To Write Code: The Cultural Fabrication of Programming Notation and Practice

Arawjo, Ian

doi:10.1145/3313831.3376731

Cited by 16 publications

(5 citation statements)

References 54 publications

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“…A related theme that is attracting attention is the similarity and dissimilarity of programming notations (and other formalisms) to natural languages [2,3,10,24,28,29,48,49,74,75,87]. Research on this intriguing and complex topic has only begun.…”

Section: 25mentioning

confidence: 99%

Should Explanations of Program Code Use Audio, Text, or Both? A Replication Study

Zavgorodniaia

Hellas

Seppälä

et al. 2020

Koli Calling '20: Proceedings of the 20th Koli Calling International Conference on Computing Education Research

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Studies in educational psychology suggest that people learn better when visual learning materials are accompanied by audio explanations rather than textual ones. Research on how this modality effect applies to computing education is scarce and inconclusive. We explore whether modality of instruction affects learning from videos that use a series of example programs to explain how variables work in Python. Learners (n=186) were crowdsourced from the internet and randomized in three groups, who received explanations as audio, text, or both, respectively. We did not find significant differences between the groups in near transfer to code-tracing tasks or perceived cognitive load. The result affirms the need to further investigate instructional modalities in programming education. There are a number of theoretical, methodological, and instructional-design factors that may explain these and earlier findings; we trace out future research that could explore those factors. CCS CONCEPTS• Social and professional topics → Computing education.

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Section: 25mentioning

confidence: 99%

Should Explanations of Program Code Use Audio, Text, or Both? A Replication Study

Zavgorodniaia

Hellas

Seppälä

et al. 2020

Koli Calling '20: Proceedings of the 20th Koli Calling International Conference on Computing Education Research

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“…In conceiving of programming as writing code, early computer scientists implicitly set forth the agenda for interface designers as code being the underlying complexity that design metaphors ought to abstract away. But this was scarcely inevitable: Arawjo traces key cultural, commercial and technical constraints, including institutional directives, the requirements to retrofit punch card machines and typewriters, and even aesthetic xenophobia (Frege's two-dimensional notation was ridiculed as "Japanese" [58]), which led to the dominance of the sentential paradigm over visual, diagrammatic alternatives [5].…”

Section: How Did We Get Here?mentioning

confidence: 99%

Should Computers Be Easy To Use? Questioning the Doctrine of Simplicity in User Interface Design

Sarkar

2023

Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems

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That computers should be easy to learn and use is a rarely-questioned tenet of user interface design. But what do we gain from prioritising usability and learnability, and what do we lose? I explore how simplicity is not an inevitable truth of user interface design, but rather contingent on a series of events in the evolution of software. Not only does a rigid adherence to this doctrine place an artificial ceiling on the power and flexibility of software, but it is also culturally relative, privileging certain information cultures over others. I propose that for feature-rich software, negotiated complexity is a better target than simplicity, and we must revisit the ill-regarded relationship between learning, documentation, and software. CCS CONCEPTS• Human-centered computing → HCI theory, concepts and models; HCI theory, concepts and models; Interaction design theory, concepts and paradigms; • Social and professional topics → Cultural characteristics; History of computing; Computing education; Computing and business.

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“…This has enabled models to achieve human-level performance for the first time in a wide variety of benchmarks including code generation, speech recognition, image generation, even passing the bar exam [46]. This is the latest development in a period typically dated to begin in 2016 that has been described as the "third summer" of AI, 3 following a common periodisation of AI research as measured by "rapid scientific advances, broad commercialisation, and exuberance" [47]. A relatively stable term of art accepted and advocated within the AI research community that encapsulates the advances of the third summer is "deep learning" [60], which is broad enough to encompass a variety of approaches developed in recent years while being specific enough to exclude older generative approaches.…”

Section: The Status Quo For End-user Programming Researchmentioning

confidence: 99%

“…On the other hand, the imprecision of natural language, particularly when it comes to discourse on matters of logic, mathematics, philosophy, and science, has long been seen as a major drawback and spurred many attempts to design more logically "perfect" languages [25,78]. Indeed, the program of analytic philosophy which was born out of such concerns eventually gave rise to our modern programming languages [3], and it is interesting that programming via generative models brings us back, full circle, to natural language. However, the trend of improving generative models seems to imply that rather than "prompt engineering" remaining just like programming but at a higher level of abstraction, the application of language formality for precision, brevity, etc.…”

Section: Does Code Still Matter? Evaluating the Value Propositions Of...mentioning

confidence: 99%

“…There are also elements that impact usability but have little or no connection with the underlying model, such as the text in dialogue boxes and the placement of menu buttons, which are not of concern here 3. 2016 is the year that Deepmind's AlphaGo program[100] beat grandmaster Lee Sedol, though some scholars point as early as 2012, referring to the so-called "ImageNet moment" referring to the solution of the ImageNet challenge by deep convolutional networks[56], while others look as recently as 2018, referring to the BERT model which similarly swept natural language processing benchmarks and is referred to as "NLP's ImageNet moment"[24].…”

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confidence: 99%

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Will Code Remain a Relevant User Interface for End-User Programming with Generative AI Models?

Sarkar

2023

Proceedings of the 2023 ACM SIGPLAN International Symposium on New Ideas, New Paradigms, and Reflections on Programming and Sof

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The research field of end-user programming has largely been concerned with helping non-experts learn to code sufficiently well in order to achieve their tasks. Generative AI stands to obviate this entirely by allowing users to generate code from naturalistic language prompts. In this essay, we explore the extent to which "traditional" programming languages remain relevant for non-expert end-user programmers in a world with generative AI. We posit the "generative shift hypothesis": that generative AI will create qualitative and quantitative expansions in the traditional scope of enduser programming. We outline some reasons that traditional programming languages may still be relevant and useful for end-user programmers. We speculate whether each of these reasons might be fundamental and enduring, or whether they may disappear with further improvements and innovations in generative AI. Finally, we articulate a set of implications for end-user programming research, including the possibility of needing to revisit many well-established core concepts, such as Ko's learning barriers and Blackwell's attention investment model. CCS Concepts:• Human-centered computing → HCI theory, concepts and models; Natural language interfaces; • Computing methodologies → Natural language processing; Neural networks; • Social and professional topics → User characteristics.

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To Write Code: The Cultural Fabrication of Programming Notation and Practice

Cited by 16 publications

References 54 publications

Should Explanations of Program Code Use Audio, Text, or Both? A Replication Study

Should Explanations of Program Code Use Audio, Text, or Both? A Replication Study

Should Computers Be Easy To Use? Questioning the Doctrine of Simplicity in User Interface Design

Will Code Remain a Relevant User Interface for End-User Programming with Generative AI Models?

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