Pattern Recognition in Computing Education: A Systematic Review
Resumo
This paper presents a systematic literature review to investigate how pattern recognition has been approached in computing education. Pattern Recognition has long been an important concept among various areas, from cognitive psychology and neuroscience to machine learning and computer vision. Recently, it gained the attention of education, being associated with computational thinking. An old concept being revisited in a new context raises important questions on how it is being approached, how it is being assessed and if it is making use of previous contributions from the other fields that have been studying the concept. This work systematically reviews the literature to answer these questions on pattern recognition. It is found that, as other concepts related with computational thinking, it is rarely treated alone and when among others, few studies have pattern recognition as the main theme. The results also show that no standardized assessment method is used and contributions from other fields are barely mentioned.
Palavras-chave:
Pattern Recognition, Computing Education, Computational Thinking
Referências
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Kellman, P. J. and Garrigan, P. (2009). Perceptual learning and human expertise. Physics of life reviews, 6(2):53–84.
Kidd, J. K., Curby, T. W., Boyer, C. E., Gadzichowski, K. M., Gallington, D. A., Machado, J. A., and Pasnak, R. (2012). Benefits of an intervention focused on oddity and seriation. Early Education & Development, 23(6):900–918.
Kitchenham, B. (2004). Procedures for performing systematic reviews. Keele, UK, Keele University, 33(2004):1–26.
Liu, J., Sun, J., and Wang, S. (2006). Pattern recognition: An overview. IJCSNS International Journal of Computer Science and Network Security, 6(6):57–61.
Miller, J. (2019). Stem education in the primary years to support mathematical thinking: Using coding to identify mathematical structures and patterns. Zdm, 51(6):915–927.
Mulligan, J. and Mitchelmore, M. (2009). Awareness of pattern and structure in early mathematical development. Mathematics Education Research Journal, 21(2):33–49.
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., et al. (2021). The prisma 2020 statement: an updated guideline for reporting systematic reviews. International Journal of Surgery, 88:105906.
Pi, Y., Liao, W., Liu, M., and Lu, J. (2008). Theory of cognitive pattern recognition. Pattern recognition techniques, technology and applications, pages 433–463.
Reed, S. K. (1972). Pattern recognition and categorization. Cognitive psychology, 3(3):382–407.
Resnick, M. et al. (2009). Scratch: Programming for all. Communications of the ACM, 52(11):60–67.
Saqr, M., Ng, K., Oyelere, S. S., and Tedre, M. (2021). People, ideas, milestones: a scientometric study of computational thinking. ACM Transactions on Computing Education (TOCE), 21(3):1–17.
Saxena, A., Lo, C. K., Hew, K. F., and Wong, G. K. W. (2020). Designing unplugged and plugged activities to cultivate computational thinking: An exploratory study in early childhood education. The Asia-Pacific Education Researcher, 29(1):55–66.
Selby, C. and Woollard, J. (2013). Computational thinking the developing definition. University of Southampton (E-prints).
Shugen, W. (2002). Framework of pattern recognition model based on the cognitive psychology. Geo-spatial Information Science, 5(2):74–78.
Tang, X., Yin, Y., Lin, Q., Hadad, R., and Zhai, X. (2020). Assessing computational thinking: A systematic review of empirical studies. Computers & Education, 148:103798.
Tanimoto, S. L. (1998). Connecting middle school mathematics to computer vision and pattern recognition. International journal of pattern recognition and artificial intelligence, 12(08):1053–1070.
Wang, C., Shen, J., and Chao, J. (2021). Integrating computational thinking in stem education: A literature review. International Journal of Science and Mathematics Education, pages 1–24.
Warren, E., Miller, J., and Cooper, T. (2012). Repeating patterns: Strategies to assist young students to generalise the mathematical structure. Australasian Journal of Early Childhood, 37(3):111–120.
Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3):33–35.
Zazkis, R. and Liljedahl, P. (2002). Generalization of patterns: The tension between algebraic thinking and algebraic notation. Educational studies in mathematics, 49(3):379–402.
Acevedo-Borrega, J., Valverde-Berrocoso, J., and Garrido-Arroyo, M. d. C. (2022). Computational thinking and educational technology: A scoping review of the literature. Education Sciences, 12(1):39.
Barrón-Estrada, M. L., Zatarain-Cabada, R., Romero-Polo, J. A., and Monroy, J. N. (2022). Patrony: A mobile application for pattern recognition learning. Education and Information Technologies, 27(1):1237–1260.
