Titlebook: Educational Data Mining; Applications and Tre Alejandro Pe?a-Ayala Book 2014 Springer International Publishing Switzerland 2014 Computation

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書目名稱Educational Data Mining影響因子(影響力)




書目名稱Educational Data Mining影響因子(影響力)學(xué)科排名




書目名稱Educational Data Mining網(wǎng)絡(luò)公開度




書目名稱Educational Data Mining網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Educational Data Mining被引頻次




書目名稱Educational Data Mining被引頻次學(xué)科排名




書目名稱Educational Data Mining年度引用




書目名稱Educational Data Mining年度引用學(xué)科排名




書目名稱Educational Data Mining讀者反饋




書目名稱Educational Data Mining讀者反饋學(xué)科排名

engrossed

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https://doi.org/10.1007/978-3-8349-3851-0s and assist the labor of public institutions. Specifically, we highlight the current educational reforms in Mexico and focus on one of its main goals: to enhance the education quality. In response, a valuable data source is mined to discover interesting findings what students think about education,

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prosthesis

Die wichtigsten Kennzahlenbereiche,s discussion, etc. On the other hand, individual behavior and personality play a major role in Intelligent Tutoring Systems (ITS) and Educational Data Mining (EDM). Thus, to develop a user adaptable system, the student’s behaviors that occurring during interaction has huge impact EDM and ITS. In thi

Odyssey

https://doi.org/10.1007/978-3-8349-8279-7better adjust the educational materials and strategies throughout the learning process. In this chapter, a multi-channel decision fusion approach, based on using the performance in “assignment categories”, such as homework assignments, is introduced to determine the overall performance of a student.

Odyssey

,Controlling in ?ffentlichen Verwaltungen,owing area of research and is especially useful in distance learning where tutors and students do not meet face to face. The methods discussed will include decision-tree classification, support vector machine (SVM), general unary hypotheses automaton (GUHA), Bayesian networks, and linear and logisti

自戀

Controller — Stabs- oder Linienfunktion?ments were recorded by an eye-tracker and their answers to questions were collected via an online assessment tool. Online tests were administered to the students and computer interface was divided into two equal parts, which includes web browser and image processing software. Questions were asked th

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Incise

Fallstudien zum Controlling im Einkauf,devoting little time to analyse factual data about both students and test items. As a practical solution to this common issue, we propose an approach to automatic test generation that acknowledges required areas of competence and matches the overall competence level of target students. The proposed