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Title:
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ASSESSING THE IMPACT OF STUDENTS’ ACTIVITIES IN E-CLASSES ON LEARNING OUTCOMES: A DATA MINING APPROACH |
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Author(s):
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Lan Umek, Nina Tomazevic, Aleksander Aristovnik and Damijana Kerzic |
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ISBN:
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978-989-8533-78-4 |
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Editors:
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Miguel Baptista Nunes and Pedro Isaias |
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Year:
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2018 |
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Edition:
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Single |
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Keywords:
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Blended Learning, Moodle, Students Activities, Quizzes, Students Performance, Predictive Modelling |
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Type:
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Full Paper |
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First Page:
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57 |
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Last Page:
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64 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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In the paper, we present the results of a case study conducted at Faculty of Administration, University of Ljubljana among 1st year undergraduate students. We investigated the correlations between students activities in the e-classroom and grades at the final exam. The sample included 92 participants who took part at the final exam in the course Basic Statistics. In the e-classroom, students learn new content for individual self-study is prepared and their knowledge is checked with quizzes. In the empirical study, we used data mining software Orange for two tasks of predictive modelling: The research question was: based on the students performance on quizzes is it possible to predict if (1) a student will pass an exam, and (2) a students grade at the exam will be good. The empirical results indicate very strong connection between students performance on quizzes and their grade at final exam in the course. Moreover, the results pointed out which quizzes, in other words topics, are most important for passing an exam or obtaining better grade. |
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