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Lundin, Deborah L. "Educational programing planning and transfer of learning strategies : a descriptive study of professional development in grantsmanship". Virtual Press, 2006. http://liblink.bsu.edu/uhtbin/catkey/1336622.
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This descriptive study, adapted from Holton and Bates' Learning Transfer System Inventory (LTSI), examined factors that facilitated and/or hindered transfer of learning for participants of a four-day grant writing workshop. The targeted population was a group of faculty and staff at a Midwest state-supported institution of higher education. The workshops included lecture, group and individual work time, and one-on-one consultation with workshop presenters. Learning focused on developing project ideas, searching for a funding sponsor, and developing the proposal narrative and budget. Multiple workshops were offered between December 2000 and December 2003.The LTSI represents sixteen factors for transfer of learning; these factors were adapted to construct an online survey related to Grantsmanship Workshop content. The survey items reflected the workshop phases and the transfer concepts of each phase: prior to the workshop (learner readiness, supervisor/peer support, motivation to attend, learning interests, pre-workshop preparation); during the workshop (workshop design, time allotment, feedback); and after the workshop ended (content validity, transfer design, personal capacity for transfer, opportunity to use). In addition to these 49 Likert scale items, the survey included yes/no, short answer, and open-end questions related to post-workshop activity, allowing the opportunity to provide additional evidence of their workshop experiences. Of the sixty-six former participants contacted via email, twenty-two voluntarily completed the survey.Issues highlighted during the pre-workshop time period were (1) understanding the significance for learning about grant writing, (2) perception of external support for workshop attendance, and (3) preparation for the workshop. During the workshop, participants acknowledged the benefits of using individual interests to learn the general concepts surrounding grant writing and connecting the learning back to their respective transfer environments. Points of debate were raised regarding program design, particularly with time allocation; responses varied from "not enough individual time" and "too much lecturing" to "too fast-paced" and "not long enough." Two transfer issues emerged after the workshop: time for completing projects, and departmental- and college-level support for pursuing externally funded projects.Findings from the study were used to recommend strategies for future study, as well to suggest transfer strategies for program planners, instructors, program attendees, and other stakeholders.Department of Educational Studies
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Léonard, Marielle. "Approche didactique et instrumentale de la pensée informatique : focus sur le concept de motif". Electronic Thesis or Diss., Université de Lille (2022-....), 2024. http://www.theses.fr/2024ULILH034.
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En France, depuis 2016, l'initiation à la programmation informatique est présente dans les curricula scolaires de l'école obligatoire. L'objectif de cette thèse est de comprendre le processus de conceptualisation lors de la résolution de puzzles de programmation par des sujets âgés de 7 à 15 ans. À cette fin, nous combinons les apports respectifs de la théorie des champs conceptuels (Vergnaud, 1991) et de l'analyse de traces d'interaction dans un EIAH. Nous nous concentrons sur le concept de motif, en particulier lors des premières confrontations avec la notion de boucle en programmation par blocs. Nous définissons un motif comme « une entité repérable au sein d'un ensemble car répétée à l'identique ou avec des variations prédictibles » et mettons en évidence la place essentielle de ce concept lors de l'initiation à la pensée algorithmique. L'approche didactique adoptée vise à positionner le concept de motif au sein d'un champ conceptuel des notions de base de l'algorithmique, champ conceptuel qui a pour périmètre la programmation impérative en langage Scratch au niveau de l'école obligatoire. Au sein de ce champ conceptuel, nous approfondissons l'étude des situations de programmation d'un robot virtuel sur une grille qui requièrent l'utilisation d'une boucle. Notre protocole expérimental est adossé au concours en ligne de programmation Algoréa. Nous avons construit un outillage méthodologique incluant un dispositif de collecte de données à trois échelles, des analyses statistiques sur de larges échantillons, une automatisation du traitement de traces d'interaction avec l'EIAH, et des analyses qualitatives d'enregistrements vidéo d'écran. Cet outillage méthodologique, qui permet de combiner précision des analyses qualitatives et robustesse statistique, constitue l'un des apports de la thèse. Avec cette approche, nous avons d'abord réalisé une étude instrumentale de l'EIAH telle que la définit Rabardel (1995). Son but est de distinguer ce qui, dans l'activité, relève de la maîtrise conceptuelle et ce qui relève de la maîtrise instrumentale d'un environnement de programmation particulier. Nous nous sommes ensuite concentrés sur la conceptualisation-en-acte au sens de Vergnaud (1991). Nous avons identifié les schèmes mis en œuvre par le sujet lors de l'activité de programmation étudiée, notamment les invariants opératoires sous-jacents. Nos analyses nous permettent ainsi d'identifier et de documenter des paliers de difficulté et des erreurs récurrentes lors des premiers apprentissages de la boucle. Une de nos perspectives de recherche est de reproduire cette démarche pour mener des investigations sur l'ensemble des concepts abordés lors de l'initiation à la programmation informatique au niveau de l'école obligatoire. Ces résultats constituent une contribution de nature à outiller les enseignants de l'école élémentaire et du collège pour accompagner leurs élèves et les aider à surmonter les difficultés rencontrées lors de l'apprentissage des concepts fondamentaux de l'algorithmiqueIn France, since 2016, introduction to computer programming has been included in compulsory school curricula. The objective of this thesis is to understand the conceptualization process when solving programming puzzles by subjects aged 7 to 15 years old. To this end, we combine the respective contributions of conceptual field theory (Vergnaud, 1991) and the analysis of pupils activity in a TEL environment. We focus on the concept of pattern, in particular during the first confrontations with the loop notion in block programming. We define a pattern as “an entity identifiable within a set because it is repeated identically or with predictable variations” and highlight the essential place of this concept when initiating algorithmic thinking. The didactic approach adopted aims to position the concept of pattern within a conceptual field of basic notions of algorithms, a conceptual field which has as its scope imperative programming in Scratch language at compulsory school level. Within this conceptual field, we deepen the study of programming situations of a virtual robot on a grid which require the use of a loop. Our experimental protocol is backed by the Algoréa online programming competition. We are building methodological tools including a data collection device at three scales, statistical analyzes on large samples, automation of the processing of interaction traces with the EIAH, and qualitative analyzes of screen video recordings. This methodological tool, which makes it possible to combine the precision of qualitative analyzes and statistical robustness, constitutes one of the contributions of this thesis. With this approach, we first carry out an instrumental study of the TEL environmentas defined by Rabardel (1995). Its goal is to distinguish what, in the activity, relates to conceptual mastery and what relates to instrumental mastery of a particular programming environment. We then focus on conceptualization-in-act in the sense of Vergnaud(1991). We identify the schemes implemented by the subject during the programming activity studied, in particular the underlying operational invariants. Our analyzes allow us to identify and document levels of difficulty and recurring errors during the first learning of the loop. One of our research perspectives is to reproduce this approach to carry out investigations on all the concepts covered during the introduction to computer programming at compulsory school level. These results constitute a contribution likely to help elementary and middle school teachers to support their pupils and help them overcome the difficulties encountered when learning fundamental concepts of algorithms
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Kažukauskas, Irmantas. "Programinio paketo AUTOCAD brėžimo komandų mokymo ir kontrolės programinių priemonių sudarymas ir tyrimas". Master's thesis, Lithuanian Academic Libraries Network (LABT), 2004. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2004~D_20040526_150546-60807.
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The created learning program is given for students to develop their general practical skills for the use of graphical system AutoCAD 2002. The learning program is given for leraning and teaching using computer. The man van use it anywhere, where is the possibility to work with computer and learn the learning program. There are practical exercises for drawing graphical primitives; hatch and dimension commands; tools for editing graphical objestc it the AutoCAD 2002 learning system. The learning system is divided into different parts by AutoCAD 2002 themes. The requirements: personal computer, Windows 95/98/Me/NT/2000/XP operating system and AutoCAD 2002. The learning system is created using VisualLISP progamming language.
