| 摘要: | 同儕互評為一個廣泛被應用的評量機制，例如:書面作業、口頭報告等各種不同的項目，亦有著為數眾多的研究結果顯示同儕互評有著許多的優點，如增進學習表現及加強解決問題的能力等優點，卻未有太多研究利用同儕互評於DGBL上，然而，近年來DGBL的學習已經被廣泛應用在許多的教學現場，相當多的研究指出，DGBL可以幫助學習者學習，例如：提升學習成效、增加學習動機等，但因每一個人的背景、需求及學習偏好是不同的，所以尚未確定的是，所設計的DGBL是否能適用於每一個學習者，因此需要從人因的角度來研究，在人因方面，本研究著重於認知風格，因為認知風格會影響資訊處理以及資訊組織的方式，所以也可能主導著DGBL的設計與評量。
然而，現今缺少研究從認知風格的角度探討同儕互評對遊戲製作與評量之影響。為了填補這一空白，本研究著重於不同認知風格組合的設計差異，以及不同認知風格的評量者差異，為進行全面性的探討，本研究共有十個研究問題，即: 1. 在遊戲元素製作方面，認知風格之組合如何影響遊戲設計者的得分? 2.在遊戲元素製作方面，認知風格如何影響遊戲評分者的評分? 3.在遊戲元素製作方面，認知風格如何影響遊戲評分者對各認知風格組合的評分? 4.在遊戲介面提案方面，認知風格之組合如何影響遊戲設計者的得分? 5.在遊戲介面提案方面，認知風格如何影響遊戲評分者的評分、6.在遊戲介面提案方面，認知風格如何影響遊戲評分者對各認知風格組合的評分? 7.在遊戲介面製作方面，認知風格之組合如何影響遊戲設計者的得分? 8.在遊戲介面製作方面，認知風格如何影響遊戲評分者的評分? 9.在遊戲介面製作方面，認知風格如何影響遊戲評分者對各認知風格組合的評分? 10.認知風格之組合如何影響遊戲元素與遊戲介面製作上之相關性。
為了回答上述研究問題，本研究受測者將同時扮演設計者與評量者兩種角色，關於設計者部分，將依照認知風格，將設計組別分為場獨立&場獨立(FI&FI)、場獨立&場依賴(FI&FD)、場依賴&場依賴(FD&FD)等三組。關於評量者部分，將區分為場獨立學習者及場依賴學習者。不論是設計者或評量者，都需經歷三階段的實驗，第一階段著重在遊戲元素，而第二和第三階段著重在使用者介面的優化。更明確的說，第一階段的任務是小組成員需將遊戲性、新奇性、功能性等三個遊戲元素融入於所製作的遊戲式學習系統中，第二階段為小組成員需依據尼爾森準則， 提出優化使用者介面的提案，第三階段為需根據提案內容，製作適當的機制，以便使用者介面能符合尼爾森準則。
不論是哪一個階段，本研究的結果都包含得分部分與評分部分，在遊戲元素製作階段的得分上，FI&FI在遊戲性、新奇性、功能性，都顯著高於FI&FD，在評分上，FI&FI及FI&FD，在遊戲性、新奇性、功能性都呈現場獨立學習者評分高於場依賴學習者的情況。遊戲介面提案階段的得分上，H1-H10的項目中，都呈現FI&FI得分高於FD&FD，在評分上，FI&FI的組別，在H2、H3、H4、H5、H7、H8等項目，都呈現場獨立學習者的評分都高於場依賴學習者的結果，而在FD&FD的評分結果，則是場獨立學習者的評分在H1-H10都顯著高於場依賴學習者，遊戲介面製作時期的得分上，FI&FI於H3-H9都顯著高於FI&FD，在評分上， FI&FI在H2-H8的項目，場獨立學習者都顯著高於場依賴學習者，在對FD&FD的評分，場獨立學習者在H3、H4、H6、H7、H8等項目顯著高於場依賴學習者。
本研究有助於了解，在運用同儕互評，設計與評量DGBL的過程中，不同認知風格的設計組合，在遊戲元素及尼爾森準則的十個H上，所著重的項目亦會有所不同，在另一方面，不同認知風格的評分者，在遊戲元素及尼爾森準則的十個H上，亦會因認知風格的差異，而在不同的項目呈現出不同的結果，換句話說，認知風格扮演一個重要的角色。此結果將可提供後進者，於使用同儕互評的方式，對於不同認知風格，或是認知風格組合上參考的依據。
關鍵字：同儕互評、數位遊戲式學習、認知風格、尼爾森準則
;Peer assessment is a mechanism widely used for assessing students’ learning outcome, such as written assignments and oral reports. Some studies indicated that peer assessment brings many benefits to student learning, e.g., improving learning performance and strengthening the ability of problem solving. However, there is a lack of research to use peer assessment to support the design and evaluation of DGBL. On the other hand, DGBL is widespread in educational settings. A great amount of research indicated that DGBL can improve students’ learning outcomes, increase their learning motivation, etc. However, each individual has different background, needs and learning preferences so it is doubtful whether the design approaches used for the DGBL can be suitable to every learner. Thus, there is a need to consider human factors. Among various human factors, this study focuses on cognitive styles, which refer to the way of how learners process and organize information. Accordingly, cognitive styles may drive the design and evaluation of DGBL.
