:::

詳目顯示

回上一頁
題名:行動學習自我效能的模型建構
作者:張玟慧
作者(外文):Chang, Wen-Hui
校院名稱:國立臺北教育大學
系所名稱:課程與教學研究所
指導教授:劉遠楨
學位類別:博士
出版日期:2018
主題關鍵詞:行動學習行動學習自我效能行動學習準備度行動學習參與度行動載具使用行為社會影響Mobile learningMobile learning self-efficacyMobile learning readinessParticipation in mobile learningUsing behaviors of mobile devicesSocial influence
原始連結:連回原系統網址new window
相關次數:
  • 被引用次數被引用次數:期刊(0) 博士論文(0) 專書(0) 專書論文(0)
  • 排除自我引用排除自我引用:0
  • 共同引用共同引用:0
  • 點閱點閱:21
在數位時代,學習者能夠以行動學習進行學習是至關重要的。世界各國的行動學習亦蓬勃的發展;然而,有關行動學習對學生素養所產生的自我效能及其影響因素仍尚待釐清。本文旨在建構學生行動學習自我效能與行動學習準備度架構與量表並加以分析,了解接受了行動學習之國中小學生的行動學習相關概念之表現現況,分析行動學習參與度、社會影響、行動載具使用行為對行動學習準備度之影響,探討行動學習準備度、行動學習參與度、社會影響、行動載具使用行為對行動學習自我效能之影響,並進一步建立行動學習自我效能的路徑分析模型。
本研究之研究方法為問卷調查法,首先,先分別以165位以及189位使用行動學習進行學習的臺灣國中小學生為行動學習自我效能量表及行動學習準備度之預試樣本,再以943位使用行動學習進行學習的臺灣國中小學生為正式施測對象,蒐集問卷數據並進行MANOVA、相關分析、多元逐步回歸分析,以及徑路分析進行研究探究。研究結果顯示:
一、本研究所建構之行動學習自我效能與行動學習準備度架構與量表具良好信效度。
二、本研究施測結果與所建構之行動學習自我效能與行動學習準備度架構有良好的適配度。
三、社會影響、行動學習參與度與行動載具使用行為等顯著影響行動學習準備度。
四、行動學習參與度、行動載具使用行為,以及行動學習準備度顯著影響行動學習自我效能。
五、行動學習自我效能影響因素路徑分析具良好的適配度。
針對研究結果,本研究對教育研究者提出建議。
Using mobile technology in the process of learning is crucial nowadays. Mobile learning invarious countries is also developed; however, the competencies self-efficacy of students and theinfluencing factors of it in the mobile learning context haven’t clarified. The purpose of this paper is to construct and analyze the structure and scale of the Mobile Learning Self-Efficacy (MLSE) and mobile learning readiness (MLR) for learners to understand the perceptions of primary and secondary students who have received mobile learning in school. The effects of participation in mobile learning, social influence, and using behaviors of mobile devices on the mobile learning readiness is discussed, and the effects of mobile learning readiness, participation in mobile learning, social influence and the using behaviors of mobile devices on the mobile learning self-efficacy is explored. The path analysis model of the mobile learning self-efficacy is further established.
To answer the research questions, a questionnaire survey was used. 165 and 189 primary and secondary learners in Taiwan who have received mobile learning are the pretesting samples of the scale of MLSE and MLR respectively, and then 943 students of primary and secondary school in Taiwan who received mobile learning as the samples of formal scale. The statics methods of MANOVA, correlation analysis, multiple stepwise regression analysis and path analysis were used. The result shows:
1. The scales of MLSE and MLR have good reliability and validity.
2. The models of MLSE and MLR have a good fit between the theory framework and data.
3. Social influence, participation in mobile learning and using behaviors of mobile devices are affected the MLR significantly.
4. Participation in mobile learning, using behaviors of mobile devices, and Mobile Learning Readiness affected the mobile learning self-efficacy significantly.
5. The model of the path analysis on the factors of the mobile learning self-efficacy has a good fitness.
According to the result, the recommendations have been proposed.
壹、中文部分
大衛‧艾理克遜(2010)。創造力與教育體系。中正教育研究,9(2), 1-16。
王子華、楊凱悌(2015)。有效行動學習課程教學模式之設計與效益評估—以評量為中心的設計。課程與教學季刊,18(1), 1-30。new window
江妤欣(2016)。淺談行動學習:翻轉「學習力」的突破與困境。臺灣教育評論月刊,5(12), 5-8。
伍柏翰(2017)。結合即時診斷機制的行動學習與自我調整學習模式對學生運用概念圖的學習成就與行為之影響。數位學習科技期刊,9(2), 1-27。new window
李坤清、陳怡婷(2016)。不同思考方式、教學方法和學習風格對行動 學習使用行為之影響。數位學習科技期刊,8(2), 17-47。new window
李堅萍、朱素貞、劉蕙儀(2015)。 Teresa M. Amabile 創造力動機理論於造形創造力的適用性與差異性研究。藝術學報,97,1-18。new window
科技部(2016)。科技部對研究人員學術倫理規範。引自:
https://www.most.gov.tw/most/attachments/a8ff2bb9-84ae-41ec-b539bc54d9085811。
許于仁、黃一倚(2017)。探討擴增實境式行動學習在博物館導覽中對學習風格與學習成效之影響。臺灣教育評論月刊,6(1), 202-222。
陳奕樺、楊雅婷(2016)。行動學習成效影響因素。教育科學研究期刊,61(3), 99-129。
陳景蔚(2006)。無所不在的運算環境與進化中的行動學習。嘉義大學通識學報,4,17-45。
黃柏叡(2011)。創造力的教育實踐及其限制。教育學誌,26,79-99。new window
楊心怡、吳佳蓉(2012)。合作學習輔以電子書包在國小四年級國語文之研究。教學科技與媒體,102,36-41。new window
溫嘉榮、 鄭國明、 郭勝煌(2010)。以 PBL 問題導向高層次思考之行動學習模式探討。工業科技教育學刊,3,9-15。
賴英娟(2007)。創造力的理論與應用。國教新知,54(4), 65-76。
劉宣谷 (2015)。數學創造力的文獻回顧與探究。臺灣數學教育期刊,2(1),23-40。doi: 10.6278/tjme.2050313.002new window
蕭顯勝、黃向偉、洪琬諦(2007)。行動導覽系統於博物館學習之研究。高雄師大學報,23,29-52。

貳、英文部分
Aesaert, K., van Braak, J., Van Nijlen, D., & Vanderlinde, R. (2015). Primary school pupils' ICT competences: Extensive model and scale development. Computers & Education, 81, 326-344.
Aesaert, K., Voogt, J., Kuiper, E., & van Braak, J. (2017). Accuracy and bias of ICT self-efficacy: An empirical study into students’ over-and underestimation of their ICT competences. Computers in Human Behavior, 75, 92-102.
