建構一個以基模為本的新聞專業知識支援系統

Constructing a Schema-based Journalistic Knowledge Support System for Novices

本研究以專家知識之認知基模為基礎，結合超文本、資料庫與網路科技，試圖建構一個新聞專業知識支援系統。本研究首先根據新聞採寫問題解決歷程的面向，觀察15位新聞系學生在實際製作一份報紙的問題解決歷程中所面臨的知識缺口；其次，我們據此深度訪談10位資深新聞工作者，捕捉其經驗、價值判定、人際互動、情境與策略等知識，並針對訪談內容進行知識分類及建立其關係架構。本研究繼而經由以下設計步驟完成系統的建構：（一）依知識架構將訪談內容分割歸類，以XML語言，標誌資訊內容與組織結構關係；（二）將標誌過的資訊單元及其層次架構關係儲存於資訊庫；以及（三）設計使用者檢索及資訊呈現介面，以連結後端資料庫。學習者在新聞採寫的問題解決歷程中，可透過此系統隨時取得專家知識與相關案例的支援，以促進有效學習。本研究期望為網路時代的新聞編採教育，提供可能的創新教學模式。

Based on a schema representation of expert knowledge, hypertext, and web technologies, this study aims to build a journalistic knowledge support system on the web.The study first observes for three days the entire problem-solving process of fifteen journalism students working on a daily newspaper and analyzes the knowledge needed. Second, we interview ten senior reporters (editors) who have been directly involved in reporting and editing. The interviewees were asked a set of questions referring to their problem-solving processes and experiences, including planning, information collecting, writing, and editing. The study then (1) decomposes the contents and builds the relationships based on the journalistic knowledge structure;(2) designs the system's internal converting mechanism using XML; and (3) devises a web-based interface. This system serves as an expandable knowledge repository for storing more experts' experiences and reporting cases in the future. The system also provides timely cognitive support by allowing novices to search and to access knowledge upon their needs and preferences.