Education planning

Els ultims avencos en l’estudi del genoma huma estan afectant diverses arees de les ciencies relacionades amb l’esport. En els ultims anys s’ha observat que el nombre d’articles apareguts en les revistes cientifiques relacionats amb la genetica i l’esport ha experimentat un increment exponencial, aquest fet fa palesa una inquietud creixent en el mon cientific pel coneixement i les possibilitats de la genetica aplicada a diferents arees de l’esport. Paral·lelament als estudis tecnics van apareixent veus que alerten dels possibles problemes etics que poden sorgir de l’aplicacio de modificacions genetiques a l’esport. Organismes com el Comite Olimpic Internacional, la World Anti-Doping Agency, el United States President’s Council on Bioethics i l’Australian Law Reforms Comissio han estat revisant els ultims desenvolupaments en investigacio genetica i s’han plantejat diferents arguments sobre la seva aplicacio legal a l’esport. Normalment, les noticies que apareixen a la premsa no espec...

En aquest article exposem com han evolucionat les tendencies i sortides professionals dels professionals de l’Educacio Fisica a partir dels estudis dels diferents autors que han intentat d’aportar una visio sobre la questio. Des del primer estudi de Mestre (1975), fins a l’actualitat, han sorgit diferents investigacions en aquest camp, que han analitzat el perfil professional en base a les demandes laborals, tot finalitzant en les aportacions de l’European Network of Sport Sciences Institutes (1999). A manera de conclusio i despres de l’exposicio efectuada, s’han elaborat unes directrius sobre les linies futures que regiran el camp laboral en la nostra professio; en destaquem la inexistencia de regulacio professional i la transcendencia que ha adquirit en els nostres dies la practica de l’esport, cosa que aconsella i justifica plenament la necessitat d’una regulacio completa i sistematica, amb el rang normatiu exigit per l’article 36 de la norma constitucional.

Seminario de Segovia" como encuentro "clave" en. el planteamiento de una estrategia de cambio. En un tercer apartado damos a conocer el origen y objeto de nuestro trabajo y declaramos los supuestos y limitaciones con las que hemos contado. Como final de esta primera parte hacemos una revisión bibliográfica relacionada con las funciones del Profesor de E.G.B. La segunda parte se centra en la encuesta realizada a nuestros alumnos y a los profesores de E.G.B. de la provincia de Badajoz. Esta segunda parte va a constituir el "cuerpo" del resumen que a continuación presentamos. La Sección de referencias se forma completa del documento original, por lo cual puede observarse que la primera referencia del resumen es la que figura con el número 25. Las 24 anteriores corresponden a las partes del original que no figuran en el .. presente resumen. Se inserta, no_ obstante, para que el lector tenga conocimiento de las fuentes utilizadas y pueda consultarlas, a su vez, si lo estima oportuno. En el documento original también figuran cuatro anexos: Anexo l. Conclusión del Seminario de Segovia (6 al 9 de febrero de 1980).

La importància d'establir indicadors de control sobre els PEC fa que l'apartat d'avaluació es consideri un eix articulador del mateix, i esdevingui el motor, any rere any, del desenvolupament dels objectius a assolir-se per parts dels agents implicats. D'altra banda, al 2018, el Consell General de Col•legis Professionals de l'Educació Física i l'Esport (COLEF) proposà, des del seu comitè d'experts en EF, l'obligatorietat del "Proyecto deportivo de fomento de la actividad física y hábitos saludables" en els centres escolars. Aquest projecte va ser premiat per l'Administració, gràcies al lliurament del distintiu de qualitat del "Segell de Vida Saludable". Aquest fet recalca la importància que l'administració dóna al PEC. Com a conclusió al apartat, s'ha de tenir en compte que en els últims vint anys, ha partir de publicacions comentades en aquest apartat, el PEC s'ha convertit en l'eina que garanteix la qualitat organitzativa i d'implementació de les AFE de les escoles i organitzacions esportives. Alhora, esdevé el punt de trobada per la coordinació entre els projectes educatiu i curricular d'EF i les AFE fora de l'horari. Per un correcte desenvolupament del PEC, la seva implantació ha de ser duta a terme per persones amb la formació requerida. D'altra banda, i com es pot veure reflectit a la Taula 3 (p.72), l'impacte que els PEC han aconseguit sobre l'AFE, realitzades en centres escolars i entitats dedicades a l'AFE, ha estat molt important i la seva extensió en tot el territori nacional és massiva. Aquesta taula ha estat elaborada, organitzant una cerca estructurada a partir de CCAA o Ciutats Autònomes, on s'ha realitzat una consulta en webs de disposició pública. En algunes d'aquestes, no ha estat possible trobar cap PEC disponible en xarxa, el que no significa que no existeixin, simplement que no han estat publicats. És possible que no comptin amb un PEC com a tal, però en consulta a especialistes en EF, aquests han informat de la seva existència i ús habitual.

