研究生: |
翁睿昕 Wong, Jui-Hsin |
---|---|
論文名稱: |
高低成就者於文字型數位卡牌遊戲之眼動差異 Differences of Eye-Movements between High-and Low-Achievers in Text-based Digital Card Games |
指導教授: |
陳志洪
Chen, Zhi-Hong |
口試委員: |
李良一
Li, Liang-Yi 鄭年亨 Cheng, Nien-Heng 陳志洪 Chen, Zhi-Hong |
口試日期: | 2022/07/08 |
學位類別: |
碩士 Master |
系所名稱: |
資訊教育研究所 Graduate Institute of Information and Computer Education |
論文出版年: | 2022 |
畢業學年度: | 110 |
語文別: | 中文 |
論文頁數: | 62 |
中文關鍵詞: | 數位卡牌教育遊戲 、遊戲式學習 、眼動歷程 |
英文關鍵詞: | Digital Card Game, Game-based Learning, Eye Movement |
研究方法: | 準實驗設計法 |
DOI URL: | http://doi.org/10.6345/NTNU202200930 |
論文種類: | 學術論文 |
相關次數: | 點閱:136 下載:6 |
分享至: |
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報 |
資訊科技融入教學是學習新趨勢,尤其是數位遊戲式學習,把枯燥艱澀知識內容以遊戲方式呈現,讓學習者能得到即時反饋,建立學習脈絡,提高學習者的學習動機和學習成效。然而過往研究是以訪談、問卷等方式理解學習者在遊戲中的認知歷程,容易受到主觀意識或記憶偏誤影響結果,缺乏客觀工具紀錄學習認知行為,因此加入眼動儀偵測學習者觀看歷程,輔以訪談解說,能更清楚了解學習者的認知歷程與策略。
本研究旨在以數位卡牌遊戲輔助借景抒情文寫作,藉由數位卡牌遊戲的判斷、組織及寫作三個版本,結合判斷主題、理解結構及編排挑戰,並以眼動儀蒐集眼動凝視數據及熱像圖,理解學習者的認知歷程與注意力分佈,進一步評估高低成就者的組織策略差異。研究問題為:(1)高低成就者於數位卡牌遊戲閱讀注意焦點有何差異;(2)高低成就者於數位卡牌遊戲組織策略有何差異。研究分為前導實驗和正式實驗,研究對象分別為前導實驗40位大專生和正式實驗30位新北市某所國中學生作為施測對象,參與45分鐘的數位卡牌遊戲實驗,在整個過程中由眼動儀收集眼動資料,再由SPSS和序列分析探討高低成就者認知歷程及組織策略差異。
研究成果顯示,(1)高低成就者注意焦點有顯著差異,高成就者在編排文章時注意焦點在前後文之間的關聯,以及其對應關鍵字。低成就者在編排文章時注意焦點在文章中關鍵字。(2)高低成就者組織策略有顯著差異,高成就者在組織文章時其序列分析注重在符合主題的景物特點描寫,低成就者在組織文章其序列分析,注重在主題情感共鳴文字撰寫。
The integration of information technology into teaching is a new trend in learning, especially digital game-based learning. The learning content, which might be difficult and boring, is presented in the form of games so that learners can get instant feedback, establish a learning context, and improve learners learning motivation and learning effectiveness. However, previous studies have used interviews, questionnaires, and other methods to understand the cognitive process of learners in games, which are easily affected by subjective consciousness or memory bias, and a lack of objective tools to record learning cognitive behaviors. As eye trackers can be used to detect learners' viewing process, supplemented by interviews and explanations, can understand the cognitive process and learners’ strategies more clearly.
To evaluate the cognitive process of high and low achievers and the influence of the learning of digital games, this study aims to use digital card games to assist in the writing of lyrical essays based on scenes. Users have to distinguish the themes, understand the structure and challenges of arrangements. Simultaneously, eye gaze data and thermal images are collected with eye-trackers to reveal the cognitive process and attention distribution of learners, and further discuss the differences in organizational strategies of high and low achievers. The research questions are as follows: (1) What are the differences in the reading focus between high and low achievers in digital card games; (2) What are the differences in organizational strategies between high and low achievers in digital card games. The research is divided into a pilot experiment and a formal experiment. The research objects are respectively 40 college students and 30 middle school students in New Taipei. They all participated in a 45-minute digital card game experiment. During the whole process, eye movement data were collected by an eye tracker. Further analysis of SPSS and sequence analysis are to explore the cognitive process and organizational differences between high and low achievers.
The research results show that (1) there are significant differences in the focus of attention between high and low achievers. High achievers pay attention to the relationship between the context and the corresponding keywords when arranging articles. Low achievers only pay attention to the keywords in the article when arranging the article. (2) There are significant differences in the organizational strategies of high and low achievers. For high achievers, when organizing articles, their eye movement sequence show that they focus on the description of scene characteristics that fit the theme, while low achievers organize article sequence analysis and focus on writing texts that resonate with the theme.
