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dc.contributor.advisorHjelsvold, Rune
dc.contributor.advisorNowostawski, Mariusz
dc.contributor.authorChirchenkova, Mariya
dc.date.accessioned2018-01-23T15:00:58Z
dc.date.available2018-01-23T15:00:58Z
dc.date.created2017-12-15
dc.date.issued2017
dc.identifierntnudaim:18393
dc.identifier.urihttp://hdl.handle.net/11250/2479190
dc.description.abstractThis research focuses on the problem of students workload planning. According to some researchers, students poor performance can be a result of poor course design, as well as a result of poor workload planning. Thesis begins with introduction to the topic thorough review of solutions proposed by another researches for the workload planning. As a method to solve this issue, we have developed serious game, allowing player to test different strategies and learn from own practice what behavioral patterns lead to good performance, which to bed performance. Initial research was carried in general domain of workload planning. For conceptualization purposes we defined all data relative to student workload planning. Serious game that was created is System Dynamics based game. Key assumptions of game were: game runs through one study semester, with known rate of new assignments published. In the beginning of each week student has to make a plan, how many hours he will work in a week. Decision is based on time til the end of semester, assignment backlog and other factors. Goal of the game is to complete all tasks within deadline and at descent grade. As a first step of development, a Casual loop diagram, summarizing problem entities and their relations was presented. Then thesis presents process of developing level and rate diagram, where authors accounted factors like subjective perception, decrease in energy and influence of dissatisfaction with grades.The model was validated using System Dynamics methods and through data collection. To provide better utility, Online simulation was developed. Simulation is hosted on Forio server and can be accessed via direct URL. In order to ensure learning effect, players can simulate pre-defined strategies and compare outcomes. In final part I present insights derived from exploration of model structure and behaviour. Those insights contain either patterns of behavior preventing positive result or patterns of behaviour promoting positive result. Hence students can learn, what behavioural patterns they should follow to achieve good result. In case they already selected strategy with expected poor performance- which behavioral patterns they should avoid, to improve their workload skills.
dc.languageeng
dc.publisherNTNU
dc.subjectApplied Computer Science, Web, Mobile, Games
dc.titleSerious game of student`s workload planning
dc.typeMaster thesis


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