|
參考文獻 一、中文部分 王昌傑(2004)。學習風格對國中生自然科學習成就之影響(未出版之碩士論文)。慈濟大學,花蓮縣。 王弈云(2015)。高雄市高一學生在多項式方程式單元之錯誤類型分析研究(未出版之碩士論文)。國立高雄師範大學,高雄市。 江采姿(2017)。在數位教材融入國文科教學的情境 下學生學習風格與成效差異之研究 ---以台南市某國中為例(未出版之碩士論文)。吳鳳科技大學,嘉義縣。 吳宇穎(2005)。多媒體組合方式與知覺偏好對學習結果的影響(未出版之碩士論文)。國立中正大學,嘉義縣。 吳志敏(2002)。電腦動畫應用於國中代數概念教學之實驗研究(未出版之碩士論文)。國立臺北科技大學,臺北市。 吳清山,2012“國家教育研究院電子報第 38 期) http://epaper.naer.edu.tw/index.php?edm_no=38&content_no=1011 宋曜廷(2000)。先前知識文章結構和多媒體呈現對文章學習的影響。 臺北:國立臺灣師範大學教育心理與輔導研究所博士論文 (未 出 版)。 林憶辰(2007)。探討多項式乘法中物件、變號、項數對國中學生解題的影響(未出版之碩士論文)。國立臺北教育大學,臺北市。 林寶山 (1990)。教學論:理論與方法。臺北市:五南書局。 凃金堂(民100)。運用「範例(worked-out example)」在國小數學問題解決的教學實驗研究。教育心理學報,43卷1期。 翁榮源、陳定威與呂榮順(民98)。Herrmann 學習風格理論對大學生有機化學學習成就之研究。科學教育月刊,318 ,31-47。 張信忠(2008)。國中數學領域「多項式四則運算」單元之線上適性學習模式研發(未出版之碩士論文)。亞洲大學,臺中市。 張春興(1994)。現代心理學。臺北:東華。臺北:東華。 張琇如(2016)。合作式數學學習的內、外在動機路徑分析。臺灣數學教師,37(1),13-30。doi: 10.6610/TJMT.20160126.0 張嵐雄(2011)。國中生在多項式乘除運算的主要錯誤類型及其補救教學之研究(未出版之碩士論文)。國立臺灣師範大學,台北市。 莊秀卿(2013)。多媒體組合與認知風格對國小自然科學學習成效之影響-以水循環單元為例(未出版之碩士論文)。國立臺灣海洋大學,基隆市。 莊煥銘、陳虹真、沈家成(2007)。學習路徑、學習風格與數位學習績效之研究-以國中數學科為例。第十八屆國際資訊管理學術研討會論文集。 陳育民(2003)。學習風格與學習模式對中學生電子化學習成效之影響(未出版之碩士論文)。國立中正大學 陳怡如(2007)。國二學生在多項式的乘除運算單元錯誤類型之分析研究(未出版之碩士論文)。 國立高雄師範大學,高雄市。 陳密桃(2003)。認知負荷理論及其對教學的啟示。國立高雄師範大學 教育系教育學刊,21,29-51。 陳嘉皇(2017)。學童「圖卡覆蓋」代數推理歷程之研究:以三個個案為例,國立嘉義大學國民教育學報,19, 79-107. 陳靜儀(2013)。多媒體組合與認知風格對國小數學科學習成效之研究-以分數乘法為例(未出版之碩士論文)。國立臺灣海洋大學,基隆市。 湯家偉(譯)(民 105)。結構方程模式--偏最小平方法PLS-SEM(原作者:Joseph F. Hair, G. Tomas M. Hult, Christian M. Ringle.)。臺北市:高等教育文化事業有限公司。(原著出版年: 2014) 程鈺涵(2018)。翻轉教室對不同學習風格之國中生其學習成效之影響(未出版之碩士論文)。中原大學,桃園市。 楊淯丞(2014)。以GeoGebra軟體融入教學對高一學生在多項式函數及其圖形進行補救教學之研究(未出版之碩士論文)。國立臺南大學應用數學系碩士班,台南。 楊惠雯(2010)。虛擬教具應用於國中學生學習多項式展開與因式分解之影響(未出版之碩士論文)。國立交通大學,新竹市。 劉耀明(2007)。學習風格在數位學習環境中對學習成效及學習態度影響之研究(未出版之碩士論文)。國立中正大學,嘉義市。 鄭宏偉(2015)。二階段評量對多項式概念教學成效之研究(碩士論文)。國立高雄師範大學,高雄市。 賴文儀(2013)。圖形表徵融入多項式電子白板教學之成效(未出版之碩士論文)。國立中正大學,嘉義縣。 薛圳宏(2002)。發展數學科教學模組之個案研究-以多項式乘法和因式分解單元為例(未出版之碩士論文)。國立高雄師範大學,高雄市。 鍾志忠(2010)。「同儕個別學習輔導」融入「多項式運算」補救教學之研究(未出版之碩士論文)。國立嘉義大學,嘉義市。 簡綜男(1999)。互動式多媒體輔助教材在電腦教學之學習成效影響研究(未出版之碩士論文)。國立中央大學,中壢市。 羅詩凱(2015)。國中資優數學多項式因式分解之解題策略(未出版之碩士論文)。中原大學,桃園市。 關佩云(2017)。比較臺灣和馬來西亞大學生個人屬性、知覺學習和情緒智力對學習風格影響之研究(未出版之碩士論文)。逢甲大學,台中。 二、外文部分 Ainsworth, S. (1999). The functions of multiple representations. Computer & Education, 33(2/3), 131-152. doi.org/10.1016/S0360-1315(99)00029-9. Ainsworth, S. (2006). DeFT: A conceptual framework for considering learning with multiple representations. Learning and Instruction, 16(3), 183-198. dx.doi.org/10.1016/j.learninstruc.2006.03.001. Amabile, T. M. (1985). Motivation and creativity: Effects of motivational orientation on creative writers. Journal of Personality and Social Psychology, 48, 393–399. dx.doi.org/10.1037/0022-3514.48.2.393. Amabile, T. M. (1993). Motivational synergy: Toward new conceptualizations of intrinsic and extrinsic motivation in the workplace. Human Resource Management Review, 3, 185–201. doi.org/10.1016/1053-4822(93)90012-S. Amabile, T. M., & Mueller, J. S. 2007. Studying creativity, its processes, and its antecedents: An exploration of the componential theory of creativity. In J. Zhou & C. Shalley (Eds.), Handbook of organizational creativity: 31–62. Mahwah, NJ: Erlbaum. Amabile, T. M., DeJong, W., & Lepper, M. (1976). Effects of externally imposed deadlines on subsequent intrinsic motivation. Journal of Personality and Social Psychology, 34, 92–98. Amabile, T. M., Hill, K. G., Hennessey, B. A., & Tighe, E. M. (1994). The Work Preference Inventory: Assessing intrinsic and extrinsic motivational orientations. Journal of Personality and Social Psychology, 66. 950–967. Anderson, J. C., & Gerbing, D. W. (1988). Structural Equation Modeling in Practice: A Review and Recommended Two-Step Approach. Psychological bulletin, 103(3), 411-423. DOI: 10.1037/0033-2909.103.3.411 Arslan, C., Gocmencelebi, S. I., & Tapan, M. S. (2009). Learning and reasoning styles of pre service teachers’: inductive or deductive reasoning on science and mathematics related to their learning style. Procedia Social and Behavioral Sciences, 1, 2460-2465. doi.org/10.1016/j.sbspro.2009.01.432. Atkinson, R. C., & Shiffrin, R. M. (1971). The control processes of short-term memory. Institute for Mathematical Studies in the Social Sciences, Stanford University. Ausubel, D. P. (1960). The use of advance organizers in the learning and retention of meaningful verbal material. Journal of Educational Psychology, 51(5), 267-272. dx.doi.org/10.1037/h0046669. Ausubel, D. P. (1968). Educational psychology. A cognitive view. New York: Holt, Rinehart and Winston, Inc. Ausubel, D. P., J. D. Novak, & H. Hanesian, (1978). Educational