Адаптация к вовлеченности пользователя в адаптивной обучающей игре
Работая с нашим сайтом, вы даете свое согласие на использование файлов cookie. Это необходимо для нормального функционирования сайта, показа целевой рекламы и анализа трафика. Статистика использования сайта отправляется в «Яндекс» и «Google»
Научный журнал Моделирование, оптимизация и информационные технологииThe scientific journal Modeling, Optimization and Information Technology
Online media
issn 2310-6018

Adaptation to user engagement in an adaptive learning game

Shabalina O.A.   Kataev A.V.   Voronina A.A.  

UDC 004.4
DOI: 10.26102/2310-6018/2020.29.2.035

  • Abstract
  • List of references
  • About authors

User engagement is one of the key indicators of the quality of interactive software (software), which is characterized by intense user interaction with the system. Training software belongs to the category of products, which, by definition, are based on interaction with the user, so the user's involvement in the process of his interaction with the training system directly affects the quality of the system. Modern trends in the development of educational software are associated with the personification of the processes of user interaction with the system, which has led to the emergence of adaptive educational systems that can monitor user actions and adapt to their capabilities and needs. User involvement has a significant impact on learning and directly affects the result, therefore, the level of user involvement in the process of its interaction with the training system, as an indirect assessment of the user's knowledge level, is applicable as a characteristic of the adaptation model in the development of adaptive learning systems. The results of the engagement analysis can be used to adapt the system aimed at retaining and increasing user engagement in the process of its interaction with the system, and thus improve its quality. The paper considers methods for assessing involvement and the possibility of their application to assessing the quality of educational software at different stages of its life cycle. The features of the use of online-assessment of engagement to adapt the learning process to the user in adaptive learning games are shown, related to the need to distinguish between involvement in the game and involvement in the learning process, and correlation of involvement and success in mastering knowledge in the game. Some possible combinations of assessments of the involvement and effectiveness of the user's knowledge level in the process of interaction with the educational game and their possible interpretations are proposed.

1. Shabalina O.A., Kataev A.V., Davtyan A.G. Faceted training classification computer games. Bulletin of the Volgograd State Technical university. 2018; 13 (223): 95-100.

2. Shabalina O.A., Davtyan A.G., Kataev A.V., Alimov A.A. Adaptive learning games as a trend in the development of teaching software. ITNOU: Information technology in science, education and management. 2018; 4 (8): 11-16.

3. Engagement: Definition Available in: https://support.google.com/analytics/answer/9355853?hl=en (accessed: 11/16/2019)

4. Attfield S., Kazai G., Lalmas M., Piwowarski B. Towards a science of user engagement (Position Paper). Web Search and Data Mining. 2011.

5. Csikszentmihalyi M. Flow: The psychology of optimal experience. Harper and Row. 1990.

6. Webster J., Ho H. Audience engagement with multimedia presentations. The DATABASE for Advances in Information Systems. 1997:63–77. DOI: 10.1145/264701.264706.

7. The Best Metrics and Tools for Measuring User Engagement Available in: https://hackernoon.com/the-best-metrics-and-tools-for-measuring-user-engagementfb083d9a9be7 (accessed: 11/16/2019).

8. Murphy D., Higgins C. Secondary Inputs for Measuring User Engagement in Immersive VR Education Environments. 2019:1-6.

9. Russell J. A., Weiss A., Mendelsohn G. A. Affect grid: A single-item scale of pleasure and arousal. Journal Personality and Social Psychology. 1988:493– 502. DOI: 10.1037/0022- 3514.57.3.493.

10. Boucsein W. Electrodermal activity. New York: Springer. 2012.

11. Hardy M., Wiebe E.N., Grafsgaard J.F., Boyer K.E., Lester J.C. Physiological responses to events during training use of skin conductance to inform future adaptive learning systems. Proceedings of the Human Factors and Ergonomics Society Annual Meeting. 2013:2101– 2105. DOI: 10.1177/1541931213571468.

12. Ashby F. G., Isen A. M., Turken A. U. A neuropsychological theory of positive affect and its influence on cognition. Psychological Review. 1999;106(3):529-550. DOI: 10.1037/0033-295x.106.3.529.

13. Lalmas M., O’Brien H., Yom-Tov E. Measuring User Engagement. Synthesis lectures on information concepts, retrieval, and services. 2015:11-58.

14. Grafsgaard J. F., Boyer K. E., Wiebe E. N., Lester J. C. Analyzing Posture and Affect in Task-Oriented Tutoring. Artificial Intelligence. Proceedings of the 25th Florida Artificial Intelligence Research Society Conference. 2012:438-443.

15. Pekrun R., Goetz T., Titz W., Perry R. Academic emotions in students’ self-regulated learning and achievement: A program of qualitative and quantitative research. Educational Psychologist. 2002;37(2):91–105. DOI: 10.1207/s15326985ep3702_4.

16. Voronina A.A., Shabalina O.A., Kataev A.V. Engagement assessment methods users of interactive applications. ITNOU: Information technology in science, education and management. 2019; 4 (14): 70-74.

17. Rebelo F., Noriega P., Duarte E., Soares M. Using virtual reality to assess user experience. Human Factors: The Journal of Human Factors and Ergonomics Society. 2012;54(6):964- 982. DOI: 10.1177/0018720812465006.

Shabalina Olga Arkadyevna
candidate of technical sciences
Email: o.a.shabalina@gmail.com

Volgograd State Technical University

Volgograd, Russian Federation

Kataev Alexander Vadimovich
candidate of technical sciences
Email: alexander.kataev@gmail.com

Volgograd State Technical University

Volgograd, Russian Federation

Voronina Angelina Andreevna

Email: angelina.vaa@gmail.com

Volgograd State Technical University

Volgograd, Russian Federation

Keywords: engagement, engagement assessment, educational software quality, learning system, engagement online- assessment, adaptive learning game

For citation: Shabalina O.A. Kataev A.V. Voronina A.A. Adaptation to user engagement in an adaptive learning game. Modeling, Optimization and Information Technology. 2020;8(2). Available from: https://moit.vivt.ru/wp-content/uploads/2020/05/ShabalinaSoavtori_2_20_1.pdf DOI: 10.26102/2310-6018/2020.29.2.035 (In Russ).


Full text in PDF