The Experts below are selected from a list of 203151 Experts worldwide ranked by ideXlab platform
Radek Pelanek - One of the best experts on this subject based on the ideXlab platform.
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applications of the elo rating system in adaptive Educational Systems
Computers in Education, 2016Co-Authors: Radek PelanekAbstract:The Elo rating system was originally developed for rating chess players, nowadays it is widely used for ranking players of many other games. The system can be used in Educational Systems when we interpret student's answer to an item as a match between the student and the item. In this way we can easily dynamically estimate the skill of students and difficulty of items. We provide a systematic overview of different variants of the Elo rating system and their application in education. We compare the Elo rating system to alternative methods and describe a specific case study (an adaptive practice of geography facts) to illustrate the application of the Elo rating system in education. We argue that the Elo rating system is simple, robust, and effective and thus suitable for use in the development of adaptive Educational Systems. We provide specific guidelines for such applications. The Elo rating system was originally developed for rating chess players.The system is well suited for development of adaptive Educational Systems.Relevant variants of the Elo rating Systems are described.The system is compared with alternative methods for estimating item difficulty.Application of the system is illustrated using a geography case study.
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modeling students memory for application in adaptive Educational Systems
Educational Data Mining, 2015Co-Authors: Radek PelanekAbstract:Human memory has been thoroughly studied and modeled in psychology, but mainly in laboratory setting under simplified conditions. For application in practical adaptive Educational Systems we need simple and robust models which can cope with aspects like varied prior knowledge or multiple-choice questions. We discuss and evaluate several models of this type. We show that using the extensive data sets collected by online Educational Systems it is possible to build well calibrated models and get interesting insight, which can be used for improvement of adaptive Educational Systems.
Felix Hernandezdelolmo - One of the best experts on this subject based on the ideXlab platform.
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supporting teachers in adaptive Educational Systems through predictive models a proof of concept
Expert Systems With Applications, 2012Co-Authors: Elena Gaudioso, Miguel Montero, Felix HernandezdelolmoAbstract:Adaptive Educational Systems (AESs) guide students through the course materials in order to improve the effectiveness of the learning process. However, AES cannot replace the teacher. Instead, teachers can also benefit from the use of adaptive Educational Systems enabling them to detect situations in which students experience problems (when working with the AES). To this end the teacher needs to monitor, understand and evaluate the students' activity within the AES. In fact, these Systems can be enhanced if tools for supporting teachers in this task are provided. In this paper, we present the experiences with predictive models that have been undertaken to assist the teacher in PDinamet, a web-based adaptive Educational system for teaching Physics in secondary education. Although the obtained models are still very simple, our findings suggest the feasibility of predictive modeling in the area of supporting teachers in adaptive Educational Systems.
Jaap Dronkers - One of the best experts on this subject based on the ideXlab platform.
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the high performance of dutch and flemish 15 year old native pupils explaining country differences in math scores between highly stratified Educational Systems
Educational Research and Evaluation, 2012Co-Authors: Tijana Prokicbreuer, Jaap DronkersAbstract:This paper aims to explain the high scores of 15-year-old native pupils in The Netherlands and Flanders by comparing them with the scores of pupils in countries with the same highly stratified Educational system: Wallonia, the German Lander, the Swiss German cantons, and Austria. We use the data from the Programme for International Pupil Assessment (PISA) 2006 together with the specific PISA data of Germany and Switzerland. We apply a multilevel model that takes into account the individual-, curriculum-, and system-level features in these highly stratified Educational Systems. The high scores of the Dutch pupils can be explained by the size of The Netherlands' vocational sector. The high Flemish scores can be partly explained by the high curriculum mobility. Central exit exams are not a good explanation of the high Dutch scores. Despite being limited to highly stratified Systems, we still find Educational policies and arrangements to have significant effects on the Educational performance of pupils.
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why are migrant students better off in certain types of Educational Systems or schools than in others
European Educational Research Journal, 2012Co-Authors: Jaap Dronkers, Rolf Van Der Velden, Allison DunneAbstract:The main research question of this article is concerned with the combined estimation of the effects of Educational Systems, school composition, track level, and country of origin on the Educational achievement of 15-year-old migrant students. The authors focus specifically on the effects of socioeconomic and ethnic background on achievement scores and the extent to which these effects are affected by characteristics of the school, track, or Educational system in which these students are enrolled. In doing so, they examine the 'sorting' mechanisms of schools and tracks in highly stratified, moderately stratified, and comprehensive education Systems. They use data from the 2006 Programme for International Student Assessment (PISA) wave. Compared with previous research in this area, the article's main contribution is in explicitly including the tracks-within-school level as a separate unit of analysis, which leads to less biased results concerning the effects of Educational system characteristics. The results highlight the importance of including factors of track level and school composition in the debate surrounding Educational inequality of opportunity for students in different education contexts. The findings clearly indicate that analyses of the effects of Educational system characteristics are flawed if the analysis only uses a country level and a student level and ignores the tracks-within-school-level characteristics. From a policy perspective, the most important finding is that Educational Systems are neither uniformly 'good' nor uniformly 'bad', but they can result in different consequences for different migrant groups. Some migrant groups are better off in comprehensive Systems, while others are better off in moderately stratified Systems.
