16 SES 08 B, Functioning in a Digital World
Gamification refers to the use of game elements in non-play environments (Deterding, Dixon, Khaled, & Nacke, 2011). It involves using of game elements in a useful way in the environment instead of designing the environment as a game completely (Deterding et al., 2011). Game mechanics and dynamics constitute the basic elements of gamification. It is important to use these basic elements, the basic elements to make learning environments fun and useful.
Gamification in education is not just about adding a game to teaching of knowledge or skills; rather, it consists of integrating engaging games that have the potential to facilitate the learning of learners into the current learning environment.
Elements of gamification, initially used in real classroom environments, are also in use in computer-assisted education through digital games today. Prensky (2001) emphasizes that the presence of interaction, problem solving, fun, set goals, rules, scenario, instant feedback and competition in digital games would enhance educational usability of digital games.
It is known that primary school-level children's acceptance of digital computer games is affected significantly by rich learning content and ease of use (Cheng & Su, 2012). Besides, effective course design is known to increase the educational value of digital games (Hong et al., 2009).
Digital games that are not well designed and not clearly known how to use in the course would bring disadvantages together (Hong et al., 2009). It is an important problem that students get drifted away from the goal in the game environment and the games with teaching purposes turn into games with entertainment purposes only (Kebritchi et al., 2009). In order to overcome this situation, it is crucial that the teaching contents and the game elements have a balanced place in games and the learning activities to be realized in the game are expressed clearly (Ribeiro, Coelho, & Aguiar, 2011). It implies that providing target-oriented customized guidance and support to pupils should be taken into consideration in the design of digital games (Papestrergiou, 2009).
For the purpose of guiding and evaluating students, determining their educational needs, advising and realizing individualised learning by following their learning process step by step; the importance of Adaptive Intelligent Tutoring Systems (AITS), built on artificial intelligence techniques, is becoming outstanding among computer-aided education technologies (Huang et al., 2012). The aim of AITS is to teach students desired behaviours by finding out students' knowledge or errors and helping them to correct their errors (Huang et al., 2012).
Therefore, it is thought that using digital games together with AITS, which can provide instant feedback, step-by-step support and orientation to learners in the learning process, can have a meaningful effect (Tobias & Duffy, 2009) because while digital game-based learning offers a learning environment that is fun, motivational, increases engagement, and supports active learning support; AITS provides students with opportunities to work with software which can be adapted according to their instant performance, individual traits and needs (Zapušek & Rugelj, 2013).
Departing from the foregoing, this study aims to describe the path and tools used in the gamification process of the ARTIBOS, an adaptive intelligent tutoring system, so that adaptive intelligent instructional system designers can integrate affective qualities into the system.
So, the study was carried out seeking answer for the following questions:
How can an adaptive intelligent tutoring system gamified?
What game dynamics can be used for adaptive intelligent tutoring systems?
What game mechanics can be used for adaptive intelligent tutoring systems?
ARTIBOS is a web-based system that allows 15 to 18-year old students to create problems on a stage by using objects given for various types of problems (mixture, movement, percentage, interest, worker, pool, profit-loss, number-fraction, age). On ARTIBOS, students can create problems by building stages to send problems to the other students logged in, solve the received problems through the system, and duel by exchanging problems at the same time. They earn or lose points according to the problem solving performance of the other students on the problems they have already sent. In addition, students can earn bonus points according to the number of entries in the system in order to avoid dropouts, or they can use the opportunities called gold points where they can earn more points. Users start at the novice level in the system and then can advance to the platinum level depending on their total points. The requirements for transition between leagues were determined by taking into consideration the characteristics of the AITS and the elements in the system. Similarly, the other students answering students' queries about the problems they prepare were determined according to their league. The evaluation of the points earned by students in different ways and the intervals of the leagues were determined by using fuzzy logic sets. In this way, static evaluation of students was replaced with dynamic evaluation which changes depending on the players' characteristics. Zichermann and Cunningham (2011) describe gamification as using the mindsets, processes and game mechanics in the game with the aim of drawing attention of the users and solving problems during the game. As a fun and motivating environment, ARTIBOS was gamified by examining a number of frameworks for gamification, and a gamification framework suitable for the ARTIBOS was selected. The planning of the gamification process is based on the D6 design model of Werbach and Hunter (2012). In this study, the findings obtained from the analysis of similar studies and literature review were assessed by 5 experts from the discipline. As a result, the game dynamic and mechanics suitable for adaptive systems and intelligent tutoring systems were determined.
