The cognitive construction of programs by novice programmers : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Computer Science at Massey University

Human memory and cognition are studied to aid novice programmers with the cognitive construction and the acquisition of program plans. Particular emphasis is placed on the storage and retrieval of program knowledge, the cognitive structure of stored program knowledge, the effects of transferring cognitive structures from one programming language to another, and the learning activities involved with learning a new programming language. Cognitive principles are applied to the design of a programming language and environment. The design of both the programming language and environment are discussed together with an introduction of how they are used. The hypothetical results of two experiments are argued to demonstrate that the programming language and environment are well suited in supporting the development of program plans

Instructional strategies and tactics for the design of introductory computer programming courses in high school

This article offers an examination of instructional strategies and tactics for the design of introductory computer programming courses in high school. We distinguish the Expert, Spiral and Reading approach as groups of instructional strategies that mainly differ in their general design plan to control students' processing load. In order, they emphasize topdown program design, incremental learning, and program modification and amplification. In contrast, tactics are specific design plans that prescribe methods to reach desired learning outcomes under given circumstances. Based on ACT* (Anderson, 1983) and relevant research, we distinguish between declarative and procedural instruction and present six tactics which can be used both to design courses and to evaluate strategies. Three tactics for declarative instruction involve concrete computer models, programming plans and design diagrams; three tactics for procedural instruction involve worked-out examples, practice of basic cognitive skills and task variation. In our evaluation of groups of instructional strategies, the Reading approach has been found to be superior to the Expert and Spiral approaches

Eye movements in code reading:relaxing the linear order

Abstract—Code reading is an important skill in programming. Inspired by the linearity that people exhibit while natural lan-guage text reading, we designed local and global gaze-based mea-sures to characterize linearity (left-to-right and top-to-bottom) in reading source code. Unlike natural language text, source code is executable and requires a specific reading approach. To validate these measures, we compared the eye movements of novice and expert programmers who were asked to read and comprehend short snippets of natural language text and Java programs. Our results show that novices read source code less linearly than natural language text. Moreover, experts read code less linearly than novices. These findings indicate that there are specific differences between reading natural language and source code, and suggest that non-linear reading skills increase with expertise. We discuss the implications for practitioners and educators. I

Applying a User-centred Approach to Interactive Visualization Design

Analysing users in their context of work and finding out how and why they use different information resources is essential to provide interactive visualisation systems that match their goals and needs. Designers should actively involve the intended users throughout the whole process. This chapter presents a user-centered approach for the design of interactive visualisation systems. We describe three phases of the iterative visualisation design process: the early envisioning phase, the global specification hase, and the detailed specification phase. The whole design cycle is repeated until some criterion of success is reached. We discuss different techniques for the analysis of users, their tasks and domain. Subsequently, the design of prototypes and evaluation methods in visualisation practice are presented. Finally, we discuss the practical challenges in design and evaluation of collaborative visualisation environments. Our own case studies and those of others are used throughout the whole chapter to illustrate various approaches

Using Eye-Tracking Data to Compare Differences in Code Comprehension and Code Perceptions between Expert and Novice Programmers

Previous research has examined how eye-tracking metrics can serve as a proxy for directly measuring the amount of cognitive effort and processing required for comprehending computer code. We conducted a pilot study comprising expert (n = 10) and novice (n = 10) computer programmers to examine group differences in code comprehension abilities and perceptions. Programmers were asked to read two pieces of computer code, rate the code on various attributes, and then describe what the code does. Results indicate that experts and novices significantly differ in terms of their fixation counts made during the task, such that experts had more fixations than novices. This was counter to our hypothesis that experts would have fewer fixations than novices. We found no evidence that experts and novices differed in their average fixation durations, trustworthiness and performance perceptions, or willingness to reuse the code

Knowledge restructing and the development of expertise in computer programming

This thesis reports a number of empirical studies exploring the development of expertise in computer programming. Experiments 1 and 2 are concerned with the way in which the possession of design experience can influence the perception and use of cues to various program structures. Experiment 3 examines how violations to standard conventions for constructing programs can affect the comprehension of expert, intermediate and novice subjects. Experiment 4 looks at the differences in strategy that are exhibited by subjects of varying skill level when constructing programs in different languages. Experiment 5 takes these ideas further to examine the temporal distribution of different forms of strategy during a program generation task. Experiment 6 provides evidence for salient cognitive structures derived from reaction time and error data in the context of a recognition task. Experiments 7 and 8 are concerned with the role of working memory in program generation and suggest that one aspect of expertise in the programming domain involves the acquisition of strategies for utilising display-based information. The final chapter attempts to bring these experimental findings together in terms of a model of knowledge organisation that stresses the importance of knowledge restructuring processes in the development of expertise. This is contrasted with existing models which have tended to place emphasis upon schemata acquisition and generalisation as the fundamental modes of learning associated with skill development. The work reported here suggests that a fine-grained restructuring of individual schemata takes places during the later stages of skill development. It is argued that those mechanisms currently thought to be associated with the development of expertise may not fully account for the strategic changes and the types of error typically found in the transition between novice, intermediate and expert problem solvers. This work has a number of implications for existing theories of skill acquisition. In particular, it questions the ability of such theories to account for subtle changes in the various manifestations of skilled performance that are associated with increasing expertise. Secondly, the work reported in this thesis attempts to show how specific forms of training might give rise to the knowledge restructuring process that is proposed. Finally, the thesis stresses the important role of display-based problem solving in complex tasks such as programming and highlights the role of programming language notation as a mediating factor in the development and acquisition of problem solving strategies