Design of a User Study to evaluate the effectiveness of a Software Security Module for Neurodivergent Students

In recent work, we developed an educational module for undergraduate computing students, to bring inclusivity and engagement into the advanced cybersecurity education topic of stack smashing attacks and defenses. Our module comprises four guided learning activities, and an active learning exercise that integrates a stack smashing attack visualization tool, DISSAV, developed in prior work. The module was deployed in an undergraduate cybersecurity course across multiple semesters, showing favorable results. In the current work, we outline a plan to evaluate the effectiveness of the module for an underrepresented, underserved community in computing-neurodivergent students, specifically, students with Autism Spectrum Disorder (ASD) or Attention Deficit Hyperactivity Disorder (ADHD). We plan to deploy our module to participants recruited from the AccessComputing group, a cohort of about 600 computing students and recent graduates across the US who have disabilities such as ADHD and ASD. We will evaluate the effectiveness of our stack smashing module in terms of learning, engagement, and accessibility for neurodivergent students through multi-pronged data collection and a mixed-methods analysis. We will use insights from the study to refine our module and to establish guidelines for future course modules and activities, to better serve neurodivergent students while continuing to serve all computing students.

Authors

Institutions

Publication Details

Published
2025-02-18
DOI
https://doi.org/10.1145/3641555.3705160
Primary Topic
Digital Mental Health Interventions
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Design of a User Study to evaluate the effectiveness of a Software Security Module for Neurodivergent Students

Harini Ramaprasad, Meera Sridhar, Soham Pradhan, Sushma Indrani Dangeti
Digital Mental Health Interventions
article

Design of a User Study to evaluate the effectiveness of a Software Security Module for Neurodivergent Students

Harini Ramaprasad, Meera Sridhar, Soham Pradhan, Sushma Indrani Dangeti
article en

Abstract

In recent work, we developed an educational module for undergraduate computing students, to bring inclusivity and engagement into the advanced cybersecurity education topic of stack smashing attacks and defenses. Our module comprises four guided learning activities, and an active learning exercise that integrates a stack smashing attack visualization tool, DISSAV, developed in prior work. The module was deployed in an undergraduate cybersecurity course across multiple semesters, showing favorable results. In the current work, we outline a plan to evaluate the effectiveness of the module for an underrepresented, underserved community in computing-neurodivergent students, specifically, students with Autism Spectrum Disorder (ASD) or Attention Deficit Hyperactivity Disorder (ADHD). We plan to deploy our module to participants recruited from the AccessComputing group, a cohort of about 600 computing students and recent graduates across the US who have disabilities such as ADHD and ASD. We will evaluate the effectiveness of our stack smashing module in terms of learning, engagement, and accessibility for neurodivergent students through multi-pronged data collection and a mixed-methods analysis. We will use insights from the study to refine our module and to establish guidelines for future course modules and activities, to better serve neurodivergent students while continuing to serve all computing students.

University of North Carolina at Charlotte (US)
Openalex Percentile: Top 97%
Digital Mental Health Interventions
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.