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Dissertations / Theses on the topic 'Educational data mining'

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Published: 4 June 2021

Last updated: 25 July 2025

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1

Войцун, О. Є. "Перспективи educational data mining в Україні". Thesis, Cумський державний університет, 2016. http://essuir.sumdu.edu.ua/handle/123456789/47901.

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Актуальність дослідження полягає в тому, що сучасний стан освіти вимагає використання сучасних методів для імплементації вказаних вище потреб, і educational data mining (EDM) надає унікальні можливості для дослідників і практиків. Метою роботи було виявлення перективних напрямків ЕDM для України.

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Melgueira, Pedro Miguel Lúcio. "Educational data mining applied to Moodle data from the University of Évora." Master's thesis, Universidade de Évora, 2017. http://hdl.handle.net/10174/21346.

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E-Learning tem vindo a ganhar popularidade como forma de transmissão de conhecimentos a nível educacional graças aos avanços nas tecnologias, como por exemplo, a Internet. Instituições como universidades e empresas têm vindo a usar E-Learning para a transmissão de conteúdos educacionais para locais remotos estendendo o seu alcance a estudantes e colaboradores que estão fisicamente distantes. Sistemas chamados “Learning Management Systems”, como o Moodle, existem para organizar E-Learning. Eles oferecem plataformas online onde professores e educadores podem publicar conteúdo, organizar activida

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3

Borg, Olivia. "Educational Data Mining : En kvalitativ studie med inriktning på dataanalys för att hitta mönster i närvarostatistik." Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-16987.

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Studien fokuserar på att hitta olika mönster i närvarostatistik hos elever som inte närvarar i skolan. Informationen som resultatet ger kan därefter användas som ett beslutsunderlag för skolor eller till andra organisationer som är intresserade av EDM inom närvarostatistik. Arbetet genomförde en kvalitativ metodansats med en fallstudie som bestod utav en litteraturstudie samt en implementation. Litteraturstudien användes för att få en förståelse över vanliga tillvägagångssätt inom EDM, som därefter låg till grund för implementationen som använde arbetssättet CRISP-DM. Resultatet blev fem olika

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Mavrikis, Manolis P. "Modelling students' behaviour and affect in ILE through educational data mining." Thesis, University of Edinburgh, 2008. http://hdl.handle.net/1842/15294.

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The long-term objective behind the research presented in this thesis is the improvement of ILEs and particularly those components that take into account students’ behaviour, as well as emotions and motivation. In related research, this is often attempted based on intuition, theoretical perspectives, or guided by results from studies in the isolation of a research lab. In this thesis, an attempt is made to inform the design of adaptation and feedback components by collecting and analysing as realistic data as possible. Guided by the belief that qualitative data analysis results can be enriched

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Rajibussalim. "Data Mining for Studying the Impact of Reflection on Learning." Thesis, The University of Sydney, 2010. http://hdl.handle.net/2123/10589.

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Title: Data Mining for Studying the Impact of Reflection on Learning Keywords: educational data mining, Reflect, learning behaviour, impact Abstract On-line Web-based education learning systems generate a large amount of students' log data and profiles that could be useful for educators and students. Hence, data mining techniques that enable the extraction of hidden and potentially useful information in educational databases have been employed to explore educational data. A new promising area of research called educational data mining (EDM) has emerged. Reflect is a Web-based learning system

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Alsuwaiket, Mohammed. "Measuring academic performance of students in Higher Education using data mining techniques." Thesis, Loughborough University, 2018. https://dspace.lboro.ac.uk/2134/34680.

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Educational Data Mining (EDM) is a developing discipline, concerned with expanding the classical Data Mining (DM) methods and developing new methods for discovering the data that originate from educational systems. It aims to use those methods to achieve a logical understanding of students, and the educational environment they should have for better learning. These data are characterized by their large size and randomness and this can make it difficult for educators to extract knowledge from these data. Additionally, knowledge extracted from data by means of counting the occurrence of certain

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Xu, Yonghong. "Using data mining in educational research: A comparison of Bayesian network with multiple regression in prediction." Diss., The University of Arizona, 2003. http://hdl.handle.net/10150/280504.

