隨著行動載具與網路的發展，學生的學習模式與資訊接收的管道也隨之改變。在強調以學生為中心的行動學習模式中，學習的內容多元化，而且學習活動可以不受到時間及空間的限制；因此，學生的自律能力顯得格外重要。為了幫助學生在行動學習環境中培養自律能力，本研究提出一個結合自動化自律回饋機制之行動學習模式。為了驗證此學習模式對學生學習成效的影響，本研究開發一個結合自動化自律回饋機制之行動學習系統，並進行準實驗設計，應用在國中自然與生活科技課程「光與顏色」單元活動中。參與實驗的是兩個班級的46名國中二年級學生，一個班(24人)為實驗組，另一個班(22人)為控制組；其中實驗組學生使用「結合自動化自律回饋機制之行動學習模式」，控制組使用「一般行動學習模式」。由研究結果發現，使用結合自動化自律回饋機制之行動學習系統的學生，在學習成就、自律能力與科學學習方法方面，顯著優於參與一般行動學習活動的學生；在自我效能方面，兩組則無顯著差異。

In recent years, students’ learning modes have been changed owing to the rapid advancement of mobile and communication technologies. In mobile learning, which is a learner-centered mode, students are able to receive learning contents from various sources without being limited by location and time. Therefore, self-regulated learning has become an important issue to them. In order to foster students’ self-regulated abilities, in this study, an automated self-regulated feedback mechanism is proposed and implemented in a mobile learning environment. To evaluate the effectiveness of the proposed approach, an experiment will be conducted in a junior high school science course to examine the students’ learning achievements, self-efficacy, self-regulated, and approaches to science learning. The participants were 46 eighth graders from two classes of a junior high school in northern Taiwan. The learning content is the “Light and Color” unit of the natural science course. The experiment group (n=24) learned with the automated self-regulated feedback mechanism-based mobile learning approach, while those in the control group (n=22) learned with the conventional mobile learning approach. The experimental results show that the designated approach effectively promoted the students’ learning achievements, self-regulated, and approaches to science learning. And no significant difference existed between the automated self-regulated feedback mechanism-based mobile learning approach and the conventional mobile learning approach in terms of students’ self-efficacy.

Artino Jr, A. R., & Jones II, K. D. (2012). Exploring the complex relations between achievement emotions and self-regulated learning behaviors in online learning. The Internet and Higher Education, 15(3), 170-175.
Bandura, A. (1986). Social foundations of thought and action. Englewood Cliffs, NJ, US: Prentice-Hall.
Barnard, L., Lan, W.Y., To, Y.M., Paton, V.O. & Lai, S.L. (2009) .Measuring self-regulation in online and blended learning environments. The Internet and Higher Education, 12, 1-6.
Boyce, C. J., Mishra, C., Halverson, K. L., & Thomas, A. K. (2014). Getting students outside: Using technology as a way to stimulate engagement. Journal of Science Education and Technology, 23(6), 815-826.
Cakiroglu, U., & Ozturk, M. (2017). Flipped classroom with problem based activities: Exploring self-regulated learning in a programming language course. Educational Technology & Society, 20(1), 337–349.
Chang, C. Y., Lai, C. L., & Hwang, G. J. (2018). Trends and research issues of mobile learning studies in nursing education: a review of academic publications from 1971 to 2016. Computers & Education,116, 28-48.
Chen, C. H, Liu, G. Z., & Hwang, G. J. (2016). Interaction between gaming and multistage guiding strategies on students' field trip mobile learning performance and motivation. British Journal of Educational Technology, 47(6), 1032-1050.
Chen, C. M., Chen, L. C., & Yang, S. M. (2019). An English vocabulary learning app with self-regulated learning mechanism to improve learning performance and motivation. Computer Assisted Language Learning, 32(3), 237-260.
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. (2010). Development of a project-based cooperative learning environment for computer programming courses. International Journal of Innovation and Learning, 8(3), 256-266.
