Evaluating the Non-Involvement of the User of Educational Web Services in Interactive Interaction Based on Reaction Time
Abstract
Modern digital platforms provide a large number of web services for learning and professional growth. In most cases, educational web services only control access when connecting to resources and platforms. For educational and other resources (internet surveys, online research), which are characterized by interactive interaction with the platform, it is important to control user involvement. The characteristic of involvement can be the delay time on the elements of the web interface. This time is required for mastering the material, reading the text of the task or test. There are two common types of users with "unnatural" reactions: bot (robot) and clicker user. The latter, although he is a person, is not involved in the interactive process of interaction with the resource. The clicker simply clicks through all the questions, texts and other elements of the web service interface. Thus, the control of involvement in the interactive process of interacting with a web resource should identify bots and clickers, they also need to be removed when conducting online research and surveys. On the basis of the hypothesis about the randomness of the dynamics of the time series, the maximal Lyapunov exponent calculated for the time series formed from the reaction time of users during prolonged work with web interfaces was chosen as an indicator for controlling involvement in interactive interaction. A feature of the proposed involvement control is the high speed and development of algorithms for calculating the maximal Lyapunov exponent. The results of experimental studies on a large amount of data are presented, demonstrating the applicability of the selected characteristic for detecting bots and clickers.
References
2. Greenhow C., Graham C.R., Koehler M.J. Foundations of online learning: Challenges and opportunities. Educational Psychologist. 2022;47(3):131-147. https://doi.org/10.1080/00461520.2022.2090364
3. Blackburn A.M., Vestergren S. COVIDiSTRESS diverse dataset on psychological and behavioural outcomes one year into the COVID-19 pandemic. Scientific data. 2022;9:1-25. https://doi.org/10.1038/s41597-022-01383-6
4. Keusch F. Why do people participate in Web surveys? Applying survey participation theory to Internet survey data collection. Management review quarterly. 2015;65:183-216. https://doi.org/10.1007/s11301-014-0111-y
5. Kuleto V., Ilić M., Dumangiu M., Ranković M., Martins O.M.D., Păun D., Mihoreanu L. Exploring Opportunities and Challenges of Artificial Intelligence and Machine Learning in Higher Education Institutions. Sustainability. 2021;13(18):10424. https://doi.org/10.3390/su131810424
6. Nikulchev E.V., Ilin D.Yu., Kolyasnikov P.V., Ismatullina V.I., Zakharov I.M., Malykh S.B. Razrabotka otkrytoj cifrovoj platformy masshtabnyh psihologicheskih issledovanij [Development of the Open Digital Platform for Conducting the Large-Scale Psychological Research]. Vestnik Rossijskogo fonda fundamental'nyh issledovanij = Russian Foundation for Basic Research Journal. 2019;(4):105-119.[ 3] (In Russ., abstract in Eng.) https://doi.org/10.22204/2410-4639-2019-104-04-105-119
7. Verhoef P.C. et al. Digital transformation: A multidisciplinary reflection and research agenda. Journal of Business Research. 2021;122:889-901. https://doi.org/10.1016/j.jbusres.2019.09.022
8. Mathôt S., Schreij D., Theeuwes J. OpenSesame: An open-source, graphical experiment builder for the social sciences. Behavior research methods. 2012;44:314-324. https://doi.org/10.3758/s13428-011-0168-7
9. Habeeb R.A.A., Nasaruddin F., Gani A., Hashem I.A.T., Ahmed E., Imran M. Real-time big data processing for anomaly detection: A survey. International Journal of Information Management. 2019;45:289-307. https://doi.org/10.1016/j.ijinfomgt.2018.08.006
10. Chetverikov A., Upravitelev P. Online versus offline: The Web as a medium for response time data collection. Behavior research methods. 2016;48:1086-1099. https://doi.org/10.3758/s13428-015-0632-x