Amabile, T. M. (1983). The social psychology of creativity: A componential conceptualization. Journal of personality and social psychology, 45(2), 357.
Angeli, C., Voogt, J., Fluck, A., Webb, M., Cox, M., Malyn-Smith, J., & Zagami, J. (2016). A K-6 Computational Thinking Curriculum Framework: Implications for Teacher Knowledge. Educational Technology & Society, 19(3), 47-57.
Aristeidou, M., Scanlon, E., & Sharples, M. (2017). Profiles of engagement in online communities of citizen science participation. Computers in Human Behavior, 74, 246-256.
Atmatzidou, S., Demetriadis, S. (2016). Cover image Advancing students’ computational thinking skills through educational robotics: A study on age and gender relevant differences. Robotics and Autonomous Systems, 75, 661-670.
Aydın, C. H., & Tasci, D. (2005). Measuring readiness for e-learning: reflections from an emerging country. Educational Technology and Society, 8(4), 244-257.
Baek, Y., & Touati, A. (2017). Exploring how individual traits influence enjoyment in a mobile learning game. Computers in Human Behavior, 69, 347-357. Retrieved from:
http://www.sciencedirect.com.metalib.lib.ntue.edu.tw/science/article/pii/S0747563216308834/pdfft?md5=5ad711b2b1cf4f7f7beed7c7e97360d1&pid=1-s2.0S0747563216308834-main.pdf
Barbeite, F. G., & Weiss, E. M. (2004). Computer self-efficacy and anxiety scales for an Internet sample: testing measurement equivalence of existing measures and development of new scales. Computers in Human Behavior, 20, 1-15. Retrieved from:
http://www.sciencedirect.com.metalib.lib.ntue.edu.tw/science/article/pii/S0747563203000499/pdfft?md5=00e28cd045bf694df1808eb63dc38e01&pid=1-s2.0
S0747563203000499-main.pdf
Barlett, J. E., Kotrlik, J. W., & Higgins, C. C. (2001). Organizational research: Determining appropriate sample size in survey research. Information technology, learning, and performance journal, 19(1), 43.
Barron, B., Martin, C. K., Takeuchi, L., & Fithian, R. (2009). Parents as Learning Partners in the Development of Technological Fluency. International Journal of Learning and Media, 1(2), 55-77. (doi: 10.1162/ijlm.2009.0021)
Bart, W. M., Hokanson, B., Sahin, I., & Abdelsamea, M. A. (2015). An investigation of the gender differences in creative thinking abilities among 8th and 11th grade students. Thinking Skills and Creativity, 17, 17-24.
Binkley, M., Erstad, O., Herman, J., Raizen, S., Ripley, M., Miller-Ricci, M., & Rumble, M. (2012). In P. Griffin, & E. Care (Eds.), Assessment and teaching of 21st century skills. Dordrecht: Springer.
Boulton, H. (2017). Exploring the effectiveness of new technologies: Improving literacy and engaging learners at risk of social exclusion in the UK. Teaching and Teacher Education, 63, 73-81.
Boyaci, S., D. B., & Atalay, N. (2016). A Scale Development for 21st Century Skills of Primary School Students: A Validity and Reliability Study. International Journal of Instruction, 9(1), 133-148.
Brennan, K., & Resnick, M. (2012, April). New frameworks for studying and assessing the development of computational thinking. In Proceedings of the 2012 annual meeting of the American Educational Research Association, Vancouver, Canada (pp. 1-25). Retrieved from: http://web.media.mit.edu/~kbrennan/files/Brennan_Resnick_AERA2012_CT.pdf
Briz-Ponce, L., Pereira, A., Carvalho, L., Juanes-Méndez, J. A., & García-Peñalvo, F. J. (2017). Learning with mobile technologies-Students’ behavior. Computers in Human Behavior, 72, 612-620.
Broos, A., & Roe, K. (2006). The digital divide in the playstation generation: Self efficacy, locus of control and ICT adoption among adolescents. Poetics, 34(4-5), 306-317.
Calvo-Porral, C., Faíña-Medín, A., & Nieto-Mengotti, M. (2017). Exploring technology satisfaction: An approach through the flow experience. Computers in Human Behavior, 66, 400-408.
Chang, C. S., Chen, T. S., & Hsu, W. H. (2011). The study on integrating WebQuest with mobile learning for environmental education. Computers & Education, 57(1), 1228-1239.
Chang, H. P., Chen, C. C., Guo, G. J., Cheng, Y. J., Lin, C. Y., & Jen, T. H. (2011). The Development of a Competence Scale for Learning Science: Inquiry and Communication. International Journal of Science & Mathematics Education,
9(5), 1213-1233.
Chang, W. C., Pan, E. C., & Huang, Y. J. (2013). Constructing A Mobile Learning System To Support Creative Thinking Program. Journal of Information Technology and Applications, 7(2), 45-51.
Chang, W. H., Liu, Y. C., & Huang, T. H. (2017). Perceptions of learning effectiveness in M‐learning: scale development and student awareness. Journal of Computer Assisted Learning, 33(5), 461-472.
Chang, Y. S., Chien, Y. H., Yu, K. C., Lin, H. C., Chen, M. Y. C. (2016). Students’ innovative environmental perceptions and creative effectivenesss in cloud-based m-learning. Computers in Human Behavior, 63, 988-994.
Chen, C. M., & Chen, M. C. (2009). Mobile formative assessment tool based on data mining techniques for supporting web-based learning. Computers & Education, 52, 256-273.
Chen, G. D., Chang, C. K., & Wang, C. Y. (2008). Ubiquitous learning website: Scaffold learners by mobile devices with information-aware techniques. Computers & Education, 50, 77-90.
Chen, H. Y., & Liu, K. Y. (2008). Web-based synchronized multimedia lecture system design for teaching/learning Chinese as second language. Computers & Education, 50(3), 693-702.
Chen, Q., & Yan, Z. (2016). Does multitasking with mobile phones affect learning? A review, 54, 34-42.
Cheon, J., Lee, S., Crooks, S. M., & Song, J. (2012). An investigation of mobile learning readiness in higher education based on the theory of planned behavior. Computers & Education, 59, 1054-1064.
Ching, D., Shuler, C., Lewis, A., & Levine, M. H. (2009). Harnessing the Potential of Mobile Technologies for Children and Learning. In A. Druin(Eds.), Mobile Technology for Children - Designing for Interaction and Learning (pp. 23-42). Unite State: Morgan Kaufmann.
Chiu, C. J., Hu, Y. H., Lin, D. C., Chang, F. Y., Chang, C. S., & Lai, C. F. (2016). The attitudes, impact, and learning needs of older adults using apps on touchscreen mobile devices: Results from a pilot study. Computers in Human Behavior, 63, 189-197.
