Relationships between reading, tracing and writing skills in introductory programming

This study analyzed student responses to an examination, after the students had completed one semester of instruction in programming. The performance of students on code tracing tasks correlated with their performance on code writing tasks. A correlation was also found between performance on "explain in plain English" tasks and code writing. A stepwise regression, with performance on code writing as the dependent variable, was used to construct a path diagram. The diagram suggests the possibility of a hierarchy of programming related tasks. Knowledge of programming constructs forms the bottom of the hierarchy, with "explain in English", Parson's puzzles, and the tracing of iterative code forming one or more intermediate levels in the hierarchy. Copyright 2008 ACM

Four approaches to teaching programming

Based on a survey of literature, four different approaches to teaching introductory programming are identified and described. Examples of the practice of each approach are identified representing procedural, visual, and object-oriented programming language paradigms. Each approach is then further analysed, identifying advantages and disadvantages for the student and the teacher. The first approach, code analysis, is analogous to reading before writing, that is, recognising the parts and what they mean. It requires learners to analyse and understand existing code prior to producing their own. An alternative is the building blocks approach, analogous to learning vocabulary, nouns and verbs, before constructing sentences. A third approach is identified as simple units in which learners master solutions to small problems before applying the learned logic to more complex problems. The final approach, full systems, is analogous to learning a foreign language by immersion whereby learners design a solution to a non-trivial problem and the programming concepts and language constructs are introduced only when the solution to the problem requires their application. The conclusion asserts that competency in programming cannot be achieved without mastering each of the approaches, at least to some extent. Use of the approaches in combination could provide novice programmers with the opportunities to acquire a full range of knowledge, understanding, and skills. Several orders for presenting the approaches in the classroom are proposed and analysed reflecting the needs of the learners and teachers. Further research is needed to better understand these and other approaches to teaching programming, not in terms of learner outcomes, but in terms of teachers’ actions and techniques employed to facilitate the construction of new knowledge by the learners. Effective classroom teaching practices could be informed by further investigations into the effect on progression of different toolset choices and combinations of teaching approache

The abstraction transition taxonomy: developing desired learning outcomes through the lens of situated cognition

We report on a post-hoc analysis of introductory programming lecture materials. The purpose of this analysis is to identify what knowledge and skills we are asking students to acquire, as situated in the activity, tools, and culture of what programmers do and how they think. The specific materials analyzed are the 133 Peer Instruction questions used in lecture to support cognitive apprenticeship -- honoring the situated nature of knowledge. We propose an Abstraction Transition Taxonomy for classifying the kinds of knowing and practices we engage students in as we seek to apprentice them into the programming world. We find students are asked to answer questions expressed using three levels of abstraction: English, CS Speak, and Code. Moreover, many questions involve asking students to transition between levels of abstraction within the context of a computational problem. Finally, by applying our taxonomy in classifying a range of introductory programming exams, we find that summative assessments (including our own) tend to emphasize a small range of the skills fostered in students during the formative/apprenticeship phase

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

Relationships: computational thinking, pedagogy of programming, and Bloom’s Taxonomy

This study explores the relationship between computational thinking, teaching programming, and Bloom’s Taxonomy. Data is collected from teachers, academics, and professionals, purposively selected because of their knowledge of the topics of problem solving, computational thinking, or the teaching of programming. This data is analysed following a grounded theory approach. A computational thinking taxonomy is developed. The relationships between cognitive processes, the pedagogy of programming, and the perceived levels of difficulty of computational thinking skills are illustrated by a model. Specifically, a definition for computational thinking is presented. The skills identified are mapped to Bloom’s Taxonomy: Cognitive Domain. This mapping concentrates computational skills at the application, analysis, synthesis, and evaluation levels. Analysis of the data indicates that abstraction of functionality is less difficult than abstraction of data, but both are perceived as difficult. The most difficult computational thinking skill is reported as decomposition. This ordering of difficulty for learners is a reversal of the cognitive complexity predicted by Bloom’s model. The plausibility of this inconsistency is explored. The taxonomy, model, and the other results of this study may be used by educators to focus learning onto the computational thinking skills acquired by the learners, while using programming as a tool. They may also be employed in the design of curriculum subjects, such as ICT, computing, or computer science. <br/

Fostering Program Comprehension in Novice Programmers - Learning Activities and Learning Trajectories

This working group asserts that Program Comprehension (ProgComp) plays a critical part in the process of writing programs. For example, this paper is written from a basic draft that was edited and revised until it clearly presented our idea. Similarly, a program is written incrementally, with each step tested, debugged and extended until the program achieves its goal. Novice programmers should develop program comprehension skills as they learn to code so that they are able both to read and reason about code created by others, and to reflect on their code when writing, debugging or extending it. To foster such competencies our group identified two main goals: (g1) to collect and define learning activities that explicitly address key components of program comprehension and (g2) to define tentative theoretical learning trajectories that will guide teachers as they select and sequence those learning activities in their CS0/CS1/CS2 or K-12 courses. The WG has completed the first goal and laid down a strong foundation towards the second goal as presented in this report. After a thorough literature review, a detailed description of the Block Model is provided, as this model has been used with a dual purpose, to classify and present an extensive list of ProgComp tasks, and to describe a possible learning trajectory for a complex task, covering different cells of the Block Model matrix. The latter is intended to help instructors to decompose complex tasks and identify which aspects of ProgComp are being fostered