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Areizaga, Ander. "Programming learning games : Identification of game design patterns in programming learning games". Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-17230.
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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.
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Sheikholeslami, Sina. "Ablation Programming for Machine Learning". Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-258413.
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As machine learning systems are being used in an increasing number of applications from analysis of satellite sensory data and health-care analytics to smart virtual assistants and self-driving cars they are also becoming more and more complex. This means that more time and computing resources are needed in order to train the models and the number of design choices and hyperparameters will increase as well. Due to this complexity, it is usually hard to explain the effect of each design choice or component of the machine learning system on its performance.A simple approach for addressing this problem is to perform an ablation study, a scientific examination of a machine learning system in order to gain insight on the effects of its building blocks on its overall performance. However, ablation studies are currently not part of the standard machine learning practice. One of the key reasons for this is the fact that currently, performing an ablation study requires major modifications in the code as well as extra compute and time resources.On the other hand, experimentation with a machine learning system is an iterative process that consists of several trials. A popular approach for execution is to run these trials in parallel, on an Apache Spark cluster. Since Apache Spark follows the Bulk Synchronous Parallel model, parallel execution of trials includes several stages, between which there will be barriers. This means that in order to execute a new set of trials, all trials from the previous stage must be finished. As a result, we usually end up wasting a lot of time and computing resources on unpromising trials that could have been stopped soon after their start.We have attempted to address these challenges by introducing MAGGY, an open-source framework for asynchronous and parallel hyperparameter optimization and ablation studies with Apache Spark and TensorFlow. This framework allows for better resource utilization as well as ablation studies and hyperparameter optimization in a unified and extendable API.Eftersom maskininlärningssystem används i ett ökande antal applikationer från analys av data från satellitsensorer samt sjukvården till smarta virtuella assistenter och självkörande bilar blir de också mer och mer komplexa. Detta innebär att mer tid och beräkningsresurser behövs för att träna modellerna och antalet designval och hyperparametrar kommer också att öka. På grund av denna komplexitet är det ofta svårt att förstå vilken effekt varje komponent samt designval i ett maskininlärningssystem har på slutresultatet.En enkel metod för att få insikt om vilken påverkan olika komponenter i ett maskinlärningssytem har på systemets prestanda är att utföra en ablationsstudie. En ablationsstudie är en vetenskaplig undersökning av maskininlärningssystem för att få insikt om effekterna av var och en av dess byggstenar på dess totala prestanda. Men i praktiken så är ablationsstudier ännu inte vanligt förekommande inom maskininlärning. Ett av de viktigaste skälen till detta är det faktum att för närvarande så krävs både stora ändringar av koden för att utföra en ablationsstudie, samt extra beräkningsoch tidsresurser.Vi har försökt att ta itu med dessa utmaningar genom att använda en kombination av distribuerad asynkron beräkning och maskininlärning. Vi introducerar maggy, ett ramverk med öppen källkodsram för asynkron och parallell hyperparameteroptimering och ablationsstudier med PySpark och TensorFlow. Detta ramverk möjliggör bättre resursutnyttjande samt ablationsstudier och hyperparameteroptimering i ett enhetligt och utbyggbart API.
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Wang, Tianze. "Machine Learning for Constraint Programming". Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254660.
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It is well established that designing good heuristics for solving Constraint Programming models requires years of domain experience and a huge amount of trial and error. In this thesis project, we conduct an empirical study of whether Machine Learning and Deep Learning techniques have the potential to help the design of constraint solving heuristics.Specifically, this thesis project examines the potential of Machine Learning and Deep Learning models for the regression task of predicting the makespan and solving time of a Job-Shop Scheduling Problem without actually solving the given Job-Shop Scheduling Problem instance. Several Machine Learning models are tested with manually designed features as input. Different Deep Learning architectures are explored with either just the Job-Shop Scheduling Problem instance as input or with an additional input of the previously designed features.××Results of the experiments justify the potential of several proposed models in predicting the makespan and solving time. For predicting the makespan (unit: machine time unit), the best Random Forest regression model achieves a Mean Squared Error of 0.78 on the test set. The best Deep Learning model achieves a Mean Squared Error of 0.74 on the test set. For predicting the solving time (unit: milliseconds) of a Job-Shop Scheduling Problem, the best Random Forest regression model achieves a Mean Squared Error of 2.12 107 on the test set. The best Deep Learning model achieves a Mean Squared Error of 5.19 107 on the test set.Discussions of the reason behind the difference of different Machine Learning and Deep Learning models are provided and future directions are proposed.Det är väl etablerat att det kräver många års erfarenhet av domänexpertis och mycket experimentell felsökning för att utforma en bra sökheuristik för villkorsprogrammeringsmodeller. I denna avhandling beskriver vi genomförandet av en empirisk studie med syftet att utreda potentialen av maskininlärningstekniker för att underlätta framtagandet av villkorsprogrammeringslösare.Mer specifikt undersöker vi maskininlärningsmodellers regressionsförmåga att förutse makespanöch lösningstid för "Job-Shop Scheduling Problem"utan att för den delen lösa den givna "Job-Shop Scheduling Problem"instansen. Flertalet maskininlärningsmodeller testas med manuellt framtagna särdrag som indata. Olika djupmaskininlärningsarkitekturer utforskas med antingen bara "Job-Shop Scheduling Problem-instanser som indata eller med ytterliggare indata i form av de manuellt framtagna särdragen.××Experimentresultaten motiverar användandet av flertalet av de föreslagna maskininlärningsmodellerna för att förutse makespanöch lösningstid. För förutsägandet av makespan"(enhet: maskintidsenhet) uppnår den bästa Random Forestregressionsmodellen ett medelkvadratfel på 0,78 på testdatamängden. Den bästa djupmaskininlärningsmodellen uppnår ett medelkvadratfel på 0,74 på testdatamängden. För förutsägandet av lösningstiden (enhet: millisekund) av "Job-Shop Scheduling Problem"uppnår den bästa Random Forestregressionsmodellen ett medelkvadratfel på 2.12 107 på testdatamängden. Den bästa djupmaskininlärningsmodellen uppnår ett medelkvadratfel på 5.19 107 på testdatamängden.Skillnadsorsakerna rörande de olika maskininlärningsmodellernas prestanda diskuteras i avhandlingen samt framtida forskningsinriktningar.
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Sundblad, Graziella. "Virtual Reality and its Impact on Programming Learning Process - Designing VR-based Programming Learning Practices". Thesis, Malmö universitet, Fakulteten för kultur och samhälle (KS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-22396.
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This qualitative thesis work investigates in which way an immersive,embodied and interactive computer-based simulation can lead to an easierunderstanding of programming concepts. It also presents a concept for VRprogramming learning tool that could turn learning into a fun and engagingexperience for the students. The target group is Interaction Design bachelorstudents – programming is an important tool to create innovative andinteractive artefacts and interfaces, and yet, the students have hard time tounderstand many of the programming concepts. The current research relieson concepts such as embodiment and tangibility, which reflects on theprototype developed – a highly immersive, embodied VR platform with astrong illusion of tangibility. Additionally, the prototype was inspired byfeedback from students and teachers, result of a participatory approach.Finally, the research showed through usability tests that the studentsexperienced that the application made the concepts more graspable and morefun to learn.
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Conti, Matteo. "Machine Learning Based Programming Language Identification". Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/20875/.