Bers, M. U., Flannery, L., Kazakoff, E. R., and Sullivan, A. (2014). Computational thinking and tinkering: Exploration of an early childhood robotics curriculum. Computers & Education, 72:145–157.
Bishop, C. M. and Nasrabadi, N. M. (2006). Pattern recognition and machine learning, volume 4. Springer.
Dasgupta, A. and Purzer, S. (2016). No patterns in pattern recognition: A systematic literature review. In 2016 IEEE Frontiers in Education Conference (FIE), pages 1–3. IEEE.
Eysenck, M. W. and Keane, M. T. (2015). Cognitive psychology: A student’handbook. Psychology press.
Guenaga, M. (2021). Lempel: Developing the pattern recognition skill in computational thinking through an online educational game. In 2021 Learning Analytics Summer Institute (LASI).
Kellman, P. J. and Garrigan, P. (2009). Perceptual learning and human expertise. Physics of life reviews, 6(2):53–84.
Kidd, J. K., Curby, T. W., Boyer, C. E., Gadzichowski, K. M., Gallington, D. A., Machado, J. A., and Pasnak, R. (2012). Benefits of an intervention focused on oddity and seriation. Early Education & Development, 23(6):900–918.
Kitchenham, B. (2004). Procedures for performing systematic reviews. Keele, UK, Keele University, 33(2004):1–26.
Liu, J., Sun, J., and Wang, S. (2006). Pattern recognition: An overview. IJCSNS International Journal of Computer Science and Network Security, 6(6):57–61.
Miller, J. (2019). Stem education in the primary years to support mathematical thinking: Using coding to identify mathematical structures and patterns. Zdm, 51(6):915–927.
Mulligan, J. and Mitchelmore, M. (2009). Awareness of pattern and structure in early mathematical development. Mathematics Education Research Journal, 21(2):33–49.
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., et al. (2021). The prisma 2020 statement: an updated guideline for reporting systematic reviews. International Journal of Surgery, 88:105906.
Pi, Y., Liao, W., Liu, M., and Lu, J. (2008). Theory of cognitive pattern recognition. Pattern recognition techniques, technology and applications, pages 433–463.
Reed, S. K. (1972). Pattern recognition and categorization. Cognitive psychology, 3(3):382–407.
Resnick, M. et al. (2009). Scratch: Programming for all. Communications of the ACM, 52(11):60–67.
Saqr, M., Ng, K., Oyelere, S. S., and Tedre, M. (2021). People, ideas, milestones: a scientometric study of computational thinking. ACM Transactions on Computing Education (TOCE), 21(3):1–17.
Saxena, A., Lo, C. K., Hew, K. F., and Wong, G. K. W. (2020). Designing unplugged and plugged activities to cultivate computational thinking: An exploratory study in early childhood education. The Asia-Pacific Education Researcher, 29(1):55–66.
Selby, C. and Woollard, J. (2013). Computational thinking the developing definition. University of Southampton (E-prints).
Shugen, W. (2002). Framework of pattern recognition model based on the cognitive psychology. Geo-spatial Information Science, 5(2):74–78.
Tang, X., Yin, Y., Lin, Q., Hadad, R., and Zhai, X. (2020). Assessing computational thinking: A systematic review of empirical studies. Computers & Education, 148:103798.
Tanimoto, S. L. (1998). Connecting middle school mathematics to computer vision and pattern recognition. International journal of pattern recognition and artificial intelligence, 12(08):1053–1070.
Wang, C., Shen, J., and Chao, J. (2021). Integrating computational thinking in stem education: A literature review. International Journal of Science and Mathematics Education, pages 1–24.
Warren, E., Miller, J., and Cooper, T. (2012). Repeating patterns: Strategies to assist young students to generalise the mathematical structure. Australasian Journal of Early Childhood, 37(3):111–120.
Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3):33–35.
Zazkis, R. and Liljedahl, P. (2002). Generalization of patterns: The tension between algebraic thinking and algebraic notation. Educational studies in mathematics, 49(3):379–402.
Publicado
16/11/2022
Como Citar
SILVA JUNIOR, Braz Araujo da; SILVA, Júlia Veiga da; CAVALHEIRO, Simone André da Costa; FOSS, Luciana.
Pattern Recognition in Computing Education: A Systematic Review. In: SIMPÓSIO BRASILEIRO DE INFORMÁTICA NA EDUCAÇÃO (SBIE), 33. , 2022, Manaus.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2022
.
p. 232-243.
DOI: https://doi.org/10.5753/sbie.2022.225128.
