KnE Social Sciences
ISSN: 2518-668X
The latest conference proceedings on humanities, arts and social sciences.
Computational Thinking with a Multi-literacy Model Using Interactive PowerPoint Media: An Experiment in Elementary Schools
Published date: Apr 26 2024
Journal Title: KnE Social Sciences
Issue title: International Conference on Mathematics and Science Education (ICMScE 2022): Learning Models and Teaching Approaches
Pages: 408–417
Authors:
Abstract:
Elementary school students need to acquire computational thinking as a crucial skill in the digital age. Similar to mathematical skills, computational thinking is a fundamental competence in digital literacy. It is used to solve problems in learning. One approach is to facilitate children’s learning by emphasizing computational thinking, such as using the multi-literacy model with interactive PowerPoint slides. This study aimed to assess and characterize the influence of multi-literacy models aided by interactive PowerPoint media on the development of computational thinking skills in elementary school students, considering their prior knowledge. Involving a total sample of 56 4th-grade elementary school students, this quantitative study employed a 3 x 2 factorial design. The sample included 14 students in the high group, 28 in the medium group, and 14 in the high group. The research revealed that the implementation of a multi-literacy learning approach, assisted by interactive PowerPoint media, significantly enhances student’s acquisition and improvement of computational thinking skills. This is because children can develop computational thinking skills in an enjoyable environment using PowerPoint media. Another study revealed that students in the high group performed much better on average when it came to learning computational thinking skills. Meanwhile, the average gain of computational thinking skills in the medium group was only slightly different from that of the low group.
Keywords: computational thinking, multi-literacy model, interactive PowerPoint media
References:
[1] Wing JM. “Computational thinking and thinking about computing.,” Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences. vol. 366, no. 1881, pp. 3717–3725, 2008. https://doi.org/10.1109/IPDPS.2008.4536091.
[2] Denning PJ, Tedre M. Computational thinking. Mit Press; 2019. https://doi.org/10.7551/mitpress/11740.001.0001.
[3] Hsu TC, Chang SC, Hung YT. How to learn and how to teach computational thinking: suggestions based on a review of the literature. Comput Educ. 2018;126:296–310.
[4] Selby C, Woollard J. “Computational thinking: the developing definition.,” p. 2013.
[5] Barr D, Harrison J, Conery L. Computational thinking: A digital age skill for everyone. Learn Lead Technol. 2011;38(6):20–3.
[6] C. Angeli and M. Giannakos, “Computational thinking education: Issues and challenges,” (2020). https://doi.org/10.1016/j.chb.2019.106185.
[7] Kong SC, Abelson H. Computational thinking education. Springer Nature; 2019. https://doi.org/10.1007/978-981-13-6528-7.
[8] Council NR. An evaluation of the public schools of the District of Columbia: Reform in a changing landscape. National Academies Press; 2015.
[9] Surya YF, Marta R, Wijaya TT. “The development of open-ended math questions on grade v students of elementary school.,” In: Journal of Physics: Conference Series. pp. 012081. IOP Publishing (2020). https://doi.org/10.1088/1742-6596/1613/1/012081.
[10] Hajizadeh A, Zali M. Prior knowledge, cognitive characteristics and opportunity recognition. Int J Entrep Behav Res. 2016;22(1):63–83.
[11] Zambrano J, Kirschner F, Sweller J, Kirschner PA. Effects of prior knowledge on collaborative and individual learning. Learn Instr. 2019;63:101214.
[12] Glogger-Frey I, Deutscher M, Renkl A. Student teachers’ prior knowledge as a prerequisite to learn how to assess pupils’ learning strategies. Teach Teach Educ. 2018;76:227–41.
[13] Yang TC, Chen MC, Chen SY. The influences of self-regulated learning support and prior knowledge on improving learning performance. Comput Educ. 2018;126:37–52.
[14] Arslan-Ari I. Learning from instructional animations: how does prior knowledge mediate the effect of visual cues? J Comput Assist Learn. 2018;34(2):140–9.
[15] Hohensee C. Brief Report: Teachers’ awareness of the relationship between prior knowledge and new learning. J Res Math Educ. 2016;47(1):17–27.
[16] Penciner R. Does Powerpoint enhance learning? CJEM. 2013 Mar;15(2):109–12.
[17] R.A. Berk, “Research on PowerPoint: From basic features to multimedia.,” International Journal of Technology in Teaching & Learning. vol. 7, no. 1, p. 2011.
[18] Plomp T. “Educational design research: An introduction.,” Educational design research. pp. 11–50, 2013.
[19] Burke Q, Bailey CS, Ruiz P. “CIRCL primer: Assessing computational thinking.,” CIRCL Primer Series. p. 2019.
[20] Barr D, Harrison J, Conery L. Computational thinking: A digital age skill for everyone. Learn Lead Technol. 2011;38(6):20–3.
[21] Kong SC, Abelson H. Computational thinking education. Springer Nature; 2019. https://doi.org/10.1007/978-981-13-6528-7.
[22] Isseks M. How PowerPoint is killing education. Educ Leadersh. 2011;68(5):74–6.
[23] Abidin Z, Jupri A. The use of multi literation model to improve mathematical connection ability of primary school on geometry. IJAEDU-International E-Journal of Advances in Education. 2017;3(9):603–10.
[24] Epstein D, Miller RT. “Slow off the Mark: Elementary school teachers and the crisis in Science, Technology, Engineering, and Math Education.,” Center for American Progress. p. 2011.
[25] Zambrano J, Kirschner F, Sweller J, Kirschner PA. Effects of prior knowledge on collaborative and individual learning. Learn Instr. 2019;63:101214.
[26] Mazzocco MM, Hanich LB, Noeder MM. “Primary school age students’ spontaneous comments about math reveal emerging dispositions linked to later mathematics achievement,” Child Development Research. vol. 2012, p. 2012. https://doi.org/10.1155/2012/170310.
[27] Simonsmeier BA, Flaig M, Deiglmayr A, Schalk L, Schneider M. Domain-specific prior knowledge and learning: A meta-analysis. Educ Psychol. 2022;57(1):31–54.
[28] Yang TC, Chen MC, Chen SY. The influences of self-regulated learning support and prior knowledge on improving learning performance. Comput Educ. 2018;126:37–52.