第五章、 結論與未來展望
第四節、 未來展望
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第四節、未來展望 一、遊戲的簡化與包裝
現階段《寶島建設》已具備基本娛樂性，也能透過競標等模式，學習掌握 需求與價格的關係。但在遊戲機制對部分受測者仍略顯複雜，受測者普遍為碩 士生的前提下，推測遊戲對普羅大衆具有一定難度。
若已證實遊戲機制的可行性，可將遊戲核心抽出，再行簡化。不一定以房 地產作為主題，或可結合當季時令蔬菜進行主題包裝，增添趣味性：遊戲機制 的可複製性讓遊戲易於包裝，為其優勢所在，結合不同主題則可提供不同的情 境，讓喜歡該主題的人更容易進行聯想，學習上也相對愉悅許多。
二、自動化教學與人工智慧
自動化教學對學習型遊戲非常重要。目前的《寶島建設》仍然仰賴研究者 進行解説，若透過自動化教學，除了能讓更多人有機會接觸遊戲，也能間接提 高採集數據量，進而從數據中提取能改進遊戲的建議方案。
目前市面上所有的數位遊戲都配有遊戲引導教學，而如《寶島建設》的數 位桌遊則需不同等級的人工智慧陪伴玩家進行遊戲，藉以幫助進入學習情境，
甚至可以設定不同難度關卡，並賦予不同挑戰。桌遊產業的前輩則認爲，數位 桌遊最好提供人工智慧陪玩，用以解決玩家找不到人陪玩的煩惱。
三、客製視覺化圖表
因應大數據的關係，越來越多人開始著手資訊視覺化研究。目前市面已有 不少資訊視覺化模組，但由於缺乏視覺與程式設計跨領域能力人才，目前仍門 檻不低。本研究所研發的數據分析系統仍以文字描述較複雜的數據運算結果。
文字描述的好處是簡單易懂，但分析花費時間長。若能客製資訊視覺化圖表，
則可以解決此問題。雖然視覺化的圖表若設計不好，容易增加認知負荷，但設 計得宜的視覺化圖表能讓人一目了然，縮短發現重點的時間。
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四、教學回饋與決策支援
透過本研究所建置的數據分析系統，能發現表現不達標準的受測者，也能 發現受測者表現不佳的原因，但距離真正幫助到教學者獲得有意義的教學回饋 與支援教學決策尚有一段很長的距離。
首先，數據分析系統必須在發現不達標準的受測者時，不透過人手的檢索 自動總結出表現不佳的原因，要達成這一點必須建立明確的學習指標，且這些 指標必須是能透過遊戲參數計算的；將不同的學習指標一一整理，再透過實驗 觀察受測者們的數據與真實反應，反复修正指標與參數計算公式，這一過程或 會非常漫長，畢竟學習障礙因人而異。
接著，必須思考結論應以怎樣的形式呈現，這也是本研究在未來展望裡強 調視覺化圖表的原因之一：如何能讓決策者一目了然地從圖表裡獲得結論？在 樣本量充足的情況下，近百人的資料該如何呈現？如何在展示總體表現時也顧 及個體的細節？如何呈現資料能有效地幫助教學者進行決策？這些都在設計數 據分析系統的視覺圖表時需要考慮的。
本研究認為深度學習透過大數據或能找到關鍵性的學習指標，且這兩門也 是 2017 年最熱門的學科之一，但就像先前所提，數據採集的樣本量增加時該如 何呈現數據的特性？這不僅僅是行為模式統計與運算的難題，當中的挑戰也包 含視覺設計、操作介面等。
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許育齡、陳聖智、許明潔（2011）。促發數位設計學生想像的心理因素及其影 響。教學科技與媒體，98，16-31。
許育齡、梁朝雲（2012）。探究想像力的意涵與特徵：探索性與驗證性因素分 析之發現。教育心理學報，44（2），349-374。
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（二）數位桌遊和桌遊數位化的市場定位 1. 您認爲桌遊產業是否需要數位桌遊？
2. 出版社或其他單位爲何會想要製作數位桌遊？
3. 您認爲數位桌遊玩家會和桌遊玩家會是同一群人嗎？
4. 您認爲數位桌遊會否帶給現今的桌遊產業衝擊？如桌遊專賣店業績降 低？
5. 請問您對數位桌遊的開發成本是否有概念嗎？
（三）數位桌遊的開發與設計
1. 過去您是否有玩過數位桌遊的經驗？請描述您的體驗經驗。
2. 數位遊戲有許多別於實體的機制，如：可持續更新，數據記錄，資訊隱 藏；您認為數位桌遊還可嘗試什麽有別於實體桌遊的新事物？
3. 數位遊戲有許多別於實體的呈現方式，如：動畫、特效、音樂、音效，
請問您認爲數位桌遊在呈現方式的導入這塊有什麼需要注意的？
4. 您認爲數位桌遊在介面設計上有什麼需要注意的？
4. 您認爲數位桌遊在介面設計上有什麼需要注意的？