To date, research of computer science education in the elementary classroom has focused on technology-dependent tools like Alice, Scratch, LOGO and LEGO Mind-storms. While these tools seem to have the potential to support learning in accordance with constructionist theory, they have not lived up to expectations. Results of this research, in particular the impact of programming instruction on student achieve- ment, have been weak or mixed. Possible reasons for this are many, including the corresponding threshold and friction associated with technology-dependent learning. Inspired by a trend of non-technology-dependent instruction of computer science topics, as demonstrated by the success of Computer Science Unplugged by Tim Bell, Mike Fellows and Ian Witten, we have chosen instead to investigate the impact of unplugged computer science instruction on Grade Six students. The shift away from programming instruction may also serve to help dispel the myth that computer science is programming. Computer science is a broad and diverse field which impacts the lives of all people in a multitude of ways. It is not yet clear what the best approach is for integrating computer science education into the elementary classroom. One suggestion is to teach computer science topics such that they support other areas of elementary education. For example, students are encouraged to adopt many different problem solving strategies, as supported by the British Columbia Ministry of Education’s K-7 Mathematics Integrated Resource Package (IRP). These strategies include “draw a picture”. Graph theory has the potential to support problem solving as a means of representing complex connections and relationships in a clear and concise manner. Alternatively, a standalone computer science curriculum may be appropriate, in the spirit of the Computer Science Teacher’s Association (CSTA) “A Model Curriculum for K-12 Computer Science”. Whatever the approach, an important, and fundamental, step in making curricular change is to support the need for change with sound educational research. Only then can we hope to earn the support of the stakeholders, such as school districts and teacher education programs, who can make this change a reality. In this pilot study, we investigate the impact of graph theory lessons in two Grade Six math classes. Because of the small class sizes and somewhat reduced participation rates, the results of this study need to be verified with further, larger scale studies. However, early indications are that Grade Six students are capable of learning graph theory, and applying it when working on mathematical word problems. In some cases, there appears to be an association between students’ ability to apply graph theory as one of many problem solving strategies, and the correctness of their solutions to problems.

Das Ziel dieser Arbeit war es eine möglichst frei skalierbare Version der Lazarus-IDE zu entwickeln. Diese soll es dem versierten Lehrer ermöglichen, eine auf seine didaktischen Intentionen und die Leistungsfähigkeit seiner Schüler angepasste Lazarus-Version zu installieren und im Unterricht zu verwenden. Hierfür ist zunächst eine theoretische Analyse der Entwicklungsumgebung Eclipse vorgenommen worden. Weiterhin wurde untersucht, welche didaktischen Anforderungen prinzipiell an eine schulische Entwicklungsumgebung zu stellen sind. Auf Basis dieser Untersuchungen sowie durch gezielte Befragung von Fachlehrern sowie Experten sind die Anforderungen an eine solche IDE verifiziert und diese schließlich implementiert worden.

Orientador: Tomasz Kowaltowski / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Computação / Made available in DSpace on 2018-08-09T11:46:19Z (GMT). No. of bitstreams: 1 Kleiman_AlanBustos_M.pdf: 724679 bytes, checksum: 98bfcce8c89306724c31252f82cf7cc0 (MD5) Previous issue date: 2007 / Resumo: Plágio em submissões de alunos e um problema que vem aumentando ao longo do tempo e instituições de ensino têm trabalho considerável para eliminá-lo. Examinamos o problema do ponto de vista de submissões de alunos em disciplinas introdutórias de programação, fazendo um resumo de alguns sistemas e algoritmos existentes. Implementamos vários algoritmos descritos com a finalidade de efetuar uma comparação direta e qualitativa, com foco no pré-processamento de programas. Em particular, desenvolvemos um mecanismo para a normalização de programas através de uma análise sintática cuidadosa e reordenação da árvore de sintaxe abstrata de maneira a minimizar a quantidade de ruído criada por plagiadores ao tentar copiar e modificar programas de outros. Conseguimos resultados positivos utilizando esse método de pré-processamento, especialmente quando combinado com o algoritmo conhecido como Running Karp Rabin Greedy String Tiling. Esses resultados positivos reforçam nossa conclusão de que o pré-processamento pode ser até mais importante que o algoritmo em si, e apontam novas direções para pesquisas futuras / Abstract: Encountering plagiarism in student coursework has become increasingly common, and signifcant effort has been undertaken to counter this problem. We focus on the plagiarism in student submissions in programming courses, in particular in introductory computer science courses, describing some of the existing systems and algorithms already dedicated to this problem. We implement many of the algorithms so that we could undertake a direct and qualitative comparison, with a special focus on pre-processing student programs. In particular, we develop a mechanism for normalizing programs through careful parsing and ordering of their abstract syntax trees so as to minimize the noise created by plagiarists attempting to copy and modify someone else's program. We achieve positive results utilizing this new pre-processing method, particularly with the Running Karp Rabin Greedy String Tiling algorithm. The positive results reinforce our conclusion that pre-processing may be more important than the algorithm itself and point to new directions for further research / Mestrado / Sistemas de Computação / Mestre em Ciência da Computação

