The Experts below are selected from a list of 226278 Experts worldwide ranked by ideXlab platform
Ekaterina Vasilyeva - One of the best experts on this subject based on the ideXlab platform.
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mining the Student Assessment data lessons drawn from a small scale case study
Educational Data Mining, 2008Co-Authors: Mykola Pechenizkiy, Tgk Toon Calders, Ekaterina VasilyevaAbstract:In this paper we describe an educational data mining (EDM) case study based on the data collected during the online Assessment of Students who were able to immediately receive tailored and elaborated feedback (EF) after answering each of the questions in the test. Our main interest as domain experts (i.e. educators) is in studying (by employing any kind of analysis) how well the questions in the test and the corresponding EF were designed or tailored towards the individual needs of the Students. The case study itself is aimed at showing that even with a modest size dataset and well-defined problems it is still rather hard to obtain meaningful and truly insightful results with a set of traditional data mining (DM) approaches and techniques including clustering, classification and association analysis.
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mining the Student Assessment data lessons drawn from a small scale case study
Educational Data Mining, 2008Co-Authors: Mykola Pechenizkiy, Tgk Toon Calders, Ekaterina Vasilyeva, P M E De BraAbstract:In this paper we describe an educational data mining (EDM) case study based on the data collected during the online Assessment of Students who were able to immediately receive tailored and elaborated feedback (EF) after answering each of the questions in the test. Our main interest as domain experts (i.e. educators) is in studying (by employing any kind of analysis) how well the questions in the test and the corresponding EF were designed or tailored towards the individual needs of the Students. The case study itself is aimed at showing that even with a modest size dataset and well-defined problems it is still rather hard to obtain meaningful and truly insightful results with a set of traditional data mining (DM) approaches and techniques including clustering, classification and association analysis.
Mykola Pechenizkiy - One of the best experts on this subject based on the ideXlab platform.
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mining the Student Assessment data lessons drawn from a small scale case study
Educational Data Mining, 2008Co-Authors: Mykola Pechenizkiy, Tgk Toon Calders, Ekaterina VasilyevaAbstract:In this paper we describe an educational data mining (EDM) case study based on the data collected during the online Assessment of Students who were able to immediately receive tailored and elaborated feedback (EF) after answering each of the questions in the test. Our main interest as domain experts (i.e. educators) is in studying (by employing any kind of analysis) how well the questions in the test and the corresponding EF were designed or tailored towards the individual needs of the Students. The case study itself is aimed at showing that even with a modest size dataset and well-defined problems it is still rather hard to obtain meaningful and truly insightful results with a set of traditional data mining (DM) approaches and techniques including clustering, classification and association analysis.
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mining the Student Assessment data lessons drawn from a small scale case study
Educational Data Mining, 2008Co-Authors: Mykola Pechenizkiy, Tgk Toon Calders, Ekaterina Vasilyeva, P M E De BraAbstract:In this paper we describe an educational data mining (EDM) case study based on the data collected during the online Assessment of Students who were able to immediately receive tailored and elaborated feedback (EF) after answering each of the questions in the test. Our main interest as domain experts (i.e. educators) is in studying (by employing any kind of analysis) how well the questions in the test and the corresponding EF were designed or tailored towards the individual needs of the Students. The case study itself is aimed at showing that even with a modest size dataset and well-defined problems it is still rather hard to obtain meaningful and truly insightful results with a set of traditional data mining (DM) approaches and techniques including clustering, classification and association analysis.
P M E De Bra - One of the best experts on this subject based on the ideXlab platform.
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mining the Student Assessment data lessons drawn from a small scale case study
Educational Data Mining, 2008Co-Authors: Mykola Pechenizkiy, Tgk Toon Calders, Ekaterina Vasilyeva, P M E De BraAbstract:In this paper we describe an educational data mining (EDM) case study based on the data collected during the online Assessment of Students who were able to immediately receive tailored and elaborated feedback (EF) after answering each of the questions in the test. Our main interest as domain experts (i.e. educators) is in studying (by employing any kind of analysis) how well the questions in the test and the corresponding EF were designed or tailored towards the individual needs of the Students. The case study itself is aimed at showing that even with a modest size dataset and well-defined problems it is still rather hard to obtain meaningful and truly insightful results with a set of traditional data mining (DM) approaches and techniques including clustering, classification and association analysis.
Tgk Toon Calders - One of the best experts on this subject based on the ideXlab platform.
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mining the Student Assessment data lessons drawn from a small scale case study
Educational Data Mining, 2008Co-Authors: Mykola Pechenizkiy, Tgk Toon Calders, Ekaterina VasilyevaAbstract:In this paper we describe an educational data mining (EDM) case study based on the data collected during the online Assessment of Students who were able to immediately receive tailored and elaborated feedback (EF) after answering each of the questions in the test. Our main interest as domain experts (i.e. educators) is in studying (by employing any kind of analysis) how well the questions in the test and the corresponding EF were designed or tailored towards the individual needs of the Students. The case study itself is aimed at showing that even with a modest size dataset and well-defined problems it is still rather hard to obtain meaningful and truly insightful results with a set of traditional data mining (DM) approaches and techniques including clustering, classification and association analysis.
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mining the Student Assessment data lessons drawn from a small scale case study
Educational Data Mining, 2008Co-Authors: Mykola Pechenizkiy, Tgk Toon Calders, Ekaterina Vasilyeva, P M E De BraAbstract:In this paper we describe an educational data mining (EDM) case study based on the data collected during the online Assessment of Students who were able to immediately receive tailored and elaborated feedback (EF) after answering each of the questions in the test. Our main interest as domain experts (i.e. educators) is in studying (by employing any kind of analysis) how well the questions in the test and the corresponding EF were designed or tailored towards the individual needs of the Students. The case study itself is aimed at showing that even with a modest size dataset and well-defined problems it is still rather hard to obtain meaningful and truly insightful results with a set of traditional data mining (DM) approaches and techniques including clustering, classification and association analysis.
Steven G Rivkin - One of the best experts on this subject based on the ideXlab platform.
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instruction time classroom quality and academic achievement
The Economic Journal, 2015Co-Authors: Steven G Rivkin, Jeffrey C SchimanAbstract:It seems likely the magnitude of any causal link between achievement and instruction time depends upon the quality of instruction, the classroom environment and the rate that Students translate classroom time into added knowledge. In this article, we use panel data methods to investigate instruction time effects in the 2009 Programme for International Student Assessment data. The empirical analysis shows that achievement increases with instruction time and that the increase varies by both the amount of time and the classroom environment. The results indicate that school circumstances are important determinants of the benefits and desirability of increased instruction time.
