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Self-regulated learning theories are used to understand the reasons for different levels of university student academic performance. Similarly, learning analytics research proposes the combination of detailed data traces derived from technology-mediated tasks with a variety of algorithms to predict student academic performance. The former approach is designed to provide meaningful pedagogical guidance,...
The goal of the instruction should be to induce the students to adopt a deep approach to subjects that are important for their professional and personal development. In to facilitate way, Inductive teaching methods motivate the students, tend to keep the students interested and actively engaged in their learning tasks. There are varieties of inductive learning approach where one approach is quite...
In software engineering, information retrieval which is also referred as data mining has attracted many researcher's attention. By the virtue of its definition, data mining is responsible for extracting relevant data from large volume of database or dataset. In this context, several techniques have been proposed in literature. Through this paper, an attempt to comparative analysis of various classification...
Workforce Intelligence incorporates various tools that capture and record details about the organizations' workforce and relevant activities, such as employees' skills, experience, education, job description and other demographic data. In addition, it correlates the enterprises' operational systems with workforce activities to increase the efficiency of the analysis process and rationalize decision-making...
The score in art exam, part of College entrance examination, is very useful and helpful. Thanks to the exam management system we got the data easily, and there are huge amount of data accumulated. We analyzed the data and visualize the data through Cluster Analysis and Correlation Analysis. And get the relationship between number of students and age, subject, position. Finally we visualize the analyzed...
In clustering data, there are two popular methods which are usually used: k-Means and Fuzzy C Means (FCM). Clustering process by these two methods, however, are sometimes influenced by the data suitable being used. This may affect the performance, for example: execution time, accuracy level. In order to overcome this problem, especially in a student evaluation system, we propose a feature extraction...
Understanding how to make education effective is a critical step in educational data mining. We have considered various socioeconomic, psychological and academic factors to fully understand what a person's life is during adolescence and how those factors impact their academic performance. Using pre-processing techniques such as feature selection, data balancing, discretization and normalization, and...
Inferring latent user preferences using both structured and unstructured data is an important social computing task. In this paper, we propose a user preference representation based on user activities embedded in unstructured data to better encode the homophily theory. The representation of an individual user is learned using a embedding based method to integrate latent user preferences in social...
In this paper, we aimed to guide about latest development and studies about students' performance analysis and Learning Analytics in Massively Open Online Courses (MOOCs) for researchers related with the topics. For this purpose short review for usage of performance prediction and Learning Analytics in MOOCs is investigated In our study, to help readers get familiar with our topic, firstly literature...
In open and distance education field, making use of data mining technologies to understand students' practical needs and usage habits about professional courses, which will greatly enhance students learning. China Open University system is Chinese largest scale organization engaging in open and distance education, and it has taken Chinese education ministry's a rural education project, called "one...
The educational evaluation requires of analysis and continue strategies to adapted the current context, so that this research presents the need to define models of educational evaluation with adaptive characteristics to the area of knowledge and the students to predict behaviors of academic performance and support the decision making in the educational context. This need is based on the theoretical...
The data science system at Udemy1, a global online education marketplace, is described. This data science system currently supports recommendation and search, but will be extended to support e-learning as well. The motivations behind and the approach to the system are explained, which allows multiple individual data scientists to all become ‘full stack’, taking control of their own destinies from...
Medical and healthcare study programmes are quite complicated in terms of branched structure and heterogeneous content. In logical sequence a lot of requirements and demands placed on students appear there. This paper focuses on an innovative way how to discover and understand complex curricula using modern information and communication technologies. We introduce an algorithm for curriculum metadata...
While the data mining in education field gained more and more popularity in recent years, there have many research endeavors to find association rules in students' academic situation. The current methods normally apply traditional association rules mining technique to identify those rules. However, traditional association rules mining technique can not identify difference between different types of...
In recent years, data mining techniques has attracted the attention from educational researchers and applied in educational research pervasively. As a famous data mining method, traditional association rules mining tend to ignore the infrequent data item and can only analyze a single dataset. To address these issues, a contrast targeted rule mining model is introduced in this paper. A complete analysis...
Clinical skills education is an essential component of the teaching plan in medical science courses, such as nursing education. Simulation-based learning is an effective teaching method in any practical or vocational-based training. The development of simulation-based teaching has been impacted by the integration of emerging technologies, such as Intelligent Tutoring Systems (ITSs), which results...
It might not seem dangerous for a person to leave some pieces of personal information on the Internet since everyone tends to do this. But the truth is that if someone ever tries to collect those pieces of information together, he might be able to find out the true identity of the person in reality after analyzing the collected data, which is what we call “cyber hunting”. This work focuses on the...
Grammar teaching and learning have always been important and difficult parts in L2 Chinese. This paper demonstrates a method for automatically extracting and recommending Grammar Points to L2 Chinese teachers and learners. First, a L2 Chinese grammar syllabus is reconstructed based on a corpus of international Chinese teaching materials. Second, a regular expression-based learning algorithm is explored...
To increase the learning effectiveness and willingness of students became the most important issue for the Universities in Taiwan. Therefore, we must find the important factors of the learning effectiveness to improve the learn willingness of students. However, it is not easy to measure the learning effectiveness because the subjective judgment of evaluators and the attributes of factors are always...
In recent decades, experts have presented a range of teaching methods and techniques which should increase the learning effectiveness. Naturally, no learning process is universal and reliable at the same time, and suitable for everyone and in every situation. Concept mapping is a method based on findings in cognitive psychology. We investigated how the learning process and effectiveness can be influenced...
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