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Advances in technology have altered data collection and popularized large databases in areas including education. To turn the collected data into knowledge, effective analysis tools are required. Traditional statistical approaches have shown some limitations when analyzing large-scale data, especially sets with a large number of variables. This dissertation introduces to educational researchers a new data analysis approach called data mining, an analytic process at the intersection of statistics, databases, machine learning/artificial intelligence (AI), and computer science, that is designed t

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Davoodi, Alireza. "User modeling and data mining in intelligent educational games : Prime Climb a case study." Thesis, University of British Columbia, 2013. http://hdl.handle.net/2429/45274.

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Educational games are designed to leverage students’ motivation and engagement in playing games to deliver pedagogical concepts to the players during game play. Adaptive educational games, in addition, utilize students’ models of learning to support personalization of learning experience according to students’ educational needs. A student’s model needs to be capable of making an evaluation of the mastery level of the target skills in the student and providing reliable base for generating tailored interventions to meet the user’s needs. Prime Climb, an adaptive educational game for students in

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9

Dailey, Matthew D. "Learning the Effectiveness of Content and Methodology in an Intelligent Tutoring System." Digital WPI, 2011. https://digitalcommons.wpi.edu/etd-theses/684.

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Classroom instruction time is a valuable yet scarce resource to teachers, who must decide how to best meet their objectives by selecting which topics to spend time on and when to move forward. Intelligent Tutoring Systems (ITS) are a powerful tool for teachers in this regard, allowing them to measure their students' current level of knowledge, helping them gauge student knowledge acquisition, and providing them with valuable insight into learning methodologies. By using ITS to identify the effectiveness of proven methods of instruction, we can more effectively teach students both in and outsid

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Xu, Beijie. "Clustering Educational Digital Library Usage Data: Comparisons of Latent Class Analysis and K-Means Algorithms." DigitalCommons@USU, 2011. https://digitalcommons.usu.edu/etd/954.

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There are common pitfalls and neglected areas when using clustering approaches to solve educational problems. A clustering algorithm is often used without the choice being justified. Few comparisons between a selected algorithm and a competing algorithm are presented, and results are presented without validation. Lastly, few studies fully utilize data provided in an educational environment to evaluate their findings. In response to these problems, this thesis describes a rigorous study comparing two clustering algorithms in the context of an educational digital library service, called the Inst

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11

Peroutka, Lukáš. "Návrh a implementace Data Mining modelu v technologii MS SQL Server." Master's thesis, Vysoká škola ekonomická v Praze, 2012. http://www.nusl.cz/ntk/nusl-199081.

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This thesis focuses on design and implementation of a data mining solution with real-world data. The task is analysed, processed and its results evaluated. The mined data set contains study records of students from University of Economics, Prague (VŠE) over the course of past three years. First part of the thesis focuses on theory of data mining, definition of the term, history and development of this particular field. Current best practices and meth-odology are described, as well as methods for determining the quality of data and methods for data pre-processing ahead of the actual data mining

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Kehrer, Paul H. "Reaching More Students: A Web-based Intelligent Tutoring System with support for Offline Access." Digital WPI, 2012. https://digitalcommons.wpi.edu/etd-theses/336.

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ASSISTments is a web-based intelligent tutoring system that can provide students with immediate feedback when they are doing math homework. Until now, ASSISTments required internet access in order to do nightly homework. Without ASSISTments, students do their work on paper and are not told if they are correct or given help for wrong answers until the next morning at best. We've developed a component that supports 'offline-mode', enabling students without internet access at home to still receive immediate feedback on their responses. Students with laptops download their assignments at school,

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Vigentini, Lorenzo. "From learning to e-learning : mining educational data : a novel, data-driven approach to evaluate individual differences in students' interaction with learning technology." Thesis, University of Edinburgh, 2010. http://hdl.handle.net/1842/5532.

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In recent years, learning technology has become a very important addition to the toolkit of instructors at any level of education and training. Not only offered as a substitute in distance education, but often complementing traditional delivery methods, e-learning is considered an important component of modern pedagogy. Particularly in the last decade, learning technology has seen a very rapid growth following the large-scale development and deployment of e-learning financed by both Governments and commercial enterprises. These turned e-learning into one of the most profitable sectors of the n

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Wang, Yutao. "Student Modeling within a Computer Tutor for Mathematics: Using Bayesian Networks and Tabling Methods." Digital WPI, 2015. https://digitalcommons.wpi.edu/etd-dissertations/383.

