The relationship between students’ self-assessments of difficulties in understanding scientific texts presented on paper or digital devices and eye-tracking indicators
Introduction. The article examines the problem of the quality of students’ understanding of a scientific text presented in a traditional format, as well as on a computer and smartphone screen. The purpose of the study is to identify the relationship between students’ self-assessments of difficulties in understanding scientific texts presented on paper or digital devices, and eye-tracking indicators of reading.
Materials and Methods. The experimental study involved 55 students divided into three subgroups: those who read the text of a scientific article on paper, on a computer monitor and on a smartphone screen. The eye-tracking characteristics were recorded using a Pupil Core binocular eytracker. The assessment of difficulties in understanding the educational text was carried out using the author’s modification of T. V. Borzova’s ‘Understanding the scientific text’ questionnaire.
Results. The results show three types of difficulties in students’ understanding of a scientific article: difficulties in comprehending the material, difficulties in memorization, and difficulties in concentration. The study has revealed: (1) negative correlations between difficulties in understanding the text and eye-tracking characteristics indicating concentration on the article and cognitive involvement in reading in the group of students who read the paper text; (2) positive correlations between subjective difficulties in understanding and indicators associated with cognitive involvement in reading with the text and concentration on it in the group of students who read the text on the computer monitor; (3) no correlations in the group of students who read the text on the smartphone screen, that suggests a variety of cognitive information processing strategies accompanied by reduced concentration on the text and underestimation of difficulties in understanding in this group.
Conclusions. The authors conclude that differences in cognitive information processing strategies when reading the scientific text presented on paper, a computer monitor and a smartphone screen determine learning attainments.
Understanding scientific text; Text understanding difficulties; Eye-tracking characteristics of reading; Cognitive regulation; Metacognitive regulation; Paper text; Digital text.
- Antonelli M., Donelli D. Reading and understanding scientific articles. The Clinical Teacher, 2020, vol. 17 (6), pp. 612-616. DOI: https://doi.org/10.1111/tct.13159
- Katz J., Smolyn J. Becoming scientifically literate: developing epistemic practices through reading scientific papers. The Science Teacher, 2024, vol. 91 (1), pp. 58-63. URL: https://my.nsta.org/resource/130754 DOI: https://doi.org/10.1080/00368555.2023.2292336
- Kuleshova I. G., Kiselnikov I. V., Breitigam E. K. Stages of understanding educational material: The issues of contents. Science for Education Today, 2019, vol. 9, no. 5, pp. 97–109. (In Russian) DOI: http://dx.doi.org/10.15293/2658-6762.1905.06
- Mosunova L. A. Managing reading of literary texts as a process of search for meaning. Novosibirsk State Pedagogical University Bulletin, 2018, vol. 8, no. 2, pp. 135–152. (In Russian) DOI: http://dx.doi.org/10.15293/2226-3365.1802.08
- Borzova T. V. Questionnaire “understanding of the scientific text”: Search for ways to diagnose understanding in learning. The Proceedings of the Samara Academy of Sciences (RAS). Social Sciences, Humanities, Biomedical Sciences, 2020, vol. 22 (72), pp. 15-26. (In Russian) URL: https://www.elibrary.ru/item.asp?id=43136156 DOI: https://doi.org/10.37313/2413-9645-2020-22-72-15-26
- Jannah F., Ni’mah M., Hasanah S. An analysis of student's reading interest in scientific article. Journey: Journal of English Language and Pedagogy, 2023, vol. 6 (1), pp. 178-184. DOI: https://doi.org/10.33503/journey.v6i1.2646
- Sujaini H., Safriadi N., Khairiyah D. System interactive reader using eye-tracker technology in ebook reader. Bulletin of Electrical Engineering and Informatics, 2024, vol. 13 (3), pp. 1676-1684. DOI: https://doi.org/10.11591/eei.v13i3.5877
- Voiskunsky A. E., Solodov M. Y. How features of digital text affect reading efficiency and comprehension. Literature review. Psychology in Education, 2020, vol. 2 (2), pp. 134-142. (In Russian) URL: https://www.elibrary.ru/item.asp?id=44034124 DOI: https://doi.org/10.33910/2686-9527-2020-2-2-134-142
- Solovyova V. A., Venig S. B., Belykh T. V. Analysis of students' oculomotor activity observed when reading from the PC screen. Integration of Education, 2021, vol. 25 (1), pp. 91-109. (In Russian) URL: https://www.elibrary.ru/item.asp?id=44869233 DOI: https://doi.org/10.15507/1991-9468.102.025.202101.091-109
10. Borzova T. V., Mosunova L. A. The conditions for fostering meaningful understanding of information in learning. Science for Education Today, 2020, vol. 10, no. 1, pp. 7–24. (In Russian) DOI: http://dx.doi.org/10.15293/2658-6762.2001.01
11. Miklyaeva A. V., Bezgodova S. A., Nikolaeva E. I. Online information search as an element of educational activity of modern schoolchildren and students: cognitive and psychophysiological prerequisites for effectiveness. Saint Petersburg: Publishing House of the Herzen State Pedagogical University of Russia, 2023, 216 p. (In Russian) URL: https://www.elibrary.ru/item.asp?id=56363619