Choi, B., & Baek, Y. (2011). Exploring factors of media characteristic influencing flow in learning through virtual worlds. Computers & Education, 57(4), 2382-2394.
Christensen, R., & Knezek, G. (2017). Readiness for integrating mobile learning in the classroom: Challenges, preferences and possibilities. Computers in Human Behavior, 76, 112-121.
Christie, B., Beames, S., & Higgins, P. (2016). Context, culture and critical thinking: Scottish secondary school teachers' and pupils' experiences of outdoor learning. British Educational Research Journal, 42(3), 417-437.
Chu, H. C. (2014). Potential Negative Effects of Mobile Learning on Students’ Learning Achievement and Cognitive Load—A Format Assessment Perspective. Educational Technology & Society, 17(1), 332-344.
Chu, H. C., Hwang, G. J., Tsai, C. C., & Tseng, J. C. R. (2010). A two-tier test approach to developing location-aware mobile learning systems for natural science courses. Computers & Education, 55, 1618-1627.new window
Chu, R. J. C. (2010). How family support and Internet self-efficacy influence the effects of e-learning among higher aged adults-Analyses of gender and age differences. Computers & Education, 55(1), 255-264.
Cobcroft, R. S., Towers, S., & Smith, J. (2006). Mobile learning in review: Opportunities and challenges for learners, teachers, and institutions. Proceedings of the Online Learning and Teaching Conference 2006, 21-30.
Crompton, H. (2013). A historical overview of mobile learning: Toward learner centered education. In Z. L. Berge, & L. Y. Muilenburg (Eds.), Handbook of mobile learning (pp. 3-14). Florence: Routledge.
Crompton, H., Burke, D., & Gregory, K. H. (2017). The use of mobile learning in PK 12 education: A systematic review. Computers & Education, 110, 51-63.
Crompton, H., Olszewski, B., & Bielefeldt, T. (2016). The mobile learning training needs of educators in technology-enabled environments. Professional Development in Education, 42(3), 482-501.
Crompton, H. (2017). Using Mobile Learning to Support Students’ Understanding in Geometry: A Design-Based Research Study. Journal of Educational Technology & Society, 20(3), 207-219.
Csikszentmihalyi, M. (1975). Beyond boredom and anxiety. San Francisco, CA: JosseyBass.
Csikszentmihalyi, M., & Getzels, J. W. (1970). Concern for discovery: An attitudinal component of creative production. Journal of Personality, 38(1), 91-105.
Damiani, E., Ceravolo, P., Frati, F., Bellandi, V., Maier, R., Seeber, I., & Waldhart, G. (2015). Applying recommender systems in collaboration environments. Computers in Human Behavior, 51, 1124-1133.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-342.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management science, 35(8), 982-1003.
de Haan, G. (2010). The development of ESD-related competencies in supportive institutional frameworks. International Review of Education, 56(2-3), 315-328.
Dignath, C., Buettner, G., & Langfeldt, H. P. (2008). How can primary school students learn self-regulated learning strategies most effectively? A meta-analysis on self regulation training programmes. Educational Research Review, 3(2), 101-129.
Domingo, M. G., & Gargant, A. B. (2016). Exploring the use of educational technology in primary education: Teachers' perception of mobile technology learning impacts and applications' use in the classroom. Computers in Human
Behavior, 56, 21-28.
Dray, B. J., Lowenthal, P. R., Miszkiewicz, M. J., Ruiz‐Primo, M. A., & Marczynski, K. (2011). Developing an instrument to assess student readiness for online learning: A validation study. Distance Education, 32(1), 29-47.
Dwyer, C., Hogan, M., & Stewart, I. (2012). An evaluation of argument mapping as a method of enhancing critical thinking effectiveness in e-learning environments. Metacognition & Learning, 7(3), 219-244.
Echeverría, A., Nussbauma, M., Calderóna, J. F., Bravoa, C., Infantea, C., & Vásquez, A. (2011). Face-to-face collaborative learning supported by mobile phones. Interactive Learning Environments, 19(4), 351-363.
Esteban-Millat, I, Martínez-López, F. J., Huertas-García, R., Meseguer, A., & Rodríguez-Ardura, I. (2014). Modelling students’ flow experiences in an online learning environment. Computers & Education, 71, 111-123.
Evans, C. (2008). The effectiveness of m-learning in the form of podcast revision lectures in higher education. Computers & education, 50(2), 491-498.
Fakomogbon, M. A., & Bolaji, H. O. (2017). Effects of Collaborative Learning Styles on Performance of Students in a Ubiquitous Collaborative Mobile Learning Environment. Contemporary Educational Technology, 8(3), 268-279.
Falloon, G. (2016). An analysis of young students' thinking when completing basic coding tasks using Scratch Jnr. On the iPad. Journal of Computer Assisted Learning, 32(6), 576-593.
Felnhofer, A., Kothgassner, O. D., Hauk, N., Beutl, L., Hlavacs, H., & Exner, I. K. (2014). Physical and social presence in collaborative virtual environments: Exploring age and gender differences with respect to empathy. Computers in Human Behavior, 31, 272-279.
Fonseca, D., Martí, N., Redondo, E., Navarro, I., & Sánchez, A. (2014). Relationship between student profile, tool use, participation, and academic performance with the use of Augmented Reality technology for visualized architecture models. Computers in Human Behavior, 31, 434-445.
Forsyth, R. A., & Ansley, T. N. (1982). The Importance of Computational Skill for Answering Items in a Mathematics Problem Solving Test: Implications for Construct Validity. Educational and Psychological Measurement, 42(1), 257-263.
Frank, J. A., & Kapila, V. (2017). Mixed-reality learning environments: Integrating mobile interfaces with laboratory test-beds. Computers & Education, 110, 88-104.
Fronza, I., & Gallo, D. (2016, October). Towards Mobile Assisted Language Learning Based on Computational Thinking. In International Conference on Web-Based Learning (pp. 141-150). Springer International Publishing.
Fulantelli, G., Taibi, D., & Arrigo, M. (2015). A framework to support educational decision making in mobile learning. Computers in Human Behavior, 47, 50-59.
Fumoto, H., Robson, S., Greenfield, S., & Hargreaves, D. J. (2012). Young Children's Creative Thinking. California: Sage.
Furber, S. (2012). Shut down or restart? The way forward for computing in UK schools. London, UK: The Royal Society.
Gangadharbatla, H. (2010). Technology component: a modified systems approach to creative thought. Creativity Research Journal, 22(2), 219-227.
Garrison, D. R. (1997). Self-directed learning: Toward a comprehensive model. Adult education quarterly, 48(1), 18-33.
Garrison, D. R. (2011). E-learning in the 21st century: A framework for research and practice. Taylor & Francis.
Gedik, N., Karademirci, A. H., Kursun, E., & Cagiltay, K. (2012). Key instructional design issues in a cellular phone-based mobile learning project. Computers & Education, 58, 1149-1159.
