Thesis (Ph. D.)--University of Washington, 2002. / Vita. Includes bibliographical references (leaves 224-232).

With the development of computer technology and Internet, e-Learning has become more and more important to support student¡¦s learning. Novice students usually lack adequate assisting tools especially in programming learning. Therefore, we propose the problem-based Python programming learning system with extendable item-bank. The system can generate program debugging exercise by using mutation testing technology. Additionally, for enhancing student¡¦s problem-exploration and reasoning capacity, the system provide another practice - Programming Exercise Creating Practice. In this kind of practice, every student can create his own programming exercise using question template and answer code template. This practice not only can enhance student¡¦s capacity but also can rich enrich the system¡¦s item-bank by using this strategy. Different from other programming learning systems, our system provide a more complete trainings on programming capacities, and building with Web2.0 concept. So, student who learns programming on this system will not only do exercise, but he also can help other students. So, student can get more kind of learning chance in this way. Additionally, we also hope that teacher¡¦s loading will be decreased and quality of course will be increased by using this system.

abstract: Online learning platforms such as massive online open courses (MOOCs) and intelligent tutoring systems (ITSs) have made learning more accessible and personalized. These systems generate unprecedented amounts of behavioral data and open the way for predicting students’ future performance based on their behavior, and for assessing their strengths and weaknesses in learning. This thesis attempts to mine students’ working patterns using a programming problem solving system, and build predictive models to estimate students’ learning. QuizIT, a programming solving system, was used to collect students’ problem-solving activities from a lower-division computer science programming course in 2016 Fall semester. Differential mining techniques were used to extract frequent patterns based on each activity provided details about question’s correctness, complexity, topic, and time to represent students’ behavior. These patterns were further used to build classifiers to predict students’ performances. Seven main learning behaviors were discovered based on these patterns, which provided insight into students’ metacognitive skills and thought processes. Besides predicting students’ performance group, the classification models also helped in finding important behaviors which were crucial in determining a student’s positive or negative performance throughout the semester. / Dissertation/Thesis / Masters Thesis Computer Science 2017

We launched an original large-scale experiment concerning informatics learning in French high schools. We are using the France-IOI platform to federate resources and share observation for research. The first step is the implementation of an adaptive hypermedia based on very fine grain epistemic modules for Python programming learning. We define the necessary traces to be built in order to study the trajectories of navigation the pupils will draw across this hypermedia. It may be browsed by pupils either as a course support, or an extra help to solve the list of exercises (mainly for algorithmics discovery). By leaving the locus of control to the learner, we want to observe the different trajectories they finally draw through our system. These trajectories may be abstracted and interpreted as strategies and then compared for their relative efficiency. Our hypothesis is that learners have different profiles and may use the appropriate strategy accordingly. This paper presents the research questions, the method and the expected results.

There is a high demand for program developers, but the dropouts from computer science courses are also high and course enrolments keep decreasing. In order to overcome that situation, several studies have found serious games as good tools for education in programming learning. As an outcome from such research, several game solutions for programming learning have appeared, each of them using a different approach. Some of these games are only used in the research field where others are published in commercial stores. The problem with commercial games is that they do not offer a clear map of the different programming concepts. This dissertation addresses this problem and analyses which fundamental programming concepts that are represented in commercial games for programming learning. The study also identifies game design patterns used to represent these concepts. The result of this study shows topics that are represented more commonly in commercial games and what game design patterns are used for that. This thesis identifies a set of game design patterns in the 20 commercial games that were analysed. A description as well as some examples of the games where it is found is included for each of these patterns. As a conclusion, this research shows that from the list of the determined fundamental programming topics only a few of them are greatly represented in commercial games where the others have nearly no representation. This shows potential spots for future research in games for programming teaching.