psychology: A cognitive view. 2nd edition. New York: Holt, Rinehart, and Winston. Ayersman, D. (1993). An overview of the research on learning styles and hypermedia environments. Paper presented at the 1993 Annual Convention of the Eastern Educational Research Association, Clearwater Beach, Florida. Ayersman, D. J., and Minden, A. V. (1995). Individual differences, computers and instruction. Computers in Human Behavior, 11 (3), 371–390. Baddeley AD (1986). Working memory. Oxford, UK: Clarendon Press; Baddeley A. Working memory: Thought and action. Oxford: Oxford University Press. Baddeley AD, Hitch GJ (1974). Working memory. In: Recent advances in learning and motivation, Vol.8 (Bower GA, ed), 47–90. New York: Academic Press; Baddeley, A. (1997). Human memory: Theory and practice. East Sussex, UK: Psychology Press. Bahar, M. (2009). The Relationships between Pupils' Learning Styles and Their Performance in Mini Science Projects. Educational Sciences: Theory and Practice, 9(1), 31-49. https://eric.ed.gov/?id=EJ837775 . Bandler, R., & Grinder, J. (1975). The structure of magic I. Palo Alto, CA: Science and Behavior Books. Bandler, R., and J. Grinder. 1979. Frogs into princes. Moab, Utah: Real People Press. Behr. M., Lesh, R.. Post, T., & Silver, E. (1983). Rational number concepts. In R. Lesh & M. Landau (Eds.). The acquisition of mathematical concepts and processes. New York: Academic Press. Berthold, K., Renkl, A. (2009). Instructional aids to support a conceptual understanding of multiple representations. Journal of Educational Psychology, 101(1), 70–87. Google Scholar, Crossref. dx.doi.org/10.1037/a0013247 . Bettye C. H. (1999). Using algebra tiles effectively. Prentice-Hall, Inc. New Jersey Billings, D., & Cobb, K. (1992). Effects of learning style preferences, attitude and GPA on learner achievement using computer assisted interactive videodisc instruction. Journal of Computer-Based Instruction, 19 (1), 12-16. Birenbaum, M., & Rosenau, S. (2006). Assessment preferences, learning orientation, and learning strategies of pre-service and in-service teachers. Journal of Education for Teaching, 32 (2), 213-225. doi.org/10.1080/02607470600655300. Blanton M.L., Kaput J.J. (2011) Functional thinking as a route into algebra in the elementary grades. In: Cai J., Knuth E. (eds) Early algebraization. advances in mathematics education. Springer, Berlin, Heidelberg Bruner, J. S.(1966). Toward a theory of instruction. Cambridge, MA: Harvard University. Brusilovsky, P. (1999). Adaptive and intelligent technologies for web-based education. KI – Kunstliche Intelligenz, 13, 19–25. Brusilovsky, P. (2001) Adaptive hypermedia. User Modeling and User Adapted Interaction. 11 (1/2), 87-110. doi.org/10.1023/A:1011143116306 Brusilovsky, P., & Maybury, M. T. (2002). From adaptive hypermedia to the adaptive web. Communications of the ACM, 45(5), 30–33. Brusilovsky, P., Eklund, J., & Schwarz, E. (1998). Web-based education for all: A tool for development adaptive courseware. Computer Networks and ISDN Systems, 30, 291–300. doi.org/10.1016/S0169-7552(98)00082-8. Brusilovsky, P., Maybury, M. T. (2002). From adaptive hypermedia to adaptive Web. In P., Brusilovsky,M. T. Maybury, (eds.), Communications of the ACM 45 (5), Special Issue on the Adaptive Web, 31-33. Burris, S, Kitchel, T., Molina, Q., Vincent, S. & Warner, W. (2008). The language of learning styles. Techniques: Connecting Education & Careers, 83(2), 44-49. Can, Ş. (2010). Determination of the learning styles of the pre-school teacher candidates (The case of Mugla University, Turkey). Procedia social and behavioral sciences, 2, 4137-4141. doi.org/10.1016/j.sbspro.2010.03.653 Carlson, H. (1991). Learning style and program design in interactive multimedia. Educational Technology Research and Development, 39 (3), 41-48. doi.org/10.1007/BF02296437 Carver, C. A., Howard, R. A., & Lane, W. D. (1999). Addressing different learning styles through course hypermedia. IEEE Transactions on Education, 42(1), 33–38. DOI: 10.1109/13.746332 Chang, H. J. (2006). Adaptation in Depth: The Use of ‘Cognitive Object-Oriented Teaching Model’. ED-MEDIA 2006--World Conference on Educational Multimedia, Hypermedia & Telecommunications, Association for the Advancement of Computing in Education, Orlando, FL, USA. Chang, H. J. (2012). Cognizable, Learnable, Expressible, Accessible, and Reasonable Model in Mathematical Thinking, Reasoning and Problem Solving. The Asian Technology Conference in Mathematics, 2012, Advanced Technology Council in Mathematics, Bangkok, Thailand, December 16-20. Chang, H. J. (2013). Evolutions of Thinking, Reasoning, and constructing in Learning Polynomial operations. The Asian Technology Conference in Mathematics_ ATCM-Korea chapter, 2013, Advanced Technology Council in Mathematics, CheongJu, South Korea, August 7-10. Chang, H. J. (2014). The cognitive object-oriented representation in learning and evaluating processes. 