Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 25 for “"educational data mining"”.
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Ensemble Learning Methods for Educational Data Mining Applications
… with the analysis of observational study data and estimation of treatment effects. Propensity score matching has widely been accepted to counteract inherent selection bias in these studies. We present an ensemble learner for propensity score estimation, and consider the use of inverse …
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Exploring student course selection through educational data mining: community detection for student interests
… Við notum gagnanám með áherslu á menntun (e. Educational data mining, EDM) og einbeitum okkur sérstaklega að netagreiningu og hvernig samfélög innan neta myndast. Gagnasafn okkar náði yfir alla þá nemendur (N = 11207) sem innrituðu sig í nám á síðustu fimm árum við Háskólann í Reykjavík (HR). …
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Data-driven decisions: a conceptual framework for integrating educational data mining in professional bodies
… investigates the transformative potential of Educational Data Mining (EDM) in shaping educational landscapes and enhancing student outcomes. Focused on a comprehensive exploration, the research delves into multiple dimensions of EDM, addressing critical areas such as student dropout …
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Using Educational Data Mining Techniques to Analyze the Effect of Instructors’ LMS Tool Use Frequency on Student Learning and Achievement in Online Secondary Courses
… posttest scores.</p> <p>This study employed a data mining procedure to determine if LMS tools could predict semester final grades (achievement) and posttest scores (learning). The findings suggest that the LMS tools can predict posttest scores but not semester final grades. Additionally, the …
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Joining and aggregating datasets using CouchDB
Data mining typically requires implementing operations that involve cross-cutting entity boundaries and are awkward to implement in document-oriented databases. CouchDB, for example, models entities as documents, with highly isolated entity boundaries, and on which joins cannot be directly …
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Predicting grade progression within the Limpopo Education System
… the challenges faced in the education sector. Educational Data Mining (EDM) is one which has gained prominence in addressing these challenges. EDM is a field of data mining using mathematical and machine learning models to improve learners’ performance, education administration, and policy …
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Minería de datos aplicada al procesamiento automático en el análisis del proceso de enseñanza-aprendizaje
… estudios más precisos, lo que se conoce como Educational Data Mining (EDM), es necesario aplicar técnicas estadísticas y de minería de datos más sofisticadas y complejas. El objetivo principal de esta tesis doctoral es el de analizar el proceso de enseñanza-aprendizaje en distintos entornos y …
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Developing and evaluating domain models for programming skills using learning curve analysis
… skill models and generating new models in a data-driven manner. These knowledge components can be evaluated by learning curve analysis, which is an educational data mining technique for modeling skill development using data on problem-solving performance of students. Yet, previous …
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Investigating prediction modelling of academic performance for students in rural schools in Kenya
… A six-step Cross-Industry Standard Process for Data Mining (CRISP-DM) theoretical framework was used to support the design of MAPPS. Experiments were conducted using two datasets collected in Kenya. One dataset had 2426 records of student data having 22 features, collected from 54 rural primary …
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Learning in MOOCS: An exploratory analysis of participation patterns and their relation to demographic variables and other influential factors
… factors that could relate to these patterns. Data was obtained from the data logs and survey results recorded by the Coursera platform of the session-based “Subsistence Marketplaces” MOOC. This was the first MOOC to be offered by the College of Business at the University of Illinois …
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Modelling the impact of schools and neighbourhoods on the pupil progress and value-added from KS2 to KS4 A cluster analysis of secondary schools in England
This quantitative study adopts an innovative educational data mining technique, cluster analysis, to model the effects of secondary schools in England on their pupils’ attainment at KS4. The aim of this study is to explore how do state-funded secondary schools cluster on value-added attainment at …
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Predikciós-modellalkotás a hallgatói lemorzsolódás korai azonosítása érdekében a felsőoktatási intézményekben elérhető adatok alapján
… (Nagy-Molontay 2018) – jelzik, hogy az EDM (educational data-mining) módszertanok társadalomtudományi megközelítésű használata új lendületet ad a kutatási területnek és magas megbízhatóságú empirikus eredményekkel segít a felsőoktatás esetleges diszfunkcióinak mérséklésében (Hellas et al. …
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Categorizing and Comparing Students' Interactions in eTextbooks
… in OpenDSA, an interactive eTextbook for data structures and algorithms courses. Using session-level interaction data, we categorize engagement into four distinct engagement states, defined as types of student activities: Reading, Visualization, Proficiency Exercises, and Multiple-Choice …
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Models and Algorithms for Performance Prediction and Course Recommendation in Higher Education
Educational institutions need to use supporting tools in order to reduce high student drop-out rates and ensure their students' timely graduation. Educational data mining involves the development of such methods that leverage student data. Their purpose is to generate warnings about students that …
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Designing and evaluating a fully interpretable neural network for learner behavior detection
… where opaque decision-making processes risk undermining fairness, accountability, and trust, among other factors. This dissertation confronts this challenge by proposing and validating an alternative paradigm: developing neural networks that are interpretable by design. Through a series of three …
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UNDERSTANDING STUDENT BEHAVIORS USING IMMEDIATE FEEDBACK FEATURES IN A BLENDED LEARNING ENVIRONMENT
Feedback serves to close the gap between learners’ current understanding and the desired understanding. Informative feedback can keep students from holding onto misconceptions, actively engage learners in knowledge acquisition, and increase confidence and motivation to learn. Yet, in the context of …
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Causal Effect Random Forest Of Interaction Trees For Learning Individualized Treatment Regimes In Observational Studies: With Applications To Education Study Data
… treatment regimes (ITR) using observational data holds great interest in various fields, as treatment recommendations based on individual characteristics may improve individual treatment benefits with a reduced cost. It has long been observed that different individuals may respond to a …
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Design and Implementation of Faculty Support System to Reduce Course Dropout Rates
The primary goal of educational systems is not only to provide quality of education but also to make sure that students graduate with a strong academic standing. One specific challenge that universities face is high course drop rates. An early prediction of students’ failure may help to identify …
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