Diagnóstico baseado em modelos (Model Based Diagnosis - MBD) é uma técnica de Inteligência Artificial usada para encontrar componentes falhos em dispositivos físicos. MBD também tem sido utilizado para auxiliar programadores experientes a encontrarem falhas em seus programas, sendo essa técnica chamada de Depuração de Programas baseada em Modelos (Model Based Software Debugging - MBSD). Embora o MBSD possa auxiliar programadores experientes a entenderem e corrigirem suas falhas, essa abordagem precisa ser aprimorada para ser usada por aprendizes de programação. Esse trabalho propõe o uso da técnica de depuração hierárquica de programas, uma extensão da técnica MBSD, para que aprendizes de programação sejam capazes de depurar seus programas raciocinando sobre componentes abstratos, tais como: padrões elementares, funções e procedimentos. O depurador hierárquico de programas proposto foi integrado ao Dr. Java e avaliado com um grupo de alunos de uma disciplina de Introdução à Programação. Os resultados mostram que a maioria dos alunos foi capaz de compreender as hipóteses de falha geradas pelo depurador automático e usar essas informações para corrigirem seus programas. / Model Based Diagnosis (MBD) in Artificial Intelligence is a technique that has been used to detect faulty components in physical devices. MBD has also been used to help senior programmers to locate faults in software with a technique known as Model Based Software Debugging (MBSD). Although this approach can help experienced programmers to detect and correct faults in their programs, this approach must be improved to be used with novice programmers. This work proposes a hierarchical program diagnosis, a MBSD extension, to help novice programmers to debug programs by exploring the idea of abstract components, such as: elementary patterns, functions and procedures. The hierarchical program debugger proposed was integrated to the Dr. Java tool and evaluated with students of an introductory programming course. The results showed that most of the students were able to understand the hypotheses of failure presented by the automated debugger and use this information to provide a correction for their programs

Submitted by Marlene Santos (marlene.bc.ufg@gmail.com) on 2014-11-14T19:45:20Z No. of bitstreams: 2 Dissertação - Alexis Vinícius de Aquino Leal - 2014.pdf: 7963653 bytes, checksum: 1b2a031ad6e6705b89c7e91509bce8ff (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) / Approved for entry into archive by Jaqueline Silva (jtas29@gmail.com) on 2014-11-17T14:47:50Z (GMT) No. of bitstreams: 2 Dissertação - Alexis Vinícius de Aquino Leal - 2014.pdf: 7963653 bytes, checksum: 1b2a031ad6e6705b89c7e91509bce8ff (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) / Made available in DSpace on 2014-11-17T14:47:50Z (GMT). No. of bitstreams: 2 Dissertação - Alexis Vinícius de Aquino Leal - 2014.pdf: 7963653 bytes, checksum: 1b2a031ad6e6705b89c7e91509bce8ff (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) Previous issue date: 2014-02-11 / Fundação de Amparo à Pesquisa do Estado de Goiás - FAPEG / Research indicates that the use of patterns in teaching programming achieve good results when included in the curriculum for High School students. However, only the use of patterns may not be sufficient to motivate students to learn programming. This work shows the results obtained by combining the teaching of Pattern-Oriented Programming (PO), along with games using materials concrete, in non-formal settings of computer programming,withHighSchoolstudents.AcasestudywasconductedwithHighSchoolstudents at the Federal Institute of Mato Grosso, the campus of Barra do Garças, and involved 30 students in the first year of High School, discipline Logic of Programming in the year 2012 . We presented in the computer lab, and discussed nine programming patterns used in teaching the subject. In addition to practical exercises using programming language C++programming,thestudentsweredividedinto5(five)groupsandcreatedgamesusing concrete materials, applying them in a gymnasium. To establish and implement games, the students made connections with programming patterns, in the teaching and learning process of computer programming. The results show an improvement in motivation and learningtoallywithgames programmingpatterns using concrete materials. / Pesquisas indicam que o uso de padrões no ensino de programação alcança bons resultados quando incluído no currículo dos estudantes do Ensino Médio. No entanto, apenas o uso de padrões pode não ser suficiente para motivar os alunos a aprender programação. Este trabalho demonstra os resultados obtidos através da combinação do ensino de programaçãobaseadoempadrões,juntamentecomjogosusandomateriaisconcretos,em espaços não formais de programação de computadores, com alunos do Ensino Médio. O estudo de caso foi realizado com alunos do Ensino Médio no Instituto Federal de Mato Grosso, câmpus da cidade de Barra do Garças e envolveu 30 estudantes do primeiro ano do Ensino Médio, da disciplina Lógica de Programação no ano de 2012. No laboratório de informática, foram apresentados e discutidos nove padrões de programação utilizados no ensino da disciplina. Além de exercícios práticos de programação utilizando a linguagem de programação C++, os estudantes foram divididos em 5 (cinco) grupos e criaram jogos usando materiais concretos, aplicando-os em uma quadra de esportes. Ao criarem e aplicarem os jogos, os estudantes fizeram as conexões com os padrões de programação no processo de ensino e aprendizagem de programação de computadores. Os resultados mostramumamelhorianamotivaçãoeaprendizagemaosealiarpadrõesdeprogramação comjogosusandomateriais concretos