吳昭容(2019)。眼球追蹤技術在幾何教育的應用與限制。臺灣數學教育期刊,6(2),1-25。
林宥宇(2016)。開發一適用於眼動儀實驗室之學習平台。未出版碩士論文。
邱淑惠、廖儷湘(2014)。學前幼兒如何閱讀繪本---眼動歷程之初探。教育傳播與科技研究,(109),57-73.
賴孟龍、陳彥樺(2012)。以眼動方法探究幼兒閱讀繪本時的注意力偏好。幼兒教保研究期刊,(8),81-96
詹明峰(2011)。如何運用遊戲來促進學習典範轉移。前瞻科技與管理,1(1),47-60。
張仙峰、葉文玲(2006)。當前閱讀研究中眼動指標述評。心理與行為研究,3(4),236-240。
呂必松 (2005)。 語言教育與對外漢語教學,外語教學與研究。
蔡福興、游光昭、蕭顯勝(2008)。從新學習遷移觀點發掘數位遊戲式學習之價值。課程與教學季刊,11(4),237-278。
韓玉昌(2000)。眼動儀和眼動實驗法的發展歷程,心理科學,23(4),454-457。
李漢偉(1995)。國小語文科教學探索,麗文。
杜淑貞(1986)。國小作文教學探究,文津。
Alemdag, E., & Cagiltay, K. (2018). A systematic review of eye tracking research on multimedia learning. Computers & Education, 125, 413-428.
Abdi, A., & Cavus, N. (2019). Developing an electronic device to teach English as a foreign language: Educational toy for pre-kindergarten children. International Journal of Emerging Technologies in Learning, 14(22), 29-44.
Becker, K. (2007). Digital game‐based learning once removed: Teaching teachers. British Journal of Educational Technology, 38(3), 478-488.
Bakeman, R. (1986). Observing interaction: an introduction to sequential analysis. Cambridge; New York: Cambridge University Press.
Boonpotjanawetchakit, P., Kaweerat, K., & Vittayakorn, S. (2020). Elemem: Interactive digital card game for chemistry. IEEE Global Engineering Education Conference, 344-348.
Buswell, G. T. (1935). How people look at pictures: a study of the psychology and perception in art. Univ. Chicago Press.
Crawford, C. (1982). The art of computer game design. Up To Date. Retrieved March 15, 2016, from
http://www.rohan.sdsu.edu/~stewart/cs583/ACGD_ArtComputerGameDesign_ChrisCrawford_1982.pdf.
Cloude, E. B., Taub, M., Lester, J., & Azevedo, R. (2019). The role of achievement goal orientation on metacognitive process use in game-based learning. In International Conference on Artificial Intelligence in Education, 36-40.
Chen, P. G., Liu, E. Z. F., Lin, C. H., Chang, W. L., Hsin, T. H., & Shih, R. C. (2012). Developing an education card game for science learning in primary education. In 2012 IEEE Fourth International Conference on Digital Game and Intelligent Toy Enhanced Learning (pp. 236-240). IEEE.
Chiou, G. L., Hsu, C. Y., & Tsai, M. J. (2022). Exploring how students interact with guidance in a physics simulation: Evidence from eye-movement and log data analyses. Interactive Learning Environments, 30(3), 484-497.
Emerson, A., Cloude, E. B., Azevedo, R., & Lester, J. (2020). Multimodal learning analytics for game‐based learning. British Journal of Educational Technology, 51(5), 1505-1526.
Gielis, K., Abeele, M. E. V., Verbert, K., Tournoy, J., De Vos, M., & Abeele, V. V. (2021). Detecting mild cognitive impairment via digital biomarkers of cognitive performance found in klondike solitaire: a machine-learning study. Digital Biomarkers, 5(1), 44-52.
Gosper, M., & McNeill, M. (2012). Implementing game-based learning: The MAPLET framework as a guide to learner-centred design and assessment. In D. Ifenthaler, D. Eseryel, & X. Ge (Eds.), Assessment in game-based Learning: Foundations, innovations and practices (pp. 217-233). NY: Springer.
Gousiou A. and Kordaki M. (2015). On the development of constructivist educational computer card games: the CLASS-Platform. In Robin Munkvold and Line Kolås
(Eds.)Proceedings of the 9th European Conference on Games Based Learning, (ECGBL' 15), Nord-Trondelag University College Steinkjer, Norway, 8-9, 210-218.
Hogle, J. G. (1996). Considering games as cognitive tools: In search of effective" edutainment.". Retrieved from ERIC database. (ED425737)
Hsu, C. Y., Chiou, G. L., & Tsai, M. J. (2019). Visual behavior and self-efficacy of game playing: An eye movement analysis. Interactive Learning Environments, 27(7), 942-952.
Just, M. A., & Carpenter, P. A. (1976). Eye Fixations and cognitive processes, Cognitive Psychology, 8, 441-480.