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L'avvento dell'era digitale ha contribuito allo sviluppo di nuovi settori tecnologici, i quali, per diretta conseguenza, hanno portato alla richiesta di nuove figure professionali capaci di assumere un ruolo chiave nel processo d'innovazione tecnologica. L'aumento di questa richiesta ha interessato particolarmente il settore dello sviluppo del software, a seguito della nascita di nuovi linguaggi di programmazione e nuovi campi a cui applicarli. La componente principale di cui è composto un software, infatti, è il codice sorgente, il quale può essere rappresentato come un archivio di uno o più file testuali contenti una serie d'istruzioni scritte in uno o più linguaggi di programmazione. Nonostante molti di questi vengano utilizzati in diversi settori tecnologici, spesso accade che due o più di questi condividano una struttura sintattica e semantica molto simile. Chiaramente questo aspetto può generare confusione nell'identificazione di questo all'interno di un frammento di codice, soprattutto se consideriamo l'eventualità che non sia specificata nemmeno l'estensione dello stesso file. Infatti, ad oggi, la maggior parte del codice disponibile online contiene informazioni relative al linguaggio di programmazione specificate manualmente. All'interno di questo elaborato ci concentreremo nel dimostrare che l'identificazione del linguaggio di programmazione di un file `generico' di codice sorgente può essere effettuata in modo automatico utilizzando algoritmi di Machine Learning e non usando nessun tipo di assunzione `a priori' sull'estensione o informazioni particolari che non riguardino il contenuto del file. Questo progetto segue la linea dettata da alcune ricerche precedenti basate sullo stesso approccio, confrontando tecniche di estrazione delle features differenti e algoritmi di classificazione con caratteristiche molto diverse, cercando di ottimizzare la fase di estrazione delle features in base al modello considerato.
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CASTRO, THAIS HELENA CHAVES DE. "SYSTEMATIC APPROACH FOR GROUP PROGRAMMING LEARNING". PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2011. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=18366@1.
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CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOA investigação aqui relatada trata da concepção de elementos estruturantes para ampliar as oportunidades de intervenção pelo professor em um contexto de aprendizagem de programação em grupo. A partir de uma série de estudos de caso com turmas de calouros em cursos de computação, foi desenvolvida a sistematização de práticas, metodologias e tecnologias em uma abordagem para apoiar a aprendizagem de programação em grupo, baseada em três frentes de investigação: pressupostos pedagógicos, ferramentas LMS e métodos de colaboração. O eixo teórico referente à aprendizagem é a teoria de desenvolvimento cognitivo de Piaget, aliada a técnicas conhecidas de programação em grupo utilizadas no ensino de graduação em disciplinas introdutórias de programação. As ferramentas computacionais são utilizadas para monitorar e intervir durante o processo de aprendizagem. Nesse contexto, ambientes CSCL incentivam a colaboração e regulam as práticas desejadas. Nesta tese, outras tecnologias, como linguagens para representação de agentes e identificação de padrões são agregadas a eles para melhorar o acompanhamento e facilitar a intervenção. Por fim, como método de colaboração, é proposto um esquema progressivo de aprendizagem de programação em grupo, que auxilia os alunos a gradativamente adotarem práticas colaborativas na resolução de exercícios e que pode ser formalizado para incorporação a plataformas automatizadas.
The research reported here deals with devising structuring elements that may broaden intervention opportunities from the teacher in a context of group programming learning. Based on a set of case studies with freshmen in computing courses a systematization for practices, methods and technologies was developed producing an approach for supporting group programming based in three investigation paths: pedagogical assumptions, CSCL environments and collaboration methods. The main learning rationale is Jean Piaget’s Cognitive Development Theory, used alongside group programming techniques commonly applied in undergraduate introductory programming courses. Computational tools are used to monitor and intervene during learning process and in such context, CSCL environments encourage collaboration and regulate expected practices. In this thesis other technologies like languages for agent representation and patterning identification are also exploited for improving control and facilitate interventions. Finally, as collaboration method, it is proposed a Programming Progressive Learning Scheme that helps students to adopt collaborative practices when solving exercises and that can be formalized to be used with automated platforms.
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Martin, Christopher James. "Designing engaging learning experiences in programming". Thesis, University of Dundee, 2017. https://discovery.dundee.ac.uk/en/studentTheses/069f0e46-ae52-450d-84e1-1ff5c3fed38f.
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This thesis describes research into supporting the creation of engaging learning experiences with programming. A review of relevant research that could contribute to the design of engaging learning experiences informed the construction of four pieces of fieldwork. These fieldwork studies were conducted to explore the framing of learning programming in tasks that motivate and are of value to the learner. Findings resulted in the design of a set of eight Learning Dimensions. These Learning Dimensions are proposed to address three key areas: (1) design and delivery of learning task, (2) rhythm or tempo of the learning experience and (3) practicalities. The Learning Dimensions provide educators with insights to support key design decisions for the creation of engaging programming learning experiences. Finally, a web-based tool was designed to make the Learning Dimensions accessible to educators. This tool has been used to evaluate one further workshop. This thesis consolidates several threads of research into a learner-centred approach to learning to program. The Learning Dimensions identify important areas of decision-making to be considered when designing a learning experience. They support the assertion that factors outwith the content can significantly affect success in programming. The complex interplay between different skills associated with computer programming will remain a challenge to learners. When placed in a rich context that fits the learner well and supports the learning aims, many of these difficulties can be overcome. The Learning Dimensions draw together positive features of a learning experience that are key to ensuring learners have the best possible opportunity to engage with and succeed with computer programming.
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Bearpark, Keith. "Learning and memory in genetic programming". Thesis, University of Southampton, 2000. https://eprints.soton.ac.uk/45930/.
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Genetic Programming is a form of Evolutionary Computation in which computer programs are evolved by methods based on simulating the natural evolution of biological species. A new generation of a species acquires the characteristics of previous generations through the inheritance of genes by sexual reproduction and through random changes in alleles by random mutation. The new generation may enhance its ability to survive by the acquisition of cultural knowledge through learning processes. This thesis combines the transfer of knowledge by genetic means with the transfer of knowledge by cultural means. In particular, it introduces a new evolutionary operator, memory operator. In conventional genetic programming systems, a new generation is formed from a mating pool whose members are selected from the fittest members of previous generation. The new generation is produced by the exchange of genes between members of the mating pool and the random replacement of genes in the offspring. The new generation may or may not be able to survive better than its predecessor in a given environment. The memory operator augments the evolutionary process by inserting into new chromosomes genetic material known to often result in fitness improvements. This material is acquired through a learning process in which the system is required to evolve generations that survive in a less demanding environment. The cultural knowledge acquired in this learning process is applied as an intelligent form of mutation to aid survival in a more demanding environment.
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Ward, Jeffrey Alan. "Answer set programming with clause learning". Connect to this title online, 2004. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1092840020.
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Thesis (Ph. D.)--Ohio State University, 2004.Title from first page of PDF file. Document formatted into pages; contains xv, 170 p. : ill. Advisors: Timothy J. Long and John S. Schlipf, Department of Computer Science and Engineering. Includes bibliographical references (p. 165-170).
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Jones, Ann Carolyn. "Empirical studies of novices learning programming". Thesis, Open University, 1989. http://oro.open.ac.uk/56445/.
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This thesis is concerned with the problems that novices have in learning to program: in particular it is concerned with the difficulties experienced by novices learning at a distance, using instructional materials which have been designed especially for novices. One of the major problems for novices is how to link the new information which they encounter with their existing knowledge. Du Boulay, O'Shea and Monk (1981) suggest helping novices to bridge the gap between their existing knowledge and new information by teaching via a conceptual model, which serves to explain the new information in familiar terms. In this thesis the difficulties which novices have when learning to program with the help of a conceptual model were investigated. The curricula and conceptual models of four different programming languages are examined, all of which were designed to teach novices. Du Boulay, O'Shea and Monk (1981) have suggested criteria for analysing conceptual models. It is argued that these criteria, however, do not address the presentation of the conceptual model, and so are insufficient to evaluate them. An additional form of analysis was proposed and used, in addition to the criteria offered by Du Boulay et al. This is a way of describing the conceptual model which distinguishes three views of the conceptual model: state, procedure and function, and which highlights the different aspects which are important for the novice learner by identifying the different kinds of knowledge which are necessary to understand the conceptual model. This analysis of the conceptual models showed that the environments are not as exemplary as the du Boulay et al's criteria suggest, and indicated that three of the environments, SOLO, PT501 and DESMOND, lack a functional representation, and that the fourth, Open Logo, has other different problems. An empirical study was carried out to study the transfer effects of learning two of the languages, a high level and a low level language, sequentially. There was no evidence for such transfer effects. The difficulties novices have in learning the four different languages were also investigated. These studies show that even though the novices were studying environments designed for novices learning at a distance, they did not develop good levels of competence, and the problems they had fall into two main categories: programming and pedagogical. Although the different languages had different aims and curricula, novices had some problems which were common to all or most of the languages. These included understanding flow of control, developing and using programming plans, developing accurate mental models, and in the high level languages, understanding recursion. It is argued that some of these problems are related to the conceptual models. In particular, the difficulties novices had in developing and using plan knowledge, which is one of their main problems, can be explained by the lack of an appropriate functional description in the languages. The subjects' pedagogical problems arose from the relationship between the style and structure of the curriculum, its content, and the subjects themselves. In all the four texts the teaching material is very carefully structured and it is suggested that this may encourage the learner to adopt an over-dependent attitude towards the text, and in some cases, to work at an inappropriate syntactic level. The relationship between the distance learning situation and the novice programmer is discussed, and recommendations are made for improving the curricula used for teaching novices programming.
