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Porter, Ronald, and ron porter@infoeng flinders edu au. "Design Patterns in Learning to Program." Flinders University. Informatics and Engineering, 2006. http://catalogue.flinders.edu.au./local/adt/public/adt-SFU20061127.153554.
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This thesis argues the case for the use of a pattern language based on the basic features of the programming language used in instruction for the teaching of programming. We believe that the difficulties that novices are known to have encountered with the task of learning to program ever since the inception of computers derive from a basic misfit between the language used to communicate with a computer, the programming language, and the way that humans think. The
thrust of the pattern language idea is that patterns are the essential element in understanding how the mind words in that they are the source of that relationship that we call `meaning'. What an entity or event `means' to us derives from the effect that it has on us as living biological beings, a relationship that exists in the `real world', not from any linguistic relationship at the symbolic level.
Meaning, as a real world relationship, derives from the patterns of interactions that constitute being. The meaning that an entity has for an individual is more than can be expressed in a formal definition, definitions are matters of agreement, convention, not the pattern of experience that the individual has acquired
through living. What is missing for a novice in any skill acquisition process is meaning, the pattern of experience. All that we can give them using a formal linguistic system like a programming language is definitions, not meaning. Pattern language is the way that we think because it exists at that fundamental level of experience as living beings. The patterns of experience become the patterns of thought through recurrence, not through definition. But this takes time, so in
presenting new material to a person trying to learn, we have to present it in the form of a pattern language, the 'cognitive map' that drives the problem solving process. Creativity is always a function of combining ideas, what is really being created is new meaning, not a program, or a house, or a poem, or a sculpture - these things are mere implementations of meaning. Ultimately meaning can derive only from experience, the pattern of life around us, so creativity is the language of experience, pattern language. The mind is the product of experience, creativity its modus operandi.
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Agrawal, Punit. "Program navigation analysis using machine learning." Thesis, McGill University, 2009. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=32599.
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Developers invest a large portion of their development time exploring program source code to find task-related code elements and to understand the context of their task. The task context is usually not recorded at the end of the task and is forgotten over time. Similarly, it is not possible to share the task context with other developers working on related tasks. Proposed solutions to automatically record the summary of the code investigation suffer from methodological limitations related to the techniques and the data sources used to generate the summary as well as the granularity at which it is generated. To overcome these limitations, we investigate the use of machine learning techniques, in particular decision tree learning, to predict automatically the task context from session navigation transcripts obtained from developers performing tasks on the source code. We conducted a user study to collect navigation transcripts from developers engaged in source code exploration tasks. We used the data from the user study to train and test decision tree classifiers. We compared the decision tree algorithm with two existing approaches, and found that it compares positively in most cases. Additionally, we developed an Eclipse plug-in that generates automatically a developer session summary using the decision tree classifier learned from the data collected during the user study. We provide qualitative analysis of the effectiveness of this plug-in.Les d\'eveloppeurs de logiciels investissent une grande partie de leur temps \`a explorer le code source pour trouver des \'el\'ements du code reli\'es \`a leurs t\^aches, et aussi pour mieux comprendre le contexte de leur t\^ache. Le contexte de leur t\^ache n'est g\'en\'eralement pas enregistr\'ee \`a la fin de leur s\'eance d'exploration de code et est oubli\'e au fil du temps. De m\^eme, il n'est pas possible de partager le contexte de leur t\^ache avec d'autres d\'eveloppeurs travaillant sur des t\^aches reli\'ees. Les solutions propos\'ees pour enregistrer automatiquement le r\'esum\'e de leur exploration du code souffrent de limitations m\'ethodologiques li\'ees aux techniques et aux sources de donn\'ees utilis\'ees pour g\'en\'erer le r\'esum\'e, ainsi qu'\`a la granularit\'e \`a laquelle il est g\'en\'er\'e. Pour surmonter ces limitations, nous \'etudions l'emploi de techniques d'apprentissage machine, en particulier l'arbre de d\'ecision d'apprentissage, pour pr\'evoir automatiquement le contexte de la t\^ache \`a partir des transcriptes de navigation d'une session d'exploration de code du d\'eveloppeur. Nous avons effectu\'e une \'etude de cas afin de recueillir des transcriptions de navigation g\'en\'er\'es par des d\'eveloppeurs lors de l'exploration du code source. Nous avons utilis\'e les donn\'ees de cette \'etude pour tester les classifications de l'arbre de d\'ecision. Nous avons compar\'e l'algorithme \`a arbre \`a d\'ecision avec deux approches existantes, et avons d\'emontr\'e que cette nouvelle approche se compare favorablement dans la plupart des cas. Additionnellement, nous avons d\'evelopp\'e un plug-in Eclipse qui g\'en\`ere automatiquement un
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SOUSA, Reudismam Rolim de. "Learning syntactic program transformations from examples." Universidade Federal de Campina Grande, 2018. http://dspace.sti.ufcg.edu.br:8080/jspui/handle/riufcg/1712.
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Capes
Ferramentas como ErrorProne, ReSharper e PMD ajudam os programadores a detectar e/ou remover automaticamente vários padrões de códigos suspeitos, possíveis bugs ou estilo de código incorreto. Essas regras podem ser expressas como quick fixes que detectam e reescrevem padrões de código indesejados. No entanto, estender seus catálogos de regras é complexo e demorado. Nesse contexto, os programadores podem querer executar uma edição repetitiva automaticamente para melhorar sua produtividade, mas as ferramentas disponíveis não a suportam. Além disso, os projetistas de ferramentas podem querer identificar regras úteis para automatizarem. Fenômeno semelhante ocorre em sistemas de tutoria inteligente, onde os instrutores escrevem transformações complicadas que descrevem "falhas comuns" para consertar submissões semelhantes de estudantes a tarefas de programação. Nesta tese, apresentamos duas técnicas. REFAZER, uma técnica para gerar automaticamente transformações de programa. Também propomos REVISAR, nossa técnica para aprender quick fixes em repositórios. Nós instanciamos e avaliamos REFAZER em dois domínios. Primeiro, dados exemplos de edições de código dos alunos para corrigir submissões de tarefas incorretas, aprendemos transformações para corrigir envios de outros alunos com falhas semelhantes. Em nossa avaliação em quatro tarefas de programação de setecentos e vinte alunos, nossa técnica ajudou a corrigir submissões incorretas para 87% dos alunos. No segundo domínio, usamos edições de código repetitivas aplicadas por desenvolvedores ao mesmo projeto para sintetizar a transformação de programa que aplica essas edições a outros locais no código. Em nossa avaliação em 56 cenários de edições repetitivas de três grandes projetos de código aberto em C#, REFAZER aprendeu a transformação pretendida em 84% dos casos e usou apenas 2.9 exemplos em média. Para avaliar REVISAR, selecionamos 9 projetos e REVISAR aprendeu 920 transformações entre projetos. Atuamos como projetistas de ferramentas, inspecionamos as 381 transformações mais comuns e classificamos 32 como quick fixes. Para avaliar a qualidade das quick fixes, realizamos uma survey com 164 programadores de 124 projetos, com os 10 quick fixes que apareceram em mais projetos. Os programadores suportaram 9 (90%) quick fixes. Enviamos 20 pull requests aplicando quick fixes em 9 projetos e, no momento da escrita, os programadores apoiaram 17 (85%) e aceitaram 10 delas.
