Computational thinking is a problem-solving skill and is considered to be an important part of today’s digital literacy. As it is an evolving research field and an emerging subject within the K-12 educational systems there’s a need to develop methods and environments for teaching and assessing computational thinking as well as establishing a cohesive view of its definition. A concern with computational thinking is it's neigh synonymity with programming and computer science in a classroom environment as they share several concepts and because programming is an effective way to teach it.  Acknowledging this need for this separation as well as the need for developing educational environments this study explored the aspects of problem-solving and perception of computational problems in different environment.  This was explored through a quantitative study on late-stage K-12 students and how perceived and performed in different types of problem posing environments. These environments included the challenge of using programming concepts through gamification as a way of exploring methods of teaching and assessing computational thinking in a metaphorical and real-life simulated situation.  It wound up measuring the effects that different problems had on the confidence and expertise of computational thinking capabilities within this exploratory experiment. The findings suggest an indication that too much given context can confuse students and that alleviating mental workload is crucial when presenting computational thinking problems if the correct solution should be reached.

Orientador: Renata Cristina Geromel Meneghetti / Resumo: Essa dissertação tem como objetivo investigar as habilidades em potencial do Pensamento Computacional no contexto da Educação Matemática no quesito das questões de Matemática dos vestibulares do estado de São Paulo, ENEM e dos documentos oficiais. Além disso, pretende contribuir com a discussão sobre o papel ou não do Pensamento Computacional na Educação Básica. Isso porque muitas habilidades estão próximas de conceitos matemáticos e o processo de ensino e aprendizagem através do Pensamento Computacional pode contribuir com o desempenho de estudantes da Educação Básica. A importância de se buscar uma melhora no desempenho dos estudantes é baseada na avaliação realizada pelo Programa Internacional de Avaliação de Alunos (PISA 2015) que apontou uma grande dificuldade por parte de estudantes em questões que exigem conclusões diretas e fórmulas básicas, sendo que sua maioria está cursando o Ensino Médio e buscando o ingresso no Ensino Superior. A partir disso, essa pesquisa explora argumentos para justificar a inclusão das habilidades do Pensamento Computacional na Educação Básica, especificamente na disciplina de Matemática. Enquadrando-se como uma pesquisa qualitativa, essa investigação utilizou da metodologia de Análise de Conteúdo para analisar os documentos oficiais como complemento de possíveis habilidades em potencial do Pensamento Computacional exploradas nestes. Também fez-se a análise das questões de Matemática das avaliações de ingresso do Ensino Superior público como ... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: This dissertation aims to investigate the potential skills of Computational Thinking in the context of Mathematics Education in the area of Mathematics questions regarding the admission exams of the São Paulo state universities, the ENEM and the official documents. In addition, it intends to contribute to the discussion about the role, or not, of Computational Thinking in Basic Education, because many skills are close to mathematical concepts and the process of teaching and learning through Computational Thinking can contribute to the performance of Basic Education students. The importance of seeking an improvement in student performance is based on the assessment carried out by the International Student Assessment Program (PISA 2015), which pointed out that students face great difficulty in issues that consider basic guidelines and formulas, the majority of whom are attending High School and trying to join Higher Education. Based on that, this research explores arguments to justify the inclusion of Computational Thinking skills in Basic Education, specifically in the Mathematics subject. Being a qualitative research, this investigation used the Content Analysis methodology to analyze the official documents as a complement to the potential Computational Thinking skills explored by them. Mathematics questions of the admission exams to join public Higher Education, such as ENEM and the admission exams of state universities of São Paulo, such as USP, UNESP and UNICAMP, for the y... (Complete abstract click electronic access below) / Mestre

No description available.

No description available.