Ginns, P., & Ellis, R. A. (2009). Evaluating the quality of e-learning at the degree level in the student experience of blended learning. British Journal of Educational Technology, 40(4), 652-663.
Glass, R. L. (2006).Call It Problem Solving, Not Computational Thinking. Communications of the ACM, 49(3), 13.
Gokcearslan, S. (2017). Perspectives of Students on Acceptance of Tablets and Self Directed Learning with Technology. Contemporary Educational Technology, 8(1), 40-55.
Greenfield, P. M., & Subrahmanyam, K. (2003). Online discourse in a teen chatroom: New codes and new modes of coherence in a visual medium. Journal of Applied Developmental Psychology, 24(6), 713-738.
Grönlund, Å., & Islam, Y. M. (2010). A mobile e-learning environment for developing countries: The Bangladesh Virtual Interactive Classroom. Information Technology for Development, 16(4), 244-259.
Gu, J. (2016). Understanding self-directed learning in the context of mobile Web 2.0– Case study with workplace learners. Interactive Learning Environments, 24(2), 306-316.
Guilford, J. P. (1959). Three faces of intellect. American psychologist, 14(8), 469-479.
Han, I., & Shin, W. S. (2016). The use of a mobile learning management system and academic achievement of online students. Computers & Education, 102, 79-89.
Hattam, R., & Smyth, J. (1998). Competing logics in the key competencies: a sociological reading of post-compulsory education and training in Australia. Research in Post-Compulsory Education, 3(2), 133-151.
Heflin, H., Shewmaker, J., & Nguyen, J. (2017). Impact of mobile technology on student attitudes, engagement, and learning. Computers & Education, 107, 91-99.
Henrie, C. R., Halverson, L. R., & Graham, C. R. (2015). Measuring student engagement in technology-mediated learning: A review. Computers & Education, 90, 36-53.
Hernandez, B., Montaner, T., Sese, F. J., & Urquizu, P. (2011). The role of social motivations in e-learning: How do they affect usage and success of ICT interactive tools? Computers in Human Behavior, 27(6), 2224-2232. Retrieved
from:http://www.sciencedirect.com.metalib.lib.ntue.edu.tw/science/article/pii/S0747563211001397/pdfft?md5=20358a560f1e7cf042dd7a35a586027e&pid=1-s2.0
S0747563211001397-main.pdf
Hill, J. R., Song, L., & West, R. E. (2009). Social learning theory and web-based learning environments: A review of research and discussion of implications. American journal of distance education, 23(2), 88-103.
Ho, L. A., & Kuo, T. H. (2010). How can one amplify the effect of e-learning? An examination of high-tech employees’ computer attitude and flow experience. Computers in Human Behavior, 26(1), 23-31.
Hong, J. C., Tai, K. H., Hwang, M. Y., & Kuo, Y. C. (2016). Internet cognitive failure affects learning progress as mediated by cognitive anxiety and flow while playing a Chinese antonym synonym game with interacting verbal–analytical and motor control. Computers & Education, 100, 32-44.
Horzum, M. B., Kaymak, Z. D., & Gungoren, O. C. (2015). Structural Equation Modeling towards Online Learning Readiness, Academic Motivations, and
Perceived Learning. Educational Sciences: Theory and Practice, 15(3), 759-770.
Howard, S. K., Ma, J., & Yang, J. (2016). Student rules: Exploring patterns of students’ computer-efficacy and engagement with digital technologies in learning. Computers & Education, 101, 29-42.
Howe, E. R. (2004). Canadian and Japanese teachers' conceptions of critical thinking: A comparative study. Teachers and Teaching, 10(5), 505-525.
Hsu, C. C., & Ho, C. C. (2012). The design and implementation of a competency-based intelligent mobile learning system. Expert Systems with Applications, 39(9), 8030-8043.
Huang, Y. M., Kuo, Y. H., Lin, Y. T., & Cheng, S. C. (2008). Toward interactive mobile synchronous learning environment with context-awareness service. Computers & Education, 51, 1205-1226.
Hung, H. L., Chou, C., Chen, C. H., & Own, Z. Y. (2010). Learner readiness for online learning: Scale development and student perceptions. Computers & Education, 55, 1080-1090.
Hwang, G. J., Wu, P. H., & Ke, H. R. (2011). An interactive concept map approach to supporting mobile learning activities for natural science courses. Computers & Education, 57, 2272-2280.
Ihsen, S., & Buschmeyer, A. (2007). Acting diverse: target group orientation as key competence in engineering education. European Journal of Engineering Education, 32(6), 665-673.
ISET (2016). Redefining learning in a technology-driven world A report to support adoption of the ISTE Standards for Students. Retrieved from: http://www.iste.org/docs/Standards-Resources/iste-standards_students
2016_research-validityreport_final.pdf?sfvrsn=0.0680021527232122&_ga=2.75269905.2064369304.1510498653-1848788721.1508337062.
Israel, M., Pearson, J. N., Tapia, T., Wherfel, Q. M., & Reese, G. (2015). Supporting all learners in school-wide computational thinking: A cross-case qualitative analysis. Computers & Education, 82, 263-279.
Jan, H., & Oi-man, K. (2007). Influence of student-teacher and parent-teacher relationships on lower achieving readers' engagement and achievement in the primary grades. Journal of Educational Psychology, 99(1), 39-51.
Järvelä, S., Näykki, P., Laru, J., & Luokkanen., T. (2007). Structuring and Regulating Collaborative Learning in Higher Education with Wireless Networks and Mobile Tools. Educational Technology & Society, 10(4), 71-79.
Johnson, R. D., Hornik, S., & Salas, E. (2008). An empirical examination of factors contributing to the creation of successful e-learning environments. International Journal of Human-Computer Studies, 66(5), 356-369.
Johnson, D. W., Johnson, R. T., & Smith, K. A. (1998). Cooperative learning returns to college what evidence is there that it works? Change: the magazine of higher learning, 30(4), 26-35.
Jones, A. C., Scanlon, E., & Clough, G. (2013). Mobile learning: Two case studies of supporting inquiry learning in informal and semiformal settings. Computers & Education, 61, 21-32.
Joo-Nagata, J., Abad, F. M., Giner, J. G. B., & García-Peñalvo, F. J. (2017). Augmented reality and pedestrian navigation through its implementation in m-learning and e-learning: Evaluation of an educational program in Chile.
Computers & Education, 111, 1-17.
Joo, Y. J., Lim, K. Y., & Kim, S. M. (2012). A model for predicting learning flow and achievement in corporate e-learning. Journal of Educational Technology & Society, 15(1), 313.
Jou, M., & Wang, J. (2015). The use of ubiquitous sensor technology in evaluating student thought process during practical operations for improving student technical and creative skills. British Journal of Educational Technology, 46(4), 818-828.
