DevEmo+: A Video Dataset of Spontaneous Facial Expressions of Students Solving Programming Tasks in the Wild

DevEmo+ - a dataset of facial expression recordings from students engaged in programming tasks. Collected "in-the-wild" from participants' personal computing environments, this dataset addresses the critical need for ecologically valid data to research student affective states during complex computer-based learning. The data was produced using a three-phase approach that integrates automatic emotion recognition, crowdsourcing for human based filtering, and a final selection stage by expert annotators to ensure high-quality labels. The final dataset contains 304 video clips from 51 participants, balanced between 152 emotional and 152 neutral expressions. A consensus protocol was applied, requiring agreement from at least two of three experts on both the emotion category and timing. The resulting annotations are dominated by cognitive states such as confusion (51.9%), happiness (22.4%), and surprise (16.4%), making the dataset particularly well-suited for investigating the cognitive-affective dynamics of problem-solving. The publicly available dataset includes detailed metadata to facilitate its use.