Tools such as ErrorProne, ReSharper, and PMD help programmers by automatically detecting and/or removing several suspicious code patterns, potential bugs, or instances of bad code style. These rules could be expressed as quick fixes that detect and rewrite unwanted code patterns. However, extending their catalogs of rules is complex and time-consuming. In this context, programmers may want to perform a repetitive edit into their code automatically to improve their productivity, but available tools do not support it. In addition, tool designers may want to identify rules helpful to be automated. A similar phenomenon appears in intelligent tutoring systems where instructors have to write cumbersome code transformations that describe “common faults” to fix similar student submissions to programming assignments. In this thesis, we present two techniques. REFAZER, a technique for automatically generating program transformations. We also propose REVISAR, our technique for learning quick fixes from code repositories. We instantiate and evaluate REFAZER in two domains. First, given examples of code edits used by students to fix incorrect programming assignment submissions, we learn program transformations that can fix other students’ submissions with similar faults. In our evaluation conducted on four programming tasks performed by seven hundred and twenty students, our technique helped to fix incorrect submissions for 87% of the students. In the second domain, we use repetitive code edits applied by developers to the same project to synthesize a program transformation that applies these edits to other locations in the code. In our evaluation conducted on 56 scenarios of repetitive edits taken from three large C# open-source projects, REFAZER learns the intended program transformation in 84% of the cases and using only 2.9 examples on average. To evaluate REVISAR, we select 9 projects, and REVISAR learns 920 transformations across projects. We acted as tool designers, inspected the most common 381 transformations and classified 32 as quick fixes. To assess the quality of the quick fixes, we performed a survey with 164 programmers from 124 projects, showing the 10 quick fixes that appeared in most projects. Programmers supported 9 (90%) quick fixes. We submitted 20 pull requests applying our quick fixes to 9 projects and, at the time of the writing, programmers supported 17 (85%) and accepted 10 of them.
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李偉柏 and Wai-pak Li. "Learning algebra with computer-assisted learning program in a primary school." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2002. http://hub.hku.hk/bib/B31256399.
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Karam, V. (Viera). "Cooperative learning through narratives of the LAB studio learning program participants." Master's thesis, University of Oulu, 2019. http://jultika.oulu.fi/Record/nbnfioulu-201908172771.
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Abstract. In 2012, Oulu University of Applied Sciences established non-degree training programs called ‘Oamk LABs’, which practice a new form of studio-based model of learning, they called the LAB studio model. Such model includes basic elements of traditional studio-based learning model (practice and reflection-in-action, solving real-life problems, active collaboration with peers and experts of the industry, as well as the learning space) and adds two more features of the multidisciplinary and international environment. This is maintained by keeping the application process open for Finnish and international students from various disciplines, as well as professionals for retraining and unemployed specialists.
Since LAB studio learning model is new and evolving phenomena, there is a continuous need to conduct research and contribute to its development. This study has looked at the students’ perspective on the learning process by conducting narrative inquiry research in collaboration with two participants enrolled in one of the Oamk LABs programs. The primary research question for the study is: ‘How do different participants experience the LAB studio learning model?’ The answer to this is presented in the form of two stories placed in the Findings section. The stories were written using narrative analysis of the collected data (narrative interviews, sketched journeys and email conversations) and co-edited together with participants during the research process. The stories reveal two unique journeys reflecting various opinions on the learning model. Those opinions are shaped by the personal and professional background of the participants, as well as the unique circumstances under which each one has studied for the semester. Despite the differences both stories highlight various aspects of cooperative learning during the LAB studies. Thus, the second research question was formed: ‘How do participants experience cooperative learning as a part of the LAB studio learning model?’ The answer to this question is placed in the Discussion part of the research. Narratives revealed three main themes related to the challenges of cooperative learning in the LAB studies: communication issues, expectation gaps, as well as complications caused by the multidisciplinary and international environment.
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Rust, William J. "Learning to program in Java using robots /." Search for this dissertation online, 2006. http://wwwlib.umi.com/cr/ksu/main.
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Bheda, Anuj. "Predictive analytics of active learning based education." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/113509.
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Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, System Design and Management Program, 2017.Cataloged from PDF version of thesis.
Includes bibliographical references (pages 113-115).
Learning Analytics (LA) is defined as the collection, measurement, and analysis of data related to student performance such that the feedback from the analytical insights can be used to optimize student learning and improve student outcomes. Blended Learning (BL) is a teaching paradigm that involves a mix of face-to-face interactions in a classroom based setting along with instructional material distributed through an online medium. In this thesis, we explore the role of a blended learning model coupled with learning analytics in an introductory programming class for non-computer science students. We identify the features that were necessary for setting up the infrastructure of the course. These include discussions on preparing the course content materials and producing assignment exercises. We then talk about the various dynamics that were in play during the duration of the class by describing the interplay between watching video tutorials, listening to mini-lectures and performing active learning exercises that are backed by modern software development practices. Lastly, we spend time analyzing the data collected to create a predictive model that can measure student performance by defining the specifications of a machine learning algorithm along with many of its adjustable parameters. The system thus created will allow instructors to identify possible outliers in teaching efficacy, the feedback from which could then be used to tune course material for the betterment of student outcomes.
by Anuj Bheda.
S.M. in Engineering and Management
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Chen, Mei 1962. "The characterization of learning environments and program structures of instructional programs produced using Logo /." Thesis, McGill University, 1992. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=56930.
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A methodology was developed in this study for identifying the cognitive, pedagogical, and computational characteristics of computer-based learning environments. The characterization of the cognitive and pedagogical features was achieved by decomposing the learning environments into episodes which were composed of sequences of "views". Each "view" was described in terms of the different types of knowledge presented, the pedagogical strategies used to present the knowledge, and the forms and functions of user-computer interactions elicited. The computational characteristics were described in terms of modularity and other programming properties. The methodology was applied to characterizing the instructional programs produced by student teachers using Logo.The results showed that this methodology can successfully identify the cognitive, pedagogical and computational characteristics of the learning environments. It can also clarify what can be learned in a microworld, especially the "powerful ideas" in Logo environments. In addition, the usability and constraints of learning environments in meeting the learners' cognitive needs during the learning process can be assessed.
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Thobani, Shaheen. "Improving e-Commerce sales using machine learning." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/118511.
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Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, System Design and Management Program, 2018.Cataloged from PDF version of thesis.
Includes bibliographical references (pages 68-70).
Trends show promising growth of the online e-Commerce industry. While the e-Commerce companies are aggressively moving towards digital sales and marketing, the customers are being bombarded with frequent and often irrelevant marketing communication from myriad sources. The thesis proposes understanding the digital purchase journeys of the customers from the lenses of both sellers and customers to make online sales and marketing efforts relevant and intelligent. The thesis applies the improved customer journey framework to identify the needs of the customers and goals of the seller at various stages of customer purchase journey. It discusses the need to take an integrated view of the purchase journey to improve the customer experience at the journey level. It illustrates with an example how to design end-to-end journeys - a starting point for consciously shaping the purchase journeys. Larger companies are using Machine Learning to improve marketing technologies and processes to create a competitive advantage and capture market share through digital presence. The thesis aims to understand and illustrate the applications of Machine Learning to digital sales and marketing ecosystem for the e- Commerce industry. It first understands the e-Commerce touchpoints using which customers interact with the brands and delves deeper into the underlying technologies powering these touchpoints. Then it illustrates and analyzes the application of Machine Learning to the e-Commerce website which includes search, recommendation system, and Product Detail Page with an aim to improve conversion, and to the advertising ecosystem which includes Data Management Platform and Demand Side Platform in order to enable prospecting and customer targeting. The thesis also illustrates and proposes the use of a framework called 'Machine Learning Canvas' to systematically apply Machine Learning to any system while keeping value proposition for the business in the center.
by Shaheen Thobani.
S.M. in Engineering and Management
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Zhen, Shuyi. "Learning in a pre-service teacher residency program." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2015. https://ro.ecu.edu.au/theses/1749.
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Teacher educators worldwide are seeking ways to develop stronger links with schools, to improve the quality of initial teacher preparation. In this study the researcher investigated a residency approach to initial teacher education (ITE) in a one-year Graduate Diploma of Education course designed to prepare primary school teachers at a university in Western Australia. A mixed methods inquiry approach was employed to examine the nature and quality of the professional learning experiences of the pre-service teacher participants.
