Sami Sarsa

Sami Sarsa
Aalto University

About

19
Publications
1,013
Reads
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32
Citations
Citations since 2017
19 Research Items
32 Citations
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Publications

Publications (19)
Conference Paper
Full-text available
Recent breakthroughs in Large Language Models (LLMs), such as GPT-3 and Codex, now enable software developers to generate code based on a natural language prompt. Within computer science education, researchers are exploring the potential for LLMs to generate code explanations and programming assignments using carefully crafted prompts. These advanc...
Conference Paper
Full-text available
The introduction of Large Language Models (LLMs) has generated a significant amount of excitement both in industry and among researchers. Recently, tools that leverage LLMs have made their way into the classroom where they help students generate code and help instructors generate learning materials. There are likely many more uses of these tools --...
Conference Paper
Every year, millions of students learn how to write programs. Learning activities for beginners almost always include programming tasks that require a student to write a program to solve a particular problem. When learning how to solve such a task, many students need feedback on their previous actions, and hints on how to proceed. For tasks such as...
Preprint
Full-text available
Recent breakthroughs in Large Language Models (LLMs), such as GPT-3 and Codex, now enable software developers to generate code based on a natural language prompt. Within computer science education, researchers are exploring the potential for LLMs to generate code explanations and programming assignments using carefully crafted prompts. These advanc...
Preprint
Full-text available
In this article, we introduce and evaluate the concept of robosourcing for creating educational content. Robosourcing lies in the intersection of crowdsourcing and large language models, where instead of a crowd of humans, requests to large language models replace some of the work traditionally performed by the crowd. Robosourcing includes a human-...
Preprint
Full-text available
Advances in natural language processing have resulted in large language models (LLMs) that are capable of generating understandable and sensible written text. Recent versions of these models, such as OpenAI Codex and GPT-3, can generate code and code explanations. However, it is unclear whether and how students might engage with such explanations....
Preprint
A key part of learning to program is learning to understand programming error messages. They can be hard to interpret and identifying the cause of errors can be time-consuming. One factor in this challenge is that the messages are typically intended for an audience that already knows how to program, or even for programming environments that then us...
Article
New knowledge tracing models are continuously being proposed, even at a pace where state-of-theart models cannot be compared with each other at the time of publication. This leads to a situation where ranking models is hard, and the underlying reasons of the models’ performance – be it architectural choices, hyperparameter tuning, performance metri...
Conference Paper
Every year, millions of students learn how to write programs. Learning activities for beginners almost always include programming tasks that require a student to write a program to solve a particular problem. When learning how to solve such a task, many students need feedback on their previous actions, and hints on how to proceed. In the case of pr...
Preprint
This article explores the natural language generation capabilities of large language models with application to the production of two types of learning resources common in programming courses. Using OpenAI Codex as the large language model, we create programming exercises (including sample solutions and test cases) and code explanations, assessing...
Preprint
In this work, we review and evaluate a body of deep learning knowledge tracing (DLKT) models with openly available and widely-used data sets, and with a novel data set of students learning to program. The evaluated DLKT models have been reimplemented for assessing reproducibility and replicability of previously reported results. We test different i...
Chapter
Full-text available
Legislation and case law are widely published on the Web as documents for humans to read. In contrast, this paper argues for publishing legal documents as Linked Open Data (LOD) on top of which intelligent legal services for end users can be created in addition to just providing the documents for close reading. To test and demonstrate this idea, we...
Chapter
Full-text available
This paper presents an effective method for case law retrieval based on semantic document similarity and a web application for querying Finnish case law. The novelty of the work comes from the idea of using legal documents for automatic formulation of the query, including case law judgments, legal case descriptions, or other texts. The query docume...

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