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pro vyhledávání: '"Piech, A."'
Teaching Computer Science (CS) by having students write programs by hand on paper has key pedagogical advantages: It allows focused learning and requires careful thinking compared to the use of Integrated Development Environments (IDEs) with intellig
Externí odkaz:
http://arxiv.org/abs/2408.07220
Publikováno v:
In Findings of the Association for Computational Linguistics (ACL 2024)
We study the problem of controlling the difficulty level of text generated by Large Language Models (LLMs) for contexts where end-users are not fully proficient, such as language learners. Using a novel framework, we evaluate the effectiveness of sev
Externí odkaz:
http://arxiv.org/abs/2406.03030
Autor:
Nie, Allen, Chandak, Yash, Suzara, Miroslav, Ali, Malika, Woodrow, Juliette, Peng, Matt, Sahami, Mehran, Brunskill, Emma, Piech, Chris
Large language models (LLMs) are quickly being adopted in a wide range of learning experiences, especially via ubiquitous and broadly accessible chat interfaces like ChatGPT and Copilot. This type of interface is readily available to students and tea
Externí odkaz:
http://arxiv.org/abs/2407.09975
Publikováno v:
In Proceedings of the 2024 Innovation and Technology in Computer Science Education (ITiCSE 2024)
One-on-one help from a teacher is highly impactful for students, yet extremely challenging to support in massive online courses (MOOCs). In this work, we present TeachNow: a novel system that lets volunteer teachers from anywhere in the world instant
Externí odkaz:
http://arxiv.org/abs/2404.11918
Publikováno v:
Proceedings of the 55th ACM Technical Symposium on Computer Science Education (SIGCSE); March 2024 (1442-1448)
Teaching students how to write code that is elegant, reusable, and comprehensible is a fundamental part of CS1 education. However, providing this "style feedback" in a timely manner has proven difficult to scale. In this paper, we present our experie
Externí odkaz:
http://arxiv.org/abs/2403.14986
Publikováno v:
Proceedings of the 55th ACM Technical Symposium on Computer Science Education (SIGCSE); March 2024 (785-791)
We propose and carry-out a novel method of formative assessment called Assessment via Teaching (AVT), in which learners demonstrate their understanding of CS1 topics by tutoring more novice students. AVT has powerful benefits over traditional forms o
Externí odkaz:
http://arxiv.org/abs/2403.14971
While the use of programming problems on exams is a common form of summative assessment in CS courses, grading such exam problems can be a difficult and inconsistent process. Through an analysis of historical grading patterns we show that inaccurate
Externí odkaz:
http://arxiv.org/abs/2403.14637
Dynamic Item Response Models extend the standard Item Response Theory (IRT) to capture temporal dynamics in learner ability. While these models have the potential to allow instructional systems to actively monitor the evolution of learner proficiency
Externí odkaz:
http://arxiv.org/abs/2311.08594
Autor:
Nie, Allen, Zhang, Yuhui, Amdekar, Atharva, Piech, Chris, Hashimoto, Tatsunori, Gerstenberg, Tobias
Human commonsense understanding of the physical and social world is organized around intuitive theories. These theories support making causal and moral judgments. When something bad happens, we naturally ask: who did what, and why? A rich literature
Externí odkaz:
http://arxiv.org/abs/2310.19677
Autor:
Tiwari, Mo, Kang, Ryan, Lee, Donghyun, Thrun, Sebastian, Piech, Chris, Shomorony, Ilan, Zhang, Martin Jinye
Clustering is a fundamental task in data science with wide-ranging applications. In $k$-medoids clustering, cluster centers must be actual datapoints and arbitrary distance metrics may be used; these features allow for greater interpretability of the
Externí odkaz:
http://arxiv.org/abs/2310.18844