This thesis reports a research project that aims to improve the teaching and learning of introductory programming from a pedagogical and psychological viewpoint. Towards this aim, seven principles for designing educational programming tools for novices were identified by reviewing literature regarding novices’ difficulties and using a theoretical framework defined by the psychological theories of Constructivism and Cognitive Load Theory. This set of design principles was not only theoretically identified, but its pedagogical impact was also empirically tested. For this reason, Koios, a new programming tool, was designed and developed as a manifestation of the combined set of principles. Empirical studies were conducted by a way of a quasi-experimental design in two different Greek secondary-education institutions. The independent variable was compliance with the set of the seven principles. Students’ level of programming skills (procedural knowledge) was the dependent variable, while the quality of their mental models in the domain of introductory programming (declarative knowledge) was the potential mediator. The effect of compliance with the set of principles on students’ programming skills and mental-model quality was explored via Koios’ evaluation. Declarative- and procedural-knowledge measurements, as well as a practical test, were used to collect data, which were analysed using ANOVA and hierarchical multiple regression. The major conclusions drawn from this study are:(a) compliance with the set of design principles does not affect the development of novices’ procedural and declarative programming knowledge, (b) a programming tool that highly complies with this set facilitates novices in the application of their procedural programming knowledge during program creation and (c) programming tools, declarative and procedural knowledge are independent components in learning to program. However, it was also concluded that the two knowledge types and a programming tool that highly complies with the set contribute significantly to novices’ programming performance. This study contributes to knowledge by theoretically identifying and empirically testing a set of design principles for educational programming software, and by producing and scientifically evaluating a programming tool as an embodiment of this set. Through this evaluation, the suggestion of Koios as a practically useful programming tool for novices seems to be well supported.

The readability of source code is essential for software maintenance. Since maintenance is an ongoing process, which is estimated to be 70 percent of the software development life cycle's total costs, it cannot be deprioritized. The readability of source code is likely to affect the program comprehension, which may help or create problems in the maintenance of the software. How different code features and functions affect the readability of source code have previously been investigated, and readability metrics have been developed. The project was initiated because of the lack of research on how programming knowledge and statically compared to dynamically typed programming languages affect the readability of the source code. A survey was conducted and included 21 computer science students with various programming knowledge, each rating eight code snippets, making it in total 168 ratings. The results showed that the type of programming language could improve the readability of source code. The results also showed that programming knowledge does not have a correlation with the ability to read source code.

