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Articles

Informed integration of IWB technology, incorporated with exposure to varied mathematics problem-solving skills: its effect on students’ real-time emotions

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Pages 1128-1151 | Received 31 May 2018, Published online: 02 Jan 2019

References

  • OECD. Connected minds: technology and today’s learners. Paris: OECD; 2012.
  • Angeli C, Valanides N. Epistemological and methodological issues for the conceptualization, development, and assessment of ICT–TPCK: Advances in technological pedagogical content knowledge (TPCK). Comput Educ. 2009;52:154–168. doi: 10.1016/j.compedu.2008.07.006
  • Koehler MJ, Mishra P. Introducing TPCK. In AACTE Committee on Innovation and Technology (Ed.), Handbook of technological pedagogical content knowledge (TPCK) for educators. New York: Routledge; 2008. p. 3–29.
  • Kohen Z, Kramarski B. Developing a TPCK-SRL assessment scheme for conceptually advancing technology in education. Stud Educ Eval. 2012;38:1–8. doi: 10.1016/j.stueduc.2012.03.001
  • Mishra P, Koehler MJ. Technological pedagogical content knowledge: a framework for teacher knowledge. Teach Coll Rec. 2006;108(6):1017–1054. doi: 10.1111/j.1467-9620.2006.00684.x
  • Niess ML. Preparing teachers to teach science and mathematics with technology: developing a technology pedagogical content knowledge. Teaching Teacher Educ. 2005;21(5):509–523. doi: 10.1016/j.tate.2005.03.006
  • Israel Ministry of Education. (2015). Adapting the educational system to the 21st century. Available from: http://cms.education.gov.il/NR/rdonlyres/79B5A8CF-F812-4A63-89BE-3BEFEB887EC5/142454/12.pdf [in Hebrew]
  • Puentedura R. Transformation, technology, and education [Blog post]; 2006. Available from: http://hippasus.com/resources/tte/
  • Blau I. Teachers for ‘smart classrooms’: the extent of implementation of an interactive Whiteboard-based professional development program on elementary teachers’ instructional practices. Interdisc J E-Learning Objects. 2011;7:275–289.
  • Glover D, Miller D. Running with technology: the pedagogic impact of the large-scale introduction of interactive whiteboards in one secondary school. J Inf Technol Teach Educ. 2001;10(3):257–278.
  • Smith HJ, Higgins S, Wall K, et al. Interactive whiteboards: boon or bandwagon? A critical review of the literature. J Comput Assist Learn. 2005;21(2):91–101. doi: 10.1111/j.1365-2729.2005.00117.x
  • Betcher C, Lee M. The interactive whiteboard revolution: teaching with IWBs. Victoria: ACER Press; 2009.
  • Gregorcic B, Etkina E, Planinsic G. A new way of using the interactive whiteboard in a high school physics classroom: a case study. Res Sci Educ. 2018;48(2):465–489. doi: 10.1007/s11165-016-9576-0
  • Courant R, Robbins H. What is mathematics? London: Oxford University Press; 1996.
  • Duval R. A cognitive analysis of problems of comprehension in a learning of mathematics. Educ Stud Math. 2006;61:103–131. doi: 10.1007/s10649-006-0400-z
  • Schoenfeld AH. Learning to think mathematically: problem solving, metacognition, and sense-making in mathematics. In: Grouws D, editor. Handbook for research on mathematics teaching and learning. New York (NY): MacMillan; 1992. p. 334–370.
  • Zollman A, Smith MC, Reisdorf P. Identity development: critical components for learning in mathematics. In: Brahier D, editor. Motivation and disposition: pathways to learning mathematics. Seventy-third national council of teachers of mathematics yearbook. Reston (VA): Author; 2011. p. 43–53.
  • Mayer RE. Cognitive, metacognitive, and motivational aspects of problem solving. Instr Sci. 1998;26(1–2):49–63. doi: 10.1023/A:1003088013286
