The eye tracking technique in the analysis of mechanisms for solving algorithmic problems
Magdalena Andrzejewska, Anna Stolińska
Abstract
The ability to solve problems using algorithms plays an increasingly important role in modern society, whereas programming, alongside with broadly understood digital skills, are considered to be one of the key competences of the future. The result of this trend is the modification in the Polish education system of the IT subjects core curriculum, under which teaching programming is planned at every stage of education. While teaching the skills of programming is important, it is not an easy task to achieve and hence it poses many methodologi- cal challenges. Researchers in this field are increasingly turning to new experimental methods, such as eye tracking techniques that allow to gain an insight into cognitive mechanisms and thus can provide objective information about the process of learning programming. The article discusses the results of authors own study, in which the state of declarative and procedural knowledge of students related to the forms of algorithm presentation was diagnosed. The questionnaires along with the tasks included in them, which the students solved in a traditional way and with the means of eye tracking techniques, were used in the study to track the process of solving comparable tasks presented on a computer monitor. The indicator of operational knowledge was the effectiveness of problem solving. The research was conducted on a group of 48 third-grade junior secondary school students. The obtained results (low level of correct answers) indicate that the situation in the area of learning the algorithmic skills of students requires improvement. The measurement data obtained using eye tracking allowed for an in-depth analysis and interpretation of visual activity of students. Therefore, it seems that eye tracking can be considered as a complementary research technique, enriching the state of knowledge on cognitive mechanisms that are triggered in the process of solving algorithmic problems.
Keywords: algorithmic problems solving, flowchart of algorithms, teaching and learning programming, eye movement parameters, eye tracking
References
- Andrzejewska, M., Stolińska, A. (2017). Kierowanie uwagą wzrokową w procesie rozwiązywania problemów algorytmicznych. Edukacja, Technika, Informatyka, 2(20), 308-314. DOI: 10.15584/eti.2017.2.40.
- Andrzejewska, M., Stolińska, A. (2016). Comparing the Difficulty of Tasks Using Eye Tracking Combined with Subjective and Behavioural Criteria. Journal of Eye Movement Research, 9(3), 1-16. DOI: 10.16910/jemr.9.3.3.
- Andrzejewska M. et. al. (2016). Eye-tracking verification of the strategy used to analyse algorithms expressed in a flowchart and pseudocode. Interactive Learning Environments, 24(8), 1981-1995. DOI: 10.1080/10494820.2015.1073746.
- Andrzejewska, M., Stolińska, A. (2015). Zastosowanie okulografii do identyfikacji metod analizy problemu algorytmicznego. Edukacja-Technika-Informatyka, 6(3), 209-215.
- Bednarik, R., Tukiainen, M. (2006). An eye-tracking methodology for characterizing program comprehension processes. Proceedings of Symposium on Eye-Tracking Research and Applications (ETRA), 125-132. DOI: 10.1145/1117309.1117356.
- Binkley, D. et.al. (2013). The impact of identifier style on effort and comprehension. Empirical Software Engineering, 18(2), 219-276.
- Busjahn, T., Shulte, C., Busjahn, A. (2011). Analysis of code reading to gain more insight in program comprehension. Proceedings of the 11th Koli Calling International Conference on Computing Education Research, 1-9.
- Busjahn, T. et.al. (2015). Eye movements in code reading: relaxing the linear order. Proceedings of the IEEE 23rd International Conference on Program Comprehension, 255-265.
- Dimitri, G.M. (2015). The impact of syntax highlighting in Sonic Pi. Proceedings of the 26th Annual Conference of the Psychology of Programming Interest Group (PPIG 2015), 59-68.
- Futschek, G. (2006). Algorithmic Thinking: The Key for Understanding Computer Science. R.T. Mittermeir (Ed.). Informatics education - the bridge between using and understanding computers, Vol. 4226, 159-168. DOI: 10.1007/11915355_15.
- Garner, S. (2002). Reducing the Cognitive Load on Novice Programmers. P. Barker, S. Rebelsky (Eds.). Proceedings of ED-MEDIA 2002 World Conference on Educational Multimedia, Hypermedia & Telecommunications, 578-583. Denver, Colorado, USA: Association for the Advancement of Computing in Education (AACE).
- Gomes, A., Mendes, A.J. (2007). Learning to program - difficulties and solutions. Proceedings of the ICEE 2007 - International Conference on Engineering Education. Retrieved from: http://icee2007.dei.uc.pt/proceedings/papers/411.pdf.
- Govender, I., Grayson, D. (2006). Learning to program and learning to teach programming: A Closer Look. E. Pearson, P. Bohman (Eds.). Proceedings of ED-MEDIA 2006 - World Conference on Educational Multimedia, Hypermedia & Telecommunications, 1687-1693.
- Lai, M.L. et.al. (2013). A review of using eye-tracking technology in exploring learning from 2000 to 2012. Educational Research Review, 10, 90-115.
- Moström, J.E. (2011). A Study of Student Problems in Learning to Program. Umea, Sweden: Department of Computing Science Umea University.
- Ozcelik, E., Karakus, T., Kursun, E., Cagiltay, K. (2009). An eye-tracking study of how color coding affects multimedia learning. Computers & Education, 53(2), 445-453. DOI: 10.1016/j.compedu.2009.03.002.
- Rozporządzenie Ministra Edukacji Narodowej z dnia 14 lutego 2017 r. w sprawie podstawy programowej wychowania przedszkolnego oraz podstawy programowej kształcenia ogólnego dla szkoły podstawowej, w tym dla uczniów z niepełnosprawnością intelektualną w stopniu umiarkowanym lub znacznym, kształcenia ogólnego dla branżowej szkoły I stopnia, kształcenia ogólnego dla szkoły specjalnej przysposabiającej do pracy oraz kształcenia ogólnego dla szkoły policealnej (Dz.U. z 2017, poz. 356, tom 1).
- Sarkar, A. (2015). The impact of syntax colouring on program comprehension. Proceedings of the 26th Annual Conference of the Psychology of Programming Interest Group (PPIG 2015), 49-58.
- Sharif, B., Falcone, M., Maletic, J.I. (2012). An eye-tracking study on the role of scan time in finding source code defects. Proceedings of Symposium on Eye-Tracking Research and Applications (ETRA), 381-384.
- Stolińska A., Andrzejewska, M. (2017a). Testing cognitive loads in solving algorithmic tasks. 15th International Conference on Emerging eLearning Technologies and Applications (ICETA), 1-6. DOI: 10.1109/ICETA.2017.8102530.
- Stolińska, A., Andrzejewska, M. (2017b). Analysis of the strategy used to solve algorithmic problem - a case study based on eye-tracking research. P. Dang, M. Ku, T. Qian, L.G. Rodino (Eds.). New trends in analysis and interdisciplinary applications, 67-76. DOI: 10.1007/978-3-319-48812-7_11.
- Uwano, H., Nakamura, M., Monden, A., Matsumoto, K.I. (2006). Analyzing individual performance of source code review using reviewers' eye movement. Proceedings of Symposium on Eye-Tracking Research and Applications (ETRA), 133-140.
- Wing, J.M. (2006). Computational thinking. ACM, 49(3), 33-35. DOI: 10.1098/rsta.2008.0118.
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About the article
DOI: https://doi.org/10.15219/em74.1347
The article is in the printed version on pages 10-18.
How to cite
Andrzejewska, M., Stolińska, A. (2018). The eye-tracking technique in the analysis of mechanisms for solving algorithmic problems. e-mentor, 2(74), 10-18. DOI: https://doi.org/10.15219/em74.1347
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