Teaching Programming in the Age of Generative AI: Insights from Literature, Pedagogical Proposals, and Student Perspectives
- URL: http://arxiv.org/abs/2507.00108v1
- Date: Mon, 30 Jun 2025 17:38:27 GMT
- Title: Teaching Programming in the Age of Generative AI: Insights from Literature, Pedagogical Proposals, and Student Perspectives
- Authors: Clemente Rubio-Manzano, Jazna Meza, Rodolfo Fernandez-Santibanez, Christian Vidal-Castro,
- Abstract summary: This article aims to review the most relevant studies on how programming content should be taught, learned, and assessed.<n>It proposes enriching teaching and learning methodologies by focusing on code comprehension and execution.<n>It advocates for the use of visual representations of code and visual simulations of its execution as effective tools for teaching, learning, and assessing programming.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Computer programming is undergoing a true transformation driven by powerful new tools for automatic source code generation based on large language models. This transformation is also manifesting in introductory programming courses at universities around the world, generating an in-depth debate about how programming content should be taught, learned, and assessed in the context of generative artificial intelligence. This article aims, on the one hand, to review the most relevant studies on this issue, highlighting the advantages and disadvantages identified in the specialized literature. On the other hand, it proposes enriching teaching and learning methodologies by focusing on code comprehension and execution rather than on mere coding or program functionality. In particular, it advocates for the use of visual representations of code and visual simulations of its execution as effective tools for teaching, learning, and assessing programming, thus fostering a deeper understanding among students. Finally, the opinions of students who took the object-oriented programming course are presented to provide preliminary context supporting the incorporation of visual simulations in Java (or other languages) as part of the training process.
Related papers
- CoderAgent: Simulating Student Behavior for Personalized Programming Learning with Large Language Models [34.62411261398559]
We propose a LLM-based agent, CoderAgent, to simulate students' programming processes in a fine-grained manner without relying on real data.<n>Specifically, we equip each human learner with an intelligent agent, the core of which lies in capturing the cognitive states of the human programming practice process.
arXiv Detail & Related papers (2025-05-27T02:43:38Z) - Charting a Path to Efficient Onboarding: The Role of Software
Visualization [49.1574468325115]
The present study aims to explore the familiarity of managers, leaders, and developers with software visualization tools.
This approach incorporated quantitative and qualitative analyses of data collected from practitioners using questionnaires and semi-structured interviews.
arXiv Detail & Related papers (2024-01-17T21:30:45Z) - Combatting Human Trafficking in the Cyberspace: A Natural Language
Processing-Based Methodology to Analyze the Language in Online Advertisements [55.2480439325792]
This project tackles the pressing issue of human trafficking in online C2C marketplaces through advanced Natural Language Processing (NLP) techniques.
We introduce a novel methodology for generating pseudo-labeled datasets with minimal supervision, serving as a rich resource for training state-of-the-art NLP models.
A key contribution is the implementation of an interpretability framework using Integrated Gradients, providing explainable insights crucial for law enforcement.
arXiv Detail & Related papers (2023-11-22T02:45:01Z) - Thinking beyond chatbots' threat to education: Visualizations to
elucidate the writing and coding process [0.0]
The landscape of educational practices for teaching and learning languages has been predominantly centered around outcome-driven approaches.
The recent accessibility of large language models has thoroughly disrupted these approaches.
This work presents a new set of visualization tools to summarize the inherent and taught capabilities of a learner's writing or programming process.
arXiv Detail & Related papers (2023-04-25T22:11:29Z) - Language-Driven Representation Learning for Robotics [115.93273609767145]
Recent work in visual representation learning for robotics demonstrates the viability of learning from large video datasets of humans performing everyday tasks.
We introduce a framework for language-driven representation learning from human videos and captions.
We find that Voltron's language-driven learning outperform the prior-of-the-art, especially on targeted problems requiring higher-level control.
arXiv Detail & Related papers (2023-02-24T17:29:31Z) - Automatic Generation of Programming Exercises and Code Explanations with
Large Language Models [4.947560475228859]
OpenAI Codex is a recent large language model from the GPT-3 family for translating code into natural language.
We explore the natural language generation capabilities of Codex in two different phases of the life of a programming exercise.
We find the majority of this automatically generated content both novel and sensible, and in many cases ready to use as is.
arXiv Detail & Related papers (2022-06-03T11:00:43Z) - K-LITE: Learning Transferable Visual Models with External Knowledge [242.3887854728843]
K-LITE (Knowledge-augmented Language-Image Training and Evaluation) is a strategy to leverage external knowledge to build transferable visual systems.
In training, it enriches entities in natural language with WordNet and Wiktionary knowledge.
In evaluation, the natural language is also augmented with external knowledge and then used to reference learned visual concepts.
arXiv Detail & Related papers (2022-04-20T04:47:01Z) - Cria\c{c}\~ao e aplica\c{c}\~ao de ferramenta para auxiliar no ensino de
algoritmos e programa\c{c}\~ao de computadores [0.0]
This work aims to report the development of a teaching tool developed during the monitoring program of the Algorithm and Computer Programming discipline of the University of Fortaleza.
The tool combines the knowledge acquired in the books, with a language closer to the students, using video lessons and exercises proposed, with all the content available on the internet.
arXiv Detail & Related papers (2022-03-31T09:48:49Z) - ProTo: Program-Guided Transformer for Program-Guided Tasks [59.34258016795216]
We formulate program-guided tasks which require learning to execute a given program on the observed task specification.
We propose the Program-guided Transformer (ProTo), which integrates both semantic and structural guidance of a program.
ProTo executes a program in a learned latent space and enjoys stronger representation ability than previous neural-symbolic approaches.
arXiv Detail & Related papers (2021-10-02T13:46:32Z) - Broader terms curriculum mapping: Using natural language processing and
visual-supported communication to create representative program planning
experiences [62.997667081978825]
Communication difficulties between faculty and non-faculty groups leave unexplored an immense collaboration potential.
This paper presents a method to deliver program plan representations that are universal, self-explanatory, and empowering.
arXiv Detail & Related papers (2021-02-09T13:27:04Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.