\textbf{Background and Context.} The importance of CS to 21st-century life and work has made it important to find ways to integrate learning CS and programming into the regular school day. However, learning CS is difficult, so teachers integrating programming need effective strategies to scaffold the learning. In this study, we analyze students’ log data and apply a novel technique to compare Parsons Problems with from-scratch programming in a middle school science class.

\textbf{Objectives.} Our research questions aimed to investigate whether, how, and when Parsons Problems improve learning efficiency for a programming exercise within science, utilizing log data analysis and an automated struggle and progress detector (SPD).

\textbf{Method.} We conducted a study on 199 students in a 6th-grade science course, divided into two groups: one engaged with Parsons problems, and the other, a control group, worked on the same programming task without scaffolding. Then, we analyzed differences in performance and coding characteristics between the groups. We also adopted an innovative application of a customized SPD to gain a better understanding of how and when Parsons problems helped students make more progress on the coding task, with an objective measure of final student grades.

\textbf{Findings.} The experimental group, with scaffolding through Parsons Problems, achieved significantly higher grades, spent significantly less time programming, and toggled less between block category tabs. Interestingly, they ran their code more frequently compared to the control group. The SPD analysis revealed that the experimental group made significantly higher progress in all four quartiles of their coding time.

\textbf{Implications.} Our findings suggest that Parsons Problems can improve learning efficiency by enhancing novices’ learning experience without negatively impacting their performance or grades, which is especially important when programming is integrated into K12 courses.