訓練ボードゲーム参加者のスキル評価における評価者判断を分析する機械学習モデル構築

カテゴリ: 論文誌(論文単位)

グループ名: 【C】電子・情報・システム部門

発行日: 2024/08/01

タイトル(英語): Building a Machine Learning Model to Analyze Evaluators’ Rating in Skill Assessment of Project Management Training Board Game Participants

著者名: 甲斐　賢（（株）日立製作所 研究開発グループ），内田　吉宣（（株）日立製作所 研究開発グループ），伊東　昌子（成城大学 経済研究所），岡田　久子（（株）日立ドキュメントソリューションズ）

著者名(英語): Satoshi Kai (Research & Development Group, Hitachi, Ltd.), Yoshinobu Uchida (Research & Development Group, Hitachi, Ltd.), Masako Itoh (The Institute for Economic Studies, Seijo University), Hisako Okada (Hitachi Document Solutions Co., Ltd.)

キーワード: プロジェクトマネージャ，訓練ボードゲーム，スキル評価，カッパ係数，決定木，説明変数　　project manager，training board game，skill rating，kappa coefficient，decision tree，explanatory variables

要約(英語): To cultivate top-tier project managers, we have created a board game specifically designed for project management training. Hundreds of participants have already benefited from this game, receiving valuable feedback on their practical skills. However, the current evaluation method relies heavily on seasoned facilitators. For more consistent and long-term participant development, we aimed to standardize the skill assessment process.Initially, we conducted a workshop with three veteran project managers and a psychology expert to identify the evaluation criteria and essential skill sets from a problem-solving perspective. We then used statistical methods to analyze rating inconsistencies attributed to the evaluator’s field of experience.As a next step, we developed a machine learning model to predict ratings from evaluators. This model uses data from a digital version of our training board game. By examining the decision tree within the model, we were able to identify the specific variables causing variations in the evaluators’ ratings.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.144 No.8 （2024） 特集Ⅰ：Smart Cityを支える高度な無線通信，センシング及び情報処理　特集Ⅱ：人と人とを繋ぐ情報・システム技術

本誌掲載ページ: 755-763 p

原稿種別: 論文／日本語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/144/8/144_755/_article/-char/ja/