Chu, H. C., Hwang, G. J., & Liang, Y. R. (2014). A cooperative computerized concept-mapping approach to improving students’ learning performance in web-based information-seeking activities. Journal of Computers in Education, 1(1), 19-33.
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 course. Computers & Education, 55(4), 1618-1627.
Davis, G. A., & Rimm, S. B. (1985). Education of the gifted and talented. Englewood Cliffs, NJ: Prentice-Hall.
Denton, P., Madden, J., Roberts, M. & Rowe, P. (2008). Students' response to traditional and computer‐assisted formative feedback: a comparative case study. British Journal of Educational Technology, 39, 486–500.
Draper, S. W. (2009). What are learners actually regulating when given feedback? British Journal of Educational Technology, 40, 306-315.
Eilam, B., & Reiter, S. (2014). Long-Term Self-Regulation of Biology Learning Using Standard Junior High School Science Curriculum. Science Education, 98(4), 705-737.
Ferreira, P. C., Simao, A. M. V., & da Silva, A. L. (2015). Does training in how to regulate one’s learning affect how students report self-regulated learning in diary tasks? Metacognition and Learning, 10(2), 199-230.
Hsu, T. C., & Hwang, G. J. (2017). Effects of a structured resource-based web issue-quest approach on students’ learning performances in computer programming courses. Journal of Educational Technology & Society, 20(3), 82-94.
Huang, Y.M., Kuo, Y.H., Lin, Y.T. and Cheng, S.C. (2008). Toward interactive mobile synchronous learning environment with context-awareness service. Computers & Education, 51(3), 1205-1226.
Hwang, G. J., & Chang, S. C. (2016). Effects of a peer competition‐based mobile learning approach on students' affective domain exhibition in social studies courses. British Journal of Educational Technology, 47(6), 1217-1231.
Hwang, G. J., & Tsai, C. C. (2011). Research trends in mobile and ubiquitous learning: a review of publications in selected journals from 2001 to 2010. British Journal ofEducational Technology, 42(4), E65-E70.
Hwang, G. J., Shi, Y. R. & Chu, H. C. (2011). A concept map approach to developing collaborative Mindtools for context-aware ubiquitous learning. British Journal of Educational Technology, 42(5), 778–789.
Hwang, G. J., Tsai, C. C., Chu, H. C., Kinshuk, & Chen, C. Y. (2012). A context-aware ubiquitous learning approach to conducting scientific inquiry activities in a science park. Australasian Journal of Educational Technology, 28(5), 931–947.
Hwang, G.J., Chu, H.C., Lin, Y.S. and Tsai, C.C. (2011). knowledge acquisition approach to developing Mindtools for organizing and sharing differentiating knowledge in a ubiquitous learning environment. Computers & Education, 57(1). 1368-1377.
Ingeç, S. K. (2009). Analysing concept maps as an assessment tool in teaching physics and comparison with the achievement tests. International Journal of Science Education, 31(14), 1897-1915.
Jeno, L. M., Grytnes, J. A., & Vandvik, V. (2017). The effect of a mobile-application tool on biology students' motivation and achievement in species identification: A Self-Determination Theory perspective. Computers & Education, 107, 1-12.
Jordan, S. & Mitchell, T. (2009). e‐Assessment for learning? The potential of short‐answer free‐text questions with tailored feedback. British Journal of Educational Technology, 40, 371-385.
Kearney, M., Schuck, S., Burden, K. & Aubusson, P. (2012). Viewing mobile learning from a pedagogical perspective. Research in Educational Technology, 20(1), 1-17.
Kember, D., Biggs, J., & Leung, D. Y. (2004). Examining the multidimensionality of approaches to learning through the development of a revised version of the Learning Process Questionnaire. British Journal of Educational Psychology, 74(2), 261-279.
Kizilcec, R. F., Perez-Sanagustin, M., & Maldonado, J. J. (2017). Self-regulated learning strategies predict learner behavior and goal attainment in Massive Open Online Courses. Computers & Education, 104, 18-33.