The Teacher Residency Program (TRP) was based on a medical residency model, with residents given a semester-length placement in two schools. Each placement provided a continuous two-day per week placement and concluded with a five-week fulltime block teaching experience. University course work complemented the in-school practical experience during each of the placement periods. The researcher used concurrent nested research design with quantitative data embedded in the qualitative data to explore the professional learning of the residents; Specifically, the researcher sought evidence of perspective transformation in the residents’ learning process, and a determination of how particular elements of the TRP supported or hindered residents’ professional development.
The findings indicate that the residents perceived their professional learning as one of continuous growth. The data confirm that the TRP provided a professionally oriented study of teaching that provided time and opportunity for cumulative learning from both course work and practical teaching. Through the lens of a transformative learning paradigm, the study found that individual development in the TRP varies considerably. Further the residents experienced perspective transformation relating to a range of aspects about learning to teach. The process of transforming perspectives about teaching and learning was multidimensional, individualistic and contextually dependent. Elements of the TRP that assisted residents’ professional development were the concurrent university course work integrated with extended clinical school placement; the opportunities for continuous two-day per week school placement; the block practicum and the two different school placement learning experiences. Aspects that appeared to hinder residents’ professional development were related to the quantity and quality of the university course work offered; the discrepancies that the residents experienced between what they studied about teaching and what they experienced in schools; differences between mentor teachers, and the length of the course. The findings of this study have implications relevant to other ITE programs for improving the learning outcomes of pre-service teachers.
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Pepper, Jeff. "Learning to train a train-the-trainer program." Menomonie, WI : University of Wisconsin--Stout, 2005. http://www.uwstout.edu/lib/thesis/2005/2005pepperj.pdf.
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Schimelpfenig, Diane Schedin. "A study of the learning resource teacher program /." Diss., ON-CAMPUS Access For University of Minnesota, Twin Cities Click on "Connect to Digital Dissertations", 2000. http://www.lib.umn.edu/articles/proquest.phtml.
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Alfano, Christopher J. 1964. "Seniors' participation in an intergenerational music learning program." Thesis, McGill University, 2008. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=115599.
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Intergenerational programs that bring together young people and older adults have been the subject of investigation in recent years. However, there is little research on the topic of intergenerational education programs, and virtually no research on collaborative, intergenerational music education programs in public school settings. This study sought to capture senior citizens' reflections on their experience as co-participants with adolescents in an Ontario Ministry of Education fully-funded daytime instrumental band program. This program has been running continuously and successfully at a high school since 1994. The site is a rich source of information about the ways in which seniors interact musically, socially and educationally with their own age cohort and with adolescents in this co-learning environment. Qualitative data were gathered using tools of ethnography including participant observation, interview and document analysis, while quantitative data regarding demographic and other information about participants' backgrounds, experience, practice habits and so forth were gathered by means of a questionnaire. An instrumental case study approach was used to investigate the associations of young and old both in social and learning contexts in a broad sense, so that the findings would not be limited to the specific interactive associations that occurred in a music learning and performance environment, but could be applied to other intergenerational associative situations. The study reports on the personal, social and intellectual benefits that senior participants divulged as they reflected on their participation in an intergenerational instrumental music program. The study concluded that an active daytime high school music program that included senior citizens as registered music students, which supported the interaction of young and old as equals in music learning activities, resulted in a greater understanding, acceptance, care, respect and appreciation of one age group for another. Recommendations for social policy regarding support for intergenerational, collaborative, publicly funded educational programs are offered.
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Jensen, Donna Mae. "Mentoring in a distributed learning social work program." Thesis, Fielding Graduate University, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=3612098.
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While strides have been made for increased access in higher education, barriers continue to impede the success of traditionally underrepresented students. Students in alternative education programs often experience differential access to faculty, advisors, university support systems, and the supportive culture established by being on campus. In addition to disconnection from university culture, they may not have the social and cultural capital that can help them feel confident and worthy or capable of an advanced degree. This study was a descriptive-exploratory program evaluation of the distributed learning social work mentoring program at California State University, Chico. The study critically analyzed the mentoring program. The three research questions were (1) what components/content areas of a mentoring program are used most by students; (2) what contributed to the utilization of a mentor; and (3) how did technology influence (impact/guide) the mentoring process? Further, the researcher examined if these components differed between first-generation and non-first-generation students, between rural and urban-dwelling students, by the age of students, graduate and undergraduate students, and the student's geographical proximity to the main CSU, Chico campus. All demographic areas of students utilized mentoring for Emotional Support, Self-Care, Help in Managing School, Family, and Work and Time Management. Other nuances of differential support were explored.
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Alfano, Christopher J. "Seniors’ participation in an intergenerational music learning program." Thesis, McGill University, 2009. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=113375.
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Note:lntergenerational programs that bring together young people and older adults have been the subject of investigation in recent years. However, there is little research on the topic of intergenerational education programs, and virtually no research on collaborative, intergenerational music education programs in public school settings. This study sought to capture senior citizens’ reflections on their experience as co-participants with adolescents in an Ontario Ministry of Education fully-funded daytime instrumental band program. This program has been running continuously and successfully at a high school since 1994. The site is a rich source of information about the ways in which seniors interact musically, socially and educationally with their own age cohort and with adolescents in this co-learning environment. Qualitative data were gathered using tools of ethnography including participant observation, interview and document analysis, while quantitative data regarding demographic and other information about participants’ backgrounds, experience, practice habits and so forth were gathered by means of a questionnaire.[...]
Les programmes intergénérationnels qui réunissent jeunes et aînés ont été l’objet d’études au cours des années récentes. Cependant, il existe peu d’études sur les programmes d’éducation intergénérationnelle et pratiquement pas de recherche sur les programmes en collaboration intergénérationnels d’éducation musicale dans des écoles publiques. La présente étude avait pour objectif d’obtenir les réflexions d’aînés concernant leur expérience de participation, en collaboration avec des adolescents, à un programme de jour d’ensemble instrumental entièrement subventionné par le Ministère de l’Éducation de l’Ontario. Il s’agit d’un programme offert sans interruption dans une école secondaire depuis 1994 et ayant connu beaucoup de succès. Le site constitue une source précieuse de renseignements sur la façon dont les aînés réagissent tant sur le plan musical que social et éducatif avec la cohorte de leur propre âge et avec des adolescents dans un environnement d’apprentissage en commun. Les données qualificatives ont été recueillies au moyen d’outils d’ethnographie y compris l’observation.[...]
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Marone, April Dawn. "A distance-learning program to serve migrant families." CSUSB ScholarWorks, 2003. https://scholarworks.lib.csusb.edu/etd-project/2464.
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The education of the children of migrant farmworkers is difficult to manage because of their mobile lifestyle. The dropout rate of these children is extremely high and remains the highest of any group in the United States. This project offers an historical overview of the creation and development of the migrant education programs of today. After examining sample distance learning programs and their important components, this project features a model distance-learning program for migrants. The goal is to create distance learning programs that will allow migrant children to continue school as they travel, guide them to graduation, and lead them toward higher education.
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Withers, Denissia Elizabeth. "Engaging Community Food Systems through Learning Garden Programs: Oregon Food Bank's Seed to Supper Program." PDXScholar, 2012. https://pdxscholar.library.pdx.edu/open_access_etds/609.
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The purpose of this study was to discover whether learning garden programs increase access to locally grown foods and successfully empower and include food insecure populations. This study examined the Oregon Food Bank's Seed to Supper program which situates garden-based learning in food insecure communities. Through a mixed-methods community-based research process, this study found that community building, learner empowerment and sustainability leadership in place-based learning garden programs increased access to locally grown foods for food insecure populations. When food insecure populations participated in these learning garden programs they often engaged in practices described in the literature as the "web of inclusion" (Helgesen, 1995). When food insecure populations were engaged in these practices, participation in food democracy and food justice increased. Additionally, participation in learning gardens led to sustainability leadership and increased access to food literacy, which led to greater community health and engaged, local community food systems.