Diagnóstico baseado em modelos (Model Based Diagnosis - MBD) é uma técnica de Inteligência Artificial usada para encontrar componentes falhos em dispositivos físicos. MBD também tem sido utilizado para auxiliar programadores experientes a encontrarem falhas em seus programas, sendo essa técnica chamada de Depuração de Programas baseada em Modelos (Model Based Software Debugging - MBSD). Embora o MBSD possa auxiliar programadores experientes a entenderem e corrigirem suas falhas, essa abordagem precisa ser aprimorada para ser usada por aprendizes de programação. Esse trabalho propõe o uso da técnica de depuração hierárquica de programas, uma extensão da técnica MBSD, para que aprendizes de programação sejam capazes de depurar seus programas raciocinando sobre componentes abstratos, tais como: padrões elementares, funções e procedimentos. O depurador hierárquico de programas proposto foi integrado ao Dr. Java e avaliado com um grupo de alunos de uma disciplina de Introdução à Programação. Os resultados mostram que a maioria dos alunos foi capaz de compreender as hipóteses de falha geradas pelo depurador automático e usar essas informações para corrigirem seus programas. / Model Based Diagnosis (MBD) in Artificial Intelligence is a technique that has been used to detect faulty components in physical devices. MBD has also been used to help senior programmers to locate faults in software with a technique known as Model Based Software Debugging (MBSD). Although this approach can help experienced programmers to detect and correct faults in their programs, this approach must be improved to be used with novice programmers. This work proposes a hierarchical program diagnosis, a MBSD extension, to help novice programmers to debug programs by exploring the idea of abstract components, such as: elementary patterns, functions and procedures. The hierarchical program debugger proposed was integrated to the Dr. Java tool and evaluated with students of an introductory programming course. The results showed that most of the students were able to understand the hypotheses of failure presented by the automated debugger and use this information to provide a correction for their programs

TITLE: LEGO Mindstorms: Didactic utilization in mathematics with a focus on fractals ABSTRACT: The objective of this thesis is to determine whether the teaching of fractal geometry supported by computer and robotic LEGO Mindstorms NXT has its place in the education of primary and secondary schools pupils in the Czech Republic. The theoretical part focuses on key topics and personalities closely connected to fractal geometry problematics. It provides a brief historical overview of the fractal geometry development, its potential use in teaching mathematics (with reference to Turkish curriculum documents), and a description of LEGO Mindstorms NXT which can well serve as a manual for teachers and pupils. The practical part contains instructions for building a robotic turtle as well as a proposal of teaching block aimed to support pupils' algorithmic and geometric thinking including key competencies. Quantitative comparison of the results taken from Turkish studies and evaluation of the project by the author and pupils are a part of the experiment as well. KEYWORDS: LEGO Mindstorms NXT, fractal, programming, Logo, learning by doing, turtle, Papert, L-system, microworlds

