@techreport{oai:ipsj.ixsq.nii.ac.jp:00078812,
 author = {野間, 慶子 and 小川, 賀代 and Keiko, Noma and Kayo, Ogawa},
 issue = {1},
 month = {Nov},
 note = {ｅ ラーニング学習では，学習履歴データの取得が容易である事から，近年では取得した学習履歴データを解析し，学習支援の活用に向けた研究が盛んである．しかし，LMS から取得できる履歴データは，学習者の行動パターンを推定することはできるが，問題に対する集中度合いや，行き詰まりなど個人の学習状況の把握は難しい．そこで，集中力や眠気によって変化する事が知られている瞳孔反応を利用し，これまでの学習履歴データと併せることで，より的確な学習支援が行えると期待できる．しかしながら，瞳孔反応は，集中力だけでなく，外界の光量の影響を受けることが知られている．そこで，本稿では，光量の影響を受けない環境条件を整備し，瞳孔反応と集中力の関係を調べ，学習状況のパターン化の検討を行った．その結果，計算時における 4 つの学習状況におけるパターンを見出し，行き詰まり判定の可能性を得た．, Many studies have been conducted recently to analyze the historical learning data to utilize for study supports, as it is easy to obtain such data through e-learning. Yet, the historical data from LMS can help assume the learners' behavioral pattern, yet it is difficult to grasp individual learning context, e.g. concentration on tasks and the impasse. Thus, it is expected to provide more accurate study supports by combining the pupillary response, which is known to change with concentration and drowsiness, and the historical learning data to date. However, it is also known that the papillary response is affected not only by the concentration but also by the external light volume. Thus, here we investigate the patterning of learning contexts, by establishing the environment which is not affected by the light volume, and investigating the relationship between the pupillary response and the concentration. As a result, we have discovered the specific patterns in four learning contexts of calculation, and saw the possibility to determine the impasse.},
 title = {学習支援システムに向けた計算時における瞳孔反応のパターン化},
 year = {2011}
}