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Eckerdal, Anna. "Novice students' learning of object-oriented programming". Licentiate thesis, Uppsala : Univ. : Dept. of Information Technology, Univ, 2006. http://www.it.uu.se/research/publications/lic/2006-006/2006-006.pdf.
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Preen, Richard John. "Dynamical genetic programming in learning classifier systems". Thesis, University of the West of England, Bristol, 2011. http://eprints.uwe.ac.uk/25852/.
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Learning Classifier Systems (LCS) traditionally use a ternary encoding to generalise over the environmental inputs and to associate appropriate actions. However, a number of schemes have been presented beyond this, ranging from integers to artificial neural networks. This thesis investigates the use of Dynamical Genetic Programming (DGP) as a knowledge representation within LCS. DGP is a temporally dynamic, graph-based, symbolic representation. Temporal dynamism has been identified as an important aspect in biological systems, artificial life, and cognition in general. Furthermore, discrete dynamical systems have been found to exhibit inherent content-addressable memory. In this thesis, the collective emergent behaviour of ensembles of such dynamical function networks are herein shown to be exploitable toward solving various computational tasks. Significantly, it is shown possible to exploit the variable-length, adaptive memory existing inherently within the networks under an asynchronous scheme, and where all new parameters introduced are self-adaptive. It is shown possible to exploit the collective mechanics to solve both discrete and continuous-valued reinforcement learning problems, and to perform symbolic regression. In particular, the representation is shown to provide improved performance beyond a traditional Genetic Programming benchmark on a number of a composite polynomial regression tasks. Superior performance to previously published techniques is also shown in a continuous-input-output reinforcement learning problem. Finally, it is shown possible to perform multi-step-ahead predictions of a financial time-series by repeatedly sampling the network states at succeeding temporal intervals.
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Lau, Tessa. "Programming by demonstration : a machine learning approach /". Thesis, Connect to this title online; UW restricted, 2001. http://hdl.handle.net/1773/6949.
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Lau, Wing-fat, e 劉永發. "Exploring the relationships among gender, learning style, mentalmodel, and programming performance: implications for learning and teaching of computer programming". Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2009. http://hub.hku.hk/bib/B41633945.
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Li, Jinlei. "Developing an online learning module for C programming and Lego robot EV3 programming". Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-279419.
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Recently, the school of electrical engineering and computer science (EECS) at the Royal institute of technology (KTH) proposed to introduce a new learning module for the course Engineering Methods - II1300. The module is to introduce both C programming and LEGO robot EV3 programming, to help the students to complete a course project. A literature study was first conducted to investigate how a learning module should be designed and what information was needed. Data from a survey routinely performed by the department and another in this work were collected. The data showed a wide variety in background knowledge among the students who attended the course. Many students believed that they did not receive enough learning material to complete the C assignments nor sufficient instructions for programming the LEGO robot. Based on the data analyses and guided with the Constructive Alignment method and the Scaffolding theory, a specification was created, and the desired learning module was developed. The module provides necessary instructions, good code examples and relevant resources that may be needed. It arranges a balanced amount of learning activities. It is expected to guide the learningprocess and improve the learning efficiency, and to facilitate the teaching process and reduce the workload. The learning module highlights a structured and modular way to teach fundamentals of C programming using the Scaffolding teaching method in conjunction with Constructive Alignment. The module can be reused with small modifications for similar courses by substituting the contents. Moreover, the strategy and the methods, which the project adopted to develop the module, are rather general and in principle are applicable to most online course development.Nyligen föreslog Skolan för elektroteknik och datavetenskap (EECS) på KungligaTekniska Högskolan (KTH) att införa en ny inlärningsmodul för kursen Engineering Methods - II1300. Modulen ska introducera både C-programmeringoch LEGO-robot EV3-programmering, för att hjälpa eleverna att slutföra ett kursprojekt. En litteraturstudie genomfördes först för att undersöka hur en inlärningsmodul ska utformas och vilken information som behövs. Data från en undersökningsom rutinmässigt utförts av institutionen och en annan i detta arbete samlades in. Uppgifterna visade en stor variation i bakgrundskunskaper blandde studenter som deltog i kursen. Många studenter trodde att de inte fick tillräckligt med läromedel för att slutföra C-uppgifterna eller tillräckliga instruktionerför att programmera LEGO-roboten. Baserat på dataanalyserna och styrs med Constructive Alignment metoden och Scaffoldning teorin skapades en specifikation och den önskade inlärningsmodulen utvecklades. Modulen innehåller nödvändiga instruktioner, bra kodexempel och relevanta resurser som kan behövas. Det ordnar en balanserad mängd lärande aktiviteter. Det förväntas vägleda inlärningsprocessen och förbättra inlärningseffektiviteten och underlätta undervisningsprocessen och minska arbetsbelastningen. Lärningsmodulen belyser ett strukturerat och modulärt sätt att undervisa i grunderna i C-programmering med hjälp av undervisningsmetoden Scaffolding i samband med Constructive Alignment. Modulen kan återanvändas med små ändringar för liknande kurser genom att ersätta innehållet. Dessutom är strategin och metoderna, som projektet antog för att utveckla modulen, ganska allmän och är i princip tillämpliga för de flesta online kursutveckling.
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Böhlmark, Gustav. "Developing an online learning module for C programming and Lego robot EV3 programming". Thesis, KTH, Skolan för kemi, bioteknologi och hälsa (CBH), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-284235.
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Dailey, John Charles. "Programming for learning : a discourse analysis of peer communication while programming a computer /". free to MU campus, to others for purchase, 1998. http://wwwlib.umi.com/cr/mo/fullcit?p9924878.
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Lategano, Antonio. "Image-based programming language recognition". Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/22208/.
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Nel presente lavoro di tesi viene affrontato per la prima volta il problema della classificazione dei linguaggi di programmazione mediante approcci image-based. Abbiamo utilizzato alcune Convolutional Neural Network pre-addestrate su task di classificazione di immagini, adattandole alla classificazione di immagini contenenti porzioni di codice sorgente scritto in 149 diversi linguaggi di programmazione. I nostri risultati hanno dimostrato che tali modelli riescono ad apprendere, con buone prestazioni, le feature lessicali presenti nel testo. Aggiungendo del rumore, tramite modifica dei caratteri presenti nelle immagini, siamo riusciti a comprendere quali fossero i caratteri che meglio permettevano ai modelli di discriminare tra una una classe e l’altra. Il risultato, confermato tramite l’utilizzo di tecniche di visualizzazione come la Class Activation Mapping, è che la rete riesce ad apprendere delle feature lessicali di basso livello concentrandosi in particolare sui simboli tipici di ogni linguaggio di programmazione (come punteggiatura e parentesi), piuttosto che sui caratteri alfanumerici.
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Kuscu, Ibrahim. "Evolutionary generalisation and genetic programming". Thesis, University of Sussex, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.285062.
