This perspective discusses two related problems in software engineering education that curriculum reform alone has not solved: persistent attrition in the early years and growing AI dependency among students who delegate judgment before developing the foundations needed to exercise it. Existing responses address content while giving little attention to the psychological conditions that also shape whether students can learn to engineer. Alfred Adler’s Individual Psychology provides a framework for understanding and redesigning those conditions. We draw on Adlerian concepts of inferiority and productive striving, fictional finalism, Gemeinschaftsgefühl (social interest), and lifestyle revision to derive four pedagogical principles for curriculum design, teaching practice, and assessment. These principles are especially relevant in the age of AI, where the central educational challenge is not learning to use powerful tools but developing the judgment required to evaluate and govern their outputs. The framework is illustrated through course design.
On June 30, 2022, the Apple App Store enforced a new policy requiring that apps that support account creation must also support user-initiated account deletion. The policy is intended to grant end-users control over their data. However, the influence of such a policy on the state of practice is yet to be explored. Understanding how platform policies shape the mobile app landscape is crucial for evaluating their effectiveness and improving practitioner compliance. To address this gap, we qualitatively analyze the account deletion option of 50 iOS apps. In addition, we interview 14 practitioners to gain insight into their perceptions of the policy. Our results show that apps often employ dark design patterns to deter users from deleting their accounts. The results also highlight practitioners? concerns about the clarity, effectiveness, and fairness of the policy. Based on our findings, we propose strategies to help improve the effectiveness of the policy and promote compliance.
We summarize findings from analyzing developers’ responses to a prompt regarding how AI-powered tools have impacted their recent development workflow. We identify four tensions that developers must balance in their use of AI and suggest strategies practitioners can use to improve developer experience with AI.
This article explores whether learning to code is still necessary in the age of AI. Drawing on survey responses, teaching experience, and personal reflection, it examines how AI coding assistants are changing software development, the skills future technologists will need, and the importance of maintaining technical understanding in an increasingly automated world.
