# Designing for Self-Regulation in Informal Programming Learning: Insights from a Storytelling-Centric Approach

arXiv: https://arxiv.org/abs/2507.22671 · HTML: https://mlsanity.com/paper/2507.22671/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 5 of its 89 references that are in the map.
- First posted on arXiv 30 Jul 2025.

## Builds on (most cited first, 5 of 5)

- [Self-Control in Cyberspace: Applying Dual Systems Theory to a Review of Digital Self-Control Tools](https://mlsanity.com/paper/1902.00157/) (2019)
- [Crystalline: Lowering the Cost for Developers to Collect and Organize Information for Decision Making](https://mlsanity.com/paper/2202.02175/) (2022)
- [Understanding How Programmers Can Use Annotations on Documentation](https://mlsanity.com/paper/2111.08684/) (2021)
- [An Exploratory Study of Live-Streamed Programming](https://mlsanity.com/paper/1907.05931/) (2019)
- [The Nudging Effect on Tracking Activity](https://mlsanity.com/paper/2209.00394/) (2022)

## Abstract (arXiv)

Many people learn programming independently from online resources and often report struggles in achieving their personal learning goals. Learners frequently describe their experiences as isolating and frustrating, challenged by abundant uncertainties, information overload, and distraction, compounded by limited guidance. At the same time, social media serves as a personal space where many engage in diverse self-regulation practices, including help-seeking, using external memory aids (e.g., self-notes), self-reflection, emotion regulation, and self-motivation. For instance, learners often mark achievements and set milestones through their posts. In response, we developed a system consisting of a web platform and browser extensions to support self-regulation online. The design aims to add learner-defined structure to otherwise unstructured experiences and bring meaning to curation and reflection activities by translating them into learning stories with AI-generated feedback. We position storytelling as an integrative approach to design that connects resource curation, reflective and sensemaking practice, and narrative practices learners already use across social platforms. We recruited 15 informal programming learners who are regular social media users to engage with the system in a self-paced manner; participation concluded upon submitting a learning story and survey. We used three quantitative scales and a qualitative survey to examine users' characteristics and perceptions of the system's support for their self-regulation. User feedback suggests the system's viability as a self-regulation aid. Learners particularly valued in-situ reflection, automated story feedback, and video annotation, while other features received mixed views. We highlight perceived benefits, friction points, and design opportunities for future AI-augmented self-regulation tools.