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平成31年度 春期 ITパスポート試験 問33

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問33
頻出度★☆☆

ポイント, バッジといったゲームの要素を駆使するゲーミフィケーションを導入する目的として, 最も適切なものはどれか。

出典 平成31年度 春期 ITパスポート試験 問33
解説

問 33

  • Incorrectア

    Deciding one's own strategy according to the opponent's strategy is an idea from game theory, which mathematically analyzes decisions involving conflicting interests. Although its name contains the word game, it is a different concept from gamification, which motivates people through game elements, and it is not a purpose of introducing gamification.

  • イ

    正解 Gamification is a method of incorporating game-specific elements and mechanisms — such as points, badges, rankings, and levels — into non-game activities (learning, work, sales promotion, health management, and so on). Its aim is to stimulate a sense of achievement, competitiveness, and reward in order to raise the motivation of customers or employees and to naturally encourage desirable behavior and goal achievement. Therefore, choice イ, which says to motivate customers or employees so that they can achieve their goals, is the most appropriate purpose for introducing it.

  • Incorrectウ

    Collecting users' evaluation information is an information-gathering activity such as surveys or review collection, and it is not the purpose of gamification itself. Gamification is not a method for handling collected information but a method for raising users' motivation, so this choice is wrong.

  • Incorrectエ

    Analyzing large volumes of data to discover useful facts and relationships is a description of data mining. It is an analytical technique for extracting insights from data, and it has nothing to do with the purpose of gamification, which motivates people through game elements.

ここがポイント
  • Gamification: a method that applies game elements such as points, badges, and rankings to non-game fields to raise users' motivation and encourage behavior and goal achievement.
  • Distinguishing confusable terms: do not confuse it with game theory (analysis of strategic decision-making) or data mining (discovering insights from large volumes of data).
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