11. Dewitt J., Capistrant B., Kohli N., Rosser B. S., Mitteldorf D., Merengwa E., West W. Addressing participant validity in a small internet health survey (The Restore Study): protocol and recommendations for survey response validation. JMIR research protocols. 2018;7(4):e7655. https://doi.org/10.2196/resprot.7655
12. Magomedov Sh.G., Kolyasnikov P.V., Nikulchev E.V. Razrabotka tekhnologii kontrolya dostupa k cifrovym portalam i platformam na osnove vstroennyh v interfejs ocenok vremeni reakcij pol'zovatelej [Development of technology for controlling access to digital portals and platforms based on estimates of user reaction time built into the interface]. Rossijskij tekhnologicheskij zhurnal = Russian Technological Journal. 2020;(6):34-46. (In Russ., abstract in Eng.) https://doi.org/10.32362/2500-316X-2020-8-6-34-46[ 4]
13. Kim J., Gabriel U., Gygax P. Testing the effectiveness of the Internet-based instrument PsyToolkit: A comparison between web-based (PsyToolkit) and lab-based (E-Prime 3.0) measurements of response choice and response time in a complex psycholinguistic task. PLoS ONE. 2019;14(9):e0221802. https://doi.org/10.1371/journal.pone.0221802
14. Magomedov S., Gusev A., Ilin D., Nikulchev E. Users Reaction Time for Improvement of Security and Access Control in Web Services. Applied Sciences. 2021;11(6):2561. https://doi.org/10.3390/app11062561
15. Magomedov S., Ilin D., Silaeva A., Nikulchev E. Dataset of user reactions when filling out web questionnaires. Data. 2020;5(4):108. https://doi.org/10.3390/data5040108
16. Nikulchev E., Ilin D., Silaeva A., Kolyasnikov P., Belov V., Runtov A., Pushkin P., Laptev N., Alexeenko A., Magomedov Sh., Kosenkov A., Zakharov I., Ismatullina, Malykh S. Digital Psychological Platform for Mass Web-Surveys. Data. 2020;5(4):95. https://doi.org/10.3390/data5040095
17. Anrijs S., Ponnet K., De Marez L. Development and psychometric properties of the Digital Difficulties Scale (DDS): An instrument to measure who is disadvantaged to fulfill basic needs by experiencing difficulties in using a smartphone or computer. PLoS ONE. 2020;15(5):e0233891. https://doi.org/10.1371/journal.pone.0233891
18. van Geert P.L.C. Dynamic Systems, Process and Development. Human Development. 2020;63(3-4):153-179. https://doi.org/10.1159/000503825
19. Gani M.O., Fayezeen T., Povinelli R.J., Smith R.O., Arif M., Kattan A.J., Ahamed S.I. A light weight smartphone based human activity recognition system with high accuracy. Journal of Network and Computer Applications. 2019;141:59-72. https://doi.org/10.1016/j.jnca.2019.05.001
20. Ramchandra S.K., Sanjay S.P., Dashrath W.N. Insider Interruption Identification and Protection by using Forensic Technique. International Research Journal of Engineering and Technology. 2019;6(3):700-704. Available at: https://www.irjet.net/archives/V6/i3/IRJET-V6I3129.pdf (accessed 12.01.2023).
21. Nikulchev E. Robust chaos generation on the basis of symmetry violations in attractors. In: 2014 2nd 2014 2nd International Conference on Emission Electronics (ICEE). St. Petersburg, Russia: IEEE Computer Society; 2014. p. 1-3. https://doi.org/10.1109/Emission.2014.6893972
22. Zemtsova N.I., Severtsev N.A. Matematicheskie metody vybora i ocenki pokazatelej bezopasnosti dinamicheskih sistem v processe ih raboty v okruzhayushchej srede [Mathematical methods for selecting and evaluating safety indicators of dynamic systems in the process of their operation in the environment]. Voprosy teorii bez-opasnosti i ustojchivosti sistem = Questions of the theory of safety and stability of systems. 2019;(21):135-155. (In Russ., abstract in Eng.) EDN: BYXIIF
23. Nikulchev E., Gusev A., Ilin D., Gazanova N., Malykh S. Evaluation of User Reactions and Verification of the Authenticity of the User s Identity during a Long Web Survey. Apply Science. 2021;11(22):11034. https://doi.org/10.3390/app112211034
24. Ong S.G.T., Quek G.C.L. Enhancing teacher-student interactions and student online engagement in an online learning environment. Learning Environments Research. 2023;26:681-707. https://doi.org/10.1007/s10984-022-09447-5
25. Tuma F. The use of educational technology for interactive teaching in lectures. Annals of Medicine and Surgery. 2021;62:231-235. https://doi.org/10.1016/j.amsu.2021.01.051
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