K. Panetta, Q. Wan, A. Kaszowska, H. A. Taylor and S. Agaian, (2019). Software Architecture for Automating Cognitive Science Eye-Tracking Data Analysis and Object Annotation. IEEE Transactions on Human-Machine Systems, 49(3), 268-277.
Kothari, R., Yang, Z., Kanan, C., Bailey, R., Pelz, J. B., & Diaz, G. J. (2020). Gaze-in-wild: A dataset for studying eye and head coordination in everyday activities. 10(1), 1-18
Klonari, A., & Gousiou, A. (2014). Encouraging Teachers' Reflection using a card game: The Game of Consequences. In Ing. Busch (Ed.), Proceedings of 8th european conference on games-based learning (14), (pp. 279-285). Academic Conferences International Limited.
Maria, K. & Anthi, G. (2017). Digital card games in education: A ten year systematic review, Computers & Education, doi: 10.1016/j.compedu.2017.02.011
Mavridis, A., & Tsiatsos, T. (2017). Game-based assessment: investigating the impact on test anxiety and exam performance. Journal of Computer Assisted Learning, 33(2), 137-151
M. T. Cheng, J. H. Chen, S. J. Chu, and S. Y. Chen. (2015) The use of serious games in science education: A review of selected empirical research from 2002 to 2013. J. Comput. Edu., 2(3),353–375.
M. H. Hussein, S. H. Ow, L. S. Cheong, M. Thong and N. Ale Ebrahim. (2019). Effects of Digital Game-Based Learning on Elementary Science Learning: A Systematic Review. IEEE, 7, 62465-62478.
Nizam, D. N. M., & Law, E. L. C. (2021). Derivation of young children's interaction strategies with digital educational games from gaze sequences analysis. International Journal of Human-Computer Studies, 146, 102558.
O. Dele Ajayi, R. Strachan, A. J. Pickard and J. J. Sanderson. (2019). Games for Teaching Mathematics in Nigeria: What Happens to Pupils’ Engagement and Traditional Classroom Dynamics. IEEE, 7, 53248-53261.
Olsen, J. K., Ozgur, A. G., Sharma, K., & Johal, W. (2022). Leveraging eye tracking to understand children’s attention during game-based, tangible robotics activities. International Journal of Child-Computer Interaction, 31, 100447.
Prensky, M. (2001). Digital game-based learning. New York:McGraw-Hill.
Rajashekar, R. K., & Bellad, A. (2016). The effectiveness of educational card games as a supplementary educational tool in academic performance. Indian Journal of Clinical Anatomy and Physiology, 3(1), 4-7.
Rayner, K. (1998). Eye movements in reading and information processing: 20 years of research. Psychological Bulletin, 124(3), 372–422.
Shaltout, E. H., Afifi, A., & Amin, K. M. (2020). Augmented Reality Based Learning Environment for Children with Special Needs. International Conference on Computer Engineering and Systems, 15, 1-7.
Su, T., Cheng, M. T., & Lin, S. H. (2014). Investigating the effectiveness of an educational card game for learning how human immunology is regulated. CBE-Life Sciences Education, 13(3), 504-515.
Taub, M., Mudrick, N. V., Azevedo, R., Millar, G. C., Rowe, J., & Lester, J. (2017). Using multi-channel data with multi-level modeling to assess in-game performance during gameplay with Crystal Island. Computers in Human Behavior, 76, 641–655.
Tsai, M. J., Huang, L. J., Hou, H. T., Hsu, C. Y., & Chiou, G. L. (2016). Visual behavior, flow and achievement in game-based learning. Computers & Education, 98, 115-129.
Tsai, M. J., Wu, A. H., & Wang, C. Y. (2022). Pre-training and cueing effects on students’ visual behavior and task outcomes in game-based learning. Computers in Human Behavior Reports, 6, 100188.
Lévêque, L., Bosmans, H., Cockmartin, L., & Liu, H. J. I. A. (2018). State of the art: Eye-tracking studies in medical imaging, 6, 37023-37034.
Liu, C. C., Cheng, Y. B., & Huang, C. W. (2011). The effect of simulation games on the learning of computational problem solving. Computers & Education, 57(3), 1907-1918.
Lo, A. (2000). The game of leaves: An inquiry into the origin of chinese playing cards. Bulletin of the School of Oriental and African Studies, 63(03), 389e406.
Wang, J., Stebbins, A., & Ferdig, R. E. (2022). Examining the effects of students' self-efficacy and prior knowledge on learning and visual behavior in a physics game. Computers & Education, 178, 104405.
Weisskirch, R. (2003). Dealing with Piaget: Analyzing card games for understanding concepts. In Paper presented at 111th annual conference of the American psychological association. Toronto, ON: Canada.
W. Li et al., (2019) Training a Camera to Perform Long-Distance Eye Tracking by Another Eye-Tracker, IEEE, 7, 155313-155324,
X. Zhang, S. Yuan, M. Chen and X. Liu,(2018) A Complete System for Analysis of Video Lecture Based on Eye Tracking, IEEE, 6, 49056-49066.