AbstractTo teach programming in upper secondary school, the teacher needs to be certified inteaching programming. Teachers can be certified by having a certain amount ofhigher education credits or if they possess equivalent knowledge and skills.Consequently, variations in terms of possessed knowledge for the teacher wouldoccur. The difference in each teacher's acquired knowledge may also affect their viewon what is considered to have the knowledge of programming. Therefore, it affectstheir education due to changes in their liking. Highlighting programming teachers'views and underlying factors enables potential improvement to increase the qualityand enable an equal programming education.Currently, there are theories regarding what can be considered programmingknowledge. However, most theories can be considered outdated due to when theywere conducted and their technical background. However, the majority of researchfocuses on learning how to program, not teaching. Therefore, teachers need to basetheir education on previous experiences and views. There is a gap regarding whatteachers deem to be the most important aspect and what are possible reasons for suchviews.Consequently, the following research questions arose:• How can programming knowledge be categorized from a knowledgetheoretical perspective?• Which aspects of programming knowledge are considered the mostimportant according to programming teachers teaching the course"Programmering 1" or "Programmering 2" in upper secondary school?• What are the possible underlying factors that could affect which aspects ofprogramming knowledge that programming teachers teaching the course"Programmering 1" or "Programmering 2" in upper secondary schoolprioritize?To answer the research questions, the method used was based on mixed methodsdesigns. The qualitative method used an integrated literature review, and as a result,PKM was developed and used later for developing the quantitative study. Thequantitative method consisted of Q-methodology and interviews with thematicanalysis, and the qualitative method was used to substantiate the findings of thequantitative method.From the ILR, four types of knowledge were acquired; theoretical knowledge,practical knowledge, abstract knowledge, and conceptual knowledge. There is noconsensus on which knowledge category is considered more essential forprogramming knowledge; underlying factors such as no didactical education and self-taught are mainly affected by underlying factors. Possible essential aspects are eithercombining all knowledge concepts or just conceptual knowledge. Due to noconsensus, underlying factors affect what can be considered essential forprogramming knowledge. Due to the findings, possible complications may arise, suchas differences in the quality of education. Furthermore, potentially harm and possiblyscare students learning for further studies in programming. / För att undervisa i programmering i gymnasieskolan behöver läraren vara legitimerad i att undervisa i programmering. Lärare kan certifieras genom att ha ett visst antal högskolepoäng eller om de besitter motsvarande kunskaper och färdigheter. Följaktligen kan lärares kunskaper variera. Skillnaden i varje lärares kunskaper kan också påverka deras syn på vad som anses ha kunskap inom ämnen som om programmering. Därför påverkar det deras utbildning på grund av ändringar efter personliga synpunkter och preferenser. Att lyfta fram programmerings lärares synpunkter och bakomliggande faktorer möjliggör potentiell förbättring för att höja kvaliteten och möjliggöra en likvärdig programmeringsutbildning. För närvarande finns det teorier om vad som kan betraktas som programmerings kunskap. De flesta teorier kan dock anses föråldrade på grund av när de genomfördes och deras tekniska bakgrund. Majoriteten av forskning fokuserar dock på att lära sig programmera, inte på undervisning. Läraren behöver utgå från egen erfarenhet och bakgrund. Det finns en lucka när det gäller vad lärare anser vara den viktigaste aspekten och vad som är möjliga orsaker till sådana synpunkter. Följaktligen uppstod följande forskningsfrågor: • Hur kan programmeringskunskaper kategoriseras ur ett kunskapsteoretiskt perspektiv? • Vilka aspekter av programmeringskunskap anses vara viktigast enligt programmeringslärare som undervisar i kursen "Programmering 1" eller "Programmering 2" på gymnasiet? • Vilka är de möjliga bakomliggande faktorerna som kan påverka vilka aspekter av programmeringskunskaper som programmeringslärare som undervisar i kursen "Programmering 1" eller "Programmering 2" i gymnasieskolan prioriterar? För att besvara forskningsfrågorna baserades den använda metoden på design av blandade metoder. Den kvalitativa metoden använde en integrerad litteraturöversikt och som ett resultat utvecklades PKM och användes senare för att utveckla den kvantitativa studien. Den kvantitativa metoden bestod av Q-metod och intervjuer med tematisk analys och den kvalitativa metoden användes för att underbygga fynden av den kvantitativa metoden.Från ILR förvärvades fyra typer av kunskap; teoretisk kunskap, praktisk kunskap, abstrakt kunskap och konceptuell kunskap. Det finns ingen konsensus om vilken kunskaps kategori som anses vara viktigast för programmeringskunskaper; bakomliggande faktorer som ingen didaktisk utbildning och självlärd påverkas främst av bakomliggande faktorer. Möjliga väsentliga aspekter är antingen att kombinera alla kunskapsbegrepp eller bara konceptuell kunskap. På grund av bristande konsensus påverkar underliggande faktorer vad som kan anses väsentligt för programmeringskunskaper. På grund av fynden kan möjliga komplikationer uppstå, såsom skillnader i utbildningens kvalitet. Dessutom potentiellt skada och eventuellt skrämma elevernas lärande för vidare studier i programmering.

Thesis (M.Sc. (Hons.)) -- University of Western Sydney, 2001. / "A thesis submitted for the degree of Master of Science (Honours) - Computing and Information Technology at University of Western Sydney" Bibliography : leaves 93-98.

While automated game playing systems like Deep Blue perform excellent within their domain, handling a different game or even a slight change of rules is impossible without intervention of the programmer. Considered a great challenge for Artificial Intelligence, General Game Playing is concerned with the development of techniques that enable computer programs to play arbitrary, possibly unknown n-player games given nothing but the game rules in a tailor-made description language. A key to success in this endeavour is the ability to reliably extract hidden game-specific features from a given game description automatically. An informed general game player can efficiently play a game by exploiting structural game properties to choose the currently most appropriate algorithm, to construct a suited heuristic, or to apply techniques that reduce the search space. In addition, an automated method for property extraction can provide valuable assistance for the discovery of specification bugs during game design by providing information about the mechanics of the currently specified game description. The recent extension of the description language to games with incomplete information and elements of chance further induces the need for the detection of game properties involving player knowledge in several stages of the game. In this thesis, we develop a formal proof method for the automatic acquisition of rich game-specific invariance properties. To this end, we first introduce a simple yet expressive property description language to address knowledge-free game properties which may involve arbitrary finite sequences of successive game states. We specify a semantic based on state transition systems over the Game Description Language, and develop a provably correct formal theory which allows to show the validity of game properties with respect to their semantic across all reachable game states. Our proof theory does not require to visit every single reachable state. Instead, it applies an induction principle on the game rules based on the generation of answer set programs, allowing to apply any off-the-shelf answer set solver to practically verify invariance properties even in complex games whose state space cannot totally be explored. To account for the recent extension of the description language to games with incomplete information and elements of chance, we correctly extend our induction method to properties involving player knowledge. With an extensive evaluation we show its practical applicability even in complex games.