Présentation d'une communication acceptée dans ICERI2018.
•Download as PPT, PDF•
0 likes•64 views
International Conference on Education, Research and Innovation. Seville - Andalousie 2019.
Recommended
Recommended
More Related Content
Similar to Présentation d'une communication acceptée dans ICERI2018.
Similar to Présentation d'une communication acceptée dans ICERI2018. (20)
More from Thouraya Daouas
More from Thouraya Daouas (10)
Recently uploaded
Recently uploaded (20)
Présentation d'une communication acceptée dans ICERI2018.
- 1. Learning Evaluation in a Persuasive Serious Game K. Sammadi & T. Daouas Institute of High Commercial Studies of Carthage (TUNISIA)
- 2. Context Use of Serious Games (SG) in education 3 big categories : – SG of message (educational, informative, persuasive) – SG of training (cognitive, driving performance) – SG of simulation (practices) ICERI'2018 Dr Thouraya Daouas 2 Introduction Concepts Proposed Model Application Conclusion
- 3. Persuasive SG Media of persuasive communication for a wide public Less studied Aim: Provoke on Player Learner (PL) behavioral changes Cognitive, affective and behavioural effects ICERI'2018 Dr Thouraya Daouas 3 Introduction Concepts Proposed Model Application Conclusion
- 4. Modeling and evaluating PL behavior ICERI'2018 Dr Thouraya Daouas 4 Concepsts Introduction Proposed Model Application Conclusion Bayesian Networks For modelling PL Influence Diagram For the formalization of the decision problem
- 5. Bayesian Networks (BN) “Belief Networks” or “Probabilistic Networks” Directed acyclic graph to formalize knowledge ICERI'2018 Dr Thouraya Daouas 5 Concepsts Introduction Proposed Model Application Conclusion Node = Variable = Knowledge Arc = Probabilistic dependencies between variables
- 6. Influence Diagram (ID) Extension to BN 3 kinds of nodes: – Chance Nodes: Same in BN (variables) – Decision Nodes: Alternatives available – Utility Nodes: Evaluation of alternatives Arcs depending on node kinds O and D: – 2 chance nodes – Points to decision node – From decision to chance node – Points to utility Node ICERI'2018 Dr Thouraya Daouas 6 Concepsts Introduction Proposed Model Application Conclusion
- 7. Three steps 1. Identifying PL behavioral characteristics 2. Modelling 3. Evaluation ICERI'2018 Dr Thouraya Daouas 7 Proposed Model Introduction Concepts Application Conclusion
- 8. 1. Identifying PL behavioral characteristics ICERI'2018 Dr Thouraya Daouas 8 Proposed Model Introduction Concepts Application Conclusion Psychological Test • Initial behavioral state before playing • Based on random couple of images • Each couple corresponds to a PL characteristic (Positive & Negative way) Game • Persuasive SG with several sessions • Two outcomes: Positive or negative behaviour • Intermediate behavioral state of PL
- 9. 2. Modeling Elements : – Initial characteristics given by the psychological test – Characteristics’ outcomes given by the game Transformation into variables having relationships between each other ICERI'2018 Dr Thouraya Daouas 9 Proposed Model Introduction Concepts Application Conclusion
- 10. 3. Evaluation with 2 floors: Probabilistic and Decision Using principles of ID to provide a behavioral evaluation of the PL in each session of the game • Calculate: • Probability of occurrence of behavioral characteristic • Chance of occurrence of results found in different sessions • Use the probabilities just calculated and concepts of utility and decision to assess behavior. ICERI'2018 Dr Thouraya Daouas 10 Proposed Model Introduction Concepts Application Conclusion
- 11. Anticorruption SG « Corjalean Planet » Project: action against corruption SG of raising awareness against corruption by Tunisia For All association Player plays with flows of money, which go towards a corrupt monster Aim: demonstrate him the utility to divert these flows towards a better use in the interest of all Change his behavior ICERI'2018 Dr Thouraya Daouas 11 Application Introduction Concepts Proposed Model Conclusion
- 12. Corjalean planet ICERI'2018 Dr Thouraya Daouas 12 Application Introduction Concepts Proposed Model Conclusion
- 13. Identifying behavioral characteristics ICERI'2018 Dr Thouraya Daouas 13 Application Introduction Concepts Proposed Model Conclusion Persuasive SG Storytelling Message
- 14. Example: Scene in a school ICERI'2018 Dr Thouraya Daouas 14 Application Introduction Concepts Proposed Model Conclusion You have an exam and you want to succeed among the first ones. You called on to a parent working on the school to spin you the subjects. However, the parent refuses. Your objective is to have the best marks. If you want to have the best marks at all costs, feed corjalean monster with the coins. Otherwise, put the coins in urns according to their colors.
