Introductory programming: a systematic literature review

As computing becomes a mainstream discipline embedded in the school curriculum and acts as an enabler for an increasing range of academic disciplines in higher education, the literature on introductory programming is growing. Although there have been several reviews that focus on specific aspects of introductory programming, there has been no broad overview of the literature exploring recent trends across the breadth of introductory programming. This paper is the report of an ITiCSE working group that conducted a systematic review in order to gain an overview of the introductory programming literature. Partitioning the literature into papers addressing the student, teaching, the curriculum, and assessment, we explore trends, highlight advances in knowledge over the past 15 years, and indicate possible directions for future research

On the domain-specificity of mindsets: The relationship between aptitude beliefs and programming practice

This is the author's accepted manuscript. The final published article is available from the link below. Copyright @ 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.Deliberate practice is important in many areas of learning, including that of learning to program computers. However, beliefs about the nature of personal traits, known as mindsets, can have a profound impact on such practice. Previous research has shown that those with a fixed mindset believe their traits cannot change; they tend to reduce their level of practice when they encounter difficulty. In contrast, those with the growth mindset believe their traits are flexible; they tend to maintain regular practice despite the level of difficulty. However, focusing on mindset as a single construct focused on intelligence may not be appropriate in the field of computer programming. Exploring this notion, a self-belief survey was distributed to undergraduate software engineering students. It revealed that beliefs about intelligence and programming aptitude formed two distinct constructs. Furthermore, the mindset for programming aptitude had greater utility in predicting software development practice, and a follow-up survey showed that it became more fixed throughout instruction. Thus, educators should consider the role of programming-specific beliefs in the design and evaluation of introductory courses in software engineering. In particular, they need to situate and contextualize the growth messages that motivate students who experience early setbacks

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

Implicit Theories and Self-efficacy in an Introductory Programming Course

Contribution: This study examined student effort and performance in an introductory programming course with respect to student-held implicit theories and self-efficacy. Background: Implicit theories and self-efficacy shed a light into understanding academic success, which must be considered when developing effective learning strategies for programming. Research Questions: Are implicit theories of intelligence and programming, and programming-efficacy related to each other and student success in programming? Is it possible to predict student course performance using a subset of these constructs? Methodology: Two consecutive surveys (N=100 and N=81) were administered to non-CS engineering students in I\c{s}{\i}k University. Findings: Implicit theories and self-beliefs are interrelated and correlated with effort, performance, and previous failures in the course and students explain failure in programming course with "programming-aptitude is fixed" theory, and also that programming is a difficult task for themselves.Comment: Programming Education. 8 page

Functional Baby Talk: Analysis of Code Fragments from Novice Haskell Programmers

What kinds of mistakes are made by novice Haskell developers, as they learn about functional programming? Is it possible to analyze these errors in order to improve the pedagogy of Haskell? In 2016, we delivered a massive open online course which featured an interactive code evaluation environment. We captured and analyzed 161K interactions from learners. We report typical novice developer behavior; for instance, the mean time spent on an interactive tutorial is around eight minutes. Although our environment was restricted, we gain some understanding of Haskell novice errors. Parenthesis mismatches, lexical scoping errors and do block misunderstandings are common. Finally, we make recommendations about how such beginner code evaluation environments might be enhanced

Links between the personalities, styles and performance in computer programming

There are repetitive patterns in strategies of manipulating source code. For example, modifying source code before acquiring knowledge of how a code works is a depth-first style and reading and understanding before modifying source code is a breadth-first style. To the extent we know there is no study on the influence of personality on them. The objective of this study is to understand the influence of personality on programming styles. We did a correlational study with 65 programmers at the University of Stuttgart. Academic achievement, programming experience, attitude towards programming and five personality factors were measured via self-assessed survey. The programming styles were asked in the survey or mined from the software repositories. Performance in programming was composed of bug-proneness of programmers which was mined from software repositories, the grades they got in a software project course and their estimate of their own programming ability. We did statistical analysis and found that Openness to Experience has a positive association with breadth-first style and Conscientiousness has a positive association with depth-first style. We also found that in addition to having more programming experience and better academic achievement, the styles of working depth-first and saving coarse-grained revisions improve performance in programming.Comment: 27 pages, 6 figure

Teaching Software Engineering through Robotics

This paper presents a newly-developed robotics programming course and reports the initial results of software engineering education in robotics context. Robotics programming, as a multidisciplinary course, puts equal emphasis on software engineering and robotics. It teaches students proper software engineering -- in particular, modularity and documentation -- by having them implement four core robotics algorithms for an educational robot. To evaluate the effect of software engineering education in robotics context, we analyze pre- and post-class survey data and the four assignments our students completed for the course. The analysis suggests that the students acquired an understanding of software engineering techniques and principles