In this study, the gamification model that can be used for adaptive intelligent tutoring systems was formed by identifying the data obtained from ARTIBOS, determining the appropriate game dynamics and mechanics for ARTIBOS, and adapting the game elements to the values obtained from ARTIBOS. The use of gamification elements in ARTIBOS was designed in the way of determining the difficulty level of the questions and calculation of the points to be earned in each league. The information that needs to be kept in the system for the calculation of points includes time, number of errors and percentage of problems solved. The game mechanics for ARTIBOS include points, level, leader's board, and challenge. Point types were determined as question points, liking points, questioning points, problem solving points, gold points, bonus points, duel points and total points. Player levels were graded as novice, copper, bronze, silver, gold, and platinum players. The leader's board, which is another game mechanic, is used as an element that the players can see the points of the players in the other leagues subject to the rules depending on their league. In ARTIBOS, challenge components which is game mechanics, were provided by use the duel competitions. The game dynamics used in the system are; reward, status, competition, story, self-expression, and feedback. This model was developed on ARTIBOS, an adaptive intelligent teaching system. However, tests and field studies are still in progress regarding its use. We think that this model can be integrated into adaptive systems into the system ultimately to develop systems which will provide individual learning by students and increase their motivation. As a conclusion, the benefits of games such as increased motivation and engagement to the lesson, can be combined with the benefits provided by AITS thanks to the present model.
Cheng, C. H., & Su, C. H., 2012. A Game-based learning system for improving student’s learning effectiveness in system analysis course. Procedia—Social and Behavioral Sciences, 31, 669–675. Deterding, S., Dixon, D., Khaled, R., Nacke, L., 2011. From game design elements to game fullness: defining gamification. In Paper presented at the 15th International Academic MindTrek Conference: Envisioning Future Media Environments, Tampere, Finland. Hong, D., Zhen, Z., Xingyan, T., 2009. Artificial pet game-based intelligent tutoring system. In Computer Science & Education. 4th IEEE International Conference on, pp. 1711-1714. Huang, T.H., Liu, Y.C, Chang, H.C., 2012. Learning achievement in solving word-based mathematical questions through a computer-assisted learning system. Educational Technology & Society, 15(1), 248–259. Kebritchi, M., Hirumi, A., Kappers, W., Henry, R., 2009. Analysis of the supporting web sites for the use of instructional games in K‐12 settings. British Journal of Educational Technology, 40(4), 733-754. Papastergiou, M., 2009. Digital game-based learning in high-school computer science education: Impact on educational effectiveness and student motivation. Computers & Education, 52 (1), 1-12. Prensky, M., 2005. Computer games and learning: Digital game-based learning. Handbook of Computer Game Studies, 18, 97-122. Ribeiro, A., Coelho, A., & Aguiar, A. (2011). Boobo World – A collaborative video game to introduce programming concepts to children. In VideoJogos 2011 – The 4th Annual Conference In Science And Art Of Video Games, Porto, Portugal. Rodrigo, M. M. T., d Baker, R. S., D’Mello, S., Gonzalez, M. C. T., Lagud, M. C., Lim, S. A., 2008. Comparing learners’ affect while using an intelligent tutoring system and a simulation problem solving game. In Intelligent Tutoring Systems, pp. 40-49. Tobias, S., & Duffy, T. M. (Eds.), 2009. Constructivist instruction: Success or failure?. Routledge. Zapušek, M., Rugelj, J., 2013. Applying ideas from intelligent tutoring systems for teaching programming in game based learning. In Proceedings of the 7th European Conference on Games Based Learning, pp. 756-760. Zichermann, G., Cunningham, C., 2011. Gamification by design: Implementing game mechanics in web and mobile apps. O'Reilly Media, Inc. . Werbach, K., & Hunter, D., 2012. For the win: How game thinking can revolutionize your business. Wharton Digital Press.
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