7th International Cognitive Load Theory Conference (ICLTC), Taipei, Taiwan, June 24-26. Chang, H. J. (2015). Beyond the Representation: Cognition in Manipulative Learning Objects within Learning Simple Equations. International Journal of Innovations in Engineering and Technology, 5(11), 855-859. doi.org/10.7763/IJIET.2015.V5.626. Chang, H. J. (2016). The Temporal Path Analysis Model of Intrinsic and Extrinsic motivation in cooperative learning environment. International Journal of Learning and Teaching, 2(2), 133-139. doi: 10.18178/ijlt.2.2. doi.org/10.7763/IJIET.2015.V5.626 . Chang, H.J, Tseng, S. S.(2003). Design of an object-oriented teaching model for Three-Dimensional Geometry, The 8TH Asia Technology Conference in Mathematic, 2003, Advanced Technology Council in Mathematics, Hsinchu, Taiwan. 404~413. Chang, H.J. (2005). Enhancing web-based instruction/learning: the use of ‘Cognitive, Object-Oriented Teaching Model’. The 10th Asian Technology Conference in Mathematics, 2005, Advanced Technology Council in Mathematics, Cheong-Ju, South Korea, 213-222 Chang, H.J. (2007a). Adaptation-in-Depth Educational System within the Rule Base Reasoning. ED-MEDIA 2007--World Conference on Educational Multimedia, Hypermedia & Telecommunications, Association for the Advancement of Computing in Education, Vancouver, BC, Canada Chang, H.J. (2007b). The Cognitive, Interactive, Transparent Teaching Interface: An Application to Teach Coordinate Plane. 科學/數學之閱讀、寫作與論證國際研討會, 彰化 (國立彰化師範大學,國立台東大學 主辦) Chang, H.J. (2007c). Beyond the Web-Based Cognitive and Interactive Metacognition Interface within Teaching Similar Triangles. The 12th Asian Technology Conference in Mathematics, 2007, Advanced Technology Council in Mathematics, Taipei, Taiwan, December16-20, 2007. Chang, H.J. (2007d). Cognitive Requirement and management of Cognitive Object-Oriented Teaching Model. The 12th Asian Technology Conference in Mathematics, 2007, Advanced Technology Council in Mathematics, Taipei, Taiwan, December16-20, 2007. Chang, H.J. (2008). Supporting Fault-Tolerance Learning within Cognitive, Object-Oriented Teaching Model, 2008--World Conference on Educational Multimedia, Hypermedia & Telecommunications, Association for the Advancement of Computing in Education, Vienna, Austria, June 30-July 4, 2008. Chang, Y. C., Kao, W.Y., Chu, C. P., Chiu, C. H. (2009) learning style classification mechanism for e-learning, Computers & Education, 53(2), 273-285, doi.10.1016/j.compedu.2009.02.008 Chi, M. T. H., Feltovich, P. J., & Glaser, R. (1981). Categorization and representation of physics problems by experts and novices. Cognitive science, 5, 121-152. doi.org/10.1207/s15516709cog0502_2. Clark, J. M., & Paivio, A. (1991). Dual coding theory and education. Educational Psychology Review, 3, 149-210. doi.org/10.1007/BF01320076 Clark, R. E. (2001). A summary of disagreements with the ‘mere vehicles’ argument. In R. E. Clark (Ed.), Learning from media: Arguments, analysis, and evidence (pp. 125–136). Greenwich, CT: Information Age Publishing Clark, R.C., Nguyen, F., and Sweller, J. (2006). Efficiency in learning: evidence-based guidelines to manage cognitive load. San Francisco: Pfeiffer Colom, R., Abad, F. J., Quiroga, M., Shih, P. C., & Flores-Mendoza, C. (2008). Working memory and intelligence are highly related constructs, but why? Intelligence, 36, 584–606. doi.org/10.1016/j.intell.2008.01.002 Csikszentmihalyi, M. (1996). Creativity, flow and the psychology of discovery and invention. New York: Harper Collins. Csikszentmihalyi, Mihaly (1975). Beyond Boredom and Anxiety: Experiencing Flow in Work and Play, San Francisco: Jossey-Bass. Csikszentmihalyi, Mihaly (1978) Intrinsic Rewards and Emergent Motivation in The Hidden Costs of Reward: New Perspectives on the Psychology of Human Motivation eds Lepper, Mark R; Greene, David, Erlbaum: Hillsdale: NY 205-216 Davidson, G., & Savenye, W. (1992, Spring). How do learning styles relate to performance in a computer applications course? Journal of Research on Computing in Education, 24 (3), 348-357. doi.org/10.1080/08886504.1992.10782016 Deci, E. L. (1971). Effects