancements applied to educational settings have enabled augmented classrooms, expanding the learning experience beyond the class, which increase students’ engagement and experiential learning. Different authors have highlighted the benefits of digital engagement in order to achieve a deeper and longer-lasting learning and comprehension of core marketing concepts. Clickers, computer-based simulations and business games have become fairly popular between instructors, but still are limited by the fact that are fictional experiences. Further exploration of real digital platforms to implement real, live projects in the classroom seem relevant for marketing and business education. Building on this, this paper describes the development of an experiential learning activity in class, in which students developed a communication campaign in teams using the BuzzFeed platform, and subsequently implementing the campaign by using other social media platforms (e.g. Facebook, Instagram, Twitter…). The article details the procedure of using the project for a marketing module in a Bachelor program with students located in France, Italy and Spain campuses working on multi-campus groups. Further, this paper describes the project outcomes in terms of students’ engagement and analytics (i.e. visits achieved). the project included a survey in order to analyze and identify main aspects related to how the learning experience is influenced by the cultural competence developed through working in geographically distant and culturally diverse teamwork. Finally, some recommendations to use project-based social media tools while working with virtual teamwork in the classroom are provided.

Keywords: cultural competences, experiential learning, social media, teamwork, virtual group work

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Authors: Shabnam Dadparvar, Laijin Shen

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After a period of conflict between Russia and the West, new signs of confrontation between the United States and China are observed. China, as the most populous country in the world with a high rate of economic growth, neither stands the hegemonic power of the United States nor has the intention of direct confrontation with it. By raising the costs of the United States’ leadership at the international level, China seeks to find a better status without direct confrontation with the US. Meanwhile, the Shanghai Cooperation Organization (SCO), as a soft balancing strategy against the hegemony of the United States is used as a tool to reach this goal. The authors by using a descriptive-analytical method try to explain the policies of China and the United States on Shanghai Cooperation Organization as well as confrontation between these two countries within the framework of 'balance of soft power theory'.

Keywords: balance of soft power, Central Asia, Shanghai cooperation organization, terrorism

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Authors: Yingqi Cui, Changran Huang, Raymond Lee

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In this paper, we proposed an AI Tutor using ontology and natural language process techniques to generate a computer science domain knowledge graph and answer users’ questions based on the knowledge graph. We define eight types of relation to extract relationships between entities according to the computer science domain text. The AI tutor is separated into two agents: learning agent and Question-Answer (QA) agent and developed on JADE (a multi-agent system) platform. The learning agent is responsible for reading text to extract information and generate a corresponding knowledge graph by defined patterns. The QA agent can understand the users’ questions and answer humans’ questions based on the knowledge graph generated by the learning agent.

Keywords: artificial intelligence, natural Language processing, knowledge graph, intelligent agents, QA system

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Authors: S. Nickolas, Shobha K.

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The treatment of incomplete data is an important step in the data pre-processing. Missing values creates a noisy environment in all applications and it is an unavoidable problem in big data management and analysis. Numerous techniques likes discarding rows with missing values, mean imputation, expectation maximization, neural networks with evolutionary algorithms or optimized techniques and hot deck imputation have been introduced by researchers for handling missing data. Among these, imputation techniques plays a positive role in filling missing values when it is necessary to use all records in the data and not to discard records with missing values. In this paper we propose a novel artificial neural network based clustering algorithm, Adaptive Resonance Theory-2(ART2) for imputation of missing values in mixed attribute data sets. The process of ART2 can recognize learned models fast and be adapted to new objects rapidly. It carries out model-based clustering by using competitive learning and self-steady mechanism in dynamic environment without supervision. The proposed approach not only imputes the missing values but also provides information about handling the outliers.

Keywords: ART2, data imputation, clustering, missing data, neural network, pre-processing

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Authors: Frantisek Mosna

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E-learning has become an efficient and widespread means in process of education at all branches of human activities. Statistics is not an exception. Unfortunately the main focus in the statistics teaching is usually paid to the substitution to formulas. Suitable web-sites can simplify and automate calculation and provide more attention and time to the basic principles of statistics, mathematization of real-life situations and following interpretation of results. We introduce our own web-sites for hypothesis testing. Their didactic aspects, technical possibilities of individual tools for their creating, experience and advantages or disadvantages of them are discussed in this paper. These web-sites do not substitute common statistical software but significantly improve the teaching of the statistics at universities.

Keywords: e-learning, hypothesis testing, PHP, web-sites

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Authors: Shri Krishna Mishra, Badri Yadav

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Effect of collaborative learning on development of process skills and attitude towards science is It rightly said that the destiny of the nation is shaped inside its classroom. Classroom is a place where the pupil and teacher interact purposefully to gain knowledge. Teaching is the principal mode of education. It can be called a transaction between teacher and pupil, in which one transmits knowledge to other. The teaching learning process consists of three important components, the pupils, the teacher and the curriculum; the classroom is the collection of students of their own individual abilities and needs. In the present classroom teaching learners are either persuasive recipient or passive observant. The school environment leading to low-achievement we have to try better to develop in the young mind. Children are the sticks of dynamite, bundles of energy and potential power waiting to be ignited. Guide them carefully to a place where their potentialities and strength will be used to build a better world. Man’s future depends to large extent on scientific advances and development of productive activity. Science is considered as an important subject in school curricular. The education commission (1964-66) has suggested that science education is necessary for all children at school stage. It is essential to develop children’s logical and critical thinking. But these days thinking process and academic achievement of students have been suppressed by competitive environment of our schools. How the students perceive each other and interact with one another is a neglected aspect of instruction. In the constructivist perspective learning in a process of construction of knowledge. Learners actively construct their own knowledge by connecting new ideas to existing ideas on the basis of materials/ activities presented to them (experience).

Keywords: effect of collaborative learning, development of process skills, science education, attitude towards science

Procedia PDF Downloads 267