- 15. Conclusion • Evaluate the PL progress using a persuasive SG • Give an indicator about the effectiveness of the SG in itself • Model : predictive results about probabilities of occurrence of behavior change • Applying this model : promising results • Next step : Experimentation with real PL samples ICERI'2018 Dr Thouraya Daouas 15 Conclusion Introduction Concepts Proposed Model Application
- 16. ICERI'2018 Dr Thouraya Daouas 16 Thank you for your attention !
Editor's Notes
- Good morning. My name is Thouraya Daouas, I’m presenting here a paper intitled Learning evaluation in a persuasive serious game. It consists on a research work belonging to a part of a thesis of one of my students whose name is Sammadi. I’m a profesor in HEC of Carthage in tunisia and for this work we collaborated with Tunisia for all association.
- The context of this work consists on using serious games in education. We can classify serious games in three big categories. First SG of message which deliver a message in an educational, informative and persuasive aim. Second SG of training which improves the cognitive or driving performances of the users and third SG of simulation or serious play which offers an open panel of practices.
- We are concerned here with the big part of SG which is less studied, upon researchers, called Persuasive SG. It is defined as a media of persuasive communication for a wide public. In this type of SG, the Player- Learner is put right into the action he is not a passive observer. The aim of persuasive SG is to provoke on PL behavioral changes at a cognitive level, affective level and behavioral effects.
- We propose a modelling using Bayesian networks in order to model the Player Learner and Influence diagram for the formalization of the decision problem.
- Bayesian Networks, also called belief networks or probabilistic networks. They are Directed acyclic graphs used to formalize knowledge. Each node of the graph represents a variable which is a knowledge. And the arc represents a probabilistic dependency between knowledges or variables.
- The influence diagram is an extension of the Bayesian networks. So we can found three kinds of nodes: the chance node which is the same in bayesian networks. The decision node which models the different alternatives available to the decision maker. And the Utility node which allows evaluating the alternatives by identifying a criterion to optimize. Arcs here depend on the node kind, if it is an origine node or a destination node of the arc. We can have 4 possibilities.
- We propose an approach following 3 steps. First identifying PL behavioral chacracteristics. Then Modelling and finally Evaluating.
- In order to identify the PL behavioral characteristics we use a psychological test. This test represents an initial behavioral state of the PL before playing. It is based on random couple of images displayed. And each couple corresponds to a PL characteristic, One image represents a positive aspect of the characteristic and the second its negative aspect. After that the PL begins playing the SG. Its a Persuasive SG with several sessions or missions. When playing we have 2 outcomes, positive or negative behaviour of the PL. These outcomes represent an intermediate behavioral state of PL.
- The second step is modelling. Using Bayesian Networks and Influence diagram, we have these elements. Initial characteristics given by the psychological test and Characteristic outcomes given by the game. We model transforming these elements into variables having relationships between each other.
- The third and last step is composed by two floors probabilistic and decision floor. We use principles of influence diagram to provide a behavioral evaluation of the PL in each session of the game. The model calculates the probability of occurrence of behavioral chacteristic as well as the chance of occurrence of results found in different sessions. Then, uses the probabilities just calculated and the concepts of utility and decision of ID to assess behavior.
- In order to apply the model, we colaborated with an association named Tunisia for All. In the framework of a project representing an action against corruption, this association developed a Persuasive SG raising awareness against corruption called Corjalean Planet. In this SG player plays with flows of money which go towards a corrupt monster. The aim of this SG is to demonstrate the Player the utility to divert these flows towards a better use in the interest of all and consequently change his behavior positively.
- This is the first screen of the SG. These are sessions with different levels, each one represents a situation, for example in a school, in the bank, in the post office, etc.
- Based on messages the SG uses storytelling. The player-Learner choses one scene or session, he reads a story explaning the situation and giving him two alternatives of playing, trying to gess if the player is more against corruption or not. After playing and depending of his choice and playing, he will read another message at the end of the session explaining him in both cases the reason of his results.
- This is an example of a scene in a school. When entering to this scene, the player reads a story. He is supposed to be in a period of exam.
- As a conclusion this model evaluates the PL progress using a persuasive SG. Second, It gives an indicator about the effectiveveness of the SG in itself. When applying the model to the SG of anticorruption, we found predictive results about probabilities of occurrence of behavior change. These are promising results. The next step in this work is what we are preparing now. Which is doing experimentation with real data of PL samples.