Eye tracking as an inclusive educational strategy: assessment with students with autism
DOI:
https://doi.org/10.5753/rbie.2020.28.0.1181Keywords:
Eye tracking, Inclusive Education, Autism Spectrum Disorder, Applied Behavior Analysis, ABAAbstract
In the education field, professionals teach and evaluate students’ academic repertoire with diverse skills, limitations, and backgrounds. Some of these students may have learning difficulties due to conventional teaching methods, mainly due to non-adaptation to pedagogical methods. Among these diverse students, there are those with Autistic Spectrum Disorder - ASD. Students with ASD present impairments in social communication and restricted and repetitive behavior patterns. Behavior Analysis indicates that activities tailored to the interests of students are more efficient in the educational process. This work proposes to use student eye-tracking analysis during computerized educational activities as a strategy for inclusive educational assessment of students with ASD. We developed digital teaching activities on the computer that were solved by students diagnosed with ASD to evaluate and demonstrate this proposal. The experimental results show areas of digital activities that do not receive student eye focus during these activities’ execution. We may also observe if exists a relation between the eyes’ movement and mouse-controlled cursor during the activity. It is essential to provide means for the professional to identify whether the activities proposed to students are efficient at a given stage of the teaching. As well as find methodologies that fit the profile of each student. Moreover, eye tracking can assist in this process.
Downloads
References
Almourad, M. B., & Bataineh, E. (2020). Visual attention toward human face recognizing for autism spectrum disorder and normal developing children: An eye tracking study. In Proceedings of the 2020 the 6th international conference on e-business and applications (p. 99–104). New York, NY, USA: Association for Computing Machinery. doi: 10.1145/3387263.3387283 [GS Search].
Almourad, M. B., Bataineh, E., Stocker, J., & Marir, F. (2018). Analyzing the behavior of autistic and normal developing children using eye tracking data. In International conference on kansei engineering & emotion research (pp. 340–349). doi: 10.1007/978-981-10-8612-036 [GS Search].
Altenmüller-Lewis, U. (2017). Designing schools for students on the spectrum. The Design Journal, 20(sup1), S2215-S2229. doi: 10.1080/14606925.2017.1352738 [GS Search].
APA, A. P. A. (2013). Diagnostic and statistical manual of mental disorders (dsm-5 R ). American Psychiatric Pub. [GS Search].
Baer, D. M., Wolf, M. M., & Risley, T. R. (1968). Some current dimensions of applied behavior analysis 1. Journal of applied behavior analysis, 1(1), 91–97. doi: 10.1901/jaba.1968.1-91 [GS Search].
Borovsky, A., Burns, E., Elman, J. L., & Evans, J. L. (2013). Lexical activation during sentence comprehension in adolescents with history of specific language impairment. Journal of Communication Disorders, 46(5), 413 - 427. doi: 10.1016/j.jcomdis.2013.09.001 [GS Search].
BRASIL (2015). Lei brasileira de inclusão da pessoa com deficiência. Retrieved from [Link].
Busjahn, T., Schulte, C., Sharif, B., Simon, Begel, A., Hansen, M., . . . Antropova, M. (2014). Eye tracking in computing education. In Proceedings of the tenth annual conference on international computing education research (p. 3–10). New York, NY, USA: Association for Computing Machinery. doi: 10.1145/2632320.2632344 [GS Search].
Catarina, A. (1999). Aprendizagem comportamento, linguagem e cognição. CDC (2001). Prevalence of autism spectrum disorders. Centers for Disease Control and Prevention, Atlanta, USA. Retrieved from: [Link].
Chawarska, K., Macari, S., & Shic, F. (2013). Decreased spontaneous attention to social scenes in 6-month-old infants later diagnosed with autism spectrum disorders. Biological psychiatry, 74(3), 195–203. doi: 10.1016/j.biopsych.2012.11.022 [GS Search].
Chita-Tegmark, M. (2016). Attention allocation in asd: A review and meta-analysis of eyetracking studies. Review Journal of Autism and Developmental Disorders, 3(3), 209–223. doi: 10.1007/s40489-016-0077-x [GS Search].