Data mining extracts the information from an enormous data provisions, often recognised as knowledge discovery in databases. It is procedure of semi-automatically examining huge amount of databases to discover valuable patterns. Knowledge management is a multifaceted approach that assists in attaining executive objectives by building the pre-eminent use of knowledge. This paper has threefold objective. Initially, it explains data mining process and numerous data mining techniques that help in the removal of concealed patterns. Furthermore, it elaborates the numerous tendencies and fields amended data mining technology for easy access and reclamation of valuable information. Data mining application area comprises marketing, telecommunication deception, funding, medicinal education area and so on. At last, emphases on educational data mining that is related with emerging techniques to explore the distinguished data gained from educational settings and consequences in dropping the intricacy of numerous data mining tools used by educationalists is given.

The study analyzed the Curriculum Reforms in Namibia’s progress, derailments, and possible solutions for a competitive future. Educational reform and curriculum revision are crucial to redressing apartheid colonialism’s inequitable and fragmented education system in Namibia and building a responsive curriculum that prepares students for a better future. While noticeable progress is observed regarding access to education, policy development, and curriculum reform, many challenges remain. Thus, this study aimed to review literature from Postcolonial Namibia to determine the causes of Namibia’s basic education responsiveness and transformation before and after independence. The paper argues that implementing a responsive curriculum is critical for many reasons. This study employed a qualitative approach encased in a phenomenological interpretive framework with the literary analysis of Namibia’s curriculum reform. Additionally, the paper was couched by Moll’s Curriculum Responsiveness T...

Educational data mining (EDM) is an emerging interdisciplinary research area which 1 deals with the development of methods for the exploration of data which have origi-2 nated in an educational context (Baker and Yacef 2009). EDM uses statistical, machine 3 learning and data mining (DM) approaches to analyse educational data in order to 4 study educational issues. On the one hand, DM has many applications, and many tasks 5 in educational environments have been resolved through DM (Romero and Ventura 6 2010), such as the analysis and visualisation of data, providing feedback in order 7 to support instructors, providing recommendations for students, student modelling, 8 detecting undesirable student behaviours, predicting student performance, grouping 9 students, social networks analysis, developing concept maps, constructing course-10 ware, planning and scheduling, etc. In particular, this special issue of User Modelling 11 and User-Adapted Interaction explores recent developments and applications of data 12 mining techniques in various aspects of user modelling and the personalisation, rec-13 ommendation and adaptation of educational systems. On the other hand, there are 14 different types of educational systems, such as traditional classrooms, test/quiz sys-15 tems, e-learning systems, learning management systems (LMS), adaptive educational 16 hypermedia systems (AEHS), intelligent tutoring systems (ITS), etc.

The study analyzed the Curriculum Reforms in Namibia’s progress, derailments, and possible solutions for a competitive future. Educational reform and curriculum revision are crucial to redressing apartheid colonialism’s inequitable and fragmented education system in Namibia and building a responsive curriculum that prepares students for a better future. While noticeable progress is observed regarding access to education, policy development, and curriculum reform, many challenges remain. Thus, this study aimed to review literature from Postcolonial Namibia to determine the causes of Namibia’s basic education responsiveness and transformation before and after independence. The paper argues that implementing a responsive curriculum is critical for many reasons. This study employed a qualitative approach encased in a phenomenological interpretive framework with the literary analysis of Namibia’s curriculum reform. Additionally, the paper was couched by Moll’s Curriculum Responsiveness T...