Syftet med studien är att beskriva och exemplifiera uppfattningar och tankar om datorkunskap och programmering inom grundskolan och Makerspace-rörelsen. Lärare, verksamhetsutvecklare och avdelningschef inom samma skolverksamhet samt, i jämförande syfte, en anställd på ett Makerspace intervjuades om deras uppfattning om datorkunskap och programmering. Resultatet av studien visar att inom skolverksamheten används i stor utsträckning färdiga lektionsupplägg för programmeringsundervisningen, framtagna av organisationen Naturkunskap och teknik för alla (NTA). NTA har en central roll i skolverksamheten och erbjuder fortbildning och lektionsmaterial för de naturorienterande ämnena, matematik och teknik. På Makerspace sker utbildning i programmering främst med programmeringsplattformen Roblox som erbjuder en virtuell programmerbar värld.   Alla i studien uttryckte att det behövs medvetenhet och kunskap hos lärare såväl som hos elever om hur och när digitala verktyg ska användas. Framtidens samhälle ställer även krav på individen att ha en grundläggande förståelse för programmering och datalogiskt tänkande. För att möta kraven på arbetsmarknaden samt för att förstå och hantera teknologiska förändringar, inklusive användningen av AI. En erfarenhet från skolverksamheten som både lärare och avdelningschef hade var att programmering tilltalade elever som kan befinna sig i riskzon för att bli hemmasittare. Det skulle vara av värde både för individ och samhälle att utforska vad det är i programmeringsämnet som tilltalar dessa individer. / The purpose of this study is to describe and exemplify perceptions and thoughts about computer science and programming in primary school and the Makerspace movement. Teachers, an educational developer, and a head of a department within the same school organisation and, for comparative purposes, an employee at a Makerspace, were interviewed about their views on computer science and programming. The study’s results showed that within the school organisation ready-made lesson plans for programming education developed by the organisation “Naturkunskap och teknik för alla” (NTA) were widely used. NTA plays a vital role in the school organisation and offers teacher education and lesson materials for the subjects of mathematics, science and technology. In Makerspace, education in programming primarily takes place using the programming platform Roblox, which offers a virtual programmable world. Everyone in the study expressed that there is a need for awareness and knowledge among both teachers and students regarding how and when digital tools should be used. The society of the future also demands that individuals have a basic understanding of programming and computational thinking, to meet the demands of the job market and to understand and manage technological advances, including the use of AI. An experience from the school organisation, that both teachers and the department head had, was that programming appealed to students who may be at risk of becoming non-attenders. It would be of value for both the individual and society to explore what it is about the subject of programming that appeals to these individuals.

Programming is a key skill in many domains outside computer science. When used judiciously, programming can empower people to accomplish what might be impossible or difficult with traditional methods. Unfortunately, students, especially non-CS majors, frequently have trouble while learning to program. This work reports on the challenges and opportunities faced by Physical Chemistry (PChem) students at Cal Poly, SLO as they learn to program in MATLAB. We assessed the PChem students through a multiple-choice concept inventory, as well as through “think-aloud” interviews. Additionally, we examined the students’ perceptions of and attitudes towards programming. We found that PChem students are adept at applying programming to a subset of problems, but their knowledge is fragile; like many intro CS students, they struggle to transfer their knowledge to different contexts and often express misconceptions about programming. However, they differ in that the PChem students are first and foremost Chemistry students, and so struggle to recognize appropriate applications of programming without scaffolding. Further, many students do not perceive themselves as competent general- purpose programmers. These factors combine to discourage students from applying programming to novel problems, even though it may be greatly beneficial to them. We leveraged this data to create a workshop with the goal of helping PChem students recognize their programming knowledge as a tool that they can apply to various contexts. This thesis presents a framework for addressing challenges and providing opportunities in domain-specific CS education.

The constant growth of technology in our world is changing the way of life all around us.We now have self-driving cars that are programmed by us to drive so we don't have to.The fact that most of us can't go a day without using something that is programmed orengineered to suit our needs is the way of life for kids nowadays. In this essay we havechosen to study programming in a preschool context.The Swedish government is planning to implement a new curriculum in 2018 that will bemore focused on digital knowledge. There is very little historical research on whatknowledge and skills children acquire and develop when they work with programmingso we wanted to do research on this subject. We have interviewed preschool teachers insouthern Sweden and created an activity where we studied preschool children playingwith programming tools in a social context to gather data on the subject. We haveanalyzed and interpreted our data with the help of Lev Vygotsky's sociocultural theory.Our results showed that all of the teachers thought programming was a good tool to workwith in preschool and gave us examples of benefits from working with programming.Most of them talked about learning through social interaction and said that the childrendeveloped better mathematical skills, social skills, problem solving skills andcomputational thinking. In our modern world, where our contact with technology isconstantly growing, research shows that having an early understanding of basicprogramming and the digital world will be highly beneficial in the future.