However, paucity of research examined the impacts of cognitive styles on the design and evaluation of DGBL of peer assessment. To fill this gap, this study examined the differences of design and evaluation among different cognitive style combinations. To achieve comprehensive understandings, this study addressed ten research questions, i.e., 1. How the combination of cognitive styles affects the scores that game designers obtain during the process of peer assessment, in terms of game elements? 2. How cognitive styles affects the scores that evaluators marks during the process of peer assessment, in terms of game elements? 3. How cognitive styles affects the scores that evaluators mark for each cognitive style combination, in terms of game elements? 4. How the combination of cognitive styles affects the scores that game designers obtain during the process of peer assessment, in terms of game proposals? 5. How cognitive styles affects the scores that evaluators marks during the process of peer assessment, in terms of game proposals? 6. How cognitive styles affect the scores that evaluators mark for each cognitive style combination, in terms of game proposals? 7. How the combination of cognitive styles affects the scores that game designers obtain during the process of peer assessment, in terms of game implementation? 8. How cognitive styles affects the score that evaluators mark during the process of peer assessment, in terms of game implementation? 9. How cognitive styles affect the scores that evaluators mark for each cognitive style combination, in terms of game implementation? 10. How the combination of cognitive styles affects the relationship between scores from game element and those from game interface design.
In order to answer the above questions, the subjects of this study play as both the roles of designers and evaluators. Regarding the role of designers, all members were divided into three groups according to their cogitative styles, i.e., field-independent & field- independent (FI&FI) 、field-independent & field-dependent (FI&FD) 、field-dependent & field- dependent (FD&FD). Regarding the role of evaluators, there are field-independent (FI) and field-dependent (FD) evaluators. All members should go through three stage of this experiment. Stage one focus on the implementation of game elements while stage two and stage three emphasize on the improvement of user interface. More specifically, all members need to incorporate three game element, i.e., playfulness、novelty and functionality, into game design in stage one. All member should make a proposal for improving uses interface based on Nielsen heuristics in stage two and then make implementation according to what they propose in stage three.
The result of this study include scores that designers obtain and those that evaluators marks at each stage. Regarding the implementation of game elements, the scores that FI&FI obtained are higher than those of FD&FD, regardless of playfulness, novelty or functionality. On the other hand, the scores that FI mark for FI&FI and FD&FD are higher than those from FD, regardless of playfulness, novelty or functionality. Regarding the stage of the proposal of game interface, the scores that, the scores that FI&FI obtained are higher than those of FD&FD, including H1-H10. On the other hand, the scores that FI mark for FI&FI are higher than those from FD, in terms of H2, H3, H4, H5, H7, H8. Furthermore, the scores that FI mark for FD&FD are higher than those of FD, including H1-H10. Regarding the stage of the implementation of game interface, the scores that FI&FI obtained are higher than those of FD&FD, including H3-H9. On the other hand, the scores that FI mark for FI&FI are higher than those from FD, including H2-H8. Furthermore, the scores that FI mark for FD&FD are higher than those of FD, in terms of H3, H4, H6, H7, H8.
The above results provide the understandings of how different cognitive style combinations react to game elements and Nielsen’s ten heuristics during the process of game design and evaluation. In addition, evaluators with different cognitive styles also mark differently, regardless of game elements or game interface. In other words, cognitive styles play a key role. Such results can provide guidance for future researchers so that they how to undertake peer assessment from a cognitive style perspective.
Keywords: peer assessment, Digital Game Base Learning cognitive styles, Nielsen Heuristic. |
