Thematic Analysis of Self-Regulation Narratives in Textual Posts by Informal Programming Learners on Social Media
Year: 2024
Type: conference-paper
Abstract: Many people from diverse backgrounds are interested in learning programming independently and often share their experiences on social media platforms. Despite this, little is known about their specific self-regulation needs, which are crucial for achieving their learning goals. This study employed qualitative analyses to examine the textual narratives of individuals engaged in informal programming learning across four social media platforms: Twitter (X), YouTube comments, Reddit, and the DEV Community. The aim was to understand the self-regulation challenges they face in their informal, interestbased learning as articulated through their textual narratives and to pinpoint potential support mechanisms for self-regulation in this context. We extracted a purposive sample from these platforms, targeting posts rich in meaning or indicative of self-regulation, and then conducted a thematic analysis. Our findings indicate that learners require personal learning spaces that support three critical self-regulation aids: refining learning goals, resuming learning during spaced sessions, and supporting reflective practice throughout the learning process. Furthermore, we observed that informal learners generally lack specifically designed tools to support their self-regulation, relying instead on their varying skills and utilising diverse, non-specific tools. This gap unveils significant design opportunities to address the specific self-regulation needs of this underserved population of learners on social media. We discuss the potential of a storytelling-centric approach in design to address the identified issues for this population, which not only aids in sense-making from their learning experiences through reflection but also promotes social learning and engagement.
Institution: Newcastle University
Language: English
Subfield: Computer Science Applications
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W4403447889