  • Pekrun R, Linnenbrink-Garcia L. Conclusions and future directions. In: Pekrun R, Linnenbrink-Garcia L, editors. International handbook of emotions in education. New York: Taylor & Francis; 2014. p. 659–675.
  • Berch DB, Mazzocco MM. Why is math so hard for some children? Baltimore (MD): Paul H Brookes; 2007.
  • Pekrun R, Goetz T, Frenzel AC, et al. Measuring emotions in students’ learning and performance: The achievement emotions questionnaire (AEQ). Contemp Educ Psychol. 2011;36(1):36–48. doi: 10.1016/j.cedpsych.2010.10.002
  • Pintrich, PR. A process-oriented view of student motivation and cognition. In: Stark JS, Mets L, editors. Improving teaching and learning through research. New directions for institutional research. Vol. 57. San Francisco: Jossey-Bass; 1988. p. 55–70.
  • Bandura A. Self-efficacy: toward a unifying theory of behavioral change. Psychol Rev. 1977;84(2):191–215. doi: 10.1037/0033-295X.84.2.191
  • Schukajlow S, Rakoczy K, Pekrun R. Emotions and motivation in mathematics education: theoretical considerations and empirical contributions. ZDM. 2017;49(3):307–322. doi: 10.1007/s11858-017-0864-6
  • Liao W, Zhang W, Zhu Z, et al. Toward a decision-theoretic framework for affect recognition and user assistance. Int J Human Comput Stud. 2006;64(9):847–873. doi: 10.1016/j.ijhcs.2006.04.001
  • Hohenwarter M, Preiner J. Dynamic mathematics with GeoGebra. J Online Math Appl. 2007;7, March 2007, Article ID 1448.
  • Glover D, Miller D, Averis D, et al. The interactive whiteboard: a literature survey. Technol Pedagogy Educ. 2005;14(2):155–170. doi: 10.1080/14759390500200199
  • Digregorio P, Sobel-Lojeski K. The effects of interactive whiteboards (IWBs) on student performance and learning: a literature review. J Educ Technol Syst. 2010/1941;38(3):255–312. doi: 10.2190/ET.38.3.b
  • Schuck S, Kearney M. Exploring pedagogy with interactive whiteboards: a case study of six schools. Sydney: University of Technology Sydney; 2007.
  • Gray C, Hagger-Vaughan L, Pilkington R, et al. The pros and cons of interactive whiteboards in relation to the key stage 3 strategy and framework. Language Learning J. 2005;32:38–44. doi: 10.1080/09571730585200171
  • Levy P. Interactive whiteboards in learning and teaching in two Sheffield schools: a developmental study. Sheffield: Department of Information Studies, University of Sheffield; 2002.
  • Solvie, P. The digital whiteboard: a tool in early literacy instruction. Read Teach. 2004;57(5):484–487.
  • Lee B, Boyle M. Teachers tell their story: interactive whiteboards at Richardson Primary School; 2004.
  • Holmes K. Planning to teach with digital tools: introducing the interactive whiteboard to pre-service secondary mathematics teachers. Aust J Educ Technol. 2009;25(3):351–365.
  • Moss G, Jewitt C, Levačić R, et al. The interactive whiteboards, pedagogy and pupil performance evaluation: an evaluation of the Schools Whiteboard Expansion (SWE) project: London Challenge; 2007.
  • Gillen J, Staarman JK, Littleton K, et al. A ‘learning revolution’? Investigating pedagogic practice around interactive whiteboards in British primary classrooms. Learning Media Technol. 2007;32(3):243–256. doi: 10.1080/17439880701511099
  • Ainley J, Button T, Clark-Wilson A, et al. (2011). Digital technologies and mathematics education. Available from https://www.ncetm.org.uk/files/9793653/JMC_Digital_Technologies_Report_2011.pdf
  • Bray A, Tangney B. Technology usage in mathematics education research – a systematic review of recent trends. Comput Educ. 2017;114:255–273. doi: 10.1016/j.compedu.2017.07.004
  • Lacina J. Interactive whiteboards: creating higher-level, technological thinkers? Childhood Educ. 2009.
  • Jonassen DH. Modeling with technology: mindtools for conceptual change. 3rd ed. Upper Saddle River (NJ): Prentice-Hall; 2006.