Klimova, B., & Poulova, P. (2016). Mobile learning in higher education. advanced science letters, 22(5-6), 1111-1114.
Kukulska-Hulme, A. (2012). How should the higher education workforce adapt to advancements in technology for teaching and learning? The Internet and Higher Education, 15(4), 247-254.
Kuo, F. R., & Hwang, G. J. (2015). A structural equation model to analyse the antecedents to students’ web-based problem-solving performance. Australasian Journal of Educational Technology, 31(4).
Labuhn, A. S., Bogeholz, S., & Hasselhorn, M. (2008). Fostering learning through stimulation of self-regulation in science lessons. Zeitschrift Fur Padagogische Psychologie, 22(1), 13-24.
Lai, C. L., & Hwang, G. J. (2016). A self-regulated flipped classroom approach to improving students’ learning performance in a mathematics course. Computers & Education, 100, 126-140.
Lai, C. L., Hwang, G. J., & Tu, Y. H. (2018). The effects of computer-supported self-regulation in science inquiry on learning outcomes, learning processes, and self-efficacy. Educational Technology Research and Development, 66(4), 863-892.
Lee, M. H., Johanson, R. E., & Tsai, C.C. (2008). Exploring Taiwanese high school students’ conceptions of and approaches to learning science through a structural equation modeling analysis. Science Education, 92, 191-220.
Li, L., Liu, X. & Steckelberg, A. L. (2010). Assessor or assessee: how student learning improves by giving and receiving peer feedback. British Journal of Educational Technology, 41, 525-536.
Liu, G. Z., & Hwang, G. J. (2009). A key step to understanding paradigm shifts in e-learning: towards context-aware ubiquitous learning. British Journal of Educational Technology, 40(6), E1–E9.
Liu, G. Z., Chen, J. Y., & Hwang, G. J. (2018). Mobile‐based collaborative learning in the fitness center: A case study on the development of English listening comprehension with a context‐aware application. British Journal of Educational Technology, 49(2), 305-320.
Liu, G. Z., Chen, J. Y., & Hwang, G. J. (2018). Mobile‐based collaborative learning in the fitness center: A case study on the development of English listening comprehension with a context‐aware application. British Journal of Educational Technology, 49(2), 305-320.
Liu, T. Y. (2009). A context-aware ubiquitous learning environment for language listening and speaking. Journal of Computer Assisted Learning, 25(6), 515-527.
Looi, C. K., Zhang, B., Chen, W., Seow, P., Chia, G., Norris, C. et al (2011). 1: 1 mobile inquiry learning experience for primary science students: a study of learning effectiveness. Journal of Computer Assisted Learning, 27(3), 269-287.
Malita, L., & Martin, C. (2010). Digital storytelling as web passport to success in the 21st century. Procedia-Social and Behavioral Sciences, 2(2), 3060-3064.
Marty, P. F., Alemanne, N. D., Mendenhall, A., Maurya, M., Southerland, S. A., Sampson, V., ... & Schellinger, J. (2013). Scientific inquiry, digital literacy, and mobile computing in informal learning environments. Learning, Media and Technology, 38(4), 407-428.
McNamara, D. (2011). Measuring deep, reflective comprehension and learning strategies: challenges and successes. Metacognition and Learning, 6(2), 195-203.
Michalsky, T., & Schechter, C. (2013). Preservice teachers' capacity to teach self-regulated learning: Integrating learning from problems and learning from successes. Teaching and Teacher Education, 30, 60-73.
Narciss, S. & Huth, K. (2006). Fostering achievement and motivation with bug‐related tutoring feedback in a computer‐based training for written subtraction. Learning and Instruction, 16(4), 310-322.
Pajares, F. (1996). Self-efficacy beliefs in academic settings. Review of educational research, 66(4), 543-578.
Panadero, E. (2017). A review of self-regulated learning: six models and four directions for research. Frontiers in Psychology, 8, 422.
Pardo, A., Han, F. F., & Ellis, R. A. (2017). Combining university student self-regulated learning indicators and engagement with online learning events to predict academic performance. IEEE Transactions on Learning Technologies, 10(1), 82-92.
