In the rapidly advancing technological landscape, acquiring programming skills has become increasingly essential, especially for students. The demand for data-driven approaches and interdisciplinary collaboration highlights the importance of developing computational thinking skills like programming. To address this challenge, this thesis aims to explore the effectiveness of reflective learning in the acquisition of programming skills. Taking inspiration from the existing frameworks and the integration of reflective prompts within some of these frameworks, we created a new jsPsych plugin that could facilitate teaching computational thinking skills, such as programming. We illustrated the utility of this plugin with an experiment (N=13) in which we devised a series of questions that prompted people to reflect on their choices based on feedback (considering past behavior) and feedforward (anticipating future behavior) prompting mechanisms. We tested participants’ task execution capabilities with a grid-based programming challenge. Each participant underwent 20 instances of the programming challenge, categorized into five blocks with varying complexity. Participants were prompted once inside each block. We found that both feedforward and feedback prompts help in programming task execution. Thus, providing a solid mechanism for learning computational thinking skills. Our results indicate that the feedback group performed better than the feedforward group in terms of using programming constructs, such as loops and while statements. We also found that participants who reflected on their choices performed better than those who did not. This indicated the importance of reflective learning in acquiring computational thinking skills in the game-based learning context of self-regulated learning.