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Lau, Wing-fat. "Exploring the relationships among gender, learning style, mental model, and programming performance implications for learning and teaching of computer programming /". Click to view the E-thesis via HKUTO, 2009. http://sunzi.lib.hku.hk/hkuto/record/B41633945.
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Eckerdal, Anna. "Novice Programming Students' Learning of Concepts and Practise". Doctoral thesis, Uppsala universitet, Avdelningen för teknisk databehandling, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-9551.
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Computer programming is a core area in computer science education that involves practical as well as conceptual learning goals. The literature in programming education reports however that novice students have great problems in their learning. These problems apply to concepts as well as to practise. The empirically based research presented in this thesis contributes to the body of knowledge on students' learning by investigating the relationship between conceptual and practical learning in novice student learning of programming. Previous research in programming education has focused either on students' practical or conceptual learning. The present research indicates however that students' problems with learning to program partly depend on a complex relationship and mutual dependence between the two. The most significant finding is that practise, in terms of activities at different levels of proficiency, and qualitatively different conceptual understandings, have dimensions of variation in common. An analytical model is suggested where the dimensions of variation relate both to concepts and activities. The implications of the model are several. With the dimensions of variation at the center of learning this implies that when students discern a dimension of variation, related conceptual understandings and the meaning embedded in related practises can be discerned. Activities as well as concepts can relate to more than one dimension. Activities at a higher level of proficiency, as well as qualitatively richer understandings of concepts, relate to more dimensions of variation. Concrete examples are given on how variation theory and patterns of variation can be applied in teaching programming. The results can be used by educators to help students discern dimensions of variation, and thus facilitate practical as well as conceptual learning.
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Affleck, Glenn. "Factors involved in teaching and learning computer programming". Thesis, University of the West of Scotland, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.730014.
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Gathercole, Christopher. "An investigation of supervised learning in genetic programming". Thesis, University of Edinburgh, 1998. http://hdl.handle.net/1842/533.
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This thesis is an investigation into Supervised Learning (SL) in Genetic Programming (GP). With its flexible tree-structured representation, GP is a type of Genetic Algorithm, using the Darwinian idea of natural selection and genetic recombination, evolving populations of solutions over many generations to solve problems. SL is a common approach in Machine Learning where the problem is presented as a set of examples. A good or fit solution is one which can successfully deal with all of the examples. In common with most Machine Learning approaches, GP has been used to solve many trivial problems. When applied to larger and more complex problems, however, several difficulties become apparent. When focusing on the basic features of GP, this thesis highlights the immense size of the GP search space, and describes an approach to measure this space. A stupendously flexible but frustratingly useless representation, Anarchically Automatically Defined Functions, is described. Some difficulties associated with the normal use of the GP operator Crossover (perhaps the most common method of combining GP trees to produce new trees) are demonstrated in the simple MAX problem. Crossover can lead to irreversible sub-optimal GP performance when used in combination with a restriction on tree size. There is a brief study of tournament selection which is a common method of selecting fit individuals from a GP population to act as parents in the construction of the next generation. The main contributions of this thesis however are two approaches for avoiding the fitness evaluation bottleneck resulting from the use of SL in GP. to establish the capability of a GP individual using SL, it must be tested or evaluated against each example in the set of training examples.
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Rainforth, Thomas William Gamlen. "Automating inference, learning, and design using probabilistic programming". Thesis, University of Oxford, 2017. http://ora.ox.ac.uk/objects/uuid:e276f3b4-ff1d-44bf-9d67-013f68ce81f0.
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Imagine a world where computational simulations can be inverted as easily as running them forwards, where data can be used to refine models automatically, and where the only expertise one needs to carry out powerful statistical analysis is a basic proficiency in scientific coding. Creating such a world is the ambitious long-term aim of probabilistic programming. The bottleneck for improving the probabilistic models, or simulators, used throughout the quantitative sciences, is often not an ability to devise better models conceptually, but a lack of expertise, time, or resources to realize such innovations. Probabilistic programming systems (PPSs) help alleviate this bottleneck by providing an expressive and accessible modeling framework, then automating the required computation to draw inferences from the model, for example finding the model parameters likely to give rise to a certain output. By decoupling model specification and inference, PPSs streamline the process of developing and drawing inferences from new models, while opening up powerful statistical methods to non-experts. Many systems further provide the flexibility to write new and exciting models which would be hard, or even impossible, to convey using conventional statistical frameworks. The central goal of this thesis is to improve and extend PPSs. In particular, we will make advancements to the underlying inference engines and increase the range of problems which can be tackled. For example, we will extend PPSs to a mixed inference-optimization framework, thereby providing automation of tasks such as model learning and engineering design. Meanwhile, we make inroads into constructing systems for automating adaptive sequential design problems, providing potential applications across the sciences. Furthermore, the contributions of the work reach far beyond probabilistic programming, as achieving our goal will require us to make advancements in a number of related fields such as particle Markov chain Monte Carlo methods, Bayesian optimization, and Monte Carlo fundamentals.
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JELILI, GBENGA ALALU. "CHILDREN TELEVISION PROGRAMMING AND CULTURAL LEARNING IN NIGERIA". Thesis, Malmö universitet, Fakulteten för kultur och samhälle (KS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-23628.
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It can today be examined in Nigeria that children are fast abandoning the indigenous cultural values for the foreign ones and the media is said to contribute to this development due to the broadcast of foreign television programmes by tv stations in the country. The need to promote, protect, and sustain the country’s indigenous cultural values are of great importance if Nigeria hopes to prevent them from being washed away. Children’s love for television is undeniable and being the future of the country, what is the extent to which television is used to impact children with social and cultural values of the society. The paper thus investigates the extent to which children Television is utilized to impact Nigerian Children with the country’s cultural values. It looks closely at the children programmes of two biggest and leading Nigeria’s television stations; the Nigerian Television Authority (NTA), and African Independent Television (AIT), representing both state-owned and privately-owned television stations in the country. Using Development Media and Cultivation theories as underlying theory, the study concludes that though there is an improvement on the part of the television stations as they now broadcast socially and culturally relevant children programmes. There is however insufficiency in both quantity and quality of children programmes, as well as the time allotted for them to allow any meaningful long-time cultural impact to be realized at the current state as may be intended by the producers of the programmes.
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Rivers, Kelly. "Automated Data-Driven Hint Generation for Learning Programming". Research Showcase @ CMU, 2017. http://repository.cmu.edu/dissertations/1055.
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Feedback is an essential component of the learning process, but in fields like computer science, which have rapidly increasing class sizes, it can be difficult to provide feedback to students at scale. Intelligent tutoring systems can provide personalized feedback to students automatically, but they can take large amounts of time and expert knowledge to build, especially when determining how to give students hints. Data-driven approaches can be used to provide personalized next-step hints automatically and at scale, by mining previous students’ solutions. I have created ITAP, the Intelligent Teaching Assistant for Programming, which automatically generates next-step hints for students in basic Python programming assignments. ITAP is composed of three stages: canonicalization, where a student's code is transformed to an abstracted representation; path construction, where the closest correct state is identified and a series of edits to that goal state are generated; and reification, where the edits are transformed back into the student's original context. With these techniques, ITAP can generate next-step hints for 100% of student submissions, and can even chain these hints together to generate a worked example. Initial analysis showed that hints could be used in practice problems in a real classroom environment, but also demonstrated that students' relationships with hints and help-seeking were complex and required deeper investigation. In my thesis work, I surveyed and interviewed students about their experience with helpseeking and using feedback, and found that students wanted more detail in hints than was initially provided. To determine how hints should be structured, I ran a usability study with programmers at varying levels of knowledge, where I found that more novice students needed much higher levels of content and detail in hints than was traditionally given. I also found that examples were commonly used in the learning process, and could serve an integral role in the feedback provision process. I then ran a randomized control trial experiment to determine the effect of next-step hints on learning and time-on-task in a practice session, and found that having hints available resulted in students spending 13.7% less time during practice while achieving the same learning results as the control group. Finally, I used the data collected during these experiments to measure ITAP’s performance over time, and found that generated hints improved as data was added to the system. My dissertation has contributed to the fields of computer science education, learning science, human-computer interaction, and data-driven tutoring. In computer science education, I have created ITAP, which can serve as a practice resource for future programming students during learning. In the learning sciences, I have replicated the expertise reversal effect by finding that more expert programmers want less detail in hints than novice programmers; this finding is important as it implies that programming teachers may provide novices with less assistance than they need. I have contributed to the literature on human-computer interaction by identifying multiple possible representations of hint messages, and analyzing how users react to and learn from these different formats during program debugging. Finally, I have contributed to the new field of data-driven tutoring by establishing that it is possible to always provide students with next-step hints, even without a starting dataset beyond the instructor’s solution, and by demonstrating that those hints can be improved automatically over time.