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Vavroušová, Darina. "Vzdělávání v komunitárních programech EU." Master's thesis, Vysoká škola ekonomická v Praze, 2012. http://www.nusl.cz/ntk/nusl-197203.
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The thesis deals with education in Community Programmes. It focuses on Education Policy in EU and Lifelong Learning Programme which was concentrated on Education and Training in 2007 - 2014. Since 2014 the programme has a new form and a new name, Erasmus+. New programme connects six existing programs into a single framework which covers Education, Training, Youth and Sport. In the final part is presented the practical example of completing funding application form to support projects in the education area. The completed form can serve as a guide for future applicants.
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Meers, Eileen G. "An investigation of an experiential education program /." The Ohio State University, 1987. http://rave.ohiolink.edu/etdc/view?acc_num=osu148732966214416.
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Shamsapour, Ali A. "HyperCard-based learning environment for DIADES." PDXScholar, 1990. https://pdxscholar.library.pdx.edu/open_access_etds/4128.
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This thesis is an attempt to create a HyperCard-based learning environment to teach DIADES and other related material. It is a departure from the classical Computer Aided Instruction methods towards a more flexible and user-controlled design. The goal was to set the foundation of a new CAI design which would closely resemble a Hyper- Text system. These systems are characterized as having interconnections between related concepts in the CAI environment.
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Thomaz, Andrea Lockerd. "Socially guided machine learning." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/36160.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2006.Includes bibliographical references (p. 139-146).
Social interaction will be key to enabling robots and machines in general to learn new tasks from ordinary people (not experts in robotics or machine learning). Everyday people who need to teach their machines new things will find it natural for to rely on their interpersonal interaction skills. This thesis provides several contributions towards the understanding of this Socially Guided Machine Learning scenario. While the topic of human input to machine learning algorithms has been explored to some extent, prior works have not gone far enough to understand what people will try to communicate when teaching a machine and how algorithms and learning systems can be modified to better accommodate a human partner. Interface techniques have been based on intuition and assumptions rather than grounded in human behavior, and often techniques are not demonstrated or evaluated with everyday people. Using a computer game, Sophie's Kitchen, an experiment with human subjects provides several insights about how people approach the task of teaching a machine. In particular, people want to direct and guide an agent's exploration process, they quickly use the behavior of the agent to infer a mental model of the learning process, and they utilize positive and negative feedback in asymmetric ways.
(cont.) Using a robotic platform, Leonardo, and 200 people in follow-up studies of modified versions of the Sophie's Kitchen game, four research themes are developed. The use of human guidance in a machine learning exploration can be successfully incorporated to improve learning performance. Novel learning approaches demonstrate aspects of goal-oriented learning. The transparency of the machine learner can have significant effects on the nature of the instruction received from the human teacher, which in turn positively impacts the learning process. Utilizing asymmetric interpretations of positive and negative feedback from a human partner, can result in a more efficient and robust learning experience.
by Andrea Lockerd Thomaz.
Ph.D.
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Moström, Jan Erik. "A study of student problems in learning to program." Doctoral thesis, Umeå universitet, Institutionen för datavetenskap, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-48216.
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Programming is a core subject within Computer Science curricula and many also consider it a particularly difficult subject to learn. There have been many studies and suggestions on what causes these difficulties and what can be done to improve the situation. This thesis builds on previous work, trying to understand what difficulties students have when learning to program. The included papers cover several areas encountered when trying to learn programming. In Paper I we study how students use annotations during problem solving. The results show that students who annotate more also tend to be more successful. However, the results also indicate that there might be a cultural bias towards the use of annotations. Not only do students have problems with programming, they also have problems with designing software. Even graduating students fail to a large extent on simple design tasks. Our results in Paper II show that the majority of the students do not go beyond restating the problem when asked to design a system. Getting stuck is something that most learners experience at one time or another. In Paper III we investigate how successful students handle these situations. The results show that the students use a large number of different strategies to get unstuck and continue their learning. Many of the strategies involve social interaction with peers and others. In Papers IV, V, and VI we study what students experience as being key and threshold concepts in Computer Science. The results show that understanding particular concepts indeed affect the students greatly, changing the way they look at Computer Science, their peers, and themselves. The two last papers, Papers VII and VIII, investigate how researchers, teachers and students view concurrency. Most researchers/teachers claim that students have difficulties because of non-determinism, not understanding synchronization, etc. According to our results the students themselves do not seem to think that concurrency is significantly more difficult than any other subject. Actually most of them find concurrency to be both easy to understand and fun.Programmering har en central roll i datavetenskapliga utbildningar. Många anser att programmering är svårt att lära sig. Ett stort antal studier har undersökt vad som orsakar dessa svårigheter och hur det är möjligt att övervinna dem. Denna avhandling är en del av denna forskning. Artiklarna i avhandlingen undersöker vilka problem som studenterna stöter på under sina programmeringsstudier. Artikel 1 beskriver hur studenter använder sig av annoteringar vid problemlösning. Resultaten visar att studenter som gör många annoteringar tenderar att prestera bättre. Resultaten antyder också att det kan finnas kulturella skillnader i hur ofta annoteringar används. Studenter har inte bara problem vid programmering, de har också problem med att utforma programvarusystem. Även sistaårsstudenter misslyckas till stor del att utforma lösningar för relativt enkla system. Resultaten i Artikel II visar att majoriteten av studenterna inte kommer längre än en omformulering av problemet. Att inte förstå ett koncept eller en specifik detalj är något som alla studenter stöter på då och då. I Artikel III undersöker vi hur framgångsrika studenter hanterar en sådan situation. Resultaten visar att studenterna använder sig av ett stort antal olika strategier för att få en förståelse för konceptet/detaljen. Många av de redovisade strategierna bygger på en social interaktion med andra. Artiklarna IV, V och VI utforskar vad studenterna uppfattar som nyckelkoncept inom datavetenskap och hur förståelsen av dessa koncept påverkar dem. Resultaten visar att förståelsen av vissa specifika koncept kan göra att studenterna ändrar hur de ser på datavetenskap, kollegor och sig själva. I artiklarna VII och VIII undersöker vi hur forskare, lärare och studenter ser på de problem studenter har vid jämlöpande programmering. De flesta forskare och lärare hävdar att studenterna har problem med att förstå icke-determinism, synkronisering, etc. Våra resultat visar dock att studenterna inte själva tycks anse att jämlöpande programmering är signifikant svårare än andra ämnen. Tvärtom, de flesta anser att jämlöpande programmering är både lätt att förstå och roligt.
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Obeda, Larry. "Impact of Learning Acceleration Program on Students Academic Success." Thesis, Wingate University, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10685692.
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This study is a review of the Learning Acceleration Program and the impact it has on student academic success in the Rural School District (pseudonym). This mixed-methods study used qualitative and quantitative data analyses to identify the impact that the Learning Acceleration Program has on the overall attendance and graduation rates for the district. The study also provided an understanding of the impact the Learning Acceleration Program has on perceptions as it pertains to the program. Data for this study were collected for the period of three academic school years on attendance, graduation rate for each year, and surveys completed by participants who have first-hand knowledge of the Learning Acceleration Program. The participants in this study were high school principals, one assistant principal, high school counselors, and Learning Acceleration Program personnel. The findings exhibited statistical significant difference in attendance or graduation rates on district. Furthermore, the findings from the survey highlighted the ability to meet the needs of each individual on an individual basis and provide future recommendations.