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"Intelligent tutoring systems rely on student modeling to understand student behavior. The result of student modeling can provide assessment for student knowledge, estimation of student¡¯s current affective states (ie boredom, confusion, concentration, frustration, etc), prediction of student performance, and suggestion of the next tutoring steps. There are three focuses of this dissertation. The first focus is on better predicting student performance by adding more information, such as student identity and information about how many assistance students needed. The second focus is to analyze d

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Mendes, Renê de Ávila. "Aplicação da arquitetura lambda na construção de um ambiente big data educacional para análise de dados." Universidade Presbiteriana Mackenzie, 2017. http://tede.mackenzie.br/jspui/handle/tede/3441.

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Submitted by Marta Toyoda (1144061@mackenzie.br) on 2018-02-09T19:36:53Z No. of bitstreams: 2 RENÊ DE ÁVILA MENDES.pdf: 2131022 bytes, checksum: 371eff9a643c4104cbd7ced2b556bab5 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5)<br>Approved for entry into archive by Paola Damato (repositorio@mackenzie.br) on 2018-02-22T13:28:09Z (GMT) No. of bitstreams: 2 RENÊ DE ÁVILA MENDES.pdf: 2131022 bytes, checksum: 371eff9a643c4104cbd7ced2b556bab5 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5)<br>Made available in DSpace on 2018-02-22T13:28:09Z (GM

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Krasniuk, M. T., and S. O. Krasniuk. "Analysis of teaching experience and prospects of the "Data Mining" and "Data Science" disciplines in light of actual world macroeconomic and educational trends." Thesis, Київський національний університет технологій та дизайну, 2020. https://er.knutd.edu.ua/handle/123456789/16653.

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McKeague-McFadden, Ikaika A. "Identifying Students at Risk of Not Passing Introductory Physics Using Data Mining and Machine Learning." Miami University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=miami1596214863294544.

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Zhu, Linglong. "A Prediction Model Uses the Sequence of Attempts and Hints to Better Predict Knowledge: Better to Attempt the Problem First, Rather Than Ask for A Hint." Digital WPI, 2014. https://digitalcommons.wpi.edu/etd-theses/445.

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Intelligent Tutoring Systems (ITS) have been proven to be efficient in providing students assistance and assessing their performance when they do their homework. Many research projects have been done to analyze how students' knowledge grows and to predict their performance from within intelligent tutoring system. Most of them focus on using correctness of the previous question or the number of hints and attempts students need to predict their future performance, but ignore how they ask for hints and make attempts. In this research work, we build a Sequence of Actions (SOA) model taking advant

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Alvarado, Mantecon Jesus Gerardo. "Towards the Automatic Classification of Student Answers to Open-ended Questions." Thesis, Université d'Ottawa / University of Ottawa, 2019. http://hdl.handle.net/10393/39093.

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One of the main research challenges nowadays in the context of Massive Open Online Courses (MOOCs) is the automation of the evaluation process of text-based assessments effectively. Text-based assessments, such as essay writing, have been proved to be better indicators of higher level of understanding than machine-scored assessments (E.g. Multiple Choice Questions). Nonetheless, due to the rapid growth of MOOCs, text-based evaluation has become a difficult task for human markers, creating the need of automated systems for grading. In this thesis, we focus on the automated short answer gradi

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Xu, Beijie. "Understanding Teacher Users of a Digital Library Service: A Clustering Approach." DigitalCommons@USU, 2011. https://digitalcommons.usu.edu/etd/890.

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This research examined teachers' online behaviors while using a digital library service--the Instructional Architect (IA)--through three consecutive studies. In the first two studies, a statistical model called latent class analysis (LCA) was applied to cluster different groups of IA teachers according to their diverse online behaviors. The third study further examined relationships between teachers' demographic characteristics and their usage patterns. Several user clusters emerged from the LCA results of Study I. These clusters were named isolated islanders, lukewarm teachers, goal-oriented

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Moro, Luis Fernando de Souza. "Caracterização de alunos em ambientes de ensino online: estendendo o uso da DAMICORE para minerar dados educacionais." Universidade de São Paulo, 2015. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-14092015-164510/.