Submitted by Verena Pereira (verenagoncalves@uefs.br) on 2018-07-13T21:40:59Z No. of bitstreams: 1 Dissertacao_Mestrado___Bianca_Santana_VF.pdf: 15500523 bytes, checksum: c68a13df2b7edb9a38dcd4a535b47768 (MD5) / Made available in DSpace on 2018-07-13T21:40:59Z (GMT). No. of bitstreams: 1 Dissertacao_Mestrado___Bianca_Santana_VF.pdf: 15500523 bytes, checksum: c68a13df2b7edb9a38dcd4a535b47768 (MD5) Previous issue date: 2018-04-06 / Funda??o de Amparo ? Pesquisa do Estado da Bahia - FAPEB / The proposed approach combines the use of the Scratch environment in a context of game creation, the Python programming language associated with the turtle graphics library, and image manipulation with the Jython Environment for Students (JES). We conducted two exploratory case studies with Civil Engineering students attending a CS1 course at our institution to analyze the impact of this approach on student motivation and learning. Our results describe the motivation present during the course in terms of the Attention, Relevance, Confidence and Satisfaction (ARCS) model, and identify the practical factors that may contribute to increase or decrease student motivation. We also present a framework that shows the positive and negative impacts of the elements of our approach on each of the categories of the ARCS model. Various such elements are common in several teaching-learning situations. From a learning point of view, our findings also show that contextualized and spiral learning has enhanced the learning of concepts such as loops and functions. Scratch facilitates the learning of programming logic, select and repeat structures. Python with Turtle enhances learning of these same concepts with the addition of functions. Finally, the media computation approach has shown potential for learning the concepts of functions and arrays. We believe that the practical factors presented in this work can support the design of CS1 courses for non-majors / Estudantes que n?o s?o da ?rea de TI, chamados non-majors , usualmente apresentam falta de interesse e maiores dificuldades na aprendizagem de programa??o em rela??o a estudantes de cursos como Ci?ncia da Computa??o. Neste trabalho descrevemos a concep??o, aplica??o e avalia??o de uma abordagem de ensino-aprendizagem de Programa??o, destinada a estudantes non-majors , cujo intuito ? aumentar a sua motiva??o e amenizar as suas dificuldades em aprender programa??o. A abordagem proposta combina o uso do ambiente l?dico Scratch em um contexto de cria??o de jogos, a linguagem de Programa??o Python associada ? biblioteca TurtleGraphics e ? manipula??o de imagens por meio do ambiente de desenvolvimento JythonEnvironment for Students (JES) . Realizamos dois estudos de caso explorat?rios com estudantes de Engenharia Civil cursando uma disciplina introdut?ria de programa??o em nossa institui??o para analisar o impacto desta abordagem sobre a motiva??o e aprendizagem dos estudantes. Nossos resultados descrevem a motiva??o presente durante o curso em termos do modelo Aten??o, Relev?ncia, Confian?a e Satisfa??o (ARCS), e identificam os fatores pr?ticos que podem contribuir para aumentar ou diminuir a motiva??o dos estudantes. Geramos um quadro que evidencia os impactos positivos e negativos dos elementos de nossa abordagem sobre cada uma das categorias do modelo ARCS, sendo que muitos destes elementos s?o comuns em diversas situa??es de ensino-aprendizagem. Do ponto de vista da aprendizagem, nossos achados demonstram que o ensino contextualizado e em espiral potencializou a aprendizagem de conceitos como loops e fun??es. Scratch potencializa a aprendizagem de l?gica de programa??o, loops e estruturas de sele??o. J? Python com Turtlepotencializa a aprendizagem destes mesmos conceitos com a adi??o de fun??es. Finalmente, a abordagem com m?dias demonstrou potencial para a aprendizagem dos conceitos de fun??es, vetores e matrizes. Acreditamos que os fatores pr?ticos apresentados nesse trabalho podem apoiar o design de disciplinas introdut?rias de programa??o para non-majors