of externally mediated rewards on intrinsic motivation. Journal of Personality and Social Psychology, 18, 105–115. DOI: 10.1037/h0030644 Deci, E. L. (1972) Intrinsic motivation, extrinsic reinforcement, and inequity. Journal of Personality and Social Psychology, 22, 113-120. dx.doi.org/10.1037/h0032355 Deci, E. L. (1975). Intrinsic motivation. New York: Plenum. Deci, E. L., & Ryan, R. M. (1985). Intrinsic motivation and self-determination in human behavior. New York: Plenum. Deci, E. L., Koestner, R., & Ryan, R. M. (1999). A meta-analytic review of experiments examining the effects of extrinsic rewards on intrinsic motivation. Psychological Bulletin, 125, 627– 668. Dunn, R., & Bruno, A. (1985, September). What does the research on learning styles have to do with Mario? The Clearing House, 59 (1), 9-12. doi.org/10.1080/00098655.1985.9955590 Dunn, R., & Dunn, K. (1994). Teaching young children through their individual learning styles-practical approaches for grades K-2. Massachusetts: Simon & Schuster. Dunn, R., and Dunn, K. (1974). Learning Style as a Criterion for Placement in Alternative Programs. Phi Delta Kappan, 56 (4), 275-278. Eilam, B. & Poyas, Y. (2008). Learning with multiple representations: Extending multimedia learning beyond the lab. Learning and Instruction, 16, 368-378. doi.org/10.1016/j.learninstruc.2007.07.003. Eisenberger, R., & Cameron, J. (1996). Detrimental effects of reward: Reality or myth? Journal of the American Psychological Association, 51, 1153-1166. doi.org/10.1177/108705479700200115 Ellis, D., Ford, N., & Wood, F. (1993, February). Hypertext and learning styles. The Electronic Library, 11 (1), 13-18. doi.org/10.1108/eb045203 Essalmi, F., Ayed, L. J. B., Jemni, M., Kinshuk, & Graf, S. (2010). A fully personalization strategy of E-learning scenarios. Computers in Human Behavior, 26(4), 581-591. doi.org/10.1016/j.chb.2009.12.010 Felder, R. M. & Soloman, B. A. (1993). Learning styles and strategies. Retrieved April 7, 2018, From North Carolina State University, http://www4.ncsu.edu/unity/lockers/users/f/felder/public//ILSdir/styles.htm Felder, R. M. (n.d.) Are learning style invalid? Retrieved April 7, 2018, From North Carolina State University, http://www4.ncsu.edu/unity/lockers/users/f/felder/public/Papers/LS_Validity(On-Course).pdf Felder, R. M., & Silverman, L. K. (1988). Learning and teaching styles in engineering education. Engineering Education, 78(7), 674–681. Preceded by a preface in 2002: http://www.ncsu.edu/felderpublic/ Papers/LS-1988.pdf Felder, R. M., & Silverman, L. K. (2016, Dec) Index of Learning Styles Questionnaire. Retrieved from North Carolina State University. https://www.webtools.ncsu.edu/learningstyles/ Fenrich, P. (2005). Creating Instructional Multimedia Solutions: Practical Guidelines for the Real World. Santa Rosa, CA: Informing Science Press. Fenrich, P. (2006). Getting practical with learning styles in “Live” and computer-based training settings. Issues in informing science and information technology. 3. 233-242. doi.org/10.28945/886. Fleming, N.D. (1995). I'm different; not dumb. Modes of presentation (VARK) in the tertiary classroom, in Zelmer,A., (ed.) Research and Development in Higher Education, Proceedings of the 1995 Annual Conference of the Higher Education and Research Development Society of Australasia (HERDSA),HERDSA, Volume 18, 308 – 313. Gagne, E. D. (1985). The cognitive psychology of school learning. Boston, MA: Little, Brown and Company. Gagne´, M., & Deci, E. L. (2005). Self-determination theory and work motivation. Journal of Organizational Behavior, 26, 331–362. doi.org/10.1002/job.322 Garger, S. & Guild, P. (1984). Learning Styles: The Crucial Differences. Curriculum Review, 9-12. Geisert, G., & Dunn, R. (1991). Effective use of computers: Assignments based on individual learning styles. The Clearing House, 64 (4), 219-224. Given, B. K. (2000). Learning Styles: A guide for teachers and parents. South Coast Highway Oceanside: Learning Forum Publication. doi.org/10.1002/dys.193 Giorgi, P., (2011).On polynomial multiplication in chebyshev basis, IEEE Transactions on Computers, 61, 780-789. doi:10.1109/TC. 2011.110 Goldin, G. & Janvier, C. (1998). Representation and the psychology of mathematics education. The Journal of Mathematics Behaviour, 17 (1), 1-4. doi.org/10.1016/S0732-3123(99)80057-1 Goldin, G. & Shteingold, (2001). System of representations and the development of mathematical concepts. In A. Cuoco & F. R. Curcio (Eds.), The roles of representation in school mathematics (pp. 