Coderre, E. L., Chernenok, M., O’Grady, J., Bosley, L., Gordon, B., & Ledoux, K. (2019). Implicit measures of receptive vocabulary knowledge in individuals with level 3 autism. Cognitive and Behavioral Neurology, 32(2), 95–119. doi: 10.10972FWNN.0000000000000194 [GS Search].
Cooper, J. O., Heron, T. E., Heward, W. L., et al. (2007). Applied behavior analysis. Retrieved from: [Link]. [GS Search].
Dalmaijer, E. S., Mathôt, S., & Van der Stigchel, S. (2014). Pygaze: An open-source, crossplatform toolbox for minimal-effort programming of eyetracking experiments. Behavior research methods, 46(4), 913–921. doi: 10.3758/s13428-013-0422-2 [GS Search].
DeMyer, M. K., Hingtgen, J. N., & Jackson, R. K. (1981). Infantile autism reviewed: A decade of research. Schizophrenia bulletin, 7(3), 388–451. doi: 10.1093/schbul/7.3.388 [GS Search].
de Rose, J. C. (2005). Análise comportamental da aprendizagem de leitura e escrita. Revista Brasileira de análise do Comportamento, 1(1), 29–50. doi: 10.18542/rebac.v1i1.676 [GS Search].
Duan, H., Zhai, G., Min, X., Fang, Y., Che, Z., Yang, X., . . . Liu, N. (2018). Learning to predict where the children with asd look. In 2018 25th ieee international conference on image processing (icip) (pp. 704–708). doi: 10.1109/ICIP.2018.8451338 [GS Search].
Ferster, C. B. (1964). Positive reinforcement and behavioral deficits of autistic children. In Conditioning techniques in clinical practice and research (pp. 255–274). Springer. doi: 10.1007/978-3-662-39876-023 [GS Search].
Foxx, R. M. (2008). The critical importance of science-based treatments for autism. Association for Behavior Analysis Internationa’s Newsletter, 30(3), 18–19. doi: 10.1016/j.chc.2008.06.007 [GS Search].
Fujioka, T., Inohara, K., Okamoto, Y., Masuya, Y., Ishitobi, M., Saito, D. N., . . . others (2016). Gazefinder as a clinical supplementary tool for discriminating between autismo spectrum disorder and typical development in male adolescents and adults. Molecular autism, 7(1), 19. doi: 10.1186/s13229-016-0083-y [GS Search]
Giordano, D., Pino, C., Kavasidis, I., Spampinato, C., Di Pietro, M., Rizzo, R., . . . Barone, R. (2017). An eye tracker based computer system to support oculomotor and attention déficit investigations. In 2017 ieee 30th international symposium on computer-based medical systems (cbms) (pp. 538–543). doi: 10.1109/CBMS.2017.175 [GS Search]
Harlow, H. F. (1949). The formation of learning sets. Psychological review, 56(1), 51. doi: 10.1037/h0062474 [GS Search].
Higbee, T. S. (2012). The assert curriculum. unpublished manuscript. Unpublished manuscript, Department of Special Education and Rehabilitation, Utah State University, Logan, Utah, USA. [GS Search].
Hunter, J. D. (2007). Matplotlib: A 2d graphics environment. Computing in Science & Engineering, 9(3), 90–95. doi: 10.1109/MCSE.2007.55 [GS Search].
Jiang, M., & Zhao, Q. (2017). Learning visual attention to identify people with autism spectrum disorder. In Proceedings of the ieee international conference on computer vision (pp. 3267–3276). doi: 10.1109/ICCV.2017.354 [GS Search].
Junior, H., de Menezes, C., & De Souza, A. (2017). Monitoramento dos movimentos dos olhos para apoiar a avaliação da aprendizagem em jogos digitais. In Brazilian symposium on computers in education (simpósio brasileiro de informática na educação-sbie) (Vol. 28, p. 787). doi: 10.5753/cbie.sbie.2019.1221 [GS Search].
Karatekin, C. (2007). Eye tracking studies of normative and atypical development. Developmental review, 27(3), 283–348. doi: 10.1016/j.dr.2007.06.006 [GS Search].