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Com a popularização do uso de recursos tecnológicos na educação, uma enorme quantidade de dados, relacionados às interações entre alunos e esses recursos, é armazenada. Analisar esses dados, visando caracterizar os alunos, é tarefa muito importante, uma vez que os resultados dessa análise podem auxiliar professores no processo de ensino e aprendizagem. Entretanto, devido ao fato de as ferramentas utilizadas para essa caracterização serem complexas e pouco intuitivas, os profissionais da área de ensino acabam por não utilizá-las, inviabilizando a implementação de tais ferramentas em ambientes e

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Chapman, John Shadrack. "Task-Level Feedback in Interactive Learning Enivonments Using a Rules Based Grading Engine." BYU ScholarsArchive, 2016. https://scholarsarchive.byu.edu/etd/6605.

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In order to improve the feedback an intelligent tutoring system provides, the grading engine needs to do more than simply indicate whether a student gives a correct answer or not. Good feedback must provide actionable information with diagnostic value. This means the grading system must be able to determine what knowledge gap or misconception may have caused the student to answer a question incorrectly. This research evaluated the quality of a rules-based grading engine in an automated online homework system by comparing grading engine scores with manually graded scores. The research sough

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Kane-Sellers, Marjorie Laura. "Predictive models of employee voluntary turnover in a North American professional sales force using data-mining analysis." [College Station, Tex. : Texas A&M University, 2007. http://hdl.handle.net/1969.1/ETD-TAMU-1486.

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Menon, Akash, and Nahida Islam. "An investigation of the relationship between online activity on Studi.se and academic grades of newly arrived immigrant students : An application of educational data mining." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-211668.

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This study attempts to analyze the impact of an online educational resource on academic performances among newly arrived immigrant students in Sweden between the grade six to nine in the Swedish school system. The study focuses on the web based educational resource called Studi.se made by Komplementskolan AB.The aim of the study was to investigate the relationship between academic performance and using Studi.se. Another purpose was to see what other factors that can impact academic performances.The study made use of the data mining process, Cross Industry Standard for Data Mining (CRISP-DM), t

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Goldstein, Adam B. "Responding to Moments of Learning." Digital WPI, 2011. https://digitalcommons.wpi.edu/etd-theses/685.

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In the field of Artificial Intelligence in Education, many contributions have been made toward estimating student proficiency in Intelligent Tutoring Systems (cf. Corbett & Anderson, 1995). Although the community is increasingly capable of estimating how much a student knows, this does not shed much light on when the knowledge was acquired. In recent research (Baker, Goldstein, & Heffernan, 2010), we created a model that attempts to answer that exact question. We call the model P(J), for the probability that a student just learned from the last problem they answered. We demonstrated an analysi

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Whitlock, Joshua Lee. "Using Data Science and Predictive Analytics to Understand 4-Year University Student Churn." Digital Commons @ East Tennessee State University, 2018. https://dc.etsu.edu/etd/3356.

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The purpose of this study was to discover factors about first-time freshmen that began at one of the six 4-year universities in the former Tennessee Board of Regents (TBR) system, transferred to any other institution after their first year, and graduated with a degree or certificate. These factors would be used with predictive models to identify these students prior to their initial departure. Thirty-four variables about students and the institutions that they attended and graduated from were used to perform principal component analysis to examine the factors involved in their decisions. A sub

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Medina, Erik Cevallos, Claudio Barahona Chunga, Jimmy Armas-Aguirre, and Elizabeth E. Grandon. "Predictive model to reduce the dropout rate of university students in Perú: Bayesian Networks vs. Decision Trees." IEEE Computer Society, 2020. http://hdl.handle.net/10757/656775.

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El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado.<br>This research proposes a prediction model that might help reducing the dropout rate of university students in Peru. For this, a three-phase predictive analysis model was designed which was combined with the stages proposed by the IBM SPSS Modeler methodology. Bayesian network techniques was compared with decision trees for their level of accuracy over other algorithms in an Educational Data Mining (EDM) scenario. Data were collected from 500 un

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Mirashrafi, Seyed Bagher [Verfasser], and G. [Akademischer Betreuer] Nakhaeizadeh. "Applying of Data Mining and Statistical Techniques to Analyze the Impact of Socioeconomic Background on University Admission - A Case Study Using the Iranian Educational Data / Seyed Bagher Mirashrafi. Betreuer: G. Nakhaeizadeh." Karlsruhe : KIT-Bibliothek, 2016. http://d-nb.info/1112224521/34.