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Pettersson, Emil. "Meta-Interpretive Learning Versus Inductive Metalogic Programming : A Comparative Analysis in Inductive Logic Programming". Thesis, Uppsala universitet, Institutionen för informatik och media, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-393291.
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Artificial intelligence and machine learning are fields of research that have become very popular and are getting more attention in the media as our computational power increases and the theories and latest developments of these fields can be put into practice in the real world. The field of machine learning consists of different paradigms, two of which are the symbolic and connectionist paradigms. In 1991 it was pointed out by Minsky that we could benefit from sharing ideas between the paradigms instead of competing for dominance in the field. That is why this thesis is investigating two approaches to inductive logic programming, where the main research goals are to, first: find similarities or differences between the approaches and potential areas where cross-pollination could be beneficial, and secondly: investigate their relative performance to each other based on the results published in the research. The approaches investigated are Meta-Interpretive Learning and Inductive Metalogic Programming, which belong to the symbolic paradigm of machine learning. The research is conducted through a comparative study based on published research papers. The conclusion to the study suggests that at least two aspects of the approaches could potentially be shared between them, namely the reversible aspect of the meta-interpreter and restricting the hypothesis space using the Herbrand base. However, the findings regarding performance were deemed incompatible, in terms of a fair one to one comparison. The results of the study are mainly specific, but could be interpreted as motivation for similar collaboration efforts between different paradigms.
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Abdul, Rahman Siti Soraya. "Learning programming via worked-examples : the effects of cognitive load and learning styles". Thesis, University of Sussex, 2012. http://sro.sussex.ac.uk/id/eprint/38517/.
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This research explored strategies for learning programming via worked-examples that promote schema acquisition and transfer. However, learning style is a factor in how much learners are willing to expend serious effort on understanding worked-examples, with active learners tending to be more impatient of them than reflective learners. It was hypothesised that these two learning styles might also interact with learners' cognitive load. The research proposed a worked-example format, called a Paired-method strategy that combines a Structure-emphasising strategy with a Completion strategy. An experiment was conducted to compare the effects of the three worked-examples strategies on cognitive load measures and on learning performance. The experiment also examined the degree to which individual learning style influenced the learning process and performance. Overall, the results of the experiment were inconsistent. In comparing the effects of the three strategies, there were significant differences in reported difficulty and effort during the learning phase, with difficulty but not effort in favour of the Completion strategy. However no significant differences were detected in reported mental effort during the post-tests in the transfer phase. This was also the case for the performance on the post-tests. Concerning efficiency measures, the results revealed significant differences between the three strategy groups in terms of the learning process and task involvement, with the learning process in favour of the Completion strategy. Unexpectedly, no significant differences were observed in learning outcome efficiencies. Despite this, there was a trend in the data that suggested a partial reversal effect for the Completion strategy. Moreover, the results partially replicated earlier findings on the explanation effect. In comparing the effects of the two learning styles, there were no significant differences between active and reflective learners in the three strategy groups on cognitive load measures and on learning performance (nor between reflective learners in the Paired-method strategy and the other strategies). Finally, concerning efficiency measures, there was a significant difference between active learners in the three strategy groups on task involvement. Despite all these, effect sizes ranging from a medium to large suggested that learning styles might have interacted with learners' cognitive load.
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McKee-Scott, Jamie. "A study of an educational game for learning programming". Thesis, University of British Columbia, 2015. http://hdl.handle.net/2429/53704.
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Introductory, first-year programming classes are challenging for many students. Unlike other first year science courses, computer science is not required for entry to most first-year science programs, and students struggle with bug hunting and code planning, especially if they have never programmed before. This thesis introduces the development of a web-based educational game, called Code Age, as a tool for supporting the learning of basic programming concepts. Code Age is a mini-game style game designed to be used at the students convenience, and currently consists of three minigames related to introductory programming concepts encountered throughout the process of learning programming. A pilot study was designed to evaluate the prototype in terms of using mini-games for learning, finding the correct measures for evaluating engagement, and continuing the project. The pilot study consisted of a heuristic evaluation and usability study. The heuristic evaluation found few usability errors in the software, which did not impact the results and analysis of the usability study. The usability study contained three questionnaires, the Intrinsic Motivation Inventory, an engagement pre/post-test, and a usability questionnaire. The IMI showed that students found value and enjoyment from the game. The engagement questionnaire was adapted from the NSSE and its results showed promise, despite the fact that the study did not have enough participants and the adapted questions were too course-oriented. Suggestions for modified questions are proposed. The usability study demonstrated that student opinion of the mini-games was diverse, but a wide variety of games is necessary to maintain engagement and throughout these games, the balance between conceptual and physical challenge must be given much attention. The pilot study ultimately concluded that the engagement questionnaire needed revision, the mini-games were a good choice, and the system was intuitive and easy to use despite the usability errors. Finally, the study showed that even the students who did not care for Code Age itself felt that games are useful to help learning and to help learning programming.Graduate Studies, College of (Okanagan)
Graduate
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Clouston, Dorothy Ruth. "Computer programming and kindergarten children in two learning environments". Thesis, University of British Columbia, 1988. http://hdl.handle.net/2429/28596.
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This study examined the appropriateness of introducing computer programming to kindergarten children. Three issues were explored in the research:
1. the programming capabilities of kindergarten children using a single keystroke program
2. suitable teaching techniques and learning environments for introducing programming
3. the benefits of programming at the kindergarten level. The subjects for the study were 40 kindergarten students
from a surburban community in British Columbia, Canada. All students used the single keystroke program, DELTA DRAWING. Two teaching techniques were used—a structured method and a guided discovery method. Quantitative data were collected by administering five skills tests (skills relating to programming) as pretests and postests to both groups. A programming posttest was also given. Qualitative data were obtained by recording detailed observation reports for each of the 22 lessons (11 for each group), conducting an interview with each child at the end of the study and distributing a parent questionnaire.
It can be concluded that it is appropriate to introduce computer programming to kindergarten students. The children in this study showed they are capable of programming. All students mastered some programming commands to instruct the "turtle" to move on the screen. DELTA DRAWING was determined to be a suitable means to introduce programming to kindergarten children.
A combination of a structured teaching method and a guided discovery method is recommended for introducing a single keystroke program. It was observed that students in a guided discovery learning environment are more enthusiastic and motivated than students in a structured environment. Students need time to explore and make discoveries, but some structure is necessary to teach specific commands and procedures which may otherwise not be discovered. Social interaction should be encouraged while children use the computer, however most kindergarten children prefer to work on their own computer. There was no significant difference between the two groups on all but one of the five skills tests for both the pretests and the posttests. On the Programming Test the two groups did not perform significantly different.
It can also be concluded that learning to program promotes cognitive development in certain areas. On all but one of the five skills test both the Structured Group and the Guided Discovery Group scored significantly better on the posttest than on the pretest.
Lesson observation reports, student interviews and responses on parent questionnaires suggested that the computer experience was positive and rewarding for the kindergarten students.Education, Faculty of
Graduate
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Tschorn, Patrick. "Incremental inductive logic programming for learning from annotated copora". Thesis, Lancaster University, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.538607.