12. Samoilov O. M., Morozov Z. A., Petukhova D. R., Dolzhenko K. I. Metacognitive regulation as a factor influencing the effectiveness of learning through digital educational technologies. Psychology in Education, 2023, vol. 5 (4), pp. 519-535. (In Russian) URL: https://www.elibrary.ru/item.asp?id=60006592 DOI: https://doi.org/10.33910/2686-9527-2023-5-4-519-535
13. Andrew M., Taylorson J., Langille D. J., Grange A., Williams N. Student attitudes towards technology and their preferences for learning tools/devices at two universities in the UAE. Journal of Information Technology Education: Research, 2018, vol. 17, pp. 309-344. DOI: https://doi.org/10.28945/4111
14. Strzelecki A. Eye-tracking studies of web search engines: A systematic literature review. Information (Switzerland), 2020, vol. 11 (6), pp. 300. DOI: https://doi.org/10.3390/INFO11060300
15. Andrei E. Adolescent English learners' use of digital technology in the classroom. Educational Forum, 2018, vol. 83 (1), pp. 102-120. DOI: https://doi.org/10.1080/00131725.2018.1478474
16. McGray H. G., Tour E., Tsang T. K. Helping students to metacognitively read scientific literature with talking to the text. CourseSource, 2023, vol. 10, pp. 28. DOI: https://doi.org/10.24918/cs.2023.28
17. Xie Y. Wang J., Li S., Zheng Y. Research on the influence path of metacognitive reading strategies on scientific literacy. Journal of Intelligence, 2023, vol. 11 (5), pp. 78. DOI: https://doi.org/10.3390/jintelligence11050078
18. Rebreikina A. B., Levkovich K. M. Development of eye-tracking based techniques for diagnosing children’s cognitive functions. Modern Foreign Psychology, 2024, vol. 13 (2), pp. 33-43. (In Russian) URL: https://elibrary.ru/item.asp?id=68520280 DOI: https://doi.org/10.17759/jmfp.2024130203
19. Vajs I., Papić T., Ković V., Savić A. M., Janković M. M. Accessible dyslexia detection with real-time reading feedback through robust interpretable eye-tracking features. Brain Sciences, 2023, vol. 13 (3), pp. 405. DOI: https://doi.org/10.3390/brainsci13030405
20. El Hmimdi A. E., Kapoula Z., Sainte Fare Garnot V. Deep learning-based detection of learning disorders on a large scale dataset of eye movement records. BioMedInformatics, 2024, vol. 4 (1), pp. 519-541. DOI: https://doi.org/10.3390/biomedinformatics4010029
21. Ktistakis E., Gleni A., Tsilimbaris M. K., Plainis S. Comparing silent reading performance for single sentences and paragraphs: an eye movement-based analysis. Clinical and Experimental Optometry, 2023, vol. 107 (4), pp. 449-456. DOI: https://doi.org/10.1080/08164622.2023.2237974
22. Miller B. W. Using reading times and eye-movements to measure cognitive engagement. Educational Psychologist, 2015, vol. 50 (1), pp. 31-42. DOI: https://doi.org/10.1080/00461520.2015.1004068
23. Zvyagina N. V., Taleeva A. I., Kuznetsova D. A. Features of oculomotor reactions in students when perceiving textual information. Journal of Biomedical Research, 2021, vol. 9 (2), pp. 145-152. (In Russian) URL: https://elibrary.ru/item.asp?id=45726635 DOI: https://doi.org/10.37482/2687-1491-Z052
24. Zivan M., Horowitz-Kraus T. Parent-child joint reading is related to an increased fixation time on print during storytelling among preschool children. Brain and Cognition, 2020, vol. 143, pp. 105596. DOI: https://doi.org/10.1016/j. bandc.2020.105596
25. Oganov S. R., Kornev A. N. Oculomotor characteristics as an indicator of the formation of the skill of analyzing written text in children aged 9-11 and 12-14 years. Special Education, 2017, no. 3, pp. 112-121. (In Russian) URL: https://elibrary.ru/item.asp?id=30162421
26. Molina R., Redondo B., Vera J., García J. A., Muñoz-Hoyos A., Jiménez R. Children with attention-deficit/hyperactivity disorder show an altered eye movement pattern during reading. Optometry and Vision Science, 2020, vol. 97 (4), pp. 265-274. DOI: https://doi.org/10.1097/OPX.0000000000001498
27. Hauschild K. M., Pomales‐Ramos A., Strauss M. S. The visual array task: A novel gaze‐based measure of object label and category knowledge. Development Science, 2021, vol. 24 (2), pp. e13015. DOI: https://doi.org/10.1111/desc.13015
28. Vargas-Cuentas N. I., Roman-Gonzalez A., Gilman R. H., Barrientos F., Ting J., Hidalgo D., Jensen K., Zimic M. Developing an eye-tracking algorithm as a potential tool for early diagnosis of autism spectrum disorder in children. PLoS One, 2017, vol. 12 (11), pp. e0188826. DOI: https://doi.org/10.1371/journal.pone.0188826
29. Viglione A., Mazziotti R., Pizzorusso T. From pupil to the brain: New insights for studying cortical plasticity through pupillometry. Frontiers in Neural Circuits, 2023, vol. 17, pp. 1151847. DOI: https://doi.org/10.3389/fncir.2023.1151847
30. Smilek D., Carriere J. S., Cheyne J. A. Out of mind, out of sight eye blinking as indicator and embodiment of mind wandering. Psychological Science, 2010, vol. 21 (6), pp. 786-789. DOI: https://doi.org/10.1177/0956797610368063
31. Yoo K., Ahn J., Lee S.-H. The confounding effects of eye blinking on pupillometry, and their remedy. PLoS One, 2021, vol. 16 (12), pp. e0261463. DOI: https://doi.org/10.1371/journal.pone.0261463