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| 題名: | 從先備能力的角度探討數位遊戲式學習系統中不確定性機制對學習成效、遊戲成效、學習動機、好奇心及自我效能之影響－以日文擬聲擬態詞為例;Investigating the Effects of Uncertainty Mechanisms in a Digital Game-Based Learning System on Learning Performance, In-Game Performance, Learning Motivation, Curiosity, and Self-Efficacy from Prior Knowledge Perspective: A Case Study of Japanese Onomatopoei皆 |
| 作者: | 葉信甫;Yeh, Hsin-Fu |
| 貢獻者: | 網路學習科技研究所 |
| 關鍵詞: | 數位遊戲式學習;不確定性機制;先備能力;日語擬聲擬態詞學習成效;遊戲成效;學習動機;好奇心;自我效能;digital game-based learning;uncertainty mechanisms;prior knowledge;Japanese onomatopoeia learning performance;game performance;learning motivation;curiosity;self-efficacy |
| 日期: | 2025-07-30 |
| 上傳時間: | 2025-10-17 12:47:28 (UTC+8) |
| 出版者: | 國立中央大學 |
| 摘要: | 在全球數位化與跨文化交流日益頻繁的潮流下，學習各國語言已然成為現代人溝通與文化交流的基本需求。然而，傳統課堂仍以線性教材與標準化測驗為主，使學習者在重複背誦與測驗的迴圈中逐漸失去動機。為因應此挑戰，學習活動的設計應更能維持學習者的長期動機，並兼顧不同能力程度學習者的需求，使學習者樂於參與、有效學習。以日語學習中的擬聲擬態詞為例，這類高度情境性的詞彙因意象抽象、語境依存度高，對非母語學習者而言難以掌握，尤以先備能力較低者為甚。故需透過更具互動性與情境化的方式協助掌握其語意與使用時機。
過去研究指出，數位遊戲式學習（Digital Game-Based Learning, DGBL）透過沉浸式情節、互動任務與即時回饋，可有效提升學習動機、降低焦慮並促進語言習得。同時，研究也發現不同先備能力學習者在遊戲學習中的表現差異顯著，需針對其特性進行設計調整。其中，遊戲中的不確定性機制被視為驅動好奇與探索行為的關鍵元素。適度的不確定性不僅有助於誘發學習動機，更能提升注意力與參與度，進而增進學習成效。
儘管如此，過去文獻多偏重於單一不確定性形式之探討，對於可預期與不可預期兩類不確定性的學習影響，以及其與先備能力間之交互作用，尚缺乏系統性的實證研究。有鑑於此，本研究開發數位遊戲式學習系統「夢幻島語」，以日語擬聲擬態詞為核心學習內容，並在獎勵、關卡與事件中設計可預期與不可預期兩種不確定性版本，同時納入先備能力高低作為調節因子，探討不同不確定性機制對不同程度學習者之學習成效、遊戲表現、學習動機、好奇心及自我效能的影響。
本研究共招募 55 名大學生，依機制分為可預期組 29 人、不可預期組 26 人；依先備能力分為高先備能力組 28 人、低先備能力組 27 人。研究工具包含擬聲擬態詞學習成效測驗、學習動機量表、好奇心量表、自我效能量表及系統行為日誌之遊戲成效。實驗總長為 100 分鐘，學習系統內含 30 組擬聲擬態詞詞條，輔以音檔與 GIF (Graphics Interchange Format) 動畫，協助學習者熟悉詞義與語用情境，提升學習動機與效果。
本研究的實驗結果表明，在使用完日語擬聲擬態詞學習系統後，不同不確定性機制對學習者的影響，主要包含以下六點: (1)日語擬聲擬態詞之學習成效在不同不確定性機制的學習者在學習成效中皆有顯著的進步；(2)在遊戲成效中，不可預期組之學習者在學習類的平均學習時間顯著高於可預期組，其餘各項指標則均為可預期組顯著高於不可預期組；(3)在學習動機中，兩組學習者無顯著差異；(4)在好奇心中，兩組學習者無顯著差異；(5)在自我效能中，兩組學習者在自我效能中皆有顯著的進步；(6)相關性分析顯示，在兩組中好奇心、學習動機、自我效能彼此皆呈顯著正相關。然而，自我效能與學習動機僅在可預期組達顯著相關。可預期組中學習成效與遊戲成效之間的相關聯結較多，而不可預期組則在學習成效、自我效能與遊戲成效之間呈現較多關聯。在使用完日語擬聲擬態詞數位遊戲式學習系統後，不同不確定性機制對不同先備能力學習者的影響，主要包含五點: (1) 在各不確定性機制組內，高先備能力與低先備能力學習者的日語擬聲擬態詞學習成效皆顯著進步；(2) 在兩種不確定性機制下，低先備能力組學習者於遊戲成效的學習時間指標上明顯高於高先備能力組，而其餘指標則皆為高先備能力組優於低先備能力組；(3)在兩組不確定性機制中，不同先備能力對學習動機無顯著差異；(4)在兩組不確定性機制中，不同先備能力對好奇心中僅低先備能力在D型好奇心高於高先備能力呈顯著差異；(5)在兩組不確定性機制中，不同先備能力對自我效能無顯著差異。
本研究透過實證資料回應數位遊戲式學習中不確定性機制的設計問題，特別強調可預期與不可預期兩類不確定性對學習歷程的不同影響，並納入先備能力因素進行交互作用檢驗，發現高度隨機環境下高先備者學習優勢更明顯，反之在可預期環境下，學生間表現趨於平衡，為未來個別化教學設計提供實證依據。
總結而言，本研究橫跨遊戲設計、動機心理與語言學習三大領域，補足過去文獻中在不確定性類型比較與能力差異操作上的缺口，並提出具體教學應用建議，對日語擬聲擬態詞教學與遊戲化學習工具開發具參考價值。
;In an era of rapid digitalization and increasing intercultural exchange, learning foreign languages has become a fundamental necessity for modern communication and cultural interaction. However, traditional classroom settings continue to rely heavily on linear instructional materials and standardized testing, which often causes learners to lose motivation in the repetitive cycles of memorization and assessment. To address this challenge, learning activities should be designed to sustain long-term learner motivation while catering to learners with varying levels of ability, fostering both engagement and effective learning outcomes.