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Gandhi, Sachin. "Learning from a Genetic Algorithm with Inductive Logic Programming". Ohio University / OhioLINK, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1125511501.
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Hoff, Carl C. "Pattern Recognition via Machine Learning with Genetic Decision-Programming". Wright State University / OhioLINK, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=wright1133882117.
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Akdag, Fusun Semiha. "The effects of computer programming on young children's learning". The Ohio State University, 1985. http://rave.ohiolink.edu/etdc/view?acc_num=osu1399480316.
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Yaman, Sibel. "A multi-objective programming perspective to statistical learning problems". Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/26470.
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Thesis (Ph.D)--Electrical and Computer Engineering, Georgia Institute of Technology, 2009.Committee Chair: Chin-Hui Lee; Committee Member: Anthony Yezzi; Committee Member: Evans Harrell; Committee Member: Fred Juang; Committee Member: James H. McClellan. Part of the SMARTech Electronic Thesis and Dissertation Collection.
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Santos, Aécio Solano Rodrigues. "Learning to schedule web page updates using genetic programming". Universidade Federal de Minas Gerais, 2013. http://hdl.handle.net/1843/ESBF-97GJSQ.
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One of the main challenges endured when designing a scheduling policy regarding freshness is to estimate the likelihood of a previously crawled web page being modified on the web, so that the scheduler can use this estimation to determine the order in which those pages should be visited. A good estimation of which pages have more chance of being modified allows the system to reduce the overall cost of monitoring its crawled web pages for keeping updated versions. In this work we present a novel approach that uses machine learning to generate score functions that produce accurate rankings of pages regarding their probability of being modified on the Web when compared to their previously crawled versions. We propose a flexible framework that uses Genetic Programming to evolve score functions to estimate the likelihood that a web page has been modified. We present a thorough experimental evaluation of the benefits of using the framework over five state-of-the-art baselines. Considering the Change Ratio metric, the values produced by our best evolved function show an improvement from 0.52 to 0.71 on average over the baselines.Um dos principais desafios enfrentados durante o desenvolvimento de políticas de escalonamento para atualizações de páginas web é estimar a probabilidade de uma página que já foi coletada previamente ser modificada na Web. Esta informação pode ser usada pelo escalonador de um coletor de páginas web para determinar a ordem na qual as páginas devem ser recoletadas, permitindo ao sistema reduzir o custo total de monitoramento das páginas coletadas para mantê-las atualizadas. Nesta dissertação é apresentada uma nova abordagem que usa aprendizado de máquina para gerar funções de score que produzem listas ordenadas de páginas com relação a probabilidade de terem sido modificadas na Web quando comparado com a última versão coletada. É proposto um arcabouço flexível que usa Programação Genética para evoluir funções que estimam a probabilidade de a página ter sido modificada. É apresentado ainda uma avaliação experimental dos benefícios de usar o arcabouço proposto em relação a cinco abordagens estado-da-arte. Considerando a métrica Change Ratio, os valores produzidos pela melhor função gerada pelo arcabouço proposto mostram uma melhora de 0.52 para 0.71, em média, em relação aos baselines.
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Bajwa, Ayesha R. (Ayesha Raji). "Analyzing student learning trajectories in an introductory programming MOOC". Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/123002.
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This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 73-75).
Understanding student learning and behavior in Massive Open Online Courses (MOOCs) can help us make online learning more beneficial for students. We investigate student learning trajectories on the individual problem level in an MITx MOOC teaching introductory programming in Python, considering simple features of the student and problem as well as more complex keyword occurrence trajectory features associated with student code submissions. Since code is so problem-specific, we develop gold standard solutions for comparison. Anecdotal observations on individual student trajectories reveal distinct behaviors which may correlate with prior experience level. We build models to correlate these trajectories with student characteristics and behaviors of interest, specifically prior experience level and video engagement. Generative modeling allows us to probe the space of submitted solutions and trajectories and explore these correlations.
by Ayesha R. Bajwa.
M. Eng.
M.Eng. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science
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Teague, Madonna Margaret. "Pedagogy of introductory computer programming : a people-first approach". Thesis, Queensland University of Technology, 2011. https://eprints.qut.edu.au/46255/1/Donna_Teague_Thesis.pdf.
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Students struggle with learning to program. In recent years, not only has there been a dramatic drop in the number of students enrolling in IT and Computer Science courses, but attrition from these courses continues to be significant. Introductory programming subjects traditionally have high failure rates and as they tend to be core to IT and Computer Science courses can be a road block for many students to their university studies.
Is programming really that difficult — or are there other barriers to learning that have a serious and detrimental effect on student progression?
In-class experiments were conducted in introductory programming units to confirm our hypothesis that that pair-programming would benefit students' learning to program. We investigated the social and cultural barriers to learning programming by questioning students' perceptions of confidence, difficulty and enjoyment of programming. The results of paired and non-paired students were compared to determine the effect of pair-programming on learning outcomes.
Both the empirical and anecdotal results of our experiments strongly supported our hypothesis.
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徐琨閔. "An Integrated MOOCs Environment for Learning Java Programing". Thesis, 2015. http://ndltd.ncl.edu.tw/handle/84053864522511074445.
Texto completo da fonteResumo:
碩士逢甲大學
資訊工程學系
103
In recent years, MOOCs is getting more and more popular, many schools in Taiwan plan to offer courses on MOOCs platform. With the convenience of online learning, students can take courses on the network; this will make a big difference on traditional education. Therefore, how to make MOOCs education also set the benefits of the traditional education is the challenge we will take. Many MOOCs provide simulation tools to help experiments. Thus, students can use browser to access course materials and make experiment on the MOOCs environment. For programming courses, students will take a better learning experience if the environment can provide the online programing environment. In this thesis we propose an integrated environment in Open edX MOOCs platform for learning java programing. With the browser-based code editor and the compiler service which is based on REST architecture, students can develop software program on browsers. With integrating the JUnit in our environment teachers can write a test code to assess students’ programs on the course.
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Kuo, Cheng-Chang, e 郭正昌. "A Study of a Game-based Learning with the Concept of Social Learning 2.0 － An Example of Object-Oriented Programing Learning". Thesis, 2010. http://ndltd.ncl.edu.tw/handle/29347764483557969950.
Texto completo da fonteResumo:
碩士中原大學
資訊管理研究所
98
The purpose of this paper is to study and to actually practice a Game-based Learning with the concepts of Social Learning 2.0 in order to provide a different learning method to learners. The learning method will be evaluated if the motivations, interactions, and satisfactions of learners are enhanced or improved. The learners will have chance to experience a different learning method from the traditional Lecture-based-learning. Game-based learning is the most attractive learning method which can arouse learner's motivation and concentration. For example, Singapore had funding 600 million SGD in 2009 for developing the digital learning games which are not only used for educating purposes but also for national defense, healthcare and other areas of learning. Therefore, it is not difficult to understand the Game-based learning has great effects and values on learning. As a result, the contents of this paper will focus on creating a system model which consolidates the concepts of social learning and related technologies by narrowing the concepts of social learning 2.0 and studying game-based Learning. The learners will be expected to enhance their motivations and have great effects on their studying through this kind of learning environment and methods.
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PENG, TZU-MIN, e 彭資閔. "Augmented Reality Combine Graphic Programing to Evaluate the Effectiveness of the Impact on Children's Learning". Thesis, 2016. http://ndltd.ncl.edu.tw/handle/49718983193704857827.