1-23). Yearbook 2001. Reston, VA: NCTM. Graf, S., Viola, S.R., Leo, T., Kinshuk, (2007). In-Depth Analysis of the Felder-Silverman Learning Style Dimensions, Journal of Research on Technology in Education, 40(1), 79-93. Gregorc, A. F. (1979). Learning/teaching styles: Their nature and effects. In National Association of Secondary School Principals (Eds.), Student learning styles: Diagnosing and prescribing programs (pp. 19-26). Reston, VA: NASSP. Gregorc, A. F. (1985). Inside styles: Beyond the basics. Columbia, CT: Gregorc Associates. Guild, P., & Garger, S. (1985). Marching to different drummers. Alexandria, VA: Association for Supervision and Curriculum Development. Hair, J. F., Hult, G. T. M., Ringle, C. M., and Sarstedt, M. 2017. A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). 2nd edition. Thousand Oaks, CA: Sage. Hair, J. F., Ringle, C.M. Sarstedt, M. (2011). PLS-SEM: Indeed a Silver Bullet, Journal of Marketing Theory and Practice (JMTP), 19, Issue 2, pp. 139-152. DOI: 10.2753/MTP1069-6679190202 Hair, J. F., Sarstedt, M. Torsten M. Pieper, and Christian M. Ringle. (2012a). The Use of Partial Least Squares Structural Equation Modeling in Strategic Management Research: A Review of Past Practices and Recommendations for Future Applications. Long Range Planning 45 (5-6). 320-340. doi.org/10.1016/j.lrp.2012.09.008 Hair, J. F., Sarstedt, M., Christian M., Ringle, C. M., and Jeannette A. Mena. (2012b). An Assessment of the Use of Partial Least Squares Structural Equation Modeling in Marketing Research. Journal of the Academy of Marketing Science 40 (3). 414-433. doi.org/10.1007/s11747-011-0261-6 Hardman, K.O. & Cowan, N. (2016). Reasoning and memory: People make varied use of the information available in working memory. Journal of Experimental Psychology: Learning Memory and Cognition, 42(5), 700-22. doi: 10.1037/xlm0000197 Harr, N. Eichler, A. and Renkl, A. (2014) Integrating pedagogical content knowledge and pedagogical/psychological knowledge in mathematics. Front. Psychol. (5), 924. doi.org/10.3389/fpsyg.2014.00924. Harr, N., Eichler, A., and Renkl, A. (2014). Integrating pedagogical content doi: 10.3389/fpsyg.2014.00924 Heinze, A., Star, J. R., & Verschaffel, L. (2009). Flexible and adaptive use of strategies and representations in mathematics education. Zentralblatt Didaktik für Mathematik (ZDM), 41(5), 535-540. doi: 10.1007/s11858-009-0214-4. Honey, P. and Mumford, A. (1986a). The Manual of Learning Styles, Peter Honey Associates. Honey, P. and Mumford, A. (1986b). Learning Styles Questionnaire, Peter Honey Publications Ltd. Honey, P., & Mumford, A. (1982). The manual of learning styles. Maidenhead Jitendra, A.K., Hoff, K., & Beck. M.M. (1999). Teaching middle school students with learning disabilities to solve word problems using a schema-based approach. Remedial and Special Education, 20(1), 50-64. doi.org/10.1177/074193259902000108 Jitendra, A.K., Star, J.R., Rodriguez, M., Lindell, M., & Someki, F. (2011). Improving students’ proportional thinking using schema-based instruction. Learning and Instruction, 21(6), 731-745. doi: 10.1016/j.learninstruc.2011.04.002 Jitendra, A.K., Star, J.R., Starosta, K., Leh, J.M., Sood, S., Caskie, G., Hughes, C.L., & Mack, T.R. (2009). Improving seventh grade students’ learning of ratio and proportion: The role of schema-based instruction. Contemporary Educational Psychology, 34(3), 250-264. doi: 10.1016/j.cedpsych.2009.06.001 Johnson, D. W. and Johnson, R. T. (2002) Learning Together and Alone: Overview and Meta-analysis, Asia Pacific Journal of Education, 22, 95- 105. doi.org/10.1080/0218879020220110 Jöreskog, K. G. (1973), A General Method for Estimating a Linear Structural Equation System, in Structural Equation Models in the Social Sciences, ed. A. S. Goldberger and O. D. Duncan, New York: Seminar Press. Kaliská, L. (2012). Felder's learning style concept and its index of learning style questionnaire in the slovak conditions. GRANT journal. http://www.grantjournal.com/issue/0101/PDF/0101kaliska.pdf. Kaliská, L., (2012). Felder’s Learning Style Concept and its Index of Learning Style Questionnaire in the Slovak Conditions. Grant Journal, 1: 52-56. Kalyuga, S. (2005). Prior knowledge principle in multimedia learning. In R. Mayer (Ed.), Cambridge handbook of multimedia learning (pp. 325–337). New York: Cambridge University Press. Kalyuga, S. (2006). Instructing and testing advanced learners: A cognitive load approach. New York: Nova Science Publishers. Kalyuga, S. (2008). Relative effectiveness of animated and static