Identifying and Correcting Programming Language Behavior Misconceptions

Proceedings of the ACM on Programming Languages, Год журнала: 2024, Номер 8(OOPSLA1), С. 334 - 361

Опубликована: Апрель 29, 2024

Misconceptions about core linguistic concepts like mutable variables, compound data, and their interaction with scope higher-order functions seem to be widespread. But how do we detect them, given that experts have blind spots may not realize the myriad ways in which students can misunderstand programs? Furthermore, once identified, what correct them? In this paper, present a curated list of misconceptions, an instrument them. These are distilled from student work over several years match extend prior research. We also automated, self-guided tutoring system. The tutor builds on strategies education literature is explicitly designed around identifying correcting misconceptions. tested multiple settings. Our data consistently show (a) misconceptions tackle widespread, (b) appears improve understanding.

Язык: Английский

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Computational Thinking and Notional Machines: The Missing Link

ACM Transactions on Computing Education, Год журнала: 2023, Номер 23(4), С. 1 - 27

Опубликована: Окт. 18, 2023

In learning to program and understanding how a programming language controls computer, learners develop both insights misconceptions whilst their mental models are gradually refined. It is important that the learner able distinguish different elements roles of computer (compiler, interpreter, memory, etc.), which novice programmers may find difficult comprehend. Forming accurate one potential sources difficulty inextricably linked mastering computing concepts processes, for programming. common use some form representation (e.g., an abstract machine or Computational Agent (CA)) support technical pedagogic explanations. The Notional Machine (NM) pedagogical device entails more computational concepts, originally described as idealised operating with constructs particular language. can be used specific general goals will typically have concrete referred to. Thinking (CT), defined way thinking [computational] problem solving, often presented using CA carry out information processing by solution. CT, where typical goal produce algorithm program, seemingly serves purpose very similar NM. Although it changes through stages development (of curriculum), CAs NMs seen versatile tools connect learner’s model conceptual program. this article, we look at relationship between NMs, indicate they would learning. We traverse range definitions usages these articulate clarify viewed in literature. This includes exploring nature machines agents, historical views relate modern pedagogy computation. argue abstract, simplified variant NM provides useful perspective them robust efficiently effectively. propose teaching should make idea learning, link connects full

Язык: Английский

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Constructing feedback for computer science MCQ wrong answers using semantic profiling (Discussion Paper)

Опубликована: Ноя. 13, 2023

Computer science (CS) for K-12 students is a hard subject with abstract concepts to learn. Multiple-choice questions (MCQ) are often used supplement classroom learning, feedback from wrong answers playing role in addressing misunderstandings. Semantics, dimension of Legitimation Code Theory, framework understanding knowledge practices, has been suggested as useful theory reviewing and structuring CS learning events. In this discussion paper, we explore the use 'semantic profiling' improve MCQ post-16 studying SQL relational databases. We describe reflexive review process developed present semantic profiles two case studies new answers. New answer five was trialed pilot study students, self-reported useful. For example, liked metacognitive aspect that explained why were or right generalised summaries. From our experience, suggest using profiling can help authors develop their literacy, particularly creating learner 'feedforward' (take-away) opportunities. The approach promise will build on, invite other researchers evaluate approach.

Язык: Английский

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Towards a Notional Machine for Runtime Stacks and Scope: When Stacks Don’t Stack Up

Опубликована: Авг. 3, 2022

Background and Context.

Язык: Английский

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Evaluating the Utility of Notional Machine Representations to Help Novices Learn to Code Trace

Опубликована: Авг. 7, 2023

Code tracing involves simulating at a high level the actions computer takes when executing program. Given that students experience difficulties learning this fundamental skill, research is needed on how to effectively teach it. We report two studies investigate pedagogical utility of various notional machine representations used explain mechanics program execution. In study 1 (N = 44), we compared instruction using concrete representation an abstract table representation. 2 50), tested if fading between improved over only providing one The in both was embedded basic tutoring systems implemented served as testbeds for present research. On average did learn each study, evidenced by pretest posttest gains, but type not significantly affect learning; Bayesian statistics provided substantial evidence null result. discuss potential explanations our findings and suggest future directions.

Язык: Английский

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Domain-Specific Theories of Teaching Computing: Do they Inform Practice?

Опубликована: Ноя. 13, 2023

Computing education research applies theories from the social sciences to build deep understanding of factors that influence students' learning process in different educational settings; but recent years, computing researchers have increasingly developed domain-specific and models address challenges phenomena specific education. Several literature surveys addressed these developments. However, little attention has been given whether actually applied improve pedagogical practices

Язык: Английский

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“Eu posso aprender tudo online”: Uma Análise das Notional Machines do TikTok para Aprender Programação

Опубликована: Июль 21, 2024

Não é surpreendente que muitos instrutores e estudantes recorram a espaços educacionais não-formais, especialmente redes sociais baseadas em vídeo como o TikTok, quando têm tarefa de aprender programar, particularmente treinamento formal raramente fornecido. No entanto, incerto tipo conteúdo educacional tais plataformas fornecem aos professores qualidade desse conteúdo. Neste trabalho, visamos diminuir essa lacuna investigando vídeos programação no extraindo explicações – as Notional Machines usadas pelos apresentadores. Analisamos 300 dessa plataforma para classificar explicar tópicos variáveis, loops, condicionais funções. Nossos resultados mostram que, geral, maioria dos não oferece uma definição explícita conceitos, ou usam superficiais ”de livro didático”, incluindo algumas consideradas perigosas na literatura. Infelizmente, conseguimos encontrar nova terminologia linguagem permitisse educadores se comunicar com sucesso alunos níveis primário secundário. Embora mais trabalho seja necessário analisar um corpus maior vídeos, oferecemos alerta sobre uso verificado substituto materiais aprendizagem bem preparados.

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Educational Materials to Train Teachers in ScratchJr: Rules of Program Behavior and Programming Patterns

Опубликована: Июнь 19, 2024

Язык: Английский

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Expressions in Java: Essential, Prevalent, Neglected?

Опубликована: Ноя. 29, 2022

Expressions are the building blocks of formal languages such as lambda calculus well programming that closely modeled after it. Although expressions also an important part programs in like Java, not primarily functional, teaching practices typically don't focus much on expressions.

Язык: Английский

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Video Analysis of a Teacher’s Use of Notional Machines in an Introductory High School Electronic Textile Unit: A three-tier framework to capture notional machines in practice

Опубликована: Окт. 12, 2022

Learners' conceptions of program dynamics shape their reading, writing, and debugging code. But, the invisibility underlying behaviors that transform code to outcomes challenges learners. Teachers adopt notional machines, defined as simplified notions about dynamics, support learners within computing classrooms. Researchers have gathered machine examples by interviewing post-secondary instructors. there is a need capture machines in practice classrooms, particularly introductory high school classes where teachers communicate with limited no prior programming experiences. Through qualitative video analysis seven online class periods (80 minutes each) across 14 weeks an physical electronic textiles unit, this paper answers: (1) What did teacher use practice? (2) At what levels granularity they dynamics? And, (3) representational forms take? The revealed three-tier framework practice. First, belonged one five themes depending on layer abstraction textiles. Second, differed along granularity—individual atoms, blocks, relations between or entire program. Third, took two distinct forms—verbal explanations participatory roleplays. Overall, has two-fold contribution: provides for future research study practice, and, at same time, presents first accounts adopted unit.

Язык: Английский

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