Educational data mining (EDM) is an emerging interdisciplinary research area which 1 deals with the development of methods for the exploration of data which have origi-2 nated in an educational context (Baker and Yacef 2009). EDM uses statistical, machine 3 learning and data mining (DM) approaches to analyse educational data in order to 4 study educational issues. On the one hand, DM has many applications, and many tasks 5 in educational environments have been resolved through DM (Romero and Ventura 6 2010), such as the analysis and visualisation of data, providing feedback in order 7 to support instructors, providing recommendations for students, student modelling, 8 detecting undesirable student behaviours, predicting student performance, grouping 9 students, social networks analysis, developing concept maps, constructing course-10 ware, planning and scheduling, etc. In particular, this special issue of User Modelling 11 and User-Adapted Interaction explores recent developments and applications of data 12 mining techniques in various aspects of user modelling and the personalisation, rec-13 ommendation and adaptation of educational systems. On the other hand, there are 14 different types of educational systems, such as traditional classrooms, test/quiz sys-15 tems, e-learning systems, learning management systems (LMS), adaptive educational 16 hypermedia systems (AEHS), intelligent tutoring systems (ITS), etc.

In the era of big data, where the amount of information is growing exponentially, the importance of data mining has never been greater. Educational institutions today collect and store vast amounts of data, such as student enrollment and attendance records, and their exam results. With the need to sift through enormous amounts of data and present it in a way that anyone can understand, educational institutions are at the forefront of this trend, and this calls for a more sophisticated set of algorithms. Data mining in education was born as a response to this problem. Traditional data mining methods cannot be directly applied to educational problems because of the special purpose and function they serve. Defining at-risk students, identifying priority learning requirements for varied groups of students, increasing graduation rates, monitoring institutional performance efficiently, managing campus resources, and optimizing curriculum renewal are just a few of the applications of educational data mining. This paper reviews methodologies used as knowledge extractors to tackle specific education challenges from large data sets of higher education institutions to the benefit of all educational stakeholders.

The intent of this project to create a presentation and facilitation guide to support School Districts with the amalgamation of early care and learning and education into the same Governmental Ministry. The early care and learning system and the kindergarten-grade 12 (K-12) systems currently sit in two separate government ministries. The project articulates both the parallel systems of the early care and learning and the K-12 systems and preparation of the amalgamation of the two systems. This project examines the historical differences between the two systems, the rights to access early care and learning and different types of governance models. This project will include a PowerPoint presentation and facilitation guide and can be used, as a template, for School Districts in British Columbia to start the initial discussion of this amalgamation with key stakeholders.

This article presents an economic decision model for planning in public education, considering the satisfaction of the total demand for education in a municipality and the annual cost involved in the system. Given a set of established schools in a municipality and possible new locations, the aim of the model is to find the optimal supply in terms of which schools should be kept open or closed, which grades (or year levels) should be made available and the number of classes that should be provided within each such grade to meet student demand. The model includes specific information about curriculum requirements in terms of the number of hours per year per subject to be provided for each grade level. The objective function essentially seeks to minimize the total fixed and variable costs to schools, which mainly relate to human resources (principal and direction, teaching, administrative, and support staff). We propose an integer optimization model for solving this problem and we appl...

Developing countries face many obstacles in the process of implementing inclusive education (IE). Effective use of assistive technologies (AT) can help governments in developing countries achieve inclusive education by helping children with disabilities in schools. Despite the importance and positive impact of AT, prior research on the use of AT in inclusive education especially in developing countries is limited. To fill the research gap in this area, this paper investigates the research question of, How can AT be effectively used for IE in developing countries? To address this question, we conducted an in-depth case study of two developing countries, Bangladesh and Tanzania, and thoroughly reviewed existing IE projects around the world and other relevant literature. Three experts in the field and 18 informants of the two selected countries were interviewed in person, by phone or by email. The analysis of findings from interviews and literature review shows that obstacles to effective use of AT for IE come from three different levels-school, national, and network. Because AT is only part of the equation for a country to achieve IE, a high level national perspective is required and other related factors also need to be considered. We recommend governments in developing countries adopt a systematic approach in tackling obstacles at each level and pay attention to five management challenges: establishment and maintenance of professional networks: identification and maintenance of knowledge and expertise; funding management; coordination among ministries, and implementation, maintenance, and monitoring of a national program. Overall, governments are suggested to adopt a "network" approach that includes a constructive view of development drawing on incentives-based cooperation from all stakeholders. The results of this research shed light on the status quo of the use of AT for inclusive education in developing countries and provide useful guidance to parties who are interested in using assistive technologies to achieve inclusive education.