  • Moreno-Armella L, Hegedus SJ, Kaput JJ. From static to dynamic mathematics: historical and representational perspectives. Educ Stud Math. 2008;68(2):99–111. doi: 10.1007/s10649-008-9116-6
  • Salomon G. Technology and education in the age of information. Hifa: Zmora-Bitan [In Hebrew]; 2000.
  • Mullis IVA, Martin MO, Ruddock GJ, et al. TIMSS 2011 assessment frameworks. Boston (MA): TIMMS & PIRLS International Study Center; 2009.
  • Israel Ministry of Education. (2006). A mathematics curriculum for elementary school students for all sectors. Available from http://cms.education.gov.il/EducationCMS/Units/Tochniyot_Limudim/Math_Yesodi/TochnitLimudim/AlHatochnit/Mavo.htm
  • Goldin GA. Discrete mathematics and the affective dimension of mathematical learning and engagement. In: Hart EW, Sandefur J, editors, Teaching and learning discrete mathematics worldwide: curriculum and research. Cham: Springer; 2017. p. 53–65.
  • Pekrun R. The control-value theory of achievement emotions: assumptions, corollaries, and implications for educational research and practice. Educ Psychol Rev. 2006;18(4):315–341. doi: 10.1007/s10648-006-9029-9
  • Eccles JS, Adler TF, Futterman R, et al. Expectancies, values, and academic behaviors. In: JT Spence, editor. Achievement and achievement motivation. San Francisco: Freeman; 1983. p. 75–146.
  • Weiner B. An attributional theory of achievement motivation and emotion. Psychol Rev. 1985;92:548–573. doi: 10.1037/0033-295X.92.4.548
  • Pintrich PR. The role of motivation in promoting and sustaining self-regulated learning. Int J Educ Res. 1999;31(6):459–470. doi: 10.1016/S0883-0355(99)00015-4
  • Bandura A. Perceived self-efficacy in cognitive development and functioning. Educ Psychol. 1993;28:117–148. doi: 10.1207/s15326985ep2802_3
  • Hackett G, Betz NE. An exploration of the mathematics self-efficacy mathematics performance correspondance. J Res Math Educ. 1989;20(3):261–273. doi: 10.2307/749515
  • Campbell D, Stanley J. Experimental and quasi-experimental designs for research on teaching. In: Gage N, editor. Handbook of research on teaching. Chicago (IL): Rand McNally; 1963. p. 171–246.
  • Pajares F, Miller MD. Mathematics self-efficacy and mathematics performances: the need for specificity of assessment. J Couns Psychol. 1995;42(2):190. doi: 10.1037/0022-0167.42.2.190
  • Thomas DR. A general inductive approach for analyzing qualitative evaluation data. Am J Eval. 2006;27(2):237–246. doi: 10.1177/1098214005283748
  • Zhang Y, Wildemuth BM. Unstructured interviews. In: Wildemuth B, editor. Applications of social research methods to questions in information and library science. Westport (CT): Libraries Unlimited; 2009. p. 222–231.
  • Barak M, Ashkar T, Dori YJ. Learning science via animated movies: its effect on students’ thinking and motivation. Comput Educ. 2011;56(3):839–846. doi: 10.1016/j.compedu.2010.10.025
  • Hoyles C, Noss R. What can digital technologies take from and bring to research in mathematics education? In: Second international handbook of mathematics education. Dordrecht: Kluwer; 2003. p. 323–349.
  • Cannady MA, Greenwald E, Harris KN. Problematizing the STEM pipeline metaphor: is the STEM pipeline metaphor serving our students and the STEM workforce? Sci Educ. 2014;98(3):443–460. doi: 10.1002/sce.21108
  • President’s Council of Advisors on Science and Technology (U.S.). (2010). Prepare and inspire: K-12 education in science, technology, engineering, and math (STEM) for America’s future: executive report. Washington (DC): Executive Office of the President, President’s Council of Advisors on Science and Technology.
  • Vedder Weiss D, Fortus D. Adolescents’ declining motivation to learn science: a follow-up study. J Res Sci Teach. 2012;49(9):1057–1095. doi: 10.1002/tea.21049

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