Karimi, S. (2016). Do learners’ characteristics matter? An exploration of mobile learning adoption in self-directed learning. Computers in Human Behavior, 63, 769-776.
Kaufman, J. C. (2012). Counting the Muses: Development of the Kaufman Domains of Creativity Scale (K-DOCS). Psychology of Aesthetics, Creativity, and the Arts, 6(4), 298-308.
Kennison, M. M. (2006). The evaluation of students' reflective writing for evidence of critical thinking. Nursing Education Perspectives, 27(5), 269-273.
Kim, K. H. (2006). Can we trust creativity tests? A review of the Torrance Tests of Creative Thinking (TTCT). Creativity research journal, 18(1), 3-14.
Kim, T. H., & Jin, S. H. (2015). Development of auditory design guidelines for improving learning on mobile phones. Computers & Education, 91, 60-72.
Kline, R. B. (2011). Principles and practice of structural equation modeling. New York: Guilford.
Knowles, M. S. (1975). Self-directed learning: A guide for learners and teachers. New York: Association Press.
Koole, M. L. (2009). A model for framing mobile learning. Mobile learning: Transforming the delivery of education and training, 1(2), 25-47.
Korkmaz, Ö., Çakir, R., & Özden, M. Y. (2017). A validity and reliability study of the computational thinking scales (CTS). Computers in Human Behavior, 72, 558-569. Retrieved from: https://ac.els-cdn.com/S0747563217300055/1-s2.0
S0747563217300055-main.pdf?_tid=da700338-e37f-11e7-a7f500000aab0f6b&acdnat=1513552572_003994aa441368bb2ce7a348abae0976
Koutromanosa, G., & Avraamidou, L. (2014). The use of mobile games in formal and informal learning environments: a review of the literature. Educational Media International, 51(1), 49-65.
Kreijns, K., Van Acker, F., Vermeulen, M., & Van Buuren, H. (2013). What stimulates teachers to integrate ICT in their pedagogical practices? The use of digital learning materials in education. Computers in human behavior, 29(1), 217-225.
Kukulska-Hulme, A., & Traxler, J. (2007). Learning design with mobile and wireless technologies. In Beetham, H. & Sharpe, R. (Eds.), Rethinking pedagogy for the digital age. London: Routledge.
Kulikovskikh, I. M., Prokhorov, S. A., & Suchkova, S. A. (2017). Promoting collaborative learning through regulation of guessing in clickers. Computers in Human Behavior, 75, 81-91.
Kuo, S. Y. (1985). Confucian idealism and Dewey’s pragmatism in philosophy of education. American Studies, 15(2), 23-65.
Lai, H. J. (2011). The influence of adult learners' self-directed learning readiness and network literacy on online learning effectiveness: A study of civil servants in Taiwan. Journal of Educational Technology & Society, 14(2), 98.
Lan, Y. F., & Sie, Y. S. (2010). Using RSS to support mobile learning based on media richness theory. Computers & Education, 55, 723-732.
Lane, E. S., & Harris, S. E. (2015). A new tool for Measuring student behavioral engagement in large university classes. Journal of College Science Teaching, 44(6), 83-91.
Laru, J., Järvelä, S., & Clariana, R. B. (2012). Supporting collaborative inquiry during a biology field trip with mobile peer-to-peer tools for learning: a case study with K-12 learners. Interactive Learning Environments, 20(2), 103-117.
Laux, D., Luse, A., & Mennecke, B. E. (2016). Collaboration, connectedness, and community: An examination of the factors influencing student persistence in virtual communities. Computers in Human Behavior, 57, 452-464.
Lee, C., Yeung, A. S., & Ip, T. (2017). University english language learners' readiness to use computer technology for self-directed learning. System, 67, 99-110.
Lee, C. S., Osop, H., Goh, D. H. L., & Kelni, G. (2017). Making sense of comments on YouTube educational videos: a self-directed learning perspective. Online Information Review, 41(5), 611-625.
Lewis, C. C. (2002). Lesson study: A handbook of teacher-led instructional change. Research for Better Schools.
Li, J., Snow, C., & White, C. (2015). Urban adolescent students and technology: access, use and interest in learning language and literacy. Innovation in Language Learning and Teaching, 9(2), 143-162.
Liaw, S. S., Hatala, M., & Huang, H. M. (2010). Investigating acceptance toward mobile learning to assist individual knowledge management: Based on activity theory approach. Computers & Education, 54(2), 446-454.
Lin, Y. T., & Lin, Y. C. (2016). Effects of mental process integrated nursing training using mobile device on students’ cognitive load, learning attitudes, acceptance, and achievements. Computers in Human Behavior, 55, 1213-1221.
Liu, T. C., Lin, Y. C., & Paas, F. (2014). Effects of prior knowledge on learning from different compositions of representations in a mobile learning environment. Computers & Education, 72, 328-338.
Liu, Y., Li, H., & Carlsson, C. (2010). Factors driving the adoption of m-learning: An empirical study. Computers & Education, 55(3), 1211-1219.
Macaskill, A., & Denovan, A. (2013). Developing autonomous learning in first year university students using perspectives from positive psychology. Studies in Higher Education, 38(1), 124-142.
Mac Callum, K., & Jeffrey, L. (2014). Comparing the role of ICT literacy and anxiety in the adoption of mobile learning. Computers in Human Behavior, 39, 8-19.
Martin, F., & Ertzberger, J. (2013). Here and now mobile learning: An experimental study on the use of mobile technology. Computers & Education, 68, 76-85.
Marty, P. F., Alemanne, N. D., Mendenhall, A., Maurya, M., Southerland, S. A., Sampson, V., Douglas, I., Kazmer, M. M., Clark, A., & Schellinger, J. (2013). Scientific inquiry, digital literacy, and mobile computing in informal learning environments. Learning, Media and Technology, 38(4), 407-428.
Masrom M., & Ismail A. (2010). Benefits and barriers to the use of mobile learning in education: review of literature. In R. Guy, (Eds.). Mobile learning: Pilot projects and initiatives(pp.9-26). California: Informing Science.
Mayer, R. E. (Eds.). (2005). The Cambridge handbook of multimedia learning. Cambridge university press.
McEwen, R. (2014). Mediating sociality: the use of iPod Touch™ devices in the classrooms of students with autism in Canada. Information, Communication & Society, 17(10), 1264-1279.
McQuiggan, S., McQuiggan, J., Sabourin, J., & Kosturko, L. (2015). Mobile learning- A Handbook for Developers, Educators and Learners. New Jersey: John Wiley & Sons.
Medley, D. M. (1977). Teacher Competence and Teacher Effectiveness. A Review of Process-Product Research. Washington: The American Association of Colleges for Teacher Education.
