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How related is skin to a quilt or door to worry? Here, we show that linguistic experience strongly informs people’s judgments of such word pairs. We asked Chinese-speakers, English-speakers, and Chinese-English bilinguals to rate semantic and visual similarity between pairs of Chinese words and of their English translation equivalents. Some pairs were unrelated, others were also unrelated but shared a radical (e.g., “expert” and “dolphin” share the radical meaning “pig”), others also shared a radical which invokes a metaphorical relationship. For example, a quilt covers the body like skin; understand, with a sun radical, invokes understanding as illumination. Importantly, the shared radicals are not part of the pronounced word form. Chinese speakers rated word pairs with metaphorical connections as more similar than other pairs. English speakers did not even though they were sensitive to shared radicals. Chinese-English bilinguals showed sensitivity to the metaphorical connections even when tested with English words. 

Large-scale educational settings have been common domains for affect detection and recognition research. Most research emphasizes improvements in the accuracy of affect measurement to enhance instructors’ efficiency in managing large numbers of students. However, these technologies are not designed from students’ perspectives, nor designed for students’ own usage. To identify the unique design considerations for affect sensors that consider student capacities and challenges, and explore the potential of affect sensors to support students’ self-learning, we conducted semi-structured interviews and surveys with both online students and on-campus students enrolled in large in-person classes. Drawing on these studies we: (a) propose using affect data to support students’ self-regulated learning behaviors through a “scaling for empowerment” design perspective, (b) identify design guidelines to mitigate students’ concerns regarding the use of affect data at scale, (c) provide design recommendations for the physical design of affect sensors for large educational settings.