This article presents an economic decision model for planning in public education, considering the satisfaction of the total demand for education in a municipality and the annual cost involved in the system. Given a set of established schools in a municipality and possible new locations, the aim of the model is to find the optimal supply in terms of which schools should be kept open or closed, which grades (or year levels) should be made available and the number of classes that should be provided within each such grade to meet student demand. The model includes specific information about curriculum requirements in terms of the number of hours per year per subject to be provided for each grade level. The objective function essentially seeks to minimize the total fixed and variable costs to schools, which mainly relate to human resources (principal and direction, teaching, administrative, and support staff). We propose an integer optimization model for solving this problem and we appl...

It is seen that the importance and need for Arabic have been increasing in Turkey in recent years, and the variety and number of programs for the Arabic language in higher education institutions are also increasing. It is noteworthy that the Arabic Language and Literature and Arabic Language Teaching departments, which have a long history, and the Arabic Translation and Interpretation departments, have been increasing in the state and private universities in recent years. In this study, the undergraduate programs of the Arabic translation and interpretation departments in the first three universities, which currently accept students from state universities, were examined from various perspectives. In these universities, the number of courses of Arabic Translation and Interpretation departments, the courses and the intensity of the translation field according to the semesters were evaluated. As a result of the study, it draws attention that there are differences between the programs....

Big Data Technology (BDT) and Analytics have gained immense recognition in recent years. BDT plays an essential role in various sectors. This study intends to provide a review of BDT in the education sector which includes analyzing, predicting learner's results based on behavior patterns, assessing their performance regularly. Education institutions are beginning to use analytics and techniques for improving the services they provide and to enhance learner's performance and retention. BDT in education involves Data Mining, Data Analytics. This study also aims at investigating the techniques referred to as Educational Data Mining (EDM) and Learning Analytics (LA) influencing online learning systems. Thus, this research study will examine the field of EDM and LA which give an effective understanding on student's learning methods and identify their educational outcomes.

It is seen that the importance and need for Arabic have been increasing in Turkey in recent years, and the variety and number of programs for the Arabic language in higher education institutions are also increasing. It is noteworthy that the Arabic Language and Literature and Arabic Language Teaching departments, which have a long history, and the Arabic Translation and Interpretation departments, have been increasing in the state and private universities in recent years. In this study, the undergraduate programs of the Arabic translation and interpretation departments in the first three universities, which currently accept students from state universities, were examined from various perspectives. In these universities, the number of courses of Arabic Translation and Interpretation departments, the courses and the intensity of the translation field according to the semesters were evaluated. As a result of the study, it draws attention that there are differences between the programs....

This paper traces the challenges faced by an innovative language programme started in Kenyan Universities in the 1980s and points out to challenges that innovative programmes can face. In the analysis of the literature that has been written on project management and language issues in development, it attempts to show how the Communication Skills programme could benefit from this knowledge on project management and educational change management in the third millennium. The paper concludes that it is necessary for those in charge of Communication Skills to borrow a leaf from this literature in order to overcome some of the educational challenges of the third millennium.

This paper traces the challenges faced by an innovative language programme started in Kenyan Universities in the 1980s and points out to challenges that innovative programmes can face. In the analysis of the literature that has been written on project management and language issues in development, it attempts to show how the Communication Skills programme could benefit from this knowledge on project management and educational change management in the third millennium. The paper concludes that it is necessary for those in charge of Communication Skills to borrow a leaf from this literature in order to overcome some of the educational challenges of the third millennium.

Data pre-processing is the first step in any data mining process, being one of the most important but less studied tasks in educational data mining research. Pre-processing allows transforming the available raw educational data into a suitable format ready to be used by a data mining algorithm for solving a specific educational problem. However, most of the authors rarely describe this important step or only provide a few works focused on the pre-processing of data. In order to solve the lack of specific references about this topic, this paper specifically surveys the task of preparing educational data. Firstly, it describes different types of educational environments and the data they provide. Then, it shows the main tasks and issues in the pre-processing of educational data, Moodle data being mainly used in the examples. Next, it describes some general and specific pre-processing tools and finally, some conclusions and future research lines are outlined.

