Learning programming is a multifaceted process shaped by diverse factors, including effectively utilizing self-regulation of learning (SRL) skills. However, students frequently require a certain level of support to effectively engage in SRL, prompting a question regarding the optimal means of providing such assistance. The current literature is limited in identifying which types of support are most effective, and it's also noted that some students do not benefit from its usage. The underlying causes remain underexplored, and a deeper understanding of this phenomenon can offer insights into improving the design of regulatory support. This research is situated within this scope and was guided by the following research questions: RQ1) How does the use of self-regulation of learning support differ among students with high and low-performance levels? RQ2) How do students use and evaluate the self-regulation of learning support? Fifty-four students enrolled in an online introductory programming course participated in this investigation. The findings indicate that higher-performance students made more extensive use of the provided regulatory support, implying the potential utilization of this resource as a learning aid. Simultaneously, it's noted that some students either avoided or utilized this support to a lesser extent, underscoring that the mere provision of resources is insufficient for their effective usage. A qualitative analysis revealed some factors that might have influenced this behavior.

Self-regulation of learning (SRL) is considered a vital skill in education, empowering students to control their learning process across multiple subjects. However, students often lack SRL abilities, which might impact their academic performance. One strategy to mitigate this problem is supporting students to assist their regulatory processes. Despite positive results in other subjects, how this support influences programming learning still needs further evidence. This study aims to contribute to this field by examining how the provision of SRL support influences students' programming performance and code development. The following research questions were established: RQ1) How does the programming performance of the group that received SRL support compare to that of the control group without support? RQ2) Do students receiving SRL support commit fewer programming errors than the control group without support? RQ3) Do students receiving SRL support maintain a more consistent learning routine than the control group without support? RQ4) What is the relationship between SRL abilities, programming performance, error commitment, and learning routine? To achieve this objective, a single-blind randomized experiment was conducted, and students were grouped into two experimental conditions, one receiving SRL support and a control group without support. Forty-nine students enrolled in an online introductory programming course participated in this study. The findings revealed that students who received SRL support achieved superior course grades, highlighting the benefit of this type of intervention. At the same time, the influence of SRL support and SRL abilities on programming error commitment is still unclear. Possibilities for future research to expand knowledge about the influence of SRL on code develonment are discussed.

This Research Full Paper presents a collection of evidences about the association between self-regulation variables and programming learning. Researchers have been investigating this thematic and despite the apparent benefits, it is necessary to summarize the published evidence and provide a new collection of them, which this study seeks to contribute. An observational investigation was performed in two countries with fifty-nine students, who had their SRL and programming learning metrics collected and correlated. Moreover, a systematic literature review was also conducted, and the existing evidence summarized. The results support an association between metacognitive and motivational regulatory strategies with programming learning but do not support for cognitive strategies. Our analysis shows a need for more studies to provide a solid body of knowledge on this thematic.

Programming students often show a reduced level of self-regulation of learning (SRL), which is known to impact their academic success. Interventions can be designed to assist in stimulating SRL, but achieving it is a challenging process for educational stakeholders. In this work, we propose a guideline that aims to support the construction of interventions to foster SRL competence in programming education. The guideline was built upon the collected evidence from a systematic literature review that identified features used to aid effective SRL interventions in the context of programming education. Fifteen studies were analyzed, and the results show the feasibility of several features to support programming learning and SRL development.

Social dimension plays a crucial role in the learning process. The use of technological resources to stimulate and mediate the interaction between students is known as Computer-supported collaborative learning (CSCL). Despite being widely used in programming education, the summarization of the academic literature about this topic is scarce. To create that body of knowledge, a systematic literature review was performed. The findings provide an understanding of how collaboration is explored in introductory programming, resources used to stimulate them and challenges in the process. Opportunities for future research are discussed, especially related to motivation, self-efficacy and engagement in CSCL, and the exploitation of learning analytics.

Students' ability to control and act upon their cognitive, behavioral, motivational, and metacognitive process is known as Self-regulation of learning (SRL). It has proved to be an effective strategy for academic programming success. However, the understanding of how programming students regulate their learning collaboratively deserves further investigation. The objective of this thesis is to study this process and use the findings to support the development and validation of a Computer-Supported Collaborative Learning (CSCL) environment grounded on the regulation of learning principles.