diagrams: An effect of learner prior knowledge. Computers in Human Behavior, 24, 852 – 861. doi.org/10.1016/j.chb.2007.02.018 Kalyuga, S., Ayres, P., Chandler, P., & Sweller, J. (2003). Expertise reversal effect. Educational Psychologist, 38, 23–31. doi.org/10.1207/S15326985EP3801_4 Kaput, J. (1999). Representations, inscriptions, descriptions and learning: a kaleidoscope of windows. Journal of Mathematical Behavior, 17(2), 265–281. doi.org/10.1016/S0364-0213(99)80062-7 Kearsley, G. (2000). Online education: Learning and technology in cyberspace. Toronnto, Canda: Wadsworth. (chap.1-2) knowledge and pedagogical/psychological knowledge in mathematics. Front. Kolb, D. A. (1984). Experiential learning: Experience as the source of learning and development. Englewood Cliffs, NJ: Prentice-Hall Kuljis, J., & Liu, F. (2005). A Comparison of learning style theories on the suitability for Elearning. Web Technologies, Applications, And Services. La Garanderie, A. (1993). Les profils pédagogiques. Paris, Bayard, Tunis, Publications de l’ATURED. In A. Chabchoub (Ed.), Enseigner à l’Université de la théorie à la pratique, 2006. Larkin, J. H. (1981). Cognition of learning physics. American Journal of Physics, 49, 534-541. doi.org/10.1119/1.12667 Leitze, A. R., & Kitt, N. A. (2000). homemade algebra tiles to develop algebra and prealgebra concepts. Mathematics teacher. 462-466. Lesh, R., Post, T., & Behr, M. (1987). Representations and translations among representations in mathematics learning and problem solving. In C. Janvier, (Ed.), Problems of representations in the teaching and learning of mathematics (33-40). Hillsdale, NJ: Lawrence Erlbaum. Levin, J.R., Anglin, G.J. and Carney, R.N. (1987) On empirically validating functions of pictures in prose. In: Willows, D.M. and Houghton, H.A., Eds., The Psychology of Illustration: Basic Research, Springer, New York, 51-85. dx.doi.org/10.1007/978-1-4612-4674-9_2. Lewin, K. (1936). Principles of topological psychology. New York: McGraw-Hill. Lowry, P. B., & Gaskin, J. (2014). Partial least squares (PLS) structural equation modeling (SEM) for building and testing behavioral causal theory: When to choose it and how to use it. IEEE Transactions on Professional Communication, 57(2), 123-146. doi.org/10.1109/TPC.2014.2312452 MathGains. (n.d.). A concrete Introduction to the abstract concepts of integers and algebra using algebra tiles. 33-39. Retrieved March 8, 2017, from http://www.edugains.ca/resourcesMath/CE/LessonsSupports/Manipulatives/ Mayer, R. E. (2003). The promise of multimedia learning: Using the same instructional design methods across different media. Learning and Instruction, 13, 125-139. doi.org/10.1016/S0959-4752(02)00016-6 Mayer, R. E. (2005). Cognitive theory of multimedia learning. In R.E. Mayer (Ed.), The Cambridge Handbook of Multimedia Learning. New York: Cambridge University Press. Mayer, R. E., & Gallini, J. K. (1990). When is an illustration worth ten thousand words? Journal of Educational Psychology, 82, 715-726. dx.doi.org/10.1037/0022-0663.82.4.715 Mayer, R. E., & Moreno, R. (1998). A split-attention effect in multimedia learning: Evidence for dual processing systems in working memory. Journal of Educational Psychology, 90(2), 312-320. dx.doi.org/10.1037/0022-0663.90.2.312 McAuley, E., Duncan, T., & Tammen, V. V. (1989). Psychometric properties of the Intrinsic Motivation Inventory in a competitive sport setting: A confirmatory factor analysis. Research Quarterly for Exercise and Sport, 60, 48-58. doi: 10.1080/02701367.1989.10607413 Meltzoff AN, Prinz W, (2002). editors. The imitative mind: Development, evolution and brain bases. Cambridge: Cambridge University Press; Miller, G. A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63, 81–97. dx.doi.org/10.1037/h0043158 Miller, L. (2005). Using learning styles to evaluate computer-based instruction. Computers in Human Behavior, 21, 287-306. doi.org/10.1016/j.chb.2004.02.011 Mullis, I. V. S., Martin, M. O., Foy, P., & Hooper, M. (2016). TIMSS 2015 International Results in Mathematics. Chestnut Hill, MA: Boston College. Retrieved from http://timssandpirls.bc.edu/ timss2015/international-results/timss-2015/mathematics/student-engagement-and-attitudes/students-views-on-engaging-teaching-in-mathematics/ Mullis, I.V.S., Martin, M.O., Foy, P., & Arora, A. (2012). TIMSS 2011 international results in mathematics. Chestnut Hill, MA: Boston College. Mwangi, W., & Sweller, J. (1998). Learning to solve compare word problems: The effect of example format and generating