It is seen that the importance and need for Arabic have been increasing in Turkey in recent years, and the variety and number of programs for the Arabic language in higher education institutions are also increasing. It is noteworthy that the Arabic Language and Literature and Arabic Language Teaching departments, which have a long history, and the Arabic Translation and Interpretation departments, have been increasing in the state and private universities in recent years. In this study, the undergraduate programs of the Arabic translation and interpretation departments in the first three universities, which currently accept students from state universities, were examined from various perspectives. In these universities, the number of courses of Arabic Translation and Interpretation departments, the courses and the intensity of the translation field according to the semesters were evaluated. As a result of the study, it draws attention that there are differences between the programs....

Decision tree induction and Clustering are two of the most prevalent data mining techniques used separately or together in many business applications. Most commercial data mining software tools provide these two techniques but few of them satisfy business needs. There are many criteria and factors to choose the most appropriate software for a particular organization. This paper aims to provide a comparative analysis for three popular data mining software tools, which are SAS® Enterprise Miner, SPSS Clementine, and IBM DB2® Intelligent Miner based on four main criteria, which are performance, functionality, usability, and auxiliary Task Support.

This study presents an efficient framework for assessment and prediction of teachers' performance in academic institutes using Artificial Neural Network (ANN) algorithm. The prediction model was tested effectively using the TA UCI dataset. The data consists of academic experiences for teachers as well as their experiences and grades of students in courses they taught among others. The SPSS tool was used to build the suggested prediction system. The TA data was dividing into three groups (70, 80, and 90) for training data, and (30, 20, and 10) for testing data respectively to study the dataset discrimination. The results are showing that the neural network obtained better accuracy results with (90%) in the training and (10%) in testing.

In Namibian (public) schools, Lower Primary learners (preprimaryGrade 3) are taught through their mother tongue and switch to English as the language of learning and teaching from Upper Primary phase (Grade 4 onwards). Upper Primary phase teachers are therefore faced with the challenges of developing learners’ cognitive and academic skills which learners need to study other subjects that are taught in English. This paper explore factors teach their subjects. A qualitative interpretive approach was used to their subjects. Data collection methods consisted of interviews, classroom observations and document analysis. Analysis of the data reveals that the syllabus are way ahead of learners’ actual competency in English Second Language. In addition, data reveals that when learners come into the Upper Primary phase, they have such a poor foundation that they continue to learn little and lag behind grade appropriate outcomes throughout their school careers. The are promoted to the next gra...

The adaptive education frameworks within e-learning platforms are designed to ensure that each learner's learning experience differs. To provide adaptive e-learning programs and research materials adapted to adaptive learning, this type of educational approach attempts to integrate the ability to understand and identify the unique needs of an individual in the context of learning with the skills needed to use suitable learning pedagogy and to improve the learning process. Thus, designing realistic student profiles and templates based on an overview of their affective states, level of experience, and individual personality traits and abilities is essential. The data collected can then be used and used effectively for the creation of an adaptive learning system. These learner models can be used in two ways once learned. The first is to educate the pedagogy of the integrated educational method suggested by the experts and designers. The second objective is to provide the framework ...

Data mining offers a new advance to data analysis using techniques based on machine learning, together with the conventional methods collectively known as educational data mining (EDM). Educational Data Mining has turned up as an interesting and useful research area for finding methods to improve quality of education and to identify various patterns in educational settings. It is useful in extracting information of students, teachers, courses, administrators from educational institutes such as schools/ colleges/universities and helps to suggest interesting learning experiences to various stakeholders. This paper focuses on the applications of data mining in the field of education and implementation of three widely used data mining techniques using Rapid Miner on the data collected through a survey.

Data pre-processing is the first step in any data mining process, being one of the most important but less studied tasks in educational data mining research. Pre-processing allows transforming the available raw educational data into a suitable format ready to be used by a data mining algorithm for solving a specific educational problem. However, most of the authors rarely describe this important step or only provide a few works focused on the pre-processing of data. In order to solve the lack of specific references about this topic, this paper specifically surveys the task of preparing educational data. Firstly, it describes different types of educational environments and the data they provide. Then, it shows the main tasks and issues in the pre-processing of educational data, Moodle data being mainly used in the examples. Next, it describes some general and specific pre-processing tools and finally, some conclusions and future research lines are outlined.