Melero, J., Hernandez, D., & Manatunga, K. (2015). Group-based mobile learning: Do group size and sharing mobile devices matter? Computers in Human Behavior, 44, 377-385.
Miller, C. J., & Crouch, J. G. (1991). Gender Differences in Problem Solving: Expectancy and Problem Context. The Journal of Psychology, 125(3), 327-336.
Mills, L. A., Knezek, G., & Khaddage, F. (2014). Information Seeking, Information Sharing, and going mobile: Three bridges to informal learning. Computers in Human Behavior, 32, 324-334.
Ministry of Education (2007). The New Zealand curriculum.Learning Media Ltd: Wellington.
Mohammadi, H. (2015). Investigating users’perspectives on e-learning: An integration of TAM and IS success model. Computers in Human Behavior, 45, 359-374.
Mohammadi, H. (2015). Social and individual antecedents of m-learning adoption in Iran. Computers in Human Behavior, 49, 191-207.
Mori, K., & Harada, E. T. (2010). Is learning a family matter?: Experimental study of the influence of social environment on learning by older adults in the use of mobile phones. Japanese Psychological Research, 52(3), 244-255.
Motiwalla, L. F. (2007). Mobile learning: A framework and evaluation. Computers & Education, 49, 581-596.
Nikou, S. A., & Economides, A. A. (2014, April). Transition in student motivation during a scratch and an app inventor course. In Global Engineering Education Conference (EDUCON), 2014 IEEE (pp. 1042-1045). Retrieved from
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6826234&isnumber=6826048 Noorhidawati, A., Ghalebandi, S. G., & Hajar, R. S. (2015). How do young children engage with mobile apps? Cognitive, psychomotor, and affective perspective. Computers & Education, 87, 385-395.
O’Bannon, B. W., & Thomas, K. (2014). Teacher perceptions of using mobile phones in the classroom: Age matters! Computers & Education, 74, 15-25.
OECD. (2014). Measuring innovation in education: A new perspective, educational research and innovation. Paris: OECD Publishing. http://dx.doi.org/10.1787/ 9789264215696-en.
Ono, Y., Ishihara, M., & Yamashiro, M. (2015). Blended Instruction Utilizing Mobile Tools in English Teaching at Colleges of Technology. Electrical Engineering in Japan, 192(2), 1-11.
Ozcelik, E., & Acarturk, C. (2011). Reducing the spatial distance between printed and online information sources by means of mobile technology enhances learning: Using 2D barcodes. Computers & Education, 57, 2077-2085.
Papert, S. (1980). Mindstorms: Children, computers, and powerful ideas. New York: Basic Books.
Park, S. Y., Nam, M. W., & Cha, S. B. (2012). University students' behavioral intention to use mobile learning: Evaluating the technology acceptance model. British Journal of Educational Technology, 43(4), 592-605.
Partnership for 21st Century Skills. (2010). 21st century readiness for every student: A policymaker’s guide. Tucson, AZ: Author. Available: http://www.p21.org/storage/documents/policymakersguide_final.pdf [accessed
March 2017].
Pimmer, C., Mateescu, M., & Grohbiel, U. (2016). Mobile and ubiquitous learning in higher education settings. A systematic review of empirical studies. Computers in Human Behavior, 63, 490-501.
Pillay, H., Irving, K., & McCrindle, A. (2006). Developing a diagnostic tool for assessing tertiary students' readiness for online learning. International journal of learning technology, 2(1), 92-104.
Pruet, P., Ang, C. S., & Farzin, D. (2016). Understanding tablet computer usage among primary school students in underdeveloped areas: Students’ technology experience, learning styles and attitudes. Computers in Human Behavior, 55, 1131-1144.
Revelle, G. (2009). Mobile Technologies in Support of Young Children's Learning Designing for Interaction and Learning. In A. Druin (Eds.), Mobile Technology for Children, (pp. 265-284). Unite State: Elsevier.
Reychav, I., Dunaway, M., & Kobayashi, M. (2016). Understanding mobile technology-fit behaviors outside the classroom. Computers & Education, 87, 142-150.
Reychav, I., & McHaney, R. (2017). The relationship between gender and mobile technology use in collaborative learning settings: An empirical investigation. Computers & Education, 113(1), 61-74.
Reychav, I., Ndicu, M., & Wu, D. (2016). Leveraging social networks in the adoption of mobile technologies for collaboration. Computers in Human Behavior, 58, 443-453.
Reychav, I., & Wu, D. (2015). Mobile collaborative learning: The role of individual learning in groups through text and video content delivery in tablets. Computers in Human Behavior, 50, 520-534.
Reychav, I., & Wu, D. (2016). The interplay between cognitive task complexity and user interaction in mobile collaborative training. Computers in Human Behavior, 62, 333-345.
Rieckmann, M. (2012). Future-oriented higher education: Which key competencies should be fostered through university teaching and learning? Futures, 44(2), 127-135.
Rieckmann, M. (2013). The global perspective of education for sustainable development: a European-Latin American study about key competencies for thinking and acting in the world society. Environmental Education Research,
19(2), 257-258.
Rodríguez‐Ardura, I., & Meseguer‐Artola, A. (2017). Flow in e‐learning: What drives it and why it matters. British Journal of Educational Technology, 48(4), 899-915.
Rodríguez-Ardura, I., & Meseguer-Artola, A. (2016). E-learning continuance: The impact of interactivity and the mediating role of imagery, presence and flow. Information & Management, 53(4), 504-516.
Rodríguez‐Ardura, I., & Meseguer‐Artola, A. (2017). Flow in e‐learning: What drives it and why it matters. British Journal of Educational Technology, 48(4), 899-915.
Rodríguez‐Ardura. I., Riaza, B. G., & Gómez, M. C. S. (2017). Collaborative learning and mobile devices: An educational experience in Primary Education. Computers in Human Behavior, 72, 664-677.
Rogers, Y., & Price, S. (2008). The role of mobile devices in facilitating collaborative inquiry in situ. Research and Practice in Technology Enhanced Learning, 3(3), 209-229.
Rogers, Y., & Price, S. (2009). How Mobile Technologies Are Changing the Way Children Learn. In A. Druin (Eds.), Mobile Technology for Children - Designing for Interaction and Learning (pp. 3-22). Unite State: Elsevier.
Rohatgi, A., Scherer, R., & Hatlevik, O. E. (2016). The role of ICT self-efficacy for students' ICT use and their achievement in a computer and information literacy test. Computers & Education, 102, 103-116.new window
Román-González, M., Pérez-González, J. C., & Jiménez-Fernández, C. (2017). Which cognitive abilities underlie computational thinking? Criterion validity of the Computational Thinking Test. Computers in Human Behavior, 72, 678-691.
Rosen, L. D., Whaling, K., Carrier, L. M., Cheever, N. A., & Rokkum, J. (2013). The media and technology usage and attitudes scale: An empirical investigation. Computers in Human Behavior, 29(6), 2501-2511.