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Li, Shoujing. "Modeling Student Retention in an Environment with Delayed Testing." Digital WPI, 2013. https://digitalcommons.wpi.edu/etd-theses/266.

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Over the last two decades, the field of educational data mining (EDM) has been focusing on predicting the correctness of the next student response to the question (e.g., [2, 6] and the 2010 KDD Cup), in other words, predicting student short-term performance. Student modeling has been widely used for making such inferences. Although performing well on the immediate next problem is an indicator of mastery, it is by far not the only criteria. For example, the Pittsburgh Science of Learning Center's theoretic framework focuses on robust learning (e.g., [7, 10]), which includes the ability to tran

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Molen, Moris Johan van der. "Minería de datos educacionales: modelos de predicción del desempeño escolar en alumnos de enseñanza básica." Tesis, Universidad de Chile, 2013. http://www.repositorio.uchile.cl/handle/2250/113034.

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Ingeniero Civil Matemático<br>En los últimos años, se ha abierto una oportunidad de hacer análisis más precisos de las habilidades y desempeños de los estudiantes. De a poco, han comenzado a proliferar sistemas de ejercitación en línea y tutores inteligentes que permiten registrar una gran cantidad de información valiosa referente al aprendizaje de los alumnos. La Minería de Datos Educacionales (MDE), es un campo de estudio dedicado a desarrollar métodos matemáticos para analizar datos provenientes de ambientes relacionados a la educación, y extraer la mayor cantidad de información para tratar

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Falci, Júnior Geraldo Ramos. "Metodologia de mineração de dados para ambientes educacionais online." [s.n.], 2010. http://repositorio.unicamp.br/jspui/handle/REPOSIP/259203.

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Orientador: Ivan Luiz Marques Ricarte<br>Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação<br>Made available in DSpace on 2018-08-17T16:59:53Z (GMT). No. of bitstreams: 1 FalciJunior_GeraldoRamos_M.pdf: 698385 bytes, checksum: 02542ffd87be662788d4f79b80ba9a7a (MD5) Previous issue date: 2010<br>Resumo: Educação a distância populariza-se como meio prático de ensino com a expansão de recursos computacionais e da Internet. Apesar disto, ela traz dificuldades ao educador para compreender as necessidades de suas classes. A análise do uso d

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CESARETTI, LORENZO. "How students solve problems during Educational Robotics activities: identification and real-time measurement of problem-solving patterns." Doctoral thesis, Università Politecnica delle Marche, 2020. http://hdl.handle.net/11566/274358.

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Questa tesi presenta l’utilizzo di tecniche di data mining e machine learning per la valutazione di attività di Robotica Educativa. Gli obiettivi di questo lavoro di ricerca sono tre: identificare differenti pattern durante le attività di problem-solving degli studenti; predire il risultato finale ottenuto nella risoluzione delle sfide di programmazione (e annotato dagli educatori) utilizzando tecniche machine learning; analizzare le correlazioni tra i pattern ottenuti e la valutazione assegnata dagli educatori. Per raggiungere questi obiettivi è stata svolta una sperimentazione con 455 stud

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Schultz, Sarah E. "Tracing Knowledge and Engagement in Parallel by Observing Behavior in Intelligent Tutoring Systems." Digital WPI, 2015. https://digitalcommons.wpi.edu/etd-theses/140.

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Two of the major goals in Educational Data Mining are determining studentsâ€™ state of knowledge and determining their affective state. It is useful to be able to determine whether a student is engaged with a tutor or task in order to adapt to his/her needs and necessary to have an idea of the students' knowledge state in order to provide material that is appropriately challenging. These two problems are usually examined separately and multiple methods have been proposed to solve each of them. However, little work has been done on examining both of these states in parallel and the combined eff

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Martinez, Maldonado Roberto. "Analysing, visualising and supporting collaborative learning using interactive tabletops." Thesis, The University of Sydney, 2013. http://hdl.handle.net/2123/10409.

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The key contribution of this thesis is a novel approach to design, implement and evaluate the conceptual and technological infrastructure that captures student’s activity at interactive tabletops and analyses these data through Interaction Data Analytics techniques to provide support to teachers by enhancing their awareness of student’s collaboration. To achieve the above, this thesis presents a series of carefully designed user studies to understand how to capture, analyse and distil indicators of collaborative learning. We perform this in three steps: the exploration of the feasibility of th

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Farghally, Mohammed Fawzi Seddik. "Visualizing Algorithm Analysis Topics." Diss., Virginia Tech, 2016. http://hdl.handle.net/10919/73539.