self-explanations. Cognition and Instruction, 16, 173-199. National Council of Teachers of Mathematics (NCTM). (2002). Principles and Standards forSchool Mathematics. Reston, VA: NCTM.Hartley, S., Gerhardt-Powals, J., Jones, D., McCormack, C., Medley, M. D., Price, B., Reek, M., and Summers, M. K., (1996). Enhancing teaching using the Internet: Report of the working group on the World Wide Web as an interactive teaching resource. In Proceedings of the Conference on Integrating Technology into Computer Science Education. Barcelona, Spain National Council of Teachers of Mathematics. (2000). Principles and Standards for School Mathematics. Available at: http://www.nctm.org/standards/content.aspx id=16909 [accessed May 05,2018]. National Mathematics Advisory Panel. (2008). Final Report: Foundations for Success. Western initiative for strengthening education in math. WISE Math. http://wisemath.org/us-national-advisory-panel/. Okur, M., & Bahar, H. H. (2010). Learning styles of primary education prospective mathematics teachers; states of trait-anxiety and academic success. Procedia social and behavioral sciences, 2, 3632-3637. doi.org/10.1016/j.sbspro.2010.03.565 Paas, F. G. W. C., Renkl, A. & Sweller, J. (2004). Cognitive load theory: instructional implications of the interaction between information structures and cognitive architecture. Instructional Science, 32, 1-8. dx.doi.org/10.1023/B:TRUC.0000021806.17516.d0. Paredes, P., and Rodríguez, P. (2004). A Mixed Approach to Modelling Learning Styles in Adaptive Educational Hypermedia. Advanced Technology for Learning, 1 (4), 210–215. Pass, F., Renkl, A., & Sweller, J. (2003). Cognitive load theory and instructional design: Recent developments. Educational Psychologist, 38(1), 1-4. Peña, C.-I., Marzo, J.-L., and de la Rosa, J.-L. (2002). Intelligent Agents in a Teaching and Learning Environment on the Web. In V. Petrushin, P. Kommers, Kinshuk & I. Galeev (Eds.), Proceedings of the International Conference on Advanced Learning Technologies. Palmerston North, NZ, IEEE Learning Technology Task Force, pp. 21-27. Peterson, L., & Peterson, M. (1959). Short-term retention of individual verbal items. Journal of Experimental Psychology, 58, 193–198. dx.doi.org/10.1037/h0049234 Picciotto, H. (1990) The Algebra Lab. Sunnyvale, CA: Creative Publications. Picciotto, H., & Wah, A. (1993). A new algebra: Tool, themes, concepts. Journal of Mathematical Behavour, 12(1), 19-42. Pintrich, P.R.(2003).Motivational Science Perspective on the Role of Student Motivation in Learning and Teaching Contexts. Journal of educational psychology, 95(4).667–686 Pollock, E., Chandler, P. A. & Sweller, J. (2002). Assimilating complex information. Learning and Instruction, 12 (1), 61-86. Price, L. (2004, October). Individual differences in learning: Cognitive control, cognitive style, and learning style. Educational Psychology, 24 (5), 681-698. doi.org/10.1080/0144341042000262971. Quilici, J. L., & Mayer, R. E. (1996). Role of examples in how students learn to categorize statistics word problems. Journal of Educational Psychology, 88(1), 144-161. dx.doi.org/10.1037/0022-0663.88.1.144 Relan, A., & Gillani, B. (1997). Web-based instruction and the traditional classrooms: Similarities and differences. In Khan BH(eds.), Web-based Instruction. Englewood Cliffs, NJ: Educational Technology Publications, 417-423. Russel, D. (2011). The distributive property. Retrieved May 15, 2018, from http://math.about.com/od/algebra/a/distributive.htm Ross, J., & Schulz, R. (1999). Can computer-aided instruction accommodate all learners equally? British Journal of Educational Technology, 30 (1), 5-24. doi.org/10.1111/1467-8535.00087 Ryan, R. M., & Deci, E. L., (2000). Intrinsic and Extrinsic Motivations: Classic Definitions and New Directions. Contemporary Educational Psychology 25, 54–67. Schnotz, W. & Kürschner, C. (2008). External and internal representations in the acquisition and use of knowledge: visualization effects on mental model construction. Instructional Science, 36 (3), 175–190. doi.org/10.1007/s11251-007-9029-2 Schnotz, W., & Bannert, M. (2003). Construction and interference in learning from multiple representations. Learning and Instruction, 13, 141-156. doi.org/10.1016/S0959-4752(02)00017-8 Schnotz, W., & Kulhavy, R. W. (Eds.). (1994). Comprehension of graphics. Amsterdam: NorthHolland. Schnotz, W., Ku ̈rschner, C. (2007). A reconsideration of cognitive load theory. Educ Psychol Rev. 19(4), 469–508. doi.org/10.1007/s10648-007-9053-4 Seufert, T., & Brünken, R. (2006). Cognitive load and the format of instructional aids for coherence formation. Applied Cognitive Psychology. 