Rossing, J. P., Miller, W. M., Cecil, A. K., & Stamper, S. E. (2012). iLearning: The future of higher education? Student perceptions on learning with mobile tablets. Journal of the Scholarship of Teaching and Learning, 12(2), 1-26.
Rychen, D. S., & Salganik, L. H. (Eds.). (2003). Key competencies for a successful life and well-functioning society. Hogrefe Publishing.
Ryu, H., & Parsons, D. (2012). Risky business or sharing the load? - Social flow in collaborative mobile learning. Computers & Education, 58(2), 707-720.
Sabah, N. M. (2016). Exploring students' awareness and perceptions: Influencing factors and individual differences driving m-learning adoption. Computers in Human Behavior, 65, 522-533.
Saez-Lopez, J. M., Roman-Gonzalez, M., & Vazquez-Cano, E. (2016). Visual programming languages integrated across the curriculum in elementary school: A two year case study using “Scratch” in five schools. Computers & Education, 97, 129-141.
Salmela-Aro, K. & Upadaya, K. (2012). The Schoolwork Engagement Inventory Energy, Dedication, and Absorption (EDA). European Journal of Psychological Assessment, 28(1), 60-67.
Sánchez, J., & Olivares, R. (2011). Problem solving and team collaboration using mobile serious games. Computers & Education, 57(3), 1943-1952.
Sánchez-Prieto, J. C., Olmos-Migueláñez, S., & García-Peñalvo, F. J. (2016). Informal tools in formal contexts: Development of a model to assess the acceptance of mobile technologies among teachers. Computers in Human Behavior, 55, 519-528.
Sánchez-Prieto, C. J., Olmos-Miguelanez, S., & García-Penalvo, F. J. (2017). MLearning and pre-service teachers: An assessment of the behavioral intention using an expanded TAM model. Computers in Human Behavior, 72, 644-654.
Sandberg, J., Maris, M., & Geus, K. (2011). Mobile English learning: An evidence-based study with fifth graders. Computers & Education, 57, 1334-1347.
Scherer, R., & Hatlevik, O. E. (2017). “Sore eyes and distracted” or “excited and confident”?–The role of perceived negative consequences of using ICT for perceived usefulness and self-efficacy. Computers & Education, 115, 188-200.
Schumacker, R. E., & Lomax, R. G. (2010). A beginner’s guide to structural equation modeling. New York: Routledge.
Sen, S., Acar, S., & Cetinkaya, C. (2014). Development of the Person-Environment Fit Scale (PEFSC): A New Measure of Creativity. Psychology of Aesthetics, Creativity, and the Arts, 8(4), 433-445.
Shadiev, R., Hwang, W. Y., Huang, Y. M., & Liu, T. Y. (2015). The Impact of Supported and Annotated Mobile Learning on Achievement and Cognitive Load. Educational Technology & Society, 18(4), 53-69.
Sharples, M., Taylor, J., & Vavoula, G. (2007). A theory of learning for the mobile age. In: R. Andrews, & C. Haythornthwaite (Eds.), The Sage Handbook of E-learning Research.(pp. 221-247). London: Sage.
Shernoff, D. J., Csikszentmihalyi, M., Shneider, B., & Shernoff, E. S. (2003). Student engagement in high school classrooms from the perspective of flow theory. School Psychology Quarterly, 18(2), 158.
Shin, N. (2006). Online learner’s ‘flow’experience: an empirical study. British Journal of Educational Technology, 37(5), 705-720.
Shuib, L., Shamshirband, S., & Ismail, M. H. (2015). A review of mobile pervasive learning: Applications and issues. Computers in Human Behavior, 46, 239-244.
Smith, P. J. (2005). Learning preferences and readiness for online learning. Educational psychology, 25(1), 3-12.
Smith, J. C. (2018). Critical Thinking: Pseudoscience and the Paranormal. John Wiley & Sons. Retrieved from: https://books.google.com.tw/books?id=YGLpCgAAQBAJ&printsec=frontcover&dq=Critical+thinking&hl=zh-TW&sa=X&ved=0ahUKEwiq
bOY5Y_YAhXBfbwKHQwrD6MQ6AEILTAB#v=onepage&q=Critical%20thinking&f=false.
Snalune, P. (2015). The Benefits of Computational Thinking. ITNOW, 57(4), 58-59.
Snodgrass, M. R., Israel, I., & Reese, G. C. (2016). Instructional supports for students with disabilities in K-5 computing: Findings from a cross-case analysis. Computers & Education, 100, 1-17.
Song, L., & Hill, J. R. (2007). A conceptual model for understanding self-directed learning in online environments. Journal of Interactive Online Learning, 6(1), 27-42.
Soparat, S., Arnold, S. R., Klaysom, S. (2015). The Development of Thai Learners’ Key Competencies by Project-Based Learning Using ICT. International Journal of Research in Education and Science, 1(1), 11-22.
Stein, S. J., Shephard, K., & Harris, I. (2011). Conceptions of e‐learning and professional development for e‐learning held by tertiary educators in New Zealand. British Journal of Educational Technology, 42(1), 145-165.
Su, C., & Hsaio, K. (2015). Developing and Evaluating Gamifying Learning System by Using Flow-Based Model. EURASIA Journal of Mathematics, Science & Technology Education, 11(6), 1283-1306.
Sung, E., & Mayer, R. E. (2013). Online multimedia learning with mobile devices and desktop computers: An experimental test of Clark’s methods-not-media hypothesis. Computers in Human Behavior, 29, 639-647.new window
Sung , H. Y., Hwang, G. J., Liu, S. Y., Chiu, I. h. (2014). A prompt-based annotation approach to conducting mobile learning activities for architecture design courses. Computers & Educations, 76, 80-90.
Swart, R. (2017). Critical thinking instruction and technology enhanced learning from the student perspective: A mixed methods research study. Nurse Education in Practice, 23, 30-39.
Tan, G. W. H., Ooi, K. B., Leong, L. Y., & Lin, B. (2014). Predicting the drivers of behavioral intention to use mobile learning: A hybrid SEM-Neural Networks approach. Computers in Human Behavior, 36, 198-213.
Tang, J. H., Chen, M. C., Yang, C. Y., Chung, T. Y., & Lee, Y. A. (2016). Personality traits, interpersonal relationships, online social support, and Facebook addiction. Telematics and Informatics, 33(1), 102-108.
Taylor, R. (2016). The multimodal texture of engagement: Prosodic language, gaze and posture in engaged, creative classroom interaction. Thinking Skills and Creativity, 20, 83-96.
Thompson, T., & Craft, C. (2001). BSW students' perceptions of keycompetencies, values, and practitioner skills Implications for social work education. Australian Social Work, 54(4), 51-62.