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Sebastian, Dipu, and dipu_sebastian@hotmail com. "Enhancing student learning in a first year business program." Deakin University. Education, 2009. http://tux.lib.deakin.edu.au./adt-VDU/public/adt-VDU20100401.122742.
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The central purpose of this study was to investigate whether specific teaching and learning activities, such as concept mapping and reconceptualising the assessment criteria, could improve student learning outcomes in a first year Business program. The rationale for designing such strategies was based on a preliminary study, which examined the specific characteristics of the student cohort, and relevant literature. Overall, findings of this research suggest that these measures can improve student learning outcomes on a written task and further lighlighted the importance of engaging the student within the learning process.
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Strachan, Kevin Winton. "Cooperative learning in a secondary school physical education program." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ29570.pdf.
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Strachan, Kevin. "Cooperative learning in a secondary school physical education program." Thesis, McGill University, 1996. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=26760.
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The purpose of this study was to describe and interpret cooperative learning in a secondary school physical education program. A multiple-method case study design was used to investigate the physical education environment. One eighth grade girls handball class in its first year of cooperative learning was compared to an eleventh grade girls handball class in its fourth year of cooperative learning. The qualitative inquiry included interviewing the students and the physical education teacher, taking field notes, and analysing relevant documents. A modified version of the task structure observational system (Siedentop, 1994) was used as a quantitative measure of the instructional ecology of the two physical education classes. Data revealed that both classes had low management, transition, and wait times. The grade eleven class spent less time in instruction and more time in engagement than the grade eight class. Both classes showed a similar amount of opportunities to respond during activity, but the eleventh grade class exhibited higher successful student responses. The cognitive engagement was integral to the functioning of both units. This included time used by the students, instead of direct instruction by the teacher, for learning a skill, reviewing material learned, planning a strategy at the beginning of a game, implementing change in activity during the game, and reflecting on activity after the game. The study revealed that both teacher and students understood and could visibly see the benefits that cooperative learning offered to the physical education program. This example of cooperative learning in physical education incorporated the basic elements of positive interdependence, individual accountability, face-to-face interaction, social and interpersonal skills, and group processing, which are germane to effective cooperative learning.
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Winitwatjana, Winit. "A computer aided learning program for pharmaceutical care teaching." Thesis, King's College London (University of London), 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.265079.
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Betts, John David. "Art as mediation for learning: The Arts Integration Program." Diss., The University of Arizona, 1994. http://hdl.handle.net/10150/186865.
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This study is based on the Arts Integration Program, a series of lesson outlines utilizing fine arts experiences (dance, music, theatre, and visual arts) to teach core curriculum subjects. The study took place over two years in six schools, combining qualitative and quantitative research methods to determine: if learning actually took place concurrently with the program's lessons; how the classroom learning environment was affected; and what teachers who use the Arts Integration Program lessons for the first time report about the experience? The study was continued into a second phase based on results of the first. In the development of an Arts Integration Program teacher-mentor model, two teachers from the first year of the study worked with new teachers in their schools who were beginning to use the program. This second phase of the study asked: What is involved in establishing a successful teacher-mentor model with the Arts Integration Program? And, How do the lessons effect the classroom learning environment? Lesson outlines and arts integration techniques are described and results from the Content Area Tests and the Perceived Self-efficacy, Attitude, and Linguistic Domain Questionnaire from both phases of the study are presented. The evolution of the Arts Integration Program Teacher-mentor Model is also described. The process of implementing the program in each school was documented through teacher journals, observations, interviews, and videotapes. The aesthetic reaction that Vygotsky (1971) wrote about seems to be present in these children. Their teachers each report having a more cohesive and supportive classroom environment as a result of the theatre lessons. They all noted improvement in the childrens' communication, expressive and receptive, skills. There is also evidence of transfer into other academic areas. The study showed the more successful Arts Integration Program Teacher-mentor model to be: (1) At least a one-year. (2) Concentrating on one, or two, arts areas. (3) With teacher observing teacher. (4) Regular meeting to plan and discuss. (5) Videotape and review for teachers and students. Plans for future implementation of the Arts Integration Program and ideas for further study are presented.
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Howard, Yvonne Mays. "Provisional Accelerated Learning Center (PAL) entrepreneurship program grant proposal." CSUSB ScholarWorks, 2004. https://scholarworks.lib.csusb.edu/etd-project/2554.
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This thesis was written as part of a process to secure funds to develop a Vocational Education Entrepreneurship Workshop for African American students attending the Provisional Accelerated Learning Center (PAL), a local community based organization which assist high risk individuals to gain vocational education and Graduation Equivalen Diploma (GED)
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O'Hara, Thomas. "Program Evaluation of a Laptop Initiative for Student Learning." ScholarWorks, 2018. https://scholarworks.waldenu.edu/dissertations/5512.
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Administrators of a New Jersey school district implemented a 1:1 laptop initiative in Grades 6-8 in 2013 to bolster student achievement. An evaluation had not been conducted to ascertain the effectiveness of the initiative. The purpose of this study was to examine the effect of the 1:1 laptop initiative on student achievement. The conceptual framework for this study was Stufflebeam's context, input, process, and product evaluation model. The focus of the research question was the differences in New Jersey Assessment of Skills and Knowledge math scores between students involved in the 1:1 laptop initiative for 1 year and students who were not involved. A quantitative post hoc analysis was used to examine data collected from the state assessment database using a convenience sample of only 6th grade students (n = 109). The students' data on the statewide test revealed a mean difference between the 1:1 group (n = 57) which scored 13 points higher than the control group (n = 52). Results of an independent t test were statistically significant at the p = 0.062 level. A position paper based on study findings includes recommendations to the local board of education to continue the initiative and plan professional development for teachers. Further research should be conducted to evaluate the effectiveness of the initiative. Investments in technology such as this initiative may result in improved teaching and learning as a positive social change outcome. Being involved in a 1:1 laptop initiative at an early age in school may assist students in becoming literate in the use of technology, which may help them meet their future career goals.
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Svensson, Niclas, and Damir Vrabac. "Sequence to Sequence Machine Learning for Automatic Program Repair." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254272.
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Most of previous program repair approaches are only able to generate fixes for one-line bugs, including machine learning based approaches. This work aims to reveal whether such a system with the state of the art technique is able to make useful predictions while being fed by whole source files. To verify whether multi-line bugs can be fixed using a state of the art solution a system has been created, using already existing Neural Machine Translation tools and data gathered from GitHub. The result of the finished system shows however, that the method used in this thesis is not sufficient to get satisfying results. No bug has successfully been corrected by the system. Although the results are poor there are still unexplored approaches to the project that possibly could improve the performance of the system. One way being narrowing down the input data to method level of source code instead of file level.
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Friis, Nicolai. "Computer game based learning - SimComp." Thesis, Norwegian University of Science and Technology, Department of Computer and Information Science, 2005. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-9207.
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This report is the result of a computer architecture simulation game development project. The goals of the project were to develop conceptual ideas for a game that could be used in teaching computer architecture at a university level and develop a prototype of game. The game should be based on simulation and the BSPlab simulator. Two types of simulation games were identified; observer and participant. The observer type puts the player outside the simulation and the participant type puts the player inside the simulation. The observer type of simulation game was selected as best suited for a game about computer architecture and simulation. Three conceptual ideas for types of observer simulation games were developed; Computer Tycoon, which puts the player in charge of a company. Computer Manager, which puts the player in the role of manager of a computer team and Computer Builder, which lets the player construct a computer city. The Computer Manager idea was developed further. The player is put in the role of the manager of a computer team. The team competes in a league against other teams, playing a series of matches against each other. A ranking system shows how well the teams have done and in the end of the series a winner will be declared. This is similar to a football-league. A simple prototype of the Computer Manager idea was designed and implemented in Java for use in evaluation of the idea.