Development and Application of a Rasch Model Measure of Student Competency in University Introductory Computer Programming

University computer programming instruction nomenclature commonly uses the term Computer Science 1 (CS1) to describe introductory units of study. Success in CS1 is important as a pre-requisite for further study in programming and related disciplines. It is important to measure student progress and the antecedent influences. This study applied the Rasch Model and Messick’s Unified Theory of Validity to construct an interval level measure of CS1 competency with demonstrable suitability for this purpose

Task-related models for teaching and assessing iteration learning in high school

A number of studies report about students’ difficulties with basic flow-control constructs, and specifically with iteration. Although such issues are less explored in the context of pre-tertiary education, this seems to be especially the case for high-school programming learning, where the difficulties concern both the “mechanical” features of the notional machine as well as the logical aspects connected with the constructs, ranging from the implications of loop conditions to a more abstract grasp of the underlying algorithms. For these reasons, the aim of this work is to: i) identifying methodological tools to enhance a comprehensive understanding of the iteration constructs, ii) suggest strategies to teach iterations. We interviewed 20 experienced upper secondary teachers of introductory programming in different kinds of schools. The interviews were mainly aimed at ascertaining teachers’ beliefs about major sources of issues for basic programming concepts and their approach to the teaching and learning of iteration constructs. Once teachers’ perception of students’ difficulties have been identified, we have submitted, to a sample of 164 students, a survey which included both questions on their subjective perception of difficulty and simple tasks probing their understanding of iteration. Data collected from teachers and students confirm that iteration is a central programming concept and indicate that the treatment of conditions and nested constructs are major sources of students’ difficulties with iteration. The interviews allowed us to identify a list of problems that are typically presented by teachers to explain the iterations. Hence, a catalogue of significant program examples has been built to support students’ learning, tasks with characteristics different from those typically presented in class. Based on the outcome of previous steps, a survey to collect related information and good practices from a larger sample of teachers has been designed. Data collected have been analysed distinguishing an orientation towards more conceptual objectives, and one towards more practical objectives. Furthermore, regarding evaluation, a orientation focused on process-based assessment and another on product-based assessment. Finally, based on the outcome of previous students’ survey and drawing from the proposed examples catalogue, we have designed and submitted a new students’ survey, composed of a set of small tasks, or tasklets, to investigate in more depth on high-school students’ understanding of iteration in terms of code reading abilities. The chosen tasklets covered the different topics: technical program feature, correlation between tracing effort and abstraction, the role of flow-charts, students’ perception of self-confidence concerning high-level thinking skills.A number of studies report about students’ difficulties with basic flow-control constructs, and specifically with iteration. Although such issues are less explored in the context of pre-tertiary education, this seems to be especially the case for high-school programming learning, where the difficulties concern both the “mechanical” features of the notional machine as well as the logical aspects connected with the constructs, ranging from the implications of loop conditions to a more abstract grasp of the underlying algorithms. For these reasons, the aim of this work is to: i) identifying methodological tools to enhance a comprehensive understanding of the iteration constructs, ii) suggest strategies to teach iterations. We interviewed 20 experienced upper secondary teachers of introductory programming in different kinds of schools. The interviews were mainly aimed at ascertaining teachers’ beliefs about major sources of issues for basic programming concepts and their approach to the teaching and learning of iteration constructs. Once teachers’ perception of students’ difficulties have been identified, we have submitted, to a sample of 164 students, a survey which included both questions on their subjective perception of difficulty and simple tasks probing their understanding of iteration. Data collected from teachers and students confirm that iteration is a central programming concept and indicate that the treatment of conditions and nested constructs are major sources of students’ difficulties with iteration. The interviews allowed us to identify a list of problems that are typically presented by teachers to explain the iterations. Hence, a catalogue of significant program examples has been built to support students’ learning, tasks with characteristics different from those typically presented in class. Based on the outcome of previous steps, a survey to collect related information and good practices from a larger sample of teachers has been designed. Data collected have been analysed distinguishing an orientation towards more conceptual objectives, and one towards more practical objectives. Furthermore, regarding evaluation, a orientation focused on process-based assessment and another on product-based assessment. Finally, based on the outcome of previous students’ survey and drawing from the proposed examples catalogue, we have designed and submitted a new students’ survey, composed of a set of small tasks, or tasklets, to investigate in more depth on high-school students’ understanding of iteration in terms of code reading abilities. The chosen tasklets covered the different topics: technical program feature, correlation between tracing effort and abstraction, the role of flow-charts, students’ perception of self-confidence concerning high-level thinking skills

Debugging: The Key to Unlocking the Mind of a Novice Programmer?

Novice programmers must master two skills to show lasting success: writing code and, when that fails, the ability to debug it. Instructors spend much time teaching the details of writing code but debugging gets significantly less attention. But what if teaching debugging could implicitly teach other aspects of coding better than teaching a language teaching debugging? This paper explores a new theoretical framework, the Theory of Applied Mind for Programming (TAMP), which merges dual process theory with Jerome Bruner’s theory of representations to model the mind of a programmer. TAMP looks to provide greater explanatory power in why novices struggle and suggest pedagogy to bridge gaps in learning. This paper will provide an example of this by reinterpreting debugging literature using TAMP as a theoretical guide. Incorporating new view theoretical viewpoints from old studies suggests a “debugging-first” pedagogy can supplement existing methods of teaching programming and perhaps fill some of the mental gaps TAMP suggests hamper novice programmers