Lai, M.-L., Tsai, M.-J., Yang, F.-Y., Hsu, C.-Y., Liu, T.-C., Lee, S. W.-Y., . . . Tsai, C.-C. (2013). A review of using eye-tracking technology in exploring learning from 2000 to 2012. Educational research review, 10, 90–115. doi: 10.1016/j.edurev.2013.10.001 [GS Search].
Menard, M. (2011). Game development with unity (1st ed.). Boston, MA, USA: Course Technology Press. [GS Search].
Mercadante, M. T., Van der Gaag, R. J., & Schwartzman, J. S. (2006). Transtornos invasivos do desenvolvimento não-autísticos: síndrome de rett, transtorno desintegrativo da infância e transtornos invasivos do desenvolvimento sem outra especificação. Brazilian Journal of Psychiatry, 28, s12–s20. doi: 10.1590/S1516-44462006000500003 [GS Search].
Moore, A., Wozniak, M., Yousef, A., Barnes, C. C., Cha, D., Courchesne, E., & Pierce, K. (2018). The geometric preference subtype in asd: identifying a consistent, early-emerging phenomenon through eye tracking. Molecular autism, 9(1), 19. doi: 10.1186/s13229-018-0202-z [GS Search].
Orsati, F. T., Mecca, T. P., de Melo, D. F., Schwartzman, J. S., & de Macedo, E. C. (2009). Padrões perceptuais nos transtornos globais do desenvolvimento: rastreamento ocular em figuras sociais e não sociais. Psicologia: teoria e prática, 11(3), 131–142. [GS Search].
Orsati, F. T., Schwartzman, J. S., Brunoni, D., Mecca, T., & de Macedo, E. C. (2008). Novas possibilidades na avaliação neuropsicológica dos transtornos invasivos do desenvolvimento: Análise dos movimentos oculares. Avaliaçao Psicologica: Interamerican Journal of Psychological Assessment, 7(3), 281–290. [GS Search].
Salvucci, D. D., & Goldberg, J. H. (2000). Identifying fixations and saccades in eye-tracking protocols. In Proceedings of the 2000 symposium on eye tracking research & applications (pp. 71–78). doi: 10.1145/355017.355028 [GS Search].
Saunders, K. J., & Spradlin, J. E. (1993). Conditional discrimination in mentally retarded subjects: Programming acquisition and learning set. Journal of the Experimental Analysis of Behavior, 60(3), 571–585. doi: 10.1901/jeab.1993.60-571 [GS Search].
Schopler, E., Reichler, R. J., DeVellis, R. F., & Daly, K. (1980). Toward objective classification of childhood autism: Childhood autism rating scale (cars). Journal of autismo and developmental disorders. doi: 10.1007/BF02408436 [GS Search].
Schwartzman, J. S., Velloso, R. d. L., D’Antino, M. E. F., & Santos, S. (2015). The eye-tracking of social stimuli in patients with rett syndrome and autism spectrum disorders: a pilot study. Arquivos de neuro-psiquiatria, 73(5), 402–407. doi: 10.1590/0004-282X20150033 [GS Search].
Shic, F., & Goodwin, M. (2015). Introduction to technologies in the daily lives of individuals with autism. Springer. doi: 10.1007/s10803-015-2640-1 [GS Search].
Silva, M., Moura, I., & Soares, A. (2017). Uso de tecnologias computacionais para o ensino de crianças com transtorno do espectro autista: Um mapeamento sistemático da literatura. In Brazilian symposium on computers in education (simpósio brasileiro de informática na educação-sbie) (Vol. 28, p. 173). doi: 10.5753/cbie.sbie.2017.173 [GS Search].
Vargas-Cuentas, N. I., Roman-Gonzalez, A., Gilman, R. H., Barrientos, F., Ting, J., Hidalgo, D., . . . Zimic, M. (2017). Developing an eye-tracking algorithm as a potential tool for early diagnosis of autism spectrum disorder in children. PloS one, 12(11). doi: 10.1371/journal.pone.0188826 [GS Search].
Additional Files
Published
How to Cite
Issue
Section
License
Copyright (c) 2020 Tardelly de Araújo Cavalcante, Jordão Frazão Soares, Ancelmo Paiva, Ivana Maia, Priscila Benitez, André Soares
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
