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The meaning of words in natural language depends crucially on context. However, most neuroimaging studies of word meaning use isolated words and isolated sentences with little context. Because the brain may process natural language differently from how it processes simplified stimuli, there is a pressing need to determine whether prior results on word meaning generalize to natural language. fMRI was used to record human brain activity while four subjects (two female) read words in four conditions that vary in context: narratives, isolated sentences, blocks of semantically similar words, and isolated words. We then compared the signal-to-noise ratio (SNR) of evoked brain responses, and we used a voxelwise encoding modeling approach to compare the representation of semantic information across the four conditions. We find four consistent effects of varying context. First, stimuli with more context evoke brain responses with higher SNR across bilateral visual, temporal, parietal, and prefrontal cortices compared with stimuli with little context. Second, increasing context increases the representation of semantic information across bilateral temporal, parietal, and prefrontal cortices at the group level. In individual subjects, only natural language stimuli consistently evoke widespread representation of semantic information. Third, context affects voxel semantic tuning. Finally, models estimated using stimuli with little context do not generalize well to natural language. These results show that context has large effects on the quality of neuroimaging data and on the representation of meaning in the brain. Thus, neuroimaging studies that use stimuli with little context may not generalize well to the natural regime.SIGNIFICANCE STATEMENT Context is an important part of understanding the meaning of natural language, but most neuroimaging studies of meaning use isolated words and isolated sentences with little context. Here, we examined whether the results of neuroimaging studies that use out-of-context stimuli generalize to natural language. We find that increasing context improves the quality of neuro-imaging data and changes where and how semantic information is represented in the brain. These results suggest that findings from studies using out-of-context stimuli may not generalize to natural language used in daily life.

This study aimed to investigate how digital games affected college students’ creativity development. A sample of 60 college students participated in the digital game design and play instruction, grounded in the playful constructivism theory. The data incorporated the students’ pre- and post-creativity scores in game design, the first and final versions of game design, and the students’ responses to the open-ended questionnaire. The findings revealed that the students’ creativity was developed after digital game design and play instruction, facilitated by three key creative learning processes, including collaborative digital game design, digital game-playing for providing peer feedback, and redesign of the games after receiving peer feedback. These collaborative processes encouraged the students’ role-reversal between designers and players, enabling the students to provide and receive peer feedback for the exchange of creative ideas. Through reflecting on received peer feedback, the students refined their initial ideas and tailored their reflections to redesign the games for the target learners, thereby cultivating their creativity in educational digital game design. This study suggests collaborative digital game design and play instruction is an effective strategy to facilitate college students’ creativity development. [ABSTRACT FROM AUTHOR]