<p>  </p> <p>This research study aims to explore the understanding and implementation of CT and its core concepts by CS High School teachers. This research study examined CS teachers' understanding of CT’s core concepts; a) decomposition, b) pattern recognition, c) abstraction and d) algorithm design. Furthermore, the study also explores how these CS teachers applied these core concepts to their instructional practice. </p> <p>The qualitative case study utilized the Pedagogical Content Knowledge (PCK) framework as a lens to explore the teachers’ understanding. For this qualitative research study, purposeful sampling was employed to recruit participants with specific knowledge or experience about a topic of interest. In-depth semi-structured interviews were performed with five CS high school teachers for data collection. The researcher used coding and thematic analysis to analyze the data. Teachers shared their understanding of CT, its core concepts, and how they incorporate these into their instructional practice.</p> <p>The findings in the study present the different understandings of the teachers regarding CT’s core concepts and how each of them applied such concepts through different pedagogical approaches to their instructional practice. The findings in the study could provide an opportunity for high school teachers to explore different understandings from other high school teachers and potentially provide collaborative opportunities. </p> <p>The research study concludes with two significant findings and their implications for the field of CS education. It also recommends other researchers and provides collaborative opportunities with other high schools. Moreover, this research contributes to and enriches the current literature on CT in education. </p>

When students use an online eTextbook with content and interactive graded exercises, they often display aspects of two types of behavior: credit-seeking, and knowledge-seeking. Any given student might behave to some degree in either way in a given assignment. In this work, we look at multiple aspects of detecting the degree to which either behavior is taking place, and investigate relationships to student performance. In particular, we focus on an eTextbook used for teaching Formal Languages, an advanced computer science course. This eTextbook is using Programmed Instruction (PI) framesets to deliver the material. We take two approaches to analyze session interactions in order to detect credit-seeking incidents. We first start with a coarse-grained approach by presenting an unsupervised model that clusters the behavior in the work sessions based on the sequence of different interactions that happens during them. Then we perform a fine-grained analysis where we consider the type of each question in the frameset, which can be a multi-choice, single-choice, or T/F question. We show that credit-seeking behavior is negatively affecting the learning outcome of the students. We also find that the type of the PI frame is a key factor in drawing students more into the credit-seeking behavior to finish the PI framesets quickly. We implement three machine learning models that predict students' midterm and overall semester grades based on their amount of credit-seeking behavior on the PI framesets. Finally, we provide a semisupervised learning model to aid in the work session labeling process. / Master of Science / Students frequently exhibit features of two types of behavior when using an online eTextbook with content and interactive graded exercises: credit-seeking and knowledge-seeking. When solving homework or studying a material, students can behave in either manner to some extent. In this research, we study links between student performance and different elements of recognizing the degree to which either behavior is occurring. We concentrate on an eTextbook used to teach an advanced computer science course, Formal Languages and Automata, using a teaching paradigm called Programmed Instruction (PI). In order to detect credit-seeking instances, we use two ways to study students' behavior in the Programmed Instruction sessions. We begin with a coarse-grained approach by building a model that can categorize work sessions into two groups based on the interactions that occur throughout them. Then we do a fine-grained analysis in which we analyze the question types in the framesets and their effect on the students' behavior. We show that credit-seeking behavior has a negative effect on students' learning outcomes. We discovered that the PI frame type is an important factor in enticing students to engage in credit-seeking behavior in an attempt to finish PI framesets fast. Finally, we present three predictive models that can forecast the students' midterm and total semester grades based on their credit-seeking behavior on the Programmed Instruction framesets.

The need to learn programming increases as more jobs require basic programming skills and computer knowledge. Compulsory school is adding programming to the curriculum, which leads to challenges due to both teachers and students are new to this subject. Even at the university level some students get in touch with programming for the first time in their lives.  This thesis aim to develop a web application that can be used by teachers as a reliable and informative tool when evaluating the learning process of its students, by combining data collected through user interactions while solving programming related puzzles in Python, with answers from periodic self-evaluation surveys.  The study shows that the web application can be seen as a valid tool when evaluating the students' learning process.

Im Jahr 2019 haben deutsche Universitäten das Jubiläum einer 50-jährigen Informatikausbildung gefeiert. Die TU Dresden blickt dabei seit 1969 als erste Universität auf Erfahrungen in beiden deutschen Staaten zurück. Während die historische Entwicklung in der Informatikausbildung für die BRD gut dokumentiert ist, besteht in der Dokumentation durch das Informatik Spektrum für die DDR eine Lücke. Die Informatikausbildung in der DDR befand sich seit ihren Anfängen auf Augenhöhe mit den Entwicklungen in der BRD. Im vorliegenden Artikel wird die historische Entwicklung des Informatik-Studienganges an der TU Dresden unter Berücksichtigung der Entstehungs- und Entwicklungsphase in der DDR und der Wendezeit bis zur heutigen Fakultät Informatik dargestellt. Aus Anlass des 50-Jahre-Jubiläums im Jahr 2019 wurde die historische Entwicklung in einem webbasierten Zeitstrahl dokumentiert und mit Interviews von Zeitzeugen ergänzt. Dabei lag der Schwerpunkt auf der Lehre einschließlich der Einheit von Lehre und Forschung.

