  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.
