Abstract


Recent studies show improvement of intellectual productivity brings great benefits, therefore the studies on office environment in order to improve an intellectual productivity have been actively conducted. However, there has been no established tool to measure the productivity quantitatively. Our laboratory has been developing a quantitative measurement method as a concentration time ratio (CTR) using the answering time data of receipt classification task as a task of uniformed difficulty. However, the answering time of the task includes time to turn over a paper receipt, which has little relation with cognitive activities, and the operation of the tasks has difficulties of preparing a huge number of paper receipts, and obtaining error rate of the answers. In this study, therefore, a new cognitive task has been proposed in a useful and more suitable style for measuring the intellectual productivity. The new task is named “comparing task” and it includes two kinds of tasks which give abstraction of office work or learning activity. One is a word comparison task which requires an ability of language recognition and the other is a number comparison task which requires that of numeral recognition. The comparing task was realized on iPad application so that it can be conducted easily. In addition, it can calculate error rate which has not been obtained by the conventional task. In order to assess the proposed task, two experiments were conducted. One experiment was to confirm that the task employs linguistic ability and numerical ability, cerebral blood flow was measured by NIRS when conducting the task. As the result, it shows activation of prefrontal area and Broca’s area. The other experiment was to confirm that the problems of the task has unformed difficulty enough to calculate CTR and to confirm that it has sensitivity to detect change of office environment. As the result, the calculated CTRs show the difference of environmental condition. In the future, it is necessary to conduct more experiments using the comparing task and shows its usefulness.

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(C) 2020 Hirotake Ishii