abstract: Computer science education is an increasingly vital area of study with various challenges that increase the difficulty level for new students resulting in higher attrition rates. As part of an effort to resolve this issue, a new visual programming language environment was developed for this research, the Visual IoT and Robotics Programming Language Environment (VIPLE). VIPLE is based on computational thinking and flowchart, which reduces the needs of memorization of detailed syntax in text-based programming languages. VIPLE has been used at Arizona State University (ASU) in multiple years and sections of FSE100 as well as in universities worldwide. Another major issue with teaching large programming classes is the potential lack of qualified teaching assistants to grade and offer insight to a student’s programs at a level beyond output analysis. In this dissertation, I propose a novel framework for performing semantic autograding, which analyzes student programs at a semantic level to help students learn with additional and systematic help. A general autograder is not practical for general programming languages, due to the flexibility of semantics. A practical autograder is possible in VIPLE, because of its simplified syntax and restricted options of semantics. The design of this autograder is based on the concept of theorem provers. To achieve this goal, I employ a modified version of Pi-Calculus to represent VIPLE programs and Hoare Logic to formalize program requirements. By building on the inference rules of Pi-Calculus and Hoare Logic, I am able to construct a theorem prover that can perform automated semantic analysis. Furthermore, building on this theorem prover enables me to develop a self-learning algorithm that can learn the conditions for a program’s correctness according to a given solution program. / Dissertation/Thesis / Doctoral Dissertation Computer Science 2020

Das Ziel dieser Arbeit war es eine möglichst frei skalierbare Version der Lazarus-IDE zu entwickeln. Diese soll es dem versierten Lehrer ermöglichen, eine auf seine didaktischen Intentionen und die Leistungsfähigkeit seiner Schüler angepasste Lazarus-Version zu installieren und im Unterricht zu verwenden. Hierfür ist zunächst eine theoretische Analyse der Entwicklungsumgebung Eclipse vorgenommen worden. Weiterhin wurde untersucht, welche didaktischen Anforderungen prinzipiell an eine schulische Entwicklungsumgebung zu stellen sind. Auf Basis dieser Untersuchungen sowie durch gezielte Befragung von Fachlehrern sowie Experten sind die Anforderungen an eine solche IDE verifiziert und diese schließlich implementiert worden.

Learning the syntax, semantics, and concepts behind software engineering can be a challenging task for many individuals. This paper examines the Alice 3 software, a three-dimensional visual environment for teaching programming concepts, to determine if it is an effective tool for improving student achievement, raising self-efficacy, and engaging students. This study compares the similarities and differences between a Fundamentals of Programming course with and without Alice integrated into the curriculum. Both the treatment and control Groups are using the same Java materials, assignments, and exams. The treatment group also completes Alice activities for each programming concept throughout the course; as well as two Alice assignments.

<p> Cybersecurity is an important aspect of all businesses as well as the public sector. As information technology becomes more interconnected with our everyday lives, it opens more opportunities for network vulnerabilities and therefore more breach opportunities. Previous work within the State of Indiana has produced a cybersecurity scorecard but leaves those using the scorecard with no way to improve their scores. This research is conducted to help Indiana counties improve their cybersecurity practices with a limited budget. As well, this research and implementation guide will be accessible in a way that any employee at the county level, despite their cybersecurity knowledge, will have a solid foundation on where to begin to improve their score. The goal of this study is to develop a framework that identifies the weaknesses in an Indiana county's response to the Cybersecurity Scorecard and provides resources to improve their scores. The framework should identify the specific issues and give definitions or resources for the counties to use to improve their score. </p>

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.

No description available.

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.