The focus of this research was to use Educational Data Mining (EDM) techniques to conduct a quantitative analysis of students interaction with an e-learning system through instructor-led non-graded and graded courses. This exercise is useful for establishing a guideline for a series of online short courses for them. A group of 412 students' access behaviour in an e-learning system were analysed and they were grouped into clusters using K-Means clustering method according to their course access log records. The results explained that more than 40% from the student group are passive online learners in both graded and non-graded learning environments. The result showed that the difference in the learning environments could change the online access behaviour of a student group. Clustering divided the student population into five access groups based on their course access behaviour. Among these groups, the least access group (NG-41% and G-42%) and the highest access group (NG-9% and G-5%) could be identified very clearly due to their access variation from the rest of the groups.

Data pre-processing is the first step in any data mining process, being one of the most important but less studied tasks in educational data mining research. Pre-processing allows transforming the available raw educational data into a suitable format ready to be used by a data mining algorithm for solving a specific educational problem. However, most of the authors rarely describe this important step or only provide a few works focused on the pre-processing of data. In order to solve the lack of specific references about this topic, this paper specifically surveys the task of preparing educational data. Firstly, it describes different types of educational environments and the data they provide. Then, it shows the main tasks and issues in the pre-processing of educational data, Moodle data being mainly used in the examples. Next, it describes some general and specific pre-processing tools and finally, some conclusions and future research lines are outlined.

This paper traces the challenges faced by an innovative language programme started in Kenyan Universities in the 1980s and points out to challenges that innovative programmes can face. In the analysis of the literature that has been written on project management and language issues in development, it attempts to show how the Communication Skills programme could benefit from this knowledge on project management and educational change management in the third millennium. The paper concludes that it is necessary for those in charge of Communication Skills to borrow a leaf from this literature in order to overcome some of the educational challenges of the third millennium.

Data pre-processing is the first step in any data mining process, being one of the most important but less studied tasks in educational data mining research. Pre-processing allows transforming the available raw educational data into a suitable format ready to be used by a data mining algorithm for solving a specific educational problem. However, most of the authors rarely describe this important step or only provide a few works focused on the pre-processing of data. In order to solve the lack of specific references about this topic, this paper specifically surveys the task of preparing educational data. Firstly, it describes different types of educational environments and the data they provide. Then, it shows the main tasks and issues in the pre-processing of educational data, Moodle data being mainly used in the examples. Next, it describes some general and specific pre-processing tools and finally, some conclusions and future research lines are outlined.

Data pre-processing is the first step in any data mining process, being one of the most important but less studied tasks in educational data mining research. Pre-processing allows transforming the available raw educational data into a suitable format ready to be used by a data mining algorithm for solving a specific educational problem. However, most of the authors rarely describe this important step or only provide a few works focused on the pre-processing of data. In order to solve the lack of specific references about this topic, this paper specifically surveys the task of preparing educational data. Firstly, it describes different types of educational environments and the data they provide. Then, it shows the main tasks and issues in the pre-processing of educational data, Moodle data being mainly used in the examples. Next, it describes some general and specific pre-processing tools and finally, some conclusions and future research lines are outlined.

Applying data mining and machine learning techniques on Moodle logs is an emerging trend that can help track student's performance and decrease the failure rate. Due to Moodle's limitation to provide these features, this study was conceptualized. The study made use of historical data from Moodle logs of past academic years to pre-process and develop machine learning models using an open source data mining tool named Weka. This study made use of predictor attributes related to study behavior of students such as Course Viewing Time, Resource Views, Quiz Taken, Replied in Discussions, and Viewed at Weekends. However, it was found out that predictor attributes such as Activities Completed, Course Views and Assignment Passed are the ones which are strongly correlated to students' performance. Moreover, the predictive accuracy of a model improves depending on the machine learning algorithm being used. Algorithms such as J48, Random Forest, JRip, and OneR have been consistently performing well regardless of the model it is being trained into; and, achieved a predictive accuracy as high as 96.42%. The study was able to reflect the predicted results of Weka back to Moodle through an integrator and developed block using Moodle API. Finally, the developed application was evaluated by IT Experts using the ISO 25010 criteria.

