Abstract
Nowadays, technology has become an essential part of our daily life. It has proven its effectiveness in many areas. One of these areas is education, where interactive educational tools have appeared to facilitate many complex scientific concepts. Meanwhile, singular value decomposition (SVD) is a linear transformation method used in many applications such as image processing. This paper aims to propose an interactive learning tool-based Graphical User Interface (GUI) using MATLAB for SVD as a technique for applying the image compression. The tool provides the user a step by step illustration of the SVD technique for image compression and allows him to try the application by compressing an image. The tool developed using MATLAB 2019b. The interactive tool enables visualization of the image compression, and it is tested with ten students to evaluate the traditional learning method against the interactive learning method. The results showed that the tool improved the learning since the treatment group used it to get better or equal results in the theoretical questions. Also, they get much better results in the practical question. The tool could motivate the students to learn the topic since the treatment group was more satisfied than the control group.
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References
Sessoms, D.: Interactive instruction: creating interactive learning environments through tomorrow’s teachers. Int. J. Technol. Teach. Learn. 4(2), 86–96 (2008)
Ibrahim, M., Al-Shara, O.: Impact of interactive learning on knowledge retention. In: Symposium on Human Interface and the Management of Information, pp. 347–355, July 2007. Springer, Berlin, Heidelberg (2007)
Eady, M., Lockyer, L.: Tools for learning: technology and teaching. Learning to Teach in the Primary School, pp. 71–89 (2013)
Sood, I.: Essential elements οf interactive learning, 30 November 2018 (2018). Accessed 27 July 2020. https://elearningindustry.com/interactive-learning-essential-elements
Brownlee, J.: A gentle introduction to linear algebra, 09 August 2019 (2019). Accessed 30 July 2020. https://machinelearningmastery.com/gentle-introduction-linear-algebra
Kahu, S., Rahate, R.: Image compression using singular value decomposition. Int. J. Adv. Res. Technol. 2(8), 244–248 (2013)
Rufai, A.M., Anbarjafari, G., Demirel, H.: Lossy medical image compression using Huffman coding and singular value decomposition. In: 2013 21st Signal Processing and Communications Applications Conference (SIU), pp. 1–4, April 2013. IEEE (2013)
Chen, S., Feng, J.: Research on detection of fabric defects based on singular value decomposition. In: The 2010 IEEE International Conference on Information and Automation, pp. 857–860, June 2010. IEEE (2010)
Guzman, J.L., Costa-Castelló, R., Dormido, S., Berenguel, M.: Study of fundamental control concepts through interactive learning objects. IFAC Proc. 44(1), 7286–7291 (2011)
Hundt, C., Schlarb, M., Schmidt, B.: SAUCE: a web application for interactive teaching and learning of parallel programming. J. Parallel Distrib. Comput. 105, 163–173 (2017)
Baronio, G., Motyl, B., Paderno, D.: Technical drawing learning tool-level 2: an interactive self-learning tool for teaching manufacturing dimensioning. Comput. Appl. Eng. Educ. 24(4), 519–528 (2016)
Dos Santos, L.M.: English language learning for engineering students: application of a visual-only video teaching strategy. Glob. J. Eng. Educ. 21(1), 37–44 (2019)
Lau, K.W., Kan, C.W., Lee, P.Y.: Doing textiles experiments in game-based virtual reality. Int. J. Inf. Learn. Technol. 34, 242–258 (2017)
Swathi, H.R., Sohini, S., Surbhi, Gopichand, G.: Image compression using singular value decomposition. IOP Conf. Ser.: Mater. Sci. Eng. 263(4), 042082 (2017)
Kumar, R., Patbhaje, U., Kumar, A.: An efficient technique for image compression and quality retrieval using matrix completion. J. King Saud Univ.-Comput. Inf. Sci. (2019)
Hochman, A.: Fast singular-value decomposition of Loewner matrices for state-space macromodeling. In: 2015 IEEE 24th Electrical Performance of Electronic Packaging and Systems (EPEPS), pp. 177–180, October 2015. IEEE (2015)
Benjamin Erichson, N., Brunton, S.L., Nathan Kutz, J.: Compressed singular value decomposition for image and video processing. In: Proceedings of the IEEE International Conference on Computer Vision Workshops, pp. 1880–1888 (2017)
Maruskin, J.M.: Essential Linear Algebra. Solar Crest Publishing LLC, San Jose (2012)
Ajami, K., Suleiman, M.: Evaluating interactive learning content in an eLearning environment. eLearn Mag. 2014(6), 4 (2014)
Raptivity: Interactive learning design: using an interactive learning software to increase engagement in eLearning courses [Pdf]. Raptivity (n.d.). https://www.raptivity.com/pdf/Interactive%20Learning%20Design%20eBook.pdf
Aishwarya, K.M.: Singular value decomposition image compression, 02 January 2016 (2016). Accessed 3 June 2020. https://www.slideshare.net/AishwaryaKM1/singular-value-decomposition-image-compression
Šošević, U., Milenković, I., Milovanović, M., Minović, M.: Support platform for learning about multimodal biometrics. J. Univ. Comput. Sci. 19(11), 1684–1700 (2013)
Joshi, A., Kale, S., Chandel, S., Pal, D.K.: Likert scale: explored and explained. Curr. J. Appl. Sci. Technol. 7, 396–403 (2015)
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We would like to thank all the participants’ students for their participation in the experimental test from the computer science department in the Faculty of Computing and Information Technology at KAU.
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Bahatheg, N., Alloqmani, A., Alsaedi, O., Alnanih, R., Elrefaei, L. (2021). Interactive Learning Tool for Image Compression Using Singular Value Decomposition. In: Arai, K. (eds) Advances in Information and Communication. FICC 2021. Advances in Intelligent Systems and Computing, vol 1364. Springer, Cham. https://doi.org/10.1007/978-3-030-73103-8_67
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