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Data Structures and Algorithms (DSA) courses are critical for any computer science curriculum. DSA courses emphasize concepts related to procedural dynamics and Algorithm Analysis (AA). These concepts are hard for students to grasp when conveyed using traditional textbook material relying on text and static images. Algorithm Visualizations (AVs) emerged as a technique for conveying DSA concepts using interactive visual representations. Historically, AVs have dealt with portraying algorithm dynamics, and the AV developer community has decades of successful experience with this. But there exist

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Sherzad, Abdul Rahman [Verfasser], Uwe [Akademischer Betreuer] Nestmann, Uwe [Gutachter] Nestmann, Niels [Gutachter] Pinkwart, Sebastian [Gutachter] Bab, and Nazir [Gutachter] Peroz. "Shaping the selection of fields of study in Afghanistan through educational data mining approaches / Abdul Rahman Sherzad ; Gutachter: Uwe Nestmann, Niels Pinkwart, Sebastian Bab, Nazir Peroz ; Betreuer: Uwe Nestmann." Berlin : Technische Universität Berlin, 2018. http://d-nb.info/1164076450/34.

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Fernandes, Warley Leite. "Aplica??o do algoritmo de classifica??o associativa (CBA) em bases educacionais para predi??o de desempenho." UFVJM, 2017. http://acervo.ufvjm.edu.br/jspui/handle/1/1726.

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Submitted by Jos? Henrique Henrique (jose.neves@ufvjm.edu.br) on 2018-05-23T19:00:06Z No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) warley_leite_fernandes.pdf: 2460576 bytes, checksum: d929e82a2e47dac8f54b1a1d52ed28fb (MD5)<br>Approved for entry into archive by Rodrigo Martins Cruz (rodrigo.cruz@ufvjm.edu.br) on 2018-06-05T14:49:36Z (GMT) No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) warley_leite_fernandes.pdf: 2460576 bytes, checksum: d929e82a2e47dac8f54b1a1d52ed28fb (MD5)<br>Made available in DSp

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Pardos, Zachary Alexander. "Predictive Models of Student Learning." Digital WPI, 2012. https://digitalcommons.wpi.edu/etd-dissertations/185.

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In this dissertation, several approaches I have taken to build upon the student learning model are described. There are two focuses of this dissertation. The first focus is on improving the accuracy with which future student knowledge and performance can be predicted by individualizing the model to each student. The second focus is to predict how different educational content and tutorial strategies will influence student learning. The two focuses are complimentary but are approached from slightly different directions. I have found that Bayesian Networks, based on belief propagation, are stron

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Miled, Mahdi. "Ressources et parcours pour l'apprentissage du langage Python : aide à la navigation individualisée dans un hypermédia épistémique à partir de traces." Thesis, Cachan, Ecole normale supérieure, 2014. http://www.theses.fr/2014DENS0045/document.

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Les travaux de recherche de cette thèse concernent principalement l‘aide à la navigation individualisée dans un hypermédia épistémique. Nous disposons d‘un certain nombre de ressources qui peut se formaliser à l‘aide d‘un graphe acyclique orienté (DAG) : le graphe des épistèmes. Après avoir cerné les environnements de ressources et de parcours, les modalités de visualisation et de navigation, de traçage, d‘adaptation et de fouille de données, nous avons présenté une approche consistant à corréler les activités de conception ou d‘édition à celles dédiées à l‘utilisation et la navigation dans le

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Borges, Vanessa Araujo. "Definição de um modelo de referência de dados educacionais para a descoberta de conhecimento." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-09112018-103702/.

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Sistemas educacionais possuem diversas funcionalidades capazes de apoiar a interação entre alunos e professores de maneira dinâmica, síncrona e assíncrona. Uma das formas de monitorar a eficácia do processo educacional e por meio da utilização dos dados armazenados nesses sistemas como fonte de informação. Pesquisas em Learning Analytics, Academic Analytics e Mineração de Dados Educacionais, buscam explorar os dados de sistemas educacionais utilizando processamento analítico e técnicas de mineração de dados. No entanto, há uma serie de fatores que dificultam a gestão eficiente do processo educ

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MELO, Allan Sales da Costa. "Previsão automática de evasão estudantil: um estudo de caso na UFCG." Universidade Federal de Campina Grande, 2016. http://dspace.sti.ufcg.edu.br:8080/jspui/handle/riufcg/800.