The Education Quarterly Reviews is an Open Access publication. It may be read, copied, and distributed free of charge according to the conditions of the Creative Commons Attribution 4.0 International license. The Asian Institute of Research Education Quarterly Reviews is a peer-reviewed International Journal. The journal covers scholarly articles in the fields of education, linguistics, literature, educational theory, research, and methodologies, curriculum, elementary and secondary education, higher education, foreign language education, teaching and learning, teacher education, education of special groups, and other fields of study related to education. As the journal is Open Access, it ensures high visibility and the increase of citations for all research articles published. The Education Quarterly Reviews aims to facilitate scholarly work on recent theoretical and practical aspects of education.

This article subverts traditional way to explore the definition of translation competence and its development. Based on dialectical thinking and system theory, division and integration are combined to develop translation competence. Elements at different levels are integrated into another system at higher level as one of elements waiting for another integration at another higher level. At each stage, corresponding competence is required and corresponding courses are used to integrate sparse knowledge and skills to meet corresponding competence requirements. A new concept and a new model are presented only with an aim to shed light on exploration of translation competence and its development in educational setting in Chinese mainland.

With the increasingly change of the world, translation has been different from that at any stage in its history. The change in its nature needs to be explored in the special era of the combination of globalization and 'Internet plus'. For the purpose, this paper is presented to delve into the evolving translation in the changing world. Through the analysis of the literature of translation studies and documents from translation profession, what is

The adoption of learning management systems in education has been increasing in the last few years. Various data mining techniques like prediction, clustering and relationship mining can be applied on educational data to study the behavior and performance of the students. This paper explores the different data mining approaches and techniques which can be applied on Educational data to build up a new environment give new predictions on the data. This study also looks into the recent applications of Big Data technologies in education and presents a literature review on Educational Data Mining and Learning Analytics.

Teachers are crucial agents of any language education planning as they can make it succeed or fail. In this article, we intend to provide state of the art, concerning teaching Tamazight in Algeria through a case study. We conducted research in Mostaganem city where Tamazight is introduced in 9 primary schools. This investigation aims to study the role of Tamazight teachers' entry-profiles and the challenges they are facing. We collect data by employing questionnaires and interviews. These research methods help to give insightful information about the reality, needs, and challenges of Tamazight's instructors. The findings reveal that educators need training, and involvement of specialists to arrange the contexts where Tamazight is being introduced (attitudes). So, more efforts should be spent to improve the situation for achieving the objectives behind the formulation of the Tamazight policy.

The report sums up the work of a group of 50 students in the MSc program in Planning at the Technion- Israel Institute of Technology. The studio is a first-year exercise in which the students prepare a city-level strategic plan. At first, students collect data on a variety of issues including: the political and socio-economic conditions, the built fabric, the history, design features, and statutory conditions in the city. Then, they analyze and study key issues and problems which the city faces (SWOT and BAU analysis). Following, the students conduct a thorough field survey of inhabitants as well as interviews with a variety of stakeholders in the city. The final stages involve the creation of a shared vision and a strategic plan. The attached report summarizes key findings and proposals of a range of planning teams which worked on this project in 2017-2018 in the City of Kiryat Shmona. The findings are presented in Hebrew. The city of Kiryat Shmona is located in Israel's north, bordering Lebanon. It has face numerous social, economic, and geo-political challenges, and is still struggling today with a deficit, weak connectivity to other regions, as well as regional competition with nearby towns and Kibbutzim.

Machine learning has been applied to various domains such as pattern recognition, image recognition, fraud detection, medical diagnosis, banking, bioinformatics, commodity trading, computer games and various control applications. Recently, there has been a paradigm shift towards the educational sector in evaluating higher education tasks. The focus of this work is on identifying a suitable algorithm for predicting tertiary students' academic performance, based on their family background factors and previous academic achievements. A university case study with 204 enrolment records of students admitted into computer science program in Kwara State University, Nigeria between 2013 and 2015 was used. The students' first year academic performance was measured by Cumulative Grade Point Average (CGPA), at the end of the first session and the previous academic achievement was measured by SSCE grade score and UME score. The MATLAB programming language was used to carry out the experimental research with emphasis on C4.5 and Randomtree algorithm. These algorithms were compared, using the holdout method, considering, accuracy level, confusion matrices and CPU time to determine the optimal model. Also, a framework of a predictive system based on the rules generated from the optimal model was designed.