<p dir="ltr">This dissertation includes three manuscripts that explore the construct of teacher-readiness for integration of computational thinking (CT) skills in their teaching. The first manuscript is a retrospective observational study that builds a binomial regression model to predict teachers’ competence in CT procedural skills using factors such as number of professional development trainings taken, time since last training, subject taught, educational background, teaching experience, and whether they currently teach CT. This study provides insights for professional development providers to better design CT trainings. Some of these insights are then incorporated in the second study which is a design case of an online gamified professional development for K-12 teachers. The second paper provides design precedents for professional development providers of CT for better CT integration in K-12 education. The third study is a phenomenological multiple case study that investigates teachers’ CT self-efficacy, autonomous motivation, and goal relevance beliefs towards CT. It captures teachers’ understanding of what CT is and what its value is to the subjects that they teach. Together, the three studies holistically understand teacher readiness for integration of CT through teachers’ own perspective and provide key insights into how they can be better prepared for this change.</p>

Computing courses struggle to retain introductory students, especially as learner demographics have expanded to include more diverse majors, backgrounds, and career interests. Motivational contexts for these courses must extend beyond short-term interest to empower students and connect to learners' long-term goals, while maintaining a scaffolded experience. To solve ongoing problems such as student retention, methods should be explored that can engage and motivate students. I propose Data Science as an introductory context that can appeal to a wide range of learners. To test this hypothesis, my work uses two educational theories — the MUSIC Model of Academic Motivation and Situated Learning Theory — to evaluate different components of a student's learning experience for their contribution to the student's motivation. I analyze existing contexts that are used in introductory computing courses, such as game design and media computation, and their limitations in regard to educational theories. I also review how Data Science has been used as a context, and its associated affordances and barriers. Next, I describe two research projects that make it simple to integrate Data Science into introductory classes. The first project, RealTimeWeb, was a prototypical exploration of how real-time web APIs could be scaffolded into introductory projects and problems. RealTimeWeb evolved into the CORGIS Project, an extensible framework populated by a diverse collection of freely available "Pedagogical Datasets" designed specifically for novices. These datasets are available in easy-to-use libraries for multiple languages, various file formats, and also through accessible web-based tools. While developing these datasets, I identified and systematized a number of design issues, opportunities, and concepts involved in the preparation of Pedagogical Datasets. With the completed technology, I staged a number of interventions to evaluate Data Science as an introductory context and to better understand the relationship between student motivation and course outcomes. I present findings that show evidence for the potential of a Data Science context to motivate learners. While I found evidence that the course content naturally has a stronger influence on course outcomes, the course context is a valuable component of the course's learning experience. / Ph. D. / Introductory computing courses struggle to keep students. This has become worse as students with more diverse majors take introductory courses. In prior research, introducing fun and interesting material into courses improved student engagement. This material provides a compelling context for the students, beyond the primary material. But instead of only relying on fun material, courses should also rely on material that is useful. This means connecting to students’ long term career goals and empowering learners. Crucial to this is not making the material too difficult for the diverse audience. To keep more students, we need to explore new methods need of teaching computing. I propose data science as a computing context that can appeal to a wide range of learners. This work tests this hypothesis using theories of academic motivation and learning theory. The components of a learning experience contribute to students’ motivation. I analyze how the components of other existing contexts can motivate students. These existing contexts include material like game design or media manipulation. I also analyze how good data science is as a context. Next, I describe two projects that make it simple to use data science in introductory classes. The first project was RealTimeWeb. This system made it easy to use real-time web APIs in introductory problems. RealTimeWeb evolved into the CORGIS Project. This is a diverse collection of free “Pedagogical Datasets” designed for novices. These datasets are suitable for many kinds of introductory computing courses. While developing this collection, I identified many design issues involved in pedagogical datasets. I also made tools that made it easy to manage and update the data. I used both projects in real introductory computing courses. First, I evaluated the projects’ suitability for students. I also evaluated data science as a learning experience. Finally, I also studied the relationship between student motivation and course outcomes. These outcomes include students interest in learning more computing and their retention rate. I present evidence for the potential of a data science context to motivate learners. But, the primary material has a stronger relationship with course outcomes than the data science context. In other words, students are more interested in continuing computing if they like computing, not if they like data science. Still, the results show that data science is an effective learning experience.

In this thesis, I discuss how the undergraduate computer scientist is trained, and how they learn what I am calling computational intuition. Computational intuition describes the methodology in which computer scientists approach their problems and solve them through the use of computers. Computational intuition is a series of skills and a way of thinking or approaching problems that students learn throughout their education. The main way that computational intuition is taught to students is through the experience they gain as they work on homework and classwork problems. To develop computational intuition, students learn explicit knowledge and techniques as well as knowledge that is tacit and harder to teach within the lectures of a classroom environment. Computational intuition includes concepts that professors and students discuss which include “computer science intuition,” “computational thinking,” general problem solving skills or heuristics, and trained judgement. This way of learning is often social, and I draw on the pedagogy of cognitive apprenticeship to understand the interactions between the professors, tutors, and other students help learners gain an understanding of the “computer science intuition.” It is this method of thinking that computer scientists at the Claremont Colleges have stated as being one of the most essential items that should be taught and gained throughout their education and signals a wider understanding of computer science as a field.