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Jaques, Natasha(Natasha M. ). "Social and affective machine learning." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/129901.
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Thesis: Ph. D., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, February, 2020Cataloged from student-submitted PDF of thesis. "February 2020."
Includes bibliographical references (pages 309-342).
Social learning is a crucial component of human intelligence, allowing us to rapidly adapt to new scenarios, learn new tasks, and communicate knowledge that can be built on by others. This dissertation argues that the ability of artificial intelligence to learn, adapt, and generalize to new environments can be enhanced by mechanisms that allow for social learning. I propose several novel deep- and reinforcement-learning methods that improve the social and affective capabilities of artificial intelligence (AI), through social learning both from humans and from other AI agents. First, I show how AI agents can learn from the causal influence of their actions on other agents, leading to enhanced coordination and communication in multi-agent reinforcement learning. Second, I investigate learning socially from humans, using non-verbal and implicit affective signals such as facial expressions and sentiment.
This ability to optimize for human satisfaction through sensing implicit social cues can enhance human-AI interaction, and guide AI systems to take actions aligned with human preferences. Learning from human interaction with reinforcement learning, however, may require dealing with sparse, off-policy data, without the ability to explore online in the environment - a situation that is inherent to safety-critical, real-world systems that must be tested before being deployed. I present several techniques that enable learning effectively in this challenging setting. Experiments deploying these models to interact with humans reveal that learning from implicit, affective signals is more effective than relying on humans to provide manual labels of their preferences, a task that is cumbersome and time-consuming. However, learning from humans' affective cues requires recognizing them first.
In the third part of this thesis, I present several machine learning methods for automatically interpreting human data and recognizing affective and social signals such as stress, happiness, and conversational rapport. I show that personalizing such models using multi-task learning achieves large performance gains in predicting highly individualistic outcomes like human happiness. Together, these techniques create a framework for building socially and emotionally intelligent AI agents that can flexibly learn from each other and from humans.
by Natasha Jaques.
Ph. D.
Ph.D. Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences
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Atkinson, Shamanie. "The Urban Parents' Learning Experiences in an Online Training Program." ScholarWorks, 2019. https://scholarworks.waldenu.edu/dissertations/7214.
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Research has shown a link between urban students' success in U.S. schools and the level of parental involvement. However, urban parents have historically low levels of engagement in their children's education. Increased involvement of urban parents in their children's education can increase student success in urban schools. The purpose of this generic qualitative research study was to understand the experiences of urban parents of children diagnosed with Attention-Deficit/Hyperactivity Disorder (ADHD) who have participated in an online training program to learn about their children's learning disability. Self-efficacy, andragogy, experiential learning, and sociocultural theory were used as conceptual foundations to guide the research. The research question was what are the experiences and perspectives of urban parents of children diagnosed with ADHD who participated in an online training program designed to develop their understanding of their child's learning disability. Participants in this generic qualitative study were 8 parents who participated in an online training program for parents of children with ADHD. Data sources included semi-structured interviews. Data were analyzed using thematic inductive data analysis to identify patterns and themes. The key findings indicated that parents found the online training program helpful in understanding their children's specific learning needs and supported them to become more involved in their children's education. This study contributed to social change by providing insights into an innovative learning environment that advanced urban parent learning and fostered parental involvement in urban schools. Educational leaders can use this knowledge to encourage productive parental outreach programs for urban parents.
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Ballard, Maribeth D. "A plan for a kindergarten-sixth grade service learning program." Online version, 1999. http://www.uwstout.edu/lib/thesis/1999/1999ballardm.pdf.
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Buo, Carrie L. "ON LEPTIN AND LEARNING: INVESTIGATING THE INTERACTION OF LEPTINA SIGNALING AND LEARNING IN ZEBRAFISH." University of Akron / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=akron162428966535721.
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Ribeiro, Andre Figueiredo. "Graph dynamics : learning and representation." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/34184.
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Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2006.Includes bibliographical references (p. 58-60).
Graphs are often used in artificial intelligence as means for symbolic knowledge representation. A graph is nothing more than a collection of symbols connected to each other in some fashion. For example, in computer vision a graph with five nodes and some edges can represent a table - where nodes correspond to particular shape descriptors for legs and a top, and edges to particular spatial relations. As a framework for representation, graphs invite us to simplify and view the world as objects of pure structure whose properties are fixed in time, while the phenomena they are supposed to model are actually often changing. A node alone cannot represent a table leg, for example, because a table leg is not one structure (it can have many different shapes, colors, or it can be seen in many different settings, lighting conditions, etc.) Theories of knowledge representation have in general concentrated on the stability of symbols - on the fact that people often use properties that remain unchanged across different contexts to represent an object (in vision, these properties are called invariants). However, on closer inspection, objects are variable as well as stable. How are we to understand such problems? How is that assembling a large collection of changing components into a system results in something that is an altogether stable collection of parts?
(cont.) The work here presents one approach that we came to encompass by the phrase "graph dynamics". Roughly speaking, dynamical systems are systems with states that evolve over time according to some lawful "motion". In graph dynamics, states are graphical structures, corresponding to different hypothesis for representation, and motion is the correction or repair of an antecedent structure. The adapted structure is an end product on a path of test and repair. In this way, a graph is not an exact record of the environment but a malleable construct that is gradually tightened to fit the form it is to reproduce. In particular, we explore the concept of attractors for the graph dynamical system. In dynamical systems theory, attractor states are states into which the system settles with the passage of time, and in graph dynamics they correspond to graphical states with many repairs (states that can cope with many different contingencies). In parallel with introducing the basic mathematical framework for graph dynamics, we define a game for its control, its attractor states and a method to find the attractors. From these insights, we work out two new algorithms, one for Bayesian network discovery and one for active learning, which in combination we use to undertake the object recognition problem in computer vision. To conclude, we report competitive results in standard and custom-made object recognition datasets.
by Andre Figueiredo Ribeiro.
S.M.
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Jebara, Tony (Tony S. ). 1974. "Discriminative, generative, and imitative learning." Thesis, Massachusetts Institute of Technology, 2002. http://hdl.handle.net/1721.1/8323.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2002.Includes bibliographical references (leaves 201-212).
I propose a common framework that combines three different paradigms in machine learning: generative, discriminative and imitative learning. A generative probabilistic distribution is a principled way to model many machine learning and machine perception problems. Therein, one provides domain specific knowledge in terms of structure and parameter priors over the joint space of variables. Bayesian networks and Bayesian statistics provide a rich and flexible language for specifying this knowledge and subsequently refining it with data and observations. The final result is a distribution that is a good generator of novel exemplars. Conversely, discriminative algorithms adjust a possibly non-distributional model to data optimizing for a specific task, such as classification or prediction. This typically leads to superior performance yet compromises the flexibility of generative modeling. I present Maximum Entropy Discrimination (MED) as a framework to combine both discriminative estimation and generative probability densities. Calculations involve distributions over parameters, margins, and priors and are provably and uniquely solvable for the exponential family. Extensions include regression, feature selection, and transduction. SVMs are also naturally subsumed and can be augmented with, for example, feature selection, to obtain substantial improvements. To extend to mixtures of exponential families, I derive a discriminative variant of the Expectation-Maximization (EM) algorithm for latent discriminative learning (or latent MED).
