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This article examines current empirical approaches to group learning. It focuses on two central questions: Are these approaches really measuring group learning, and what critical issues should be resolved in future group-learning research? The rationale for this examination is threefold. First, the last 10 years have seen a substantial increase in research on group learning. As this literature accumulates, it is useful to do a critical review of the connection between the concept of group learning and its operational form. Second, there is a lack of clarity in how learning is operationalized—how researchers capture whether learning has occurred. The third rationale is to make explicit some of the features of group learning to serve as a guide for future research.

This special issue of IEEE Software focuses on diversity and inclusion in software development, presenting research results and best practices for making the field equitable for all. It is well documented that the industry does not provide evenhanded participation conditions. Research has shown that implicit gender biases significantly impact hiring decisions, women disengage faster than men, Palestinian tech entrepreneurs do not have access to Internet-based distribution and payment platforms, software developers with a visual impairment lack tools to navigate code editors, and women are sometimes less likely to get their code accepted. Tools, processes, products, and education are not inclusive. Dimensions such as geography, gender, socioeconomic politics, age, ethnicity, and disability shape who can participate in creating technology.