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Submitted by Maria Medeiros (maria.dilva1@ufcg.edu.br) on 2018-05-24T14:28:20Z No. of bitstreams: 1 ALLAN SALES DA COSTA MELO - DISSERTAÇÃO (PPGCC) 2016.pdf: 1339540 bytes, checksum: b3bbc96d990dd77ee344c4f5434a4d00 (MD5)<br>Made available in DSpace on 2018-05-24T14:28:20Z (GMT). No. of bitstreams: 1 ALLAN SALES DA COSTA MELO - DISSERTAÇÃO (PPGCC) 2016.pdf: 1339540 bytes, checksum: b3bbc96d990dd77ee344c4f5434a4d00 (MD5) Previous issue date: 2016<br>A evasão estudantil é uma das maiores preocupações dos institutos de ensino superior brasileiros já que ela pode ser uma das causas de desperdíci

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Gottardo, Ernani. "Estimativa de desempenho acadêmico de estudantes em um AVA utilizando técnicas de mineração de dados." Universidade Tecnológica Federal do Paraná, 2012. http://repositorio.utfpr.edu.br/jspui/handle/1/439.

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Alguns ambientes educacionais têm incorporado softwares que são utilizados como apoio ou, em alguns casos, como condição básica para a disponibilização de cursos. Neste cenário, destacam-se os Ambientes Virtuais de Aprendizagem (AVA) usados para apoiar o desenvolvimento de cursos presenciais, semipresenciais e a distância. Os AVA caracterizam-se por armazenar um grande volume de dados. Contudo, esses ambientes carecem de ferramentas que permitam extrair informações úteis para o desenvolvimento de processos de acompanhamento eficiente dos estudantes. Diante disso, esta pesquisa investiga como o

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AMARAL, Marcelo Gomes do. "Mineração de dados aplicada à classificação do risco de evasão de discentes ingressantes em instituições federais de ensino superior." Universidade Federal de Pernambuco, 2016. https://repositorio.ufpe.br/handle/123456789/19502.

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Submitted by Fabio Sobreira Campos da Costa (fabio.sobreira@ufpe.br) on 2017-07-11T14:35:16Z No. of bitstreams: 3 license_rdf: 811 bytes, checksum: e39d27027a6cc9cb039ad269a5db8e34 (MD5) projeto_v26016.pdf: 1271790 bytes, checksum: f724d8523f2ffdb11ce599aff1eb8eb6 (MD5) projeto_v26016.pdf: 1271790 bytes, checksum: f724d8523f2ffdb11ce599aff1eb8eb6 (MD5)<br>Made available in DSpace on 2017-07-11T14:35:16Z (GMT). No. of bitstreams: 3 license_rdf: 811 bytes, checksum: e39d27027a6cc9cb039ad269a5db8e34 (MD5) projeto_v26016.pdf: 1271790 bytes, checksum: f724d8523f2ffdb11ce599aff1eb8eb6 (MD5) p

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Silva, Sandro José Ribeiro da. "TRILUA: um ambiente gamificado para apoio ao ensino de lógica de programação." Universidade do Vale do Rio dos Sinos, 2016. http://www.repositorio.jesuita.org.br/handle/UNISINOS/6050.

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Submitted by Silvana Teresinha Dornelles Studzinski (sstudzinski) on 2017-03-03T16:51:21Z No. of bitstreams: 1 Sandro José Ribeiro da Silva_.pdf: 1958508 bytes, checksum: 927c5b673859ca465e35998f946b5a64 (MD5)<br>Made available in DSpace on 2017-03-03T16:51:21Z (GMT). No. of bitstreams: 1 Sandro José Ribeiro da Silva_.pdf: 1958508 bytes, checksum: 927c5b673859ca465e35998f946b5a64 (MD5) Previous issue date: 2016-11-03<br>Nenhuma<br>O desenvolvimento de habilidades de programação de sistemas computacionais é uma necessidade crescente, devido ao amplo uso de recursos computacionais nas mais

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Xiong, Xiaolu. "Theory and Practice: Improving Retention Performance through Student Modeling and System Building." Digital WPI, 2017. https://digitalcommons.wpi.edu/etd-dissertations/139.

