Towards More Empathic Programming Environments: An Experimental Empathic AI-Enhanced IDE
Justin Rainier Go, Kurt Christian Andaya, Roemer Gabriel Caliboso, Aaron Daniel Go, Jocelynn Cu

TL;DR
This study introduces Ceci, an empathic AI-enhanced IDE aimed at supporting novice programmers emotionally and educationally, and compares it with standard tools to evaluate its effectiveness.
Contribution
It presents a novel empathic IDE design and provides initial experimental evidence on its impact on novice programmers' perceived helpfulness and workload.
Findings
Ceci users reported significantly greater perceived helpfulness in error correction.
No significant difference in perceived effectiveness, learning, or workload between Ceci and control groups.
The study offers a foundational framework for future research on empathic programming environments.
Abstract
As generative AI becomes integral to software development, the risk of over-reliance and diminished critical thinking grows. This study introduces "Ceci," our Caring Empathic C IDE designed to support novice programmers by prioritizing learning and emotional support over direct code generation. The researchers conducted a comparative pilot study between Ceci and VSCode + ChatGPT [9, 40]. Participants completed a coding task and were evaluated using the NASA-TLX workload assessment and a post-test usability survey. Although the sample size was small (n = 11), results show that there is no significant difference in perceived effectiveness, learning and workload between the Experimental Ceci group and the Control group, though Ceci users reported significantly greater perceived helpfulness in error correction (p = 0.0220). These findings suggest that empathic responses may not be…
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