Ting, Y. L. (2013). Using mobile technologies to create interwoven learning interactions: An intuitive design and its evaluation. Computers & Education, 60, 1-13.
Torrance, E. P. (1972). Predictive validity of the Torrance Tests of Creative Thinking. Journal of Creative Behavior, 6(4), 236–252.
Traxler, J. (2007). Defining, discussing and evaluating mobile learning: The moving finger writes and having writ. The International Review of Research in Open and Distance Learning, 8(2), 1–12.
Traxler, J. (2009). Current State of Mobile Learning. In M. Ally (Eds.), Mobile learning: Transforming the delivery of education and training (pp. 9-24). Edmonton, Alberta: AU.
Tsuei, M. P. (2012). Using synchronous peer tutoring system to promote elementary students’ learning in mathematics. Computers & Education, 58, 1171–1182.
Tsiotsou, R. H. (2015). The role of social and parasocial relationships on social networking sites loyalty. Computers in Human Behavior, 48, 401-414.
Turel, V., Calık, S., & Doganer, A. (2015). Tertiary Students' ICT Self-efficacy Beliefs and the Factors Affecting Their ICT-Use. International Journal of Information and Communication Technology Education, 11(2), 90-104.
Urban, K. K. (2007). Assessing creativity: A componential model. In Tan, A. G. (Eds.), Creativity: A handbook for teachers (pp. 167-184). Singapore: World Scientific.
Upadyaya, K. & Salmela-Aro, K. (2013). Development of School Engagement in Association with Academic Success and Well-Being in Varying Social Contexts- A Review of Empirical Research. European Psychologist, 18(2), 136-147.
Uzunboylu, H., Cavus, N., & Ercag, E. (2009). Using mobile learning to increase environmental awareness. Computers & Education, 52, 381-389.
Venkatesh, V., & Bala, H. (2008). Technology Acceptance Model 3 and a Research Agenda on Interventions. Decision Sciences, 39(2), 273-315.
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management science, 46(2), 186-204.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 27(3),425-478.
Viberg, O., & Grönlund, Å. (2013). Cross-cultural analysis of users’ attitudes toward the use of mobile devices in second and foreign language learning in higher education: A case from Sweden and China. Computers & Education, 69, 169-180.
von Davier, A. A., Hao, J., Liu, L., & Kyllonen, P. (2017). Interdisciplinary research agenda in support of assessment of collaborative problem solving: lessons learned from developing a Collaborative Science Assessment Prototype.
Computers in Human Behavior, 76, 631-640.
Wang, C. C., & Hsu, M. C. (2014). An exploratory study using inexpensive electroencephalography (EEG) to understand flow experience in computer-based instruction. Information & Management, 51(7), 912-923.
Wang, Y., Chiew, V. (2010). On the cognitive process of human problem solving. Cognitive Systems Research, 11(1), 81-92.
Watkins, R., Leigh, D., & Triner, D. (2004). Assessing readiness for e‐learning. Performance Improvement Quarterly, 17(4), 66-79.
Watson, G., & Glaser, E. M. (2010). Watson-GlaserTM II Critical Thinking Appraisal. Pearson: USA.
Welter, M. M., Jaarsveld, S., & Lachmann, T. (2017). Problem Space Matters: The Development of Creativity and Intelligence in Primary School Children. Creativity Research Journal, 29(2), 125-132.
Wing, Jeannette M. (2006). Computational Thinking. Communications of the ACM, 49(3), 33-35.
Winne, P. H. (1987). Why process-product research cannot explain process-product findings and a proposed remedy: The cognitive mediational paradigm. Teaching and teacher education, 3(4), 333-356.
Wladis, C., & Samuels, J. (2016). Do online readiness surveys do what they claim? Validity, reliability, and subsequent student enrollment decisions. Computers & Education, 98, 39-56.
Wong, S. L., & Bakar, K. A. (2009). Qualitative findings of students’ perception on practice of self-regulated strategies in online community discussion. Computers & education, 53(1), 94-103.
Wu, W. H., Wu, Y. C. J., Chen, C. Y., Kao, H. Y., Lin, C. H., & Huang, S. H. (2012). Review of trends from mobile learning studies: A meta-analysis. Computers & Education, 59(2), 817-827.
Wu, M., Siswanto, I., & Ko, C. (2017). The influential factors and hierarchical structure of college students’ creative capabilities—An empirical study in Taiwan. Thinking Skills and Creativity, 26,176-185.
Xu, R., Frey, R. M., Fleisch, E.,& Ilic, A. (2016). Understanding the impact of personality traits on mobile app adoption e Insights from a large-scale field study. Computers in Human Behavior, 62, 244-256.
Yang, G., Chen, N. S., Kinshuk , Sutinen , E., Anderson, T., & Wen, D. (2013). The effectiveness of automatic text summarization in mobile learning contexts. Computers & Education, 68, 233-243.
Yang, S. H. (2012). Exploring college students' attitudes and self-efficacy of mobile learning. TOJET: The Turkish Online Journal of Educational Technology, 11(4), 148-154.
Ye, Y. Z., Ye, Y. L., & Lin, J. F. (2013). The Development of Positive-Trait Inventories in E-learning: Knowledge Management, Self-regulation Learning, and Meaning. International Journal on Digital Learning Technology, 5(3), 59-89.
Yen, J. C., Lee, C. Y. (2011). Exploring problem solving patterns and their impact on learning achievement in a blended learning environment. Computers & Education, 56(1), 138-145.
Yorganci, S. (2017). Investigating Students’ Self-Efficacy and Attitudes Towards the Use of Mobile Learning. Learning, 8(6), 181-185.
Young, C., Hill, R., Morris, G., & Woods, F. (2016). Engaging in Collaboration: A Team of Teams Approach. Kappa Delta Pi Record, 52(2), 76-78.
Yu, C., Yu, W. C. W., & Lin, C. F. (2009). Computer-Mediated Learning: What Have We Experienced and where do we go next? Handbook of Research on Practices and Outcomes in E-Learning: Issues and Trends, 1-13.USA: IGI Globle.
Zhang, X., Meng, Y., de Pablos, P. O., & Sun, Y. (2017) (in press). Learning analytics in collaborative learning supported by Slack: From the perspective of engagement. Computers in Human Behavior. Retrieved from https://ac.els
cdn.com/S0747563217304788/1-s2.0-S0747563217304788main.pdf?_tid=55bf6c12-cae0-11e7-bb2b00000aacb35f&acdnat=1510845233_3706e69e27e68a3d68895333f8ec267b
Zhoc, K. C., & Chen, G. (2016). Reliability and validity evidence for the Self-Directed Learning Scale (SDLS). Learning and Indivi dual Differences, 49, 245-250.
 
 
 
 
第一頁 上一頁 下一頁 最後一頁 top
:::
無相關書籍
 
無相關著作
 
無相關點閱
 
QR Code
QRCODE