Computing is becoming exponentially more pervasive, and so-called process of ``Digital Transformation'' is but starting. As computers become ever more relevant, our societies will need computing professionals that are well-equipped to face the many challenges their own discipline amplified. The education of computer scientists, so far, mostly focused on equipping them with technical skills. Society and academia, however, are increasingly recognising computing as a field where disciplines collide and intersect. An example that we investigate is that of Innovation and Entrepreneurship (I&amp;E), a field that has often be used to equip computer science students with soft skills and non-technical competences. Computer science faces some unique problems, among which a lower student interest for non-technical subjects, and a constant process of epistemic and technological obsolescence. This thesis showcases some experiences that aim to address these challenges, going towards (re)connecting the Humans and Machines participating in computer science education with the needs of the World of today and tomorrow. Our work combines some theoretical reflections with pedagogical experiments, to ensure that our work has at the same time descriptive power and empirical validation. To aid teachers and learners in the change process, these experiments share a pedagogical approach rooted on Active Learning, ranging from Challenge-Based Learning to Peer Education, to custom-tailored teaching methodologies. In designing each experiment, we start by asking ourselves: how is what we want to teach practiced in the real world? Theoretically, this thesis contributes to the state of the art by conducting a horizontal exploration of how computer science education can enter an age ever more dominated by so-called ambiguity. Methodologically, we propose lightweight techniques for qualitative measurement that are rigorous, but introduce little methodological burden, emphasising our work's reflective and exploratory dimension. Our work aims to show how, using the same broad design process, courses can be flexibly adapted to fit an ever-changing world, including significant disruptions such as the transition to online education.

Educators in many disciplines are too often forced to rely on intuition about how students learn and the effectiveness of teaching to guide changes and improvements to their curricula. In computer science, systems that perform automated collection and assessment of programming assignments are seeing increased adoption, and these systems generate a great deal of meaningful intermediate data and statistics during the grading process. Continuous collection of these data and long-term retention of collected data present educators with a new resource to assess both learning (how well students understand a topic or how they behave on assignments) and teaching (how effective a response, intervention, or assessment instrument was in evaluating knowledge or changing behavior), by basing their decisions on evidence rather than intuition. It is only possible to achieve these goals, however, if such data are easily accessible. I present an infrastructure that has been added to one such automated grading system, Web-CAT, in order to facilitate routine data collection and access while requiring very little added effort by instructors. Using this infrastructure, I present three case studies that serve as representative examples of educational questions that can be explored thoroughly using pre-existing data from required student work. The first case study examines student time management habits and finds that students perform better when they start earlier but that offering extra credit for finishing earlier did not encourage them to do so. The second case study evaluates a tool used to improve student understanding of manual memory management and finds that students made fewer errors when using the tool. The third case study evaluates the reference tests used to grade student code on a selected assignment and confirms that the tests are a suitable instrument for assessing student ability. In each case study, I use a data-driven, evidence-based approach spanning multiple semesters and students, allowing me to answer each question in greater detail than was possible using previous methods and giving me significantly increased confidence in my conclusions. / Ph. D.