In the past decade, we have witnessed a tremendous rise in the use of electronic devices in education. Starting from nursery classes at the preschool level to the postgraduate programs at the universities, electronic devices are being used extensively to enhance and facilitate quality of education. Although the use of computer networks is an inherent feature of online learning, the traditional schools and universities are also making extensive use of network-connected electronic devices such as mobile phones, tablets, and computers. However, it is humanly impossible to analyze enormous volume of data generated from the active usage of devices connected through a large network. The educators and academic administrators can benefit from their counterparts in business and service industries where a complex system of methods and techniques, usually referred as data analytics or data mining, are being used to analyze a large influx of real-time data in decision-making. Researchers have started paying attention to the application of data mining and data analytics to handle big data generated in the educational sector. In the context of education, these techniques are specifically referred to as Educational Data Mining (EDM) and Learning Analytics (LA). Generally, EDM looks for new patterns in data and develops new algorithms and/or new models, while LA applies known predictive models in instructional systems. This chapter starts by describing major EDM and LA techniques used in handling big data in commercial and other activities. It will also provide a brief description of how EDM and LA are affecting the typical stakeholders of a higher education institution. Furthermore, the chapter will provide a detailed account of how these techniques are used to analyze the learning process of students, assessing their performance and providing them with detailed feedback in real-time. The technologies can also assist in planning administrative strategies to provide quality services to all stakeholders of an educational institution. Not all the stakeholders involved in providing education are experts of big data. However, in order to meet their analytical requirements, the researchers have developed easy-to-use data mining and visualization tools. In this chapter, we have provided the necessary details of some of these tools. The institutions/governments across the world are adopting EDM/LA to frame strategic policies, to understand the students learning behaviors etc. As case studies, we have also discussed some implementation of EDM and LA techniques in universities in different countries.

The use of recent technology creates more impact in the teaching and learning process nowadays. Improvement of students' knowledge by using the various technologies like smart class room environment, internet, mobile phones, television programs, use of iPods and etc. are play a very important role. Most of the education institutions used classroom teaching using advanced technologies such as smart class environment, visualization by power point projector and etc. This research work focusses on such technologies used for the improvement of student's performance using some of the Data Mining (DM) techniques particularly classification and clustering. Information repositories (Educational Data Bases, Data Warehouses) are the source place for collecting study materials and use them for their learning purposes is the number one source for preparation of examinations. Particularly, this research work analyzes about the use of clustering and classification algorithms to enable the student's performances and their learning capabilities using these modern technologies. During the study period, the student's family background and their economic status are also play a very important role in their daily activities. These things are not considered in this survey work. A comparative study is carried out in this work by comparing students performance based on their results. The comparison is carried out based on the results of some of the classification and clustering algorithms. Finally, it states that the best algorithm for the improvement of students performance using these algorithms.

Extraction of information available in various data base repositories is a tedious task. A composed works of Data Mining (DM) method is accessible for different category of applications for the same work. Many researchers involve analyzing the student's performance using some relevant DM techniques. This attracting little field is named as Learning Data Mining (LDM). The organizations of the syllabus also increase a very big contact about the growth of the student's information and their performance. Among the different data mining methods, classification plays a vital role in learning data mining. The primary intention of this research work is to cross the data mining methods which are apply for the improvement of the student's performance and also identify the most excellent appropriate structure of syllabus for the new environment. This study investigates about the use of ID3 and C4.5 classification algorithms for the improvement of student performance evaluation system. A comparative analysis of various works is carried out in this survey to identify the best classification algorithms for LDM.

A variety of Data mining techniques are available for different kind of applications. One of the new research communities of application involves analyzing the Students performance. This attracting young field is named as Educational Data Mining (EDM). The structure of the curriculum also raises a very big impact about the development of student's knowledge and their performance. Among the various data mining techniques, classification plays a vital role in Educational data mining. The foremost intention of this research is to traverse the data mining techniques which are used for the improvement of student's performance and also identify the best suited structure of curriculum for the current environment. Particularly, this survey analyses about the use of classification algorithms ID3 and C4.5 for the student performance evaluation system.