Event Title

Understanding the Self Regulated Learning Struggles Programming Students Face

Co-Author(s)

Tyler Greer, Qiang Hao, Lu Ding

Research Mentor(s)

Hao, Qiang

Description

Effective self-regulated learning (SRL) is important to student academic success. Understanding what SRL struggles students face in programming assignments is critical to guide many efforts in computing education, such as designing scalable interventions and developing effective learning technologies. Prior studies on this topic contributed to understanding what SRL strategies CS students typically use in programming assignments, and the interventions for some SRL struggles such as procrastination. However, few studies have investigated student SRL struggles in programming systematically. To fill this gap, we investigate student SRL struggles in the context of CS2 through a case study. We used multiple approaches to collect real-time data and validate our findings, such as tracking student progress, identifying potential SRL struggles, and interviewing identified struggling students to confirm our identifications. This study contributes to a deeper understanding of what SRL struggles students face in programming at a fine-grained level, and provides guidance on interventions for SRL struggles.

Document Type

Event

Start Date

May 2020

End Date

May 2020

Department

Computer Science

Genre/Form

student projects, posters

Type

Image

Rights

Copying of this document in whole or in part is allowable only for scholarly purposes. It is understood, however, that any copying or publication of this document for commercial purposes, or for financial gain, shall not be allowed without the author’s written permission.

Language

English

Format

application/pdf

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May 18th, 9:00 AM May 22nd, 5:00 PM

Understanding the Self Regulated Learning Struggles Programming Students Face

Effective self-regulated learning (SRL) is important to student academic success. Understanding what SRL struggles students face in programming assignments is critical to guide many efforts in computing education, such as designing scalable interventions and developing effective learning technologies. Prior studies on this topic contributed to understanding what SRL strategies CS students typically use in programming assignments, and the interventions for some SRL struggles such as procrastination. However, few studies have investigated student SRL struggles in programming systematically. To fill this gap, we investigate student SRL struggles in the context of CS2 through a case study. We used multiple approaches to collect real-time data and validate our findings, such as tracking student progress, identifying potential SRL struggles, and interviewing identified struggling students to confirm our identifications. This study contributes to a deeper understanding of what SRL struggles students face in programming at a fine-grained level, and provides guidance on interventions for SRL struggles.