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the high performance of dutch and flemish 15 year old native pupils explaining country differences in math scores between highly stratified Educational Systems
2012Co-Authors: Tijana Prokicbreuer, Jaap DronkersAbstract:This paper aims to explain the high scores of 15-year-old native pupils in the Netherlands andFlanders by comparing them with the scores of pupils in countries with the same highly stratifiedEducational system. Therefore, we compare only the Educational performance of 15-year-old pupilsfrom the following regions: the Netherlands, Flanders, Wallonia, the German Lander, the SwissGerman cantons, and Austria. We use the data from the general Program for International PupilAssessment (PISA) 2006 together with the specific PISA data of Germany and Switzerland also from2006. We apply a multilevel model that takes into account the individual-, curriculum-, andsystem-level features in these highly stratified Educational Systems. The high scores of the Dutchpupils can be explained by the size of the Netherlands’ vocational sector. The high Flemish scorescan be only partly explained by the high curriculum mobility (as indicated by the lowest level ofentrance selection). Central exit exams are not a good explanation of the high Dutch scores.Despite being limited to highly stratified Systems, we still find Educational policies andarrangements to have significant effects on the Educational performance of pupils.
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the high performance of dutch and flemish 15 year old native pupils explaining country differences in math scores between highly stratified Educational Systems
Meteor Research Memorandum, 2012Co-Authors: Tijana Prokicbreuer, Jaap DronkersAbstract:This paper aims to explain the high scores of 15-year-old native pupils in the Netherlands andFlanders by comparing them with the scores of pupils in countries with the same highly stratifiedEducational system. Therefore, we compare only the Educational performance of 15-year-old pupilsfrom the following regions: the Netherlands, Flanders, Wallonia, the German LA¤nder, the SwissGerman cantons, and Austria. We use the data from the general Program for International PupilAssessment (PISA) 2006 together with the specific PISA data of Germany and Switzerland also from2006. We apply a multilevel model that takes into account the individual-, curriculum-, andsystem-level features in these highly stratified Educational Systems. The high scores of the Dutchpupils can be explained by the size of the Netherlands’ vocational sector. The high Flemish scorescan be only partly explained by the high curriculum mobility (as indicated by the lowest level ofentrance selection). Central exit exams are not a good explanation of the high Dutch scores.Despite being limited to highly stratified Systems, we still find Educational policies andarrangements to have significant effects on the Educational performance of pupils. (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed fro (This abstract was borrowed from another version of this item.)
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why are migrant students better off in certain types of Educational Systems or schools than in others
Research Papers in Economics, 2011Co-Authors: Jaap Dronkers, Rolf Van Der Velden, Allison DunneAbstract:The main research question of this paper is the combined estimation of the effects of Educational Systems, school composition, track level, and country of origin on the Educational achievement of 15-year-old migrant students. We focus specifically on the effects of socioeconomic and ethnic background on achievement scores and the extent to which these effects are affected by characteristics of the school, track, or Educational system in which these students are enrolled. In doing so, we examine the ‘sorting’ mechanisms of schools and tracks in highly stratified, moderately stratified, and comprehensive education Systems. We use data from the 2006 Programme for International Student Assessment (PISA) wave. Compared with previous research in this area, the paper’s main contribution is that we explicitly include the tracks-within-school level as a separate unit of analyses, which leads to less biased results concerning the effects of Educational system characteristics. The results highlight the importance of including factors of track level and school composition in the debate surrounding Educational inequality of opportunity for students in different education contexts. The findings clearly indicate that the effects of Educational system characteristics are flawed if the analysis only uses a country- and a student level and ignores the tracks-within-school level characteristics. From a policy perspective, the most important finding is that Educational Systems are neither uniformly ‘good’ nor ‘bad’, but they can result in different consequences for different migrant groups. Some migrant groups are better off in comprehensive Systems, while others are better off in moderately stratified Systems.
Elvys Soares - One of the best experts on this subject based on the ideXlab platform.
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a computational model for developing semantic web based Educational Systems
Knowledge Based Systems, 2009Co-Authors: Ig Ibert Bittencourt, Evandro Costa, Marlos Silva, Elvys SoaresAbstract:Recently, some initiatives to start the so-called semantic web-based Educational Systems (SWBES) have emerged in the field of artificial intelligence in education (AIED). The main idea is to incorporate semantic web resources to the design of AIED Systems aiming to update their architectures to provide more adaptability, robustness and richer learning environments. However, the construction of such Systems is highly complex and faces several challenges in terms of software engineering and artificial intelligence aspects. This paper presents a computational model for developing SWBES focusing on the problem of how to make the development easier and more useful for both developers and authors. In order to illustrate the features of the proposed model, a case study is presented. Furthermore, a discussion about the results regarding the computational model construction is available.
Stephen J H Yang - One of the best experts on this subject based on the ideXlab platform.
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learning styles and cognitive traits their relationship and its benefits in web based Educational Systems
Computers in Human Behavior, 2009Co-Authors: Sabine Graf, Tzuchien Liu, Nianshing Chen, Stephen J H YangAbstract:Different learners have different needs; they differ, for example, in their learning goals, their prior knowledge, their learning styles, and their cognitive abilities. Adaptive web-based Educational Systems aim to cater individual learners by customizing courses to suit their needs. In this paper, we investigate the benefits of incorporating learning styles and cognitive traits in web-based Educational Systems. Adaptivity aspects based on cognitive traits and learning styles enrich each other, enabling Systems to provide learners with courses which fit their needs more accurately. Furthermore, consideration of learning styles and cognitive traits can contribute to more accurate student modelling. In this paper, the relationship between learning styles, in particular the Felder-Silverman learning style model (FSLSM), and working memory capacity, a cognitive trait, is investigated. For adaptive Educational Systems that consider either only learning styles or only cognitive traits, the additional information can be used to provide more holistic adaptivity. For Systems that already incorporate both learning styles and cognitive traits, the relationship can be used to improve the detection process of both by including the additional information of learning style into the detection process of cognitive traits and vice versa. This leads to a more reliable student model.