Women are lacking in Science, Engineering, Technology, and Mathematics (STEM). One of the proven solutions to reduce this gap is to offer extra support to the students needing it. Further, creativity has been shown to give positive effects on females’ participation in STEM. In this thesis, a creative tool for programming education in junior high schools in Sweden was developed to give alternatives to how programming is taught and further evaluate the possible contributions it can give. The tool was tested among 14 students participating in a face-to-face workshop. To further evaluate the tool use, the study participants took part in interviews and a survey. The results show that further iterations of the tool would have been needed since the tested tool was not perceived as easy to use. Regarding perceived usefulness, the tool is on the right path since the results indicate it was fun to use but again, improvements need to be done. The contributions made are therefore an exploration of the creative alternative to programming learning in the Swedish school. Furthermore, to find out what improvements needed to be done to offer an, by users, accepted tool. Offering creative programming tools will hopefully attract a more diverse group of people to programming and decrease the gender gap within computer science. / Det finns en brist på kvinnor inom STEM. En beprövad lösning för att minska könsskillnaderna är att erbjuda extra hjälp till de som behöver. Kreativitet har också visats ha positiva effekter på kvinnors deltagande inom STEM. I denna uppsats så utvecklas ett kreativt verktyg för programmering i högstadiet i Sverige för att ge alternativ till hur programmering lärs ut och för att utvärdera vad det kan tillföra. Verktyget testades av 14 studenter som närvarade i en workshop. För att utvärdera verktyget så deltog studenterna i intervjuer och fyllde i ett formulär. Resultatet visar att ytterligare iterationer av produkten behövs eftersom verktyget inte upplevdes som enkelt att använda. Angående upplevd användbarhet så är verktyget på rätt väg eftersom resultaten indikerar att det var roligt att använda men ytterligare förbättringar är nödvändiga. Uppsatsen bidrar därför till ett utforskande av det kreativa alternativet till programmeringsinlärningen i den svenska skolan. Den bidrar även till att testa fram vilka förbättringar som är nödvändiga för att erbjuda ett, av användarna, accepterat verktyg. Förhoppningsvis kommer en grupp med större mångfald att attraheras till programmering genom att erbjuda ett kreativt programmeringsverktyg och därmed minska könsskillnaderna inom datavetenskap.

This study was motivated by a desire to address the challenges of introductory programming courses. Ethiopian universities teach such courses in large classes (80+ students) and students complain about the difficulty of the courses and teaching variation of instructors. The study was set to explore optimum course and learning environment design approaches. The research question raised was: how can a blended learning approach be used to improve large class teaching of programming? In an action design research approach, the study was initiated with redesigning two consecutive courses and a supportive blended learning environment on the basis of existing learning theories and educational design frameworks. Two cycles of action research were conducted for a dual goal of refinement and evaluation of the intervention. The action research was conducted during the 2012/13 academic year with 240 students at the beginning. A predominantly quantitative first cycle of action research produced a mixed outcome. The students’ marks from assessment activities were fairly close to results from two other international universities. A pre- and post-implementation survey of students’ approach to learning showed a slight class level change towards the deep learning approach. Conversely, some students were found at-risk (not progressing well) and certain technologies, particularly program visualisation tools, were found underutilised. The second action research cycle aimed to explain the result from the first round. A grounded action research evaluation of data from focus group discussions, interviews and participants’ memos identified plausible factors for meaningful programming learning in a large class. These factors were use of collaborative and pair programming; alignment of learning and assignment activities; integrated use of e-learning; and use of large class strategies like student mentors and team teaching. A critical realist interpretation of the result of the action research suggested that students can learn programming in large classes, 200+ in this study, with a course and learning environment design that keeps them engaged in learning and assessment activities. The study concludes that improved learning of programming can be possible with the use of students as mentors and changed role-dynamics of instructors, which presupposes adaptation of suitable pedagogical approaches and use of technologies. / School of Computing / D. Litt. et Phil. (Information Systems)

