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Datamining (DM) brings together a wide range of techniques and algorithms which allow the extraction of knowledge from databases for timely decision making. DM has been applied to different fields of study. One important research field is Education. Applying DM in education is known as educational datamining (EDM). The main purpose of EDM is to analyze data from educational institutions using different...
Vocational is one of education types in Indonesia. Graduates from vocational school need to have enough motivation to get into working environment either as employees or as entrepreneurs. In vocational education, it is important to monitor students' motivation and achievement. It will help to understand students' condition and give an overview in setting the appropriate program for the students. This...
A good scholar evaluation system is very important for students to select advisors and majors and for government to get a good policy of the educational resource. The factor of scholars should be the most important parameter in the various college rankings, however, it seems not appear in the college ranking since it is difficult to evaluate it. In this paper, we propose a new evaluation system for...
This research focuses to measure readiness of a Data Warehouse of Higher Education (in Indonesia it's called “Sistem Pangkalan Data Pendidikan Tinggi” or PDPT System) with Andrea Sodano's perspective as publish in Fortune which have domain of the research in Higher Education of Nation of Indonesia. A model that is used to asses the readiness of Data Warehouse of Higher Education or PDPT System before...
The benefits of using assessment tools for programming assignments have been widely discussed in computing education. However, as both researchers and instructors are unaware of the characteristics of existing tools, they are either not used or are reimplemented. This paper presents the results of a study conducted to collect and evaluate evidence about tools that assist in the assessment of programming...
To help solve the ongoing problem of student retention, new expected performance-prediction techniques are needed to facilitate degree planning and determine who might be at risk of failing or dropping a class. Personalized multiregression and matrix factorization approaches based on recommender systems, initially developed for e-commerce applications, accurately forecast students' grades in future...
Educational Data Mining and Learning Analytics are two growing fields of study, trying to make sense of education data and to improve teaching and learning experience. We study dropout prediction in Massively Open Online Courses (MOOCS), where the goal is given student's learning behavior log data in one month, to predict whether students would drop out in next ten days. We collect 39 courses data...
Smart devices applications can assist children in improving their learning capabilities and comprehension skills. However most applications are built without taking into consideration the effective needs and background of Arab children and youth. They are somehow incompatible with their local environment. We propose in this paper an Arabic-based mobile educational system that displays illustrations...
Data mining plays an important role in the business world and it helps to the educational institution to predict and make decisions related to the students' academic status. With a higher education, now a days dropping out of students' has been increasing, it affects not only the students' career but also on the reputation of the institute. The existing system is a system which maintains the student...
Education is one of the primary requirements for leading a good life. In India, still a large section of population is not educated, which makes them lag behind everyone. For overall development of our country, the citizens have to be educated and consequently employed. This paper analyses the most important factor that will result in the improved education level of our country, using data mining...
Educational Data Mining (EDM) is an interdisciplinary ingenuous research area that handles the development of methods to explore data arising in a scholastic fields. Computational approaches used by EDM is to examine scholastic data in order to study educational questions. As a result, it provides intrinsic knowledge of teaching and learning process for effective education planning. This paper conducts...
The ideological and political education is facing new and greater challenges in the large data environment. In the current environment, the full use of information technology to carry out ideological and political education work, is the effective strategy to adapt to the big data environment. This paper mainly introduces the new situation of College Students' Ideological and political education, and...
The purpose of this paper is to explore whether the use of big data has the potential for application in the Higher Education (HE) sector in Oman in addressing part of their current challenges. Higher Education institutions in Oman are facing challenges relate to enhancing the learning experience, improving educator effectiveness, providing appropriate and effective learning methods tailored to individual...
This research work reports a systematic analysis of association of age with academic performance in a higher education institution. The correlation coefficient between key parameters of the student data were absorbed to derive the attributes that contributed strong positive influence on student results and also to identify the attributes that donated a negative impact. Further, a predictive model...
The impact of big data although being very insubstantial in its inception however has gradually originated to make significant contributions to variety of spheres of life. Development of smart cities, big data in e-business, big data in health care sector, big data in environmental sciences and implementation of Big Data in other areas has indisputably revealed to critics what can be achieved by Big...
This paper explores opinion mining using supervised learning algorithms to find the polarity of the student feedback based on pre-defined features of teaching and learning. The study conducted involves the application of a combination of machine learning and natural language processing techniques on student feedback data gathered from module evaluation survey results of Middle East College, Oman....
The main function of robots is to assist humans with tasks. We can find successful examples in factories and hospitals. Yet, service mobile robots, designed to help humans in houses, are still in its early stages. The current state of service mobile robotics inspired me to start my research in this field. First, during my Master thesis I developed a semi-direct teaching method for robots. The method...
The paper titled “STEP-A career zone Android APP for Higher Secondary Students” is an application which helps the higher secondary school students for their career. STEP stands for (Skill towards Entry and Prediction). It involves the analysis and prediction process to choose the students' career using Mobile and Tablets. It creates awareness among the students about the courses, degrees, entrance...
To increase efficacy in traditional classroom courses as well as in Massive Open Online Courses (MOOCs), automated systems supporting the instructor are needed. One important problem is to automatically detect students that are going to do poorly in a course early enough to be able to take remedial actions. Existing grade prediction systems focus on maximizing the accuracy of the prediction while...
Data Analysis is key to understand the importance of accumulated data over a period of time. The importance of the accumulated data is understood by the data analyst over period of time. The authors had shown the importance of the data collected of the higher education by finding the new and un-identified facts using the statistically techniques. The authors found that the regression techniques could...
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