Taking Japanese language learning as an example, onomatopoeia and mimetic words (giongo/gitaigo) represent a highly context-dependent and abstract category of vocabulary, which poses significant difficulty for non-native learners, particularly those with lower prior knowledge. Therefore, more interactive and contextualized approaches are needed to help learners understand both the meaning and appropriate usage of these words.
Previous research has indicated that Digital Game-Based Learning (DGBL), through immersive storytelling, interactive tasks, and real-time feedback, can effectively enhance learning motivation, reduce anxiety, and promote language acquisition. It has also been found that learners with different levels of prior knowledge perform differently in game-based environments, underscoring the importance of adaptive design. Among game mechanics, uncertainty mechanisms have been identified as a key element in stimulating curiosity and exploratory behavior. Appropriate levels of uncertainty can trigger motivation, increase attention, and enhance engagement, ultimately leading to improved learning outcomes.
Nevertheless, prior studies have predominantly focused on a single type of uncertainty, lacking systematic investigation into how predictable and unpredictable forms of uncertainty affect learning, particularly in interaction with prior knowledge. To fill this gap, the present study developed a DGBL system called “Fantasy Island Language”, centered on Japanese mimetic vocabulary. The system incorporates two types of uncertainty—predictable and unpredictable—into its reward structure, level design, and random events. Furthermore, learner prior knowledge was introduced as a moderating factor to explore the effects of different uncertainty mechanisms on learning outcomes, game performance, motivation, curiosity, and self-efficacy across different learner profiles.
A total of 55 undergraduate students participated in the study. Participants were assigned to either the predictable (n = 29) or unpredictable (n = 26) condition. Based on a pretest, they were further divided into high prior knowledge (n = 28) and low prior knowledge (n = 27) groups. Research instruments included a vocabulary learning test on mimetic words, learning motivation scale, curiosity scale, self-efficacy scale, and system log data for game performance metrics. The experimental session lasted 100 minutes and included 30 Japanese mimetic expressions, supplemented with audio files and GIF animations to support vocabulary comprehension and contextual usage, aiming to enhance both motivation and effectiveness.
After using the Japanese mimetic word learning system, the experimental results of this study demonstrated six main findings regarding the effects of different uncertainty mechanisms on learners: (1) Learners under both predictable and unpredictable uncertainty conditions showed significant improvement in mimetic word learning performance; (2) In terms of game performance, learners in the unpredictable condition spent significantly more time on learning-related tasks, while all other indicators favored the predictable condition with significantly higher scores; (3) There was no significant difference in learning motivation between the two groups; (4) No significant difference was found in curiosity between the two groups; (5) Learners in both groups showed significant improvement in self-efficacy after using the system; (6) Correlation analysis indicated that curiosity, learning motivation, and self-efficacy were all significantly positively correlated within both groups. However, only in the predictable group was the correlation between self-efficacy and learning motivation statistically significant. The predictable group showed more linkages between learning performance and game performance, while the unpredictable group exhibited more associations among learning outcomes, self-efficacy, and gameplay behavior.
In addition, the effects of different uncertainty mechanisms on learners with different levels of prior knowledge were also examined, leading to five key findings: (1) Within both uncertainty conditions, learners with high and low prior knowledge significantly improved their mimetic word learning performance; (2) Under both uncertainty conditions, learners with low prior knowledge spent more time on learning-related game tasks, while learners with high prior knowledge outperformed in all other game performance indicators; (3) There was no significant difference in learning motivation across different levels of prior knowledge within either uncertainty condition; (4) Regarding curiosity, only deprivation-type curiosity was significantly higher among learners with low prior knowledge; (5) There was no significant difference in self-efficacy between high and low prior knowledge learners under either uncertainty condition.
This study responds to the lack of empirical research on the design and impact of different uncertainty mechanisms in DGBL. It specifically highlights the differential effects of predictable and unpredictable uncertainty and incorporates prior knowledge as a key variable in understanding these effects. Results suggest that learners with higher prior knowledge benefit more in highly unpredictable environments, whereas predictable conditions lead to more balanced performance across different learner levels. This provides an empirical foundation for future personalized instructional design.
In conclusion, this study spans three key domains: game design, motivational psychology, and language education. It addresses prior gaps in the literature by systematically comparing types of uncertainty and operationalizing learner ability differences. Practical teaching implications are offered, making this study a valuable reference for educators and developers working with Japanese mimetic words and gamified language learning tools. |
| 顯示於類別: | [網路學習科技研究所 ] 博碩士論文
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