A Study of Code Design Skills in Novice Programmers using the SOLO taxonomy

Izu, Cruz; Weerasinghe, Amali; Pope, Cheryl

doi:10.1145/2960310.2960324

Cited by 72 publications

(25 citation statements)

References 15 publications

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“…Bloom believed that "...his taxonomy could serve, among other things, to provide a common language of reference, defining educational goals, and provide a panorama of educational possibilities" [37, p. 8]. These taxonomies have been widely researched and used within computing education and, in part, they illustrate their importance as Bloom anticipated [23,27,34,38,39,70].…”

Section: Taxonomy Importance and Usagementioning

confidence: 99%

Construction of a Taxonomy for Tools, Languages, and Environments across Computing Education

McGill

Decker

2020

Proceedings of the 2020 ACM Conference on International Computing Education Research

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The sheer number of tools, languages, and environments (TLEs) used in computing education has proliferated in the last few years as more tools are developed to meet new demands of the growing amount of K-12 computing education that has been undertaken. However, there is little formalized language at either the K-12 or post-secondary level that provides for a way to classify these TLEs for discussing research and for classifying in databases. In this research study, we step through a formal process for building a taxonomy for TLEs. As part of the supporting research, we first discuss the importance of taxonomies and classification systems in computing education, provide a formal method for building a taxonomy, and provide working definitions of TLEs based on previous literature. This is followed by a systematic literature review using a widely-accepted methodology for finding articles that have examined TLEs in primary, secondary, and post-secondary computing education. This literature review focuses on studies that looked at multiple TLEs and specifically attempted to classify or categorize them. We then propose a new taxonomy for classifying TLEs and provide definitions and samples for each category. This is followed by a discussion of the next steps in vetting the taxonomy and the challenges and issues that need to be considered when evaluating it for classifying TLEs in computing education.

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Section: Taxonomy Importance and Usagementioning

confidence: 99%

Construction of a Taxonomy for Tools, Languages, and Environments across Computing Education

McGill

Decker

2020

Proceedings of the 2020 ACM Conference on International Computing Education Research

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“…In general, CER resorted to adaptations of taxonomies such as Bloom's [218] (emphasizing the general types of activities that programmers engage), and SOLO [29] (outlining the general degree of structuredness in learning outcomes) to categorize tasks or skills [35,219,155,364,82,105,47]. However, these taxonomies are not particularly concerned with the complexity of the tasks, nor evaluate the content used in programming tasks, the concrete programs employed in such activities.…”

Section: Gaps In Current Researchmentioning

confidence: 99%

“…Novice understanding of programs has been explored from a variety of perspectives, among them: interpreting students' ways of classifying code fragments based on perceived similarities and differences [365]; categorizing novices' mental models of the notional machine underlying imperative [33] and recursive [307] computations, as well as comparing students' mastery of recursion vs. iteration [237]; assessing the understanding of conditionals, loops and nested loops [155,48]; analyzing the relations between students' performance and their annotations in the exam papers [223], and finally comparing block versus textual representations of programs [385].…”

Section: Program Comprehension Activitiesmentioning

confidence: 99%

“…In this respect, our work shares some goals with earlier work that has proposed learning trajectories for introductory programming such as Mead et al al. [155] suggested an intuitive learning trajectory in which the learner abstracts increasingly complex "building blocks" (language constructs and plan-like "templates") in order to tackle the next concepts; the CCCP differs from this work in its use of MHC to structure the plan hierarchy.…”

Section: How To Design Explicit Representations Of the Rules Of Progrmentioning

confidence: 99%

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

Izu

Schulte

Aggarwal

et al. 2019

Proceedings of the Working Group Reports on Innovation and Technology in Computer Science Education

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“…Results indicate that students with greater proficiency at writing code were more likely to use multiple levels of abstraction when describing the code they were writing and moved between levels of abstraction with higher frequency. Izu et al [7] used an adjusted SOLO taxonomy to classify programming questions' by using a "building block" as the granular structure in the taxonomy to overcome the variability in problem difficulty. A building block was defined as a code pattern or template that students had seen, allowing for differentiation between recall and synthesis in problem difficulty.…”

Section: Category Definitionmentioning

confidence: 99%

Using the SOLO Taxonomy to Understand Subgoal Labels Effect in CS1

Decker

Margulieux

Morrison

2019

Proceedings of the 2019 ACM Conference on International Computing Education Research

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This work extends previous research on subgoal labeled instructions by examining their effect across a semester-long, Java-based CS1 course. Across four quizzes, students were asked to explain in plain English the process that they would use to solve a programming problem. In this mixed methods study, we used the SOLO taxonomy to categorize student responses about problem-solving processes and compare students who learned with subgoal labels to those who did not. The use of the SOLO taxonomy classification allows us to look deeper than the mere correctness of answers to focus on the quality of the answers produced in terms of completeness of relevant concepts and explanation of relationships among concepts. Students who learned with subgoals produced higher-rated answers in terms of complexity and quality on three of four quizzes. Also, they were three times more likely to discuss issues of data type on a question about assignments and expressions than students who did not learn with subgoal labeling. This suggests that the use of subgoal labeling enabled students to gain a deeper and more complex understanding of the material presented in the course. CCS CONCEPTS • Social and professional topics → Computing education → Computer science education → CS1

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A Study of Code Design Skills in Novice Programmers using the SOLO taxonomy

Cited by 72 publications

References 15 publications

Construction of a Taxonomy for Tools, Languages, and Environments across Computing Education

Construction of a Taxonomy for Tools, Languages, and Environments across Computing Education

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

Using the SOLO Taxonomy to Understand Subgoal Labels Effect in CS1

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