(cont.) While EM and Jensen lower bound log-likelihood, a dual upper bound is made possible via a novel reverse-Jensen inequality. The variational upper bound on latent log-likelihood has the same form as EM bounds, is computable efficiently and is globally guaranteed. It permits powerful discriminative learning with the wide range of contemporary probabilistic mixture models (mixtures of Gaussians, mixtures of multinomials and hidden Markov models). We provide empirical results on standardized data sets that demonstrate the viability of the hybrid discriminative-generative approaches of MED and reverse-Jensen bounds over state of the art discriminative techniques or generative approaches. Subsequently, imitative learning is presented as another variation on generative modeling which also learns from exemplars from an observed data source. However, the distinction is that the generative model is an agent that is interacting in a much more complex surrounding external world. It is not efficient to model the aggregate space in a generative setting. I demonstrate that imitative learning (under appropriate conditions) can be adequately addressed as a discriminative prediction task which outperforms the usual generative approach. This discriminative-imitative learning approach is applied with a generative perceptual system to synthesize a real-time agent that learns to engage in social interactive behavior.
by Tony Jebara.
Ph.D.
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Ivanov, Yuri A. 1967. "State discovery for autonomous learning." Thesis, Massachusetts Institute of Technology, 2002. http://hdl.handle.net/1721.1/8324.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2002.Includes bibliographical references (p. 163-171).
This thesis is devoted to the study of algorithms for early perceptual learning for an autonomous agent in the presence of feedback. In the framework of associative perceptual learning with indirect supervision, three learning techniques are examined in detail: * short-term on-line memory-based model learning; * long-term on-line distribution-based statistical estimation; * mixed on- and off-line continuous learning of gesture models. The three methods proceed within essentially the same framework, consisting of a perceptual sub-system and a sub-system that implements the associative mapping from perceptual categories to actions. The thesis contributes in several areas - it formulates the framework for solving incremental associative learning tasks; introduces the idea of incremental classification with utility, margin and boundary compression rules; develops a technique of sequence classification with Support Vector Machines; introduces an idea of weak transduction and offers an EM-based algorithm for solving it; proposes a mixed on- and off-line algorithm for learning continuous gesture with reward-based decomposition of the state space. The proposed framework facilitates the development of agents and human-computer interfaces that can be trained by a naive user. The work presented in this dissertation focuses on making these incremental learning algorithms practical.
by Yuri A. Ivanov.
Ph.D.
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Shaffer, David Williamson. "Expressive mathematics : learning by design." Thesis, Massachusetts Institute of Technology, 1998. http://hdl.handle.net/1721.1/29141.
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Whitman, Brian A. (Brian Alexander). "Learning the meaning of music." Thesis, Massachusetts Institute of Technology, 2005. http://hdl.handle.net/1721.1/32500.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2005.Includes bibliographical references (p. 99-104).
Expression as complex and personal as music is not adequately represented by the signal alone. We define and model meaning in music as the mapping between the acoustic signal and its contextual interpretation - the 'community metadata' based on popularity, description and personal reaction, collected from reviews, usage, and discussion. In this thesis we present a framework for capturing community metadata from free text sources, audio representations general enough to work across domains of music, and a machine learning framework for learning the relationship between the music signals and the contextual reaction iteratively at a large scale. Our work is evaluated and applied as semantic basis functions - meaning classifiers that are used to maximize semantic content in a perceptual signal. This process improves upon statistical methods of rank reduction as it aims to model a community's reaction to perception instead of relationships found in the signal alone. We show increased accuracy of common music retrieval tasks with audio projected through semantic basis functions. We also evaluate our models in a 'query-by-description' task for music, where we predict description and community interpretation of audio. These unbiased learning approaches show superior accuracy in music and multimedia intelligence tasks such as similarity, classification and recommendation.
by Brian A. Whitman.
Ph.D.
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Cavallo, David Paul. "Leveraging learning through technological fluency." Thesis, Massachusetts Institute of Technology, 1996. http://hdl.handle.net/1721.1/61091.
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Jackel, Daniel. "Evaluating the Effectiveness of an Internship Program." TopSCHOLAR®, 2011. http://digitalcommons.wku.edu/theses/1117.
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The traditional way to learn about social sciences in a university setting includes taking courses that teach theoretical frameworks and scientific methodologies that are required for one’s major area of study. The courses that are taught to students are determined by what major they sign up for. After a student has taken all required courses,what skills does the student have to take with him after graduation?
Whether participation is pursued solely for academic credit, for career development, or for civic engagement, an experiential experience typically enhances a student’s connection between academic content and “real world” applications. Bridging the gap between “real world” situations and the classroom demonstrates the need for the application of knowledge.
This project’s primary purpose was to examine the student’s internship experience and determine whether it helped to enhance his or her ability to achieve the predicted outcomes of the internship program. A combination of quantitative and qualitative methodologies was deemed appropriate for empirical analysis. This evaluation project measured enhancement outcomes of an internship program, which rationalized potential designs for the undergraduate sociology major/minor and the undergraduate criminology minor, offered by a higher educational institution.
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Kvarv, Gøran Sveia. "Ontology Learning - Suggesting Associations from Text." Thesis, Norwegian University of Science and Technology, Department of Computer and Information Science, 2007. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-8776.
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In many applications, large-scale ontologies have to be constructed and maintained. A manual construction of an ontology is a time consuming and resource demanding process, often involving some domain experts. It would therefore be beneficial to support this process with tools that automates the construction of an ontology. This master thesis has examined the use of association rules for suggesting associations between words in text. In ontology learning, concepts are often extracted from domain specific text. Applying the association rules algorithm on the same text, the associations found can be used to discover candidate relations between concepts in an ontology. This algorithm has been implemented and integrated in GATE, a framework for natural language processing. Alongside the association rules algorithm, several information extraction and natural language processing techniques have been implemented, in which this algorithm is built upon. This has resulted in a framework for ontology learning. A qualitative evaluation of the associations found by the system has shown that the associations found by the association rules algorithm has promising results for detecting relations between concepts in an ontology. It has also been found that this algorithm is dependent on an accurate extraction of keywords. Further, a subjective evaluation of GATE has shown that it is suited as a framework for ontology learning.
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Vázquez, Machado Christian David. "Embodied language learning in virtual reality." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/119088.
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Thesis: S.M., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2018.Cataloged from PDF version of thesis.
Includes bibliographical references (pages 87-93).
Embodied theories of language propose that the way we communicate verbally is grounded in our body. Nevertheless, the way a second language is conventionally taught does not capitalize on embodied modalities. The tracking and immersive capabilities of virtual reality systems can enable a change in the way students learn language by engaging them in kinesthetic activities that explicitly use body movement to encode knowledge. The body can also be used implicitly to alter a student's perception of themselves in order to enhance the way they approach learning in immersive environments. In this work, we seek to explore the potential of both explicit and implicit embodied language learning using virtual reality as a platform. For the purpose of this thesis we focus on vocabulary acquisition to assess the potential impact these methodologies can have on language education. Two systems were developed that afford explicit (Words in Motion) and implicit (Inner Child) embodied learning. Both systems were evaluated separately during controlled experiments with 6o participants each. Explicit embodied learners displayed enhanced retention positively correlated with performing actions in the Words in Motion platform. Our findings from the implicit embodied study highlight the importance of having a body in virtual reality. Inner Child successfully increased word retention when inducing a subjective age reduction that correlated with the feeling of ownership of a virtual child avatar. These results support the hypothesis that virtual reality can deeply impact language learning by leveraging the body explicitly and implicitly.
by Christian David Vázquez Machado.
S.M.
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Adjodah, Dhaval D. K. (Adjodlah Dhaval Dhamnidhi Kumar). "Social inductive biases for reinforcement learning." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/128415.
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Thesis: Ph. D., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, September, 2019Cataloged from the official PDF of thesis. "The Table of Contents does not accurately represent the page numbering"--Disclaimer page.
Includes bibliographical references (pages 117-126).
How can we build machines that collaborate and learn more seamlessly with humans, and with each other? How do we create fairer societies? How do we minimize the impact of information manipulation campaigns, and fight back? How do we build machine learning algorithms that are more sample efficient when learning from each other's sparse data, and under time constraints? At the root of these questions is a simple one: how do agents, human or machines, learn from each other, and can we improve it and apply it to new domains? The cognitive and social sciences have provided innumerable insights into how people learn from data using both passive observation and experimental intervention. Similarly, the statistics and machine learning communities have formalized learning as a rigorous and testable computational process.