Pintrich, P. R., & De Groot, E. V. (1990). Motivational and self-regulated learning components of classroom academic performance. Journal of Educational Psychology, 82(1), 33-40.
Ruchter, M., Klar, B. & Geiger, W. (2010). Comparing the effects of mobile computers and traditional approaches in environmental education. Computers & Education, 54(4), 1054-1067.
Ruchter, M., Klar, B., & Geiger, W. (2010). Comparing the effects of mobile computers and traditional approaches in environmental education. Computers & Education, 54(4), 1054-1067.
Ruchter, M., Klar, B., & Geiger, W. (2010). Comparing the effects of mobile computers and traditional approaches in environmental education. Computers & Education, 54(4), 1054-1067.
Schunk, D. H., & Zimmerman, B. J. (1996). Modeling and self-efficacy influences on children’s development of self-regulation. In J. Juvonen & K. R. Wentzel (Eds.), Social motivation: Understanding children’s school adjustment (pp. 313-345)., Cambridge studies in social and emotional development New York: Cambridge University Press.
Sharples, M., Milrad, M., Arnedillo, S. I., & Vavoula, G. (2009). Mobile learning: small devices, big issues. In N. Balacheff, S. Ludvigsen, T. de Jong, A. Lazonder, & S. Barnes (Eds.). Technology enhanced learning: principles and products, 233-240. Heidelberg: Springer.
Stoeger, H., Fleischmann, S., & Obergriesser, S. (2015). Self-regulated learning (SRL) and the gifted learner in primary school: the theoretical basis and empirical findings on a research program dedicated to ensuring that all students learn to regulate their own learning. Asia Pacific Education Review, 16(2), 257-267.
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.
Tatar, D., Roschelle, J. M., Vahey, P., & Penuel, W. R. (2003). Handhelds go to school: lessons learned. Computer, 36(9), 30-37
Tu, Y. F., & Hwang, G. J. (2018). The roles of sensing technologies and learning strategies in library-associated mobile learning: a review of 2007-2016 journal publications. International Journal of Mobile Learning and Organisation, 12(1), 42-54.
Wang, S. L. & Wu, C. Y. (2011). Application of context-aware and personalized recommendation to implement an adaptive ubiquitous learning system. Expert Systems with Applications, 38(9), 10831-10838.
Wang, S. L., & Hwang, G. J. (2012). The role of collective efficacy, cognitive quality, and task cohesion in computer-supported collaborative learning. Computers & Education, 58(2), 679-687.
Wu, P. H., Hwang, G. J., Milrad, M., Ke, H. R., & Huang, Y. M. (2012). An innovative concept map approach for improving students' learning performance with an instant feedback mechanism. British Journal of Educational Technology, 43(2), 217-232.
Yoon, H., Woo, A. J., Treagust, D., & Chandrasegaran, A. L. (2014). The Efficacy of Problem-based Learning in an Analytical Laboratory Course for Pre-service Chemistry Teachers. International Journal of Science Education, 36(1), 79-102.
Zhao, H., Chen, L., & Panda, S. (2014). Self‐regulated learning ability of Chinese distance learners. British Journal of Educational Technology, 45(5), 941-958.
Zhonggen, Y., Ying, Z., Zhichun, Y., & Wentao, C. (2018). Student satisfaction, learning outcomes, and cognitive loads with a mobile learning platform. Computer Assisted Language Learning, 1-19. https://doi.org/10.1080/09588221.2018.1517093
Zhou, M., & Li, Z. (2019). Blended mobile learning in theatre arts classrooms in higher education. Innovations in Education and Teaching International, 56(3), 307-317.
Zimmerman, B. J. (2002). Becoming a Self-Regulated Learner: An Overview. Theory Into Practice, 41(2), 64-70.
Zimmerman, B. J., Bonner, S., & Kovach, R. (1996). Developing self-regulated learner: Beyond achievement to self-efficacy. Washington, DC: American Psychological Association.