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The ideological and political education of college students is facing enormous challenge under new situation. Thus, it is necessary to continuously adjust the way of ideological work and strengthen the exchanging of advanced experience, to improve the ideological and political education effects for colleges. Based on the clustering method of data mining, this paper studies its application on ideological...
Learning analytics (LA) is a multidisciplinary area of research, where education, statistics, and technology experts collaborate with other disciplines to get insights from learning data sets. This involves a continuous cycle of gathering data from teachers’ and students’ interactions, filtering and translating it to proper formats, using a wide range of analysis techniques and starting again after...
Over the past few years, we have witnessed the rapid growth of Massive Open Online Courses (MOOCs). More and more researches focus on MOOCs, especially grade prediction, due to the low completion rate in MOOCs. In this paper, we proposed a grade prediction model to automatically predict students' grades based on students' previous performances. We utilized regression, back-propagation neural network...
Education helps people develop as individuals. It not only helps build social skills but also enhances the problem solving and decision making skills of individuals. With the growing number of schools, colleges and universities around the globe, education now has taken new dimension. The main focus of higher Educational Institutes is to improve the overall quality and effectiveness of education. Predicting...
Data mining techniques have been found useful in understanding and enhancing student performance as well as decision making related to teaching and learning in HEIs. Literature review enabled the choice of time to degree and cumulative grade point average (CGPA) as examples of student performance factors for investigation. Student features that could be extracted using SQL query from student dataset...
In recent years, higher education has been gaining importance in graduate students to make successful careers. So, academic organizations are given utmost importance for quality in academics to build the careers of the students. Faculty performance plays a vital role in academic institutions. In this paper, the performance of faculty members is evaluated on the basis of different parameters are taken...
This study presents a proposal for the analysis of student's engagement level in an online course. Data was used from a graduate course at a Brazilian public university. The method was based on the process of Educational Data Mining (EDM) to identify transactional distance constructs in the data collected and metrics defined by Social Network Analysis (SNA) and also the use of logistic regression...
Previous research shows how student's effort is found in Learning Management Systems (LMS). In this paper, we verified if positive effort in face-to-face courses supported by Moodle LMS carries on to their completion. We used logs of several courses and compared them with teachers' diaries. We developed an algorithm to analyze data and retrieve information about students. The results confirm that...
The use of digital games in education is already a reality, but their use in this area has been hampered by the lack of consolidated resources for evaluation of game-based learning. This paper reports a computational architecture for learning analytics in game-based learning that is based on relational analysis and data mining of data containing evidences of learning collected during the game play...
Massive Open Online Courses (MOOCs) are growing substantially in numbers, and also in interest from the educational community. MOOCs are online courses aimed at large-scale interactive participation and open access via the Web that made them possible for anyone with an internet connection to enroll in free, university level courses. In this paper, we propose a novel method to discover various types...
In this paper, we conduct a preliminary study about a newly established course evaluation survey given to the students by our institution. This survey contains several free-text questions which generates more qualitative but also voluminous unstructured feedback compared to the previous Likert scale question-based survey. Our aim is to apply data mining techniques to extract knowledge from these surveys,...
Digital technology integration in schools and what this means for teaching and learning plays an significant role in shaping the education environment. There has been a growing body of literature addressing students' perceptions towards technology integration. A large amount of student and teacher self-reported questionnaire or survey data therefore has been collected for different modelling purposes...
This study focuses on bovine sociality and proposes a new method of detecting estrus through the detection and the analysis of interactions between cows. In the proposed method, we mainly trace bovine behavior when an animal approaches other cows based on their time-series location data measured by a GPS installed on each animal. The cow's estrus is detected by analyzing the interaction information...
Educational Data Mining can help predict dropout prone students and the factors institutions should observe in trying to avoid an important social problem in modern societies. However, most current predicting models use academic credit worth information from the curricula, ignoring extracurricular activities, while there is evidence from other research fields that some activities like sports can be...
The financial data time series of a university contain important information of its resource allocation and developing trends, which can be revealed in their distinctive patterns. This work uses selective subsequence time series clustering based on motifs to discovery financial subsequence patterns in Chinese universities. The research finds out interesting patterns in eight university categories...
We develop a practical technique in this paper to classify the scholars in different disciplines, organizations according to their research interests. The scholar classification is important to the scholars, research organizations,, government for research, evaluation, education, research resource allocation. It becomes really difficult because name abbreviation, interdisciplinary, especially tautonym...
In recent years, with the gradual development of mobile Internet technology, the number of mobile applications increases dramatically. Users facing numerous mobile applications are often caught off guard. It is necessary to automatically classify the applications according to the applications' information, so as to recommend appropriate applications to users. However, the text information directly...
Researchers in higher education are beginning to explore the potential of data mining in analyzing data for the purpose of giving quality service and needs of their graduates. Thus, educational data mining emerges as one tools to study academic data to identify patterns and help for decision making affecting the education. This paper predicts the employability of IT graduates using nine variables...
The achievement of good honours in Undergraduate degrees is important in the context of Higher Education (HE), both for students and for the institutions that host them. In this paper, we look at whether data mining can be used to highlight performance problems early on and propose remedial actions. Furthermore, some of the methods may also form the basis for recommender systems that may guide students...
Work abroad appears as a saving version among the uncertainties which many of us encounter. The phenomenon is relatively recent and “information is not sufficient for a complete doctrine.” [1]. According to a study of the Romanian Academy since 2007, migration is selective, because especially young people and a segment of valuable, competitive and well trained labour are migrating, thus reducing the...
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