Novice programmers need to write basic code as part of the learning
process, but they often face difficulties. To assist struggling students,
we recently implemented personalized Parsons problems, which are
code puzzles where students arrange blocks of code to solve them, as
pop-up scaffolding. Students found them to be more engaging and
preferred them for learning, instead of simply receiving the correct
answer, such as the response they might get from generative AI
tools like ChatGPT. However, a drawback of using Parsons problems
as scaffolding is that students may be able to put the code blocks in
the correct order without fully understanding the rationale of the
correct solution. As a result, the learning benefits of scaffolding are
compromised. Can we improve the understanding of personalized
Parsons scaffolding by providing textual code explanations? In this
poster, we propose a design that incorporates multiple levels of
textual explanations for the Parsons problems. This design will be
used for future technical evaluations and classroom experiments.
These experiments will explore the effectiveness of adding textual
explanations to Parsons problems to improve instructional benefits.
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This content will become publicly available on October 23, 2024
XAI to Increase the Effectiveness of an Intelligent Pedagogical Agent.
We explore eXplainable AI (XAI) to enhance user experience and understand the value of explanations in AI-driven pedagogical decisions within an Intelligent Pedagogical Agent (IPA). Our real-time and personalized explanations cater to students' attitudes to promote learning. In our empirical study, we evaluate the effectiveness of personalized explanations by comparing three versions of the IPA: (1) personalized explanations and suggestions, (2) suggestions but no explanations, and (3) no suggestions. Our results show the IPA with personalized explanations significantly improves students' learning outcomes compared to the other versions.
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- Award ID(s):
- 2013502
- NSF-PAR ID:
- 10525825
- Publisher / Repository:
- ACM
- Date Published:
- Format(s):
- Medium: X
- Location:
- In Proceedings of the 23rd ACM International Conference on Intelligent Virtual Agents (IVA 2023)
- Sponsoring Org:
- National Science Foundation
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