There is a growing movement to apply insights from the cognitive and social sciences to improving machine learning, as well as opportunities to use machine learning as a sandbox to test, simulate and expand ideas from the cognitive and social sciences. A less researched and fertile part of this intersection is the modeling of social learning: past work has been more focused on how agents can learn from the 'environment', and there is less work that borrows from both communities to look into how agents learn from each other. This thesis presents novel contributions into the nature and usefulness of social learning as an inductive bias for reinforced learning.
I start by presenting the results from two large-scale online human experiments: first, I observe Dunbar cognitive limits that shape and limit social learning in two different social trading platforms, with the additional contribution that synthetic financial bots that transcend human limitations can obtain higher profits even when using naive trading strategies. Second, I devise a novel online experiment to observe how people, at the individual level, update their belief of future financial asset prices (e.g. S&P 500 and Oil prices) from social information. I model such social learning using Bayesian models of cognition, and observe that people make strong distributional assumptions on the social data they observe (e.g. assuming that the likelihood data is unimodal).
I were fortunate to collect one round of predictions during the Brexit market instability, and find that social learning leads to higher performance than when learning from the underlying price history (the environment) during such volatile times. Having observed the cognitive limits and biases people exhibit when learning from other agents, I present an motivational example of the strength of inductive biases in reinforcement learning: I implement a learning model with a relational inductive bias that pre-processes the environment state into a set of relationships between entities in the world. I observe strong improvements in performance and sample efficiency, and even observe the learned relationships to be strongly interpretable.
Finally, given that most modern deep reinforcement learning algorithms are distributed (in that they have separate learning agents), I investigate the hypothesis that viewing deep reinforcement learning as a social learning distributed search problem could lead to strong improvements. I do so by creating a fully decentralized, sparsely-communicating and scalable learning algorithm, and observe strong learning improvements with lower communication bandwidth usage (between learning agents) when using communication topologies that naturally evolved due to social learning in humans. Additionally, I provide a theoretical upper bound (that agrees with our empirical results) regarding which communication topologies lead to the largest learning performance improvement.
Given a future increasingly filled with decentralized autonomous machine learning systems that interact with humans, there is an increasing need to understand social learning to build resilient, scalable and effective learning systems, and this thesis provides insights into how to build such systems.
by Dhaval D.K. Adjodah.
Ph. D.
Ph.D. Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences
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Ye, Chen S. M. Massachusetts Institute of Technology. "A system approach to implementation of predictive maintenance with machine learning." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/118502.
Full textAbstract:
Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, System Design and Management Program, 2018.Cataloged from PDF version of thesis.
Includes bibliographical references (pages 87-91).
Digital technology is changing the industrial sector, yet how to make rational use of some technologies and create considerable value in a variety of industrial scenarios is an issue. Many digital industrial companies have stated that they have helped clients with their digital transformation, create much value, but the real effects have not been shown in public. Venture capitals firms have made huge investment in potential digital industrial startups. Numerous industrial IoT platforms are emerging in the market, but a number of them fade soon after. Many people have heard about industrial maintenance technology, but they have difficulty in differentiate concepts such as reactive maintenance, planned maintenance, proactive maintenance, and predictive maintenance. Many people know that big data and Al are essential in industrial sector, but they do not know how to process, analyze, and extract value from industrial data and how to use Al algorithms and tools to implement a research project. This thesis analyzes the entire digital industrial ecosystem in various dimensions such as initiatives, technologies in related domains, stakeholders, markets, and strategies. This work also analyzes of the predictive maintenance solution in various dimensions such as background, importance, suitable scenarios, market, business model, and technology. The author plans an experiment for the predictive maintenance solution, including goal, data source and description, methods and steps, and flow and tools. Then author uses a baseline approach and an optimal approach to implement the experiment, including data preparation, selection and evaluation of both regression and classification models, and deep learning practice through neural network building and optimization. Finally, contributions and expectations, and limitations and future research are discussed. This work uses a system approach, including system architecting, system engineering, and project management, to complete the process of analysis, design, and implementation.
by Chen Ye.
S.M. in Engineering and Management
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Moore, Rachel M. (Rachel Meredith). "Conflicting goals in product development : learning from the fatal Firestone flaw." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/122338.
Full textAbstract:
Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, System Design and Management Program, 2019Cataloged from PDF version of thesis.
Includes bibliographical references (pages 119-121).
The human-centered design approach is a powerful methodology for developing products that are considerate of humanity. Yet, in spite of the proven success of empathetic design, we still see products that fail, amplify negative social behaviors, or take advantage of human tendencies for the sake of profit or competitive success. These outcomes are often the result of poor negotiation between conflicting organizational and value-driven goals. The purpose of this analysis is to consider how goal conflict inhibits the product development process and leads to suboptimal or destructive results. This exploration seeks to learn from an analysis of the deadly product failure of Firestone ATX, ATX 11, and Wilderness AT tires in the late 1990s. Drawing from Congressional testimony, expert evaluation, and depositions of relevant engineers, this analysis considers the impact of goal conflict on product design requirements and testing. Recommendations include methods for identifying goals and framing conflict to encourage balance between organizational goals and human wellbeing. This project is the beginning of a larger body of work that aims to equip "makers" with skills they need to reconcile conflicting goals in order to focus on making the world better by making better things.
by Rachel M. Moore.
S.M. in Engineering and Management
S.M.inEngineeringandManagement Massachusetts Institute of Technology, System Design and Management Program
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Xu, Hua S. M. Massachusetts Institute of Technology. "A system approach to augment clinical decision-making using machine learning." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/121803.
Full textAbstract:
Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, System Design and Management Program, 2019Cataloged from PDF version of thesis.
Includes bibliographical references (pages 76-80).
This thesis helps find limits within which automated methods can support and surpass the capabilities of medical professionals and the limits beyond which these methods are not yet adequate. This will inform later exploration about (a) what improvements in data collection, interpretation, and visualization will enhance technology's capacity and (b) what changes clinicians can make to improve their decision making-augmented or not. This thesis includes (a) describing clinical decisions, informed by literature and clinical case studies and (b) reviewing current capabilities of machine methods. This led to (c) a test experiment-how to use data about a particular condition (e.g. in-hospital mortality rate prediction) from a particular source (the MIMIC III data base). The results will help define current limits on augmenting clinical decisions and establish direction for future work including more demanding experiments.
Artificial Intelligence (AI) includes Machine Learning (ML), Natural Language Processing (NLP), Computer Vision, Speech Recognition, and Robotics. As an important branch of Al, ML builds statistical models to learn from sample data, known as "training", identifies patterns, and makes predictions based on new data, known as "inference." In this way, ML is useful in rationalizing and predicting in uncertain environments, with minimum human interventions. Decision making is central to the healthcare practice, with many decisions made under conditions of uncertainty. Clinicians must integrate a huge variety of data while pressured to decrease diagnostic uncertainties and risks to patients. Deciding what information to gather, which test to order, how to interpret and integrate this information to draw diagnostic conclusions, and which treatments to give are essential.
In typical situations, clinicians evaluate patient symptoms and potential disease patterns, confirmed by a variety of tests, and they initiate treatments based on their experience and customary practice. This is complicated when multiple illnesses coexist, the illness may be rare, the information may be conflicting, or prior interventions may affect the presenting symptoms.
by Hua Xu.
S.M. in Engineering and Management
S.M.inEngineeringandManagement Massachusetts Institute of Technology, System Design and Management Program
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Nelson, LIsa V. "International Service Learning: Program Elements Linked to Learning Outcomes, and Six Participant Motivation Factors Revealed." Ohio University / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1418671274.
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