20, 321–331.doi: 10.1002/acp.1248 Shaaron, A. (1999). The functions of multiple representations. Computers & Education, 33, 131-152. Shang, Y., H. Shi, and S.-S. Chen. 2001. An intelligent distributed environment for active learning. ACM Journal of Educational Resources in Computing, 1 (2). Shivers, D. G. V., Nowlin, B., &Lanouette, M. (2002). Do multimedia lesson structure and learning styles influence undergraduate writing performance?.College Student Journal,36(1),20-32. Smith, L., & Renzulli, J. (1984). Learning style preferences: A practical approach for classroom teachers. Theory Into Practice, 23 (1), 44-50. Stash, N., Cristea, A. and De Bra, P. (2006a). Adaptation to Learning Styles in ELearning: Approach Evaluation. In T. Reeves & S. Yamashita (Eds.), Proceedings of World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education. Chesapeake, VA, AACE, pp. 284-291. Stash, N., Cristea, A. and De Bra, P. (2006b) ‘Learning styles adaptation language for adaptive hypermedia’, Proceedings of AH’2006 Conference, Dublin, Ireland, pp.323–327. Steele, D., Palensky, J., Lynch, T., Lacy, N., & Duffy, S. (2002). Learning preferences, computer attitudes, and student evaluation of computerized instruction. Medical Education, 36, 225-232. Suits, J., & Lagowski, J. (1994). Chemistry problem-solving abilities: Gender, reasoning level and computer-simulated experiments. Paper presented at the Annual Meeting of the National Association for Research in Science Teaching, Anaheim, California. Suzuki.J.(1999). Multiplying and dividing polynomials using Geloxia. The college mathematics journal. 30(1), 50-53. Sowell, E. (1989). Effects of manipulative materials in mathematics instruction. Journal for Research in Mathematics Education, 20, 498-505. Sweller, J. (1988). Cognitive load during problem solving: effects on learning. Cognitive Science, 12, 257-285. Sweller, J. (1994). Cognitive load theory, learning difficulty and instructional design. Learning and Instruction, 4, 295-312. Sweller, J. (2003). Evolution of human cognitive architecture. In B. Ross (Ed.), The psychology of learning and motivation, 43 (pp. 215-266). San Diego: Academic Press. Sweller, J. (2004). Intructional design consequences of an analogy between evolution by natural selection and human cognitive architecture. Intructional science, 32, 9-31 Sweller, J., & Sweller, S. (2006). Natural information processing systems. Evolutionary Psychology, 4, 434-458. Sweller, J., (2007). Human cognitive architecture in J. M. Spector, M. D. Merrill, J. Van Merrienboer, and M. P. Driscoll (Eds.) Handbook of Research for Educational Communications and Technology (3rd Edition). Routledge//Taylor & Francis Group, 85-96. Sweller, J., Van Merriënboer, J. J. G. & Paas, F. G. W. C. (1998). Cognitive architecture and instructional design. Educational Psychology Review, 10(3), 251-285. doi.org/10.1023/A:1022193728205 Takacs, J., Reed, W., Wells, J., & Dombrowski, L. (1999, Summer). The effects of online multimedia project development, learning style, and prior computer experiences on teacher’s attitudes toward the Internet and hypermedia. Journal of Research on Computing in Education, 31 (4), 341-355. Tulbure, C. (2011). Do different learning styles require differentiated teaching strategies? Procedia social and behavioral sciences. 11, 155–159. http://dx.doi.org/10.1016/j.sbspro.2011.01.052 Van Merrienboer, J. J. G. (1997). Training Complex Cognitive Skills: A Four-Component Instructional Design Model for Technical Training, Educational Technology Publications, Englewood Cliffs, NJ. Van Merrienboer, J. J. G., and Dijkstra, S. (1997). The four-component instructional designmodel for training complex cognitive skills. In Tennyson, R. D., and Schott, F. (eds.), Instructional Design: Theory and Research (Vol. 1), Lawrence Erlbaum, Hillsdale, NJ. Weinstein, C. E. & Mayer, R. (1986). The teaching of learning strategies. In M. C. Wittrock (Ed.), Handbook of research on teaching (pp.315-327). New York: Macmillan. Weinstein, C. E., & Underwood, V. L. (1985). Learning strategies: The how of learning. In J. Segal, S. Chipman, & R. Glaser (Eds.), Relating instruction to basic research. Hillsdale, NJ: Lawrence Erlbaum. Yerushalmy, M. (1991). Students' perceptions of aspects of algebric function using multiple representation software. Journal of Computer Assisted Learning, 7, 42-57.
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