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The goal of Intelligent Tutoring systems (ITSs) is to engage the students in sustained reasoning activity and to interact with students based on a deep understanding of student behavior. In order to understand student behavior, ITSs rely on student modeling methods to observes student actions in the tutor and creates a quantitative representation of student knowledge, interests, affective states. Good student models are going to effectively help ITSs customize instructions, engage student's interest and then promote learning. Thus, the work of building ITSs and advancing student modeling shoul

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Santana, Marcelo Almeida. "Um estudo comparativo das técnicas de predição na identificação de insucesso acadêmico dos estudantes durante cursos de programação introdutória." Universidade Federal de Alagoas, 2015. http://www.repositorio.ufal.br/handle/riufal/1722.

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The high failure rates of students in the introductory programming course within the universities worldwide have alarmed and worried many educators. Those rates can lead to losses of various types and interests. Thus, there are important reasons to try to clarify the main factors that possibly influence such failures. Furthermore, one of the major challenges is on how to early identify the students likely to in the introductory programming course, eventually allowing effective pedagogical interventions. Thus, in this study we aim to explore educational data mining techniques, in order to compa

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Cambruzzi, Wagner Luiz. "GVwise: uma aplicação de learning analytics para a redução da evasão na educação à distância." Universidade do Vale do Rio dos Sinos, 2014. http://www.repositorio.jesuita.org.br/handle/UNISINOS/4646.

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Submitted by William Justo Figueiro (williamjf) on 2015-07-28T20:32:18Z No. of bitstreams: 1 27d.pdf: 4180188 bytes, checksum: 617cda1d8cedaa910bb66676e96c33d1 (MD5)<br>Made available in DSpace on 2015-07-28T20:32:18Z (GMT). No. of bitstreams: 1 27d.pdf: 4180188 bytes, checksum: 617cda1d8cedaa910bb66676e96c33d1 (MD5) Previous issue date: 2014-04-15<br>Nenhuma<br>Aplicações que fazem uso de tecnologias como Mineração de Dados Educacionais (MDE) e Learning Analytics (LA) vêm sendo adotadas na mitigação da evasão escolar, disponibilizando informações sobre os alunos que são utilizadas em in

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Sao, Pedro Michael A. "Real-time Assessment, Prediction, and Scaffolding of Middle School Studentsâ€™ Data Collection Skills within Physical Science Simulations." Digital WPI, 2013. https://digitalcommons.wpi.edu/etd-dissertations/168.

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Despite widespread recognition by science educators, researchers and K-12 frameworks that scientific inquiry should be an essential part of science education, typical classrooms and assessments still emphasize rote vocabulary, facts, and formulas. One of several reasons for this is that the rigorous assessment of complex inquiry skills is still in its infancy. Though progress has been made, there are still many challenges that hinder inquiry from being assessed in a meaningful, scalable, reliable and timely manner. To address some of these challenges and to realize the possibility of formative

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Stützer, Cathleen M. "Informations- und Wissenstransfer in kollaborativen Lernsystemen." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2013. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-130139.

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In der Netzwerkgesellschaft des 21. Jahrhunderts gilt die kollaborative Verteilung und Nutzung von Information und Wissen als Schlüsselstrategie für den webbasierten Informations- und Wissenstransfer. Durch die technologischen Möglichkeiten werden technische Zugangsbarrieren weitestgehend überwunden und traditionelle Formen der Wissensvermittlung durch moderne webbasierte Lernumgebungen ergänzt. Der Umgang mit kollaborativen Lehr- und Lernszenarien im dynamischen Informations- und Wissenstransfer bildet die Grundlage für den soziokulturellen Fortschritt innerhalb der Bildungsforschung. Der Sch

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Manspeaker, Rachel Bechtel. "Using data mining to differentiate instruction in college algebra." Diss., Kansas State University, 2011. http://hdl.handle.net/2097/8542.

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Doctor of Philosophy<br>Department of Mathematics<br>Andrew G. Bennett<br>The main objective of the study is to identify the general characteristics of groups within a typical Studio College Algebra class and then adapt aspects of the course to best suit their needs. In a College Algebra class of 1,200 students, like those at most state funded universities, the greatest obstacle to providing personalized, effective education is the anonymity of the students. Data mining provides a method for describing students by making sense of the large amounts of information they generate. Instructors

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