Texto completo da fonteResumo:
碩士國立臺北教育大學
數位科技設計學系(含玩具與遊戲設計碩士班)
104
The rapid development of digital technology has affected all our lives in many dramatic ways. Digital games, devised for educational purposes, are taking the place of traditional teaching methods. These digital waves not only affect the educational circle by adding digital content to teaching techniques, but digital games, purely for entertainment, have recently undergone a huge surge in popularity and use. While much of this is digital education and can have positive effect, children exposed to the Internet can often become distracted and even addicted. Smartphones and Tablets are now available to almost everyone and e-learning allows people to accumulate new knowledge at a rapid rate. There are thousands of online learning programs and downloadable stand-alone software that makes it possible to say good-bye to traditional reading. In this study our goal was to achieve learning through games, logical thinking, and the popularization of virtual reality through a study of robots. In this study, an educational software program “Play a Big Robot”, was used to augment reality in a way that would allow children to develop logical skill in a practical way. The children followed a narrative that guided them into the plot of the story and provided a clear concept of the definition of a robot.
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Kuo, Wen-Ming, e 郭文明. "The Effect of Advance Organizer on Learning Attitude and Achievement for Third Graders in Scratch Programing Classes". Thesis, 2015. http://ndltd.ncl.edu.tw/handle/90025173129902401190.
Texto completo da fonteResumo:
碩士淡江大學
教育科技學系碩士在職專班
103
The major purpose of this study is to investigate the effect of advance organizer strategy on third graders’ learning attitude and learning effectiveness in Scratch programming classes. This study adopted quasi experimental design to conduct a learning experiment for Scratch programming. The subjects are third graders from two classes in Taipei City, and they were divided into the experiment group (n=27) and the control group (n=27). The experiment group accepted the instructionwithan advance organizer strategy, and the control group accepted the instruction with a traditional expository strategy. The experiment lasted for eight weeks. All participants used the same Scratch projects designed by the researcher to learn the fundamental Scratch commands and how to implement a Scratch project. In the end of the experiment, the results were analyzed in accordance with t-test and two-Way ANOVA. The conclusions were as the followings. 1. No significant differences on third graders’ learning effectiveness were found in both the group instructed with advance organizer strategy and the groupwith the traditional expository strategy. 2. The researcher divided the students into three levels of learning achievement (i.e. higher-level, medium-level, and lower-level) based on their four Scratch performance test results. The results showed that the high-level students made better achievements in Scratch learning than the medium-level students, and the medium-level students also made better achievements than the lower-level students. In addition, the achievements of the higher-level students were significantly betterthan the lower-level students. 3. As to learning attitudes towards Scratch learning, the experiment groupmade better achievements than the control group. 4. The experiment group also made better achievements than the control group on the questionnaire of satisfaction and interest on learning attitudes towards Scratch learning. However, there is no significant gender difference on the questionnaire of usefulness, confidence and cooperation.
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LIN, HSING-HSUAN, e 林欣璇. "The Effect of Applying Peer Tutoring to Programing Teaching on 7th Grader’s Computational Thinking Ability and Learning Achievement". Thesis, 2018. http://ndltd.ncl.edu.tw/handle/j9t7z7.
Texto completo da fonteResumo:
碩士臺北市立大學
資訊科學系
106
Abstract Coding education becomes a big trend in compulsory education all over the world recently. How to promote the effect of programming learning is valuable. Peer tutoring strategy has the potential for enhancing the learning achievement and attitudes. As a result, the main purpose of this study was to investigate the learning effects of peer-tutoring strategy on Scratch programming learning. The study adopted quasi experiment design for conducting a learning experiment. The subjects are seventh graders in a junior high school in Taipei city, divided into experimental group (n=56) and control group (n=110). The experimental group accepted peer tutoring strategy while control group accepted general teaching method. The eight instruments were employed for measuring the learning effect including computer attitudes, self-efficacy for general learning, self-efficacy for programming learning, Scratch learning attitudes, Scratch learning achievement, Scratch programming skill test, and Bebras computational thinking test I and II. The learning experiment lasted for one and half month, and the collected data were analyzed by descriptive statistics, one-way ANCOVA, one-way ANOVA, and t test. The results showed as follows: (1) peer tutoring strategy has significant positive impact on Scratch achievement, but its impact on other effects are not significant including Scratch learning attitudes, self-efficacy for programming learning, Scratch programming skill test. (2) Programming learning can enhance the students’ computational thinking abilities by peer tutoring or general teaching method significantly, but the difference of computational thinking abilities between experimental group and control group are not significant. (3) There are no significant difference on all measurement between genders. (4) Computer attitudes significantly affect the students’ Scratch attitudes, self-efficacy for programming learning, and Scratch achievement in both group, but do not affect other measurement. (5) general learning self-efficacy significantly affect the students’ Scratch attitudes, self-efficacy for programming learning in experimental group, but do not affect other measurement. On the other hand, general learning self-efficacy significantly affect the students’ Scratch attitudes, Scratch achievement, computational thinking test, and self-efficacy for programming learning in control group, but do not affect other measurement. Keywords: peer tutoring, Scratch programming, computational thinking, learning effect, junior high school
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Lin, Chih-Yuan, e 林志垣. "Adaptive Programming Learning Environment". Thesis, 2010. http://ndltd.ncl.edu.tw/handle/49992715977488559003.
Texto completo da fonteResumo:
碩士雲林科技大學
資訊管理系碩士班
98
In a traditional programming language course, the instructor provides one set of exercises for all the students, not considering the background and portfolio of each student. Resulting in many students with good capabilities wasting unnecessary time on some basic questions lengthening the language learning time, and reduces learning performance. This study provides an adaptive programming learning environment that allows students to join a course, according to their background ability. Adaptive analysis and determination system automatically provides students with different levels of questions according to student’s learning performance, and no longer require all students to practicing the same set of exercises. This study, takes 76 students from the Department of Information Management of National Yunlin University of Science and Technology as samples. They use an adaptive programming learning environment to learn Java programming language, and use post-test analysis to study the effect of adaptive learning and traditional learning. Our study shows that adaptive learning and traditional learning no significant difference in their effectiveness.
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Tran, Dustin. "Probabilistic Programming for Deep Learning". Thesis, 2020. https://doi.org/10.7916/d8-95c9-sj96.
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We propose the idea of deep probabilistic programming, a synthesis of advances for systems at the intersection of probabilistic modeling and deep learning. Such systems enable the development of new probabilistic models and inference algorithms that would otherwise be impossible: enabling unprecedented scales to billions of parameters, distributed and mixed precision environments, and AI accelerators; integration with neural architectures for modeling massive and high-dimensional datasets; and the use of computation graphs for automatic differentiation and arbitrary manipulation of probabilistic programs for flexible inference and model criticism.
After describing deep probabilistic programming, we discuss applications in novel variational inference algorithms and deep probabilistic models. First, we introduce the variational Gaussian process (VGP), a Bayesian nonparametric variational family, which adapts its shape to match complex posterior distributions. The VGP generates approximate posterior samples by generating latent inputs and warping them through random non-linear mappings; the distribution over random mappings is learned during inference, enabling the transformed outputs to adapt to varying complexity of the true posterior. Second, we introduce hierarchical implicit models (HIMs). HIMs combine the idea of implicit densities with hierarchical Bayesian modeling, thereby defining models via simulators of data with rich hidden structure.
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Bennett, Kristin P. "Machine learning via mathematical programming". 1993. http://catalog.hathitrust.org/api/volumes/oclc/30652338.html.
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Thesis (Ph. D.)--University of Wisconsin--Madison, 1993.Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 153-160).
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Liu, Wei-Shung, e 劉偉晟. "Dialogue Assisted Programming Learning System". Thesis, 2013. http://ndltd.ncl.edu.tw/handle/31990736661833210752.
Texto completo da fonteResumo:
碩士崑山科技大學
數位生活科技研究所
101
With the popularization of information technology, program coding and modifying capabilities gradually become the fundamentals of IT industry's job requirement. Meanwhile, the programming has become one of necessary courses in the department of computer science. However, during the process of teaching programming, the arrangement is not really suited for the novice students. If we simply forced learners to complete lots of programs without sufficient practice or time, they may hate to program and this phenomenon may cause learning obstacles or fear. In order to enhance the effectiveness of student learning program design, this study developed a conversational-assisted learning systems. Through the use of conversational way to enable users to understand their content strategies to enhance students' willingness to learn and improve learning.