Submitted by Jadson Francisco de Jesus SILVA (jadson@uefs.br) on 2018-07-31T22:19:12Z No. of bitstreams: 1 Dissertacao_LuisGustavoAraujo.pdf: 8660411 bytes, checksum: cba36d7b6e819bd2743bd4343cccbccf (MD5) / Made available in DSpace on 2018-07-31T22:19:12Z (GMT). No. of bitstreams: 1 Dissertacao_LuisGustavoAraujo.pdf: 8660411 bytes, checksum: cba36d7b6e819bd2743bd4343cccbccf (MD5) Previous issue date: 2018-04-06 / Teaching programming is a great challenge in every educational stage and in several institutions of the world, being a general problem in the area of computing education. In the Brazilian Informatics vocational high school programs, historical issues of the Professional Education System in Brazil make this problem even harder. With these issues in mind, we proposed and evaluated a teaching approach based on spiral learning associated with programming environments for novices and contexts relevant to students, aiming to improve motivation and learning in programming courses. Three case studies were carried out: one in Midlle School, and two in vocational high school programs in Informatics in Feira de Santana, Bahia, Brazil. The case studies were split into three contextualized blocks, where programming content was learned through a context, using appropriate tools. Contexts such as games, geometric figures and images were used, as well as Scratch, JES and PPlay tools. Given the qualitative and quantitative nature of this research, we used sur- veys, interviews, observations, evaluations and logbooks to obtain the data. Results on motivation are described in terms of the ARCS model (Attention, Relevance, Confidence and Satisfaction), and the results on learning are described from student exams and qualitative data. Results point to high levels of motivation during the whole approach and to the influence in student motivation of either maintaining or changing context and tools used in each block. Regarding learning, results demonstrate that the approach has enhanced learning of some concepts. One noti- ces that Scratch helped in understanding Functions, Select and Repeart Structures, and that the use of the Python language led to better understanding of Variables and Relational Operators. About object-oriented programming concepts, students showed ease with Classes, Constructors, Objects and Variables. This study also reveals the mutual influence between student motivation and learning. The results, materials, research design and the courses presented in this work may contribute to the design of other vocational courses and to the research on teaching and learning programming. / O ensino de programa??o ? um grande desafio em todas as modalidades de ensino e em v?rias institui??es de diversos pa?ses, configurando-se como um problema geral na ?rea de Computa??o. Nos cursos t?cnicos em inform?tica brasileiros, somam-se os problemas hist?ricos da Educa??o Profissional no Brasil. Diante destes problemas, buscou-se a motiva??o e o aprendizado em disciplinas de programa??o, atrav?s de uma abordagem se ensino em espiral e contextualizada. Foram realizados tr?s estudos de caso: um, no ensino Fundamental, e dois, em cursos t?cnicos de Inform?tica, no munic?pio de Feira de Santana, Bahia. Os estudos de caso foram divididos em tr?s blocos contextualizados, onde estudavam-se conte?dos de programa??o atrav?s de um contexto, usando ferramentas apropriadas. Foram utilizados contextos como Jogos, Figuras geom?tricas e Imagens, assim como as ferramentas Scratch, JES e PPlay. Tendo em vista o car?ter qualitativo e quantitativo da pesquisa, utilizamos question?rios, entrevistas, observa??es, avalia??es e di?rios de bordo para obten??o dos dados. Os resultados sobre motiva??o s?o descritos em termos do modelo ARCS (Aten??o, Relev?ncia, Confian?a e Satisfa??o), enquanto que os resultados sobre aprendizagem s?o descritos a partir das avalia??es e dos dados qualitativos. Os resultados apontam para altos ?ndices de motiva??o, durante toda a abordagem e para a influ?ncia direta da manuten??o ou mudan?a do contexto e das ferramentas, utilizadas nos blocos, na motiva??o dos estudantes. Quanto `a aprendizagem, os resultados demonstram que a abordagem potencializou a aprendizagem de alguns conceitos. Percebe-se que o Scratch auxiliou na compreens?o de Fun??o, Estruturas de Repeti??o e Sele??o e que o uso da linguagem Python possibilitou uma maior compreens?o sobre Vari?veis e sobre Operadores Relacionais. Quanto ? orienta??o a objetos, os estudantes apresentaram facilidades em Classes, Construtores e Objetos. Este estudo revela ainda, rela??es de influ?ncia entre a motiva??o dos estudantes e a aprendizagem. Espera-se que os resultados, os materiais e o design da pesquisa e das disciplinas, aqui apresentados, possam contribuir para a concep??o de disciplinas de programa??o em outros cursos t?cnicos e para a investiga??o sobre o ensino-aprendizagem de programa??o.

My study is focused on women in graduate Computer Science programs at two universities in Ontario, Canada. My research problem emerges from earlier feminist research addressing the low numbers of women in university Computer Science programs, particularly at the graduate level. After over twenty years of active feminist representation of this problem, mostly through large survey-based studies, there has been little change. I argue that rather than continuing to focus on the rising and falling numbers of women studying Computer Science, it is critical to analyze the specific socio-economic and socio-cultural conditions which produce gendered and racialized exclusion in the field. Informed by Institutional Ethnography – a method of inquiry developed by Dorothy Smith – and by Foucault’s work on governmentality, I examine how specific institutional processes shape the everyday lives of women students. Through on-site observation and interviews with women in graduate Computer Science studies, Computer Science professors and university administrators, I investigate how the participants’ everyday institutional work is coordinated through external textual practices such as evaluation, reporting and accounting. I argue that the university’s institutional practices produce ‘women in computing’ as a ‘problem’ group in ways that re-inscribe women’s outsider status in the field. At the same time, I show that professionalized feminist educational projects may contradict their progressive and inclusive intentions, contributing to the ‘institutional capture’ (Smith) of women as an administrative ‘problem’. Through ethnographic research that follows women students through a range of experiences, I demonstrate how they variously endorse, subvert and exploit the contradictory subject positions produced for them. I illustrate how a North American-based institutional feminist representation of ‘women in computing’ ignores the everyday experiences of ethnoculturally diverse female student participants in graduate Computer Science studies. I argue that rather than accepting the organization of universal characteristics which reproduce conditions of exclusion, North American feminist scholars need to consider the specificity of social relations and forms of knowledge transnationally. Finally, I revisit how women in the study engage with ‘women in computing’ discourse through their lived experiences. I suggest the need for ongoing analysis of the gender effects and changing socio-cultural conditions of new technologies.