Interactive Narrative for Adaptive Educational Games: Architecture and an Application to Character Education

This thesis presents AEINS, Adaptive Educational Interactive Narrative System, that supports teaching ethics for 8-12 year old children. AEINS is designed based on Keller's and Gagné's learning theories. The idea is centered around involving students in moral dilemmas (called teaching moments) within which the Socratic Method is used as the teaching pedagogy. The important unique aspect of AEINS is that it exhibits the presence of four features shown to individually increase effectiveness of edugames environments, yet not integrated together in past research: a student model, a dynamic generated narrative, scripted branched narrative and evolving non-player characters. The student model aims to provide adaptation. The dynamic generated narrative forms a continuous story that glues the scripted teaching moments together. The evolving agents increase the realism and believability of the environment and perform a recognized pedagogical role by helping in supplying the educational process. AEINS has been evaluated intrinsically and empirically according to the following themes: architecture and implementation, social aspects, and educational achievements. The intrinsic evaluation checked the implicit goals embodied by the design aspects and made a value judgment about these goals. In the empirical evaluation, twenty participants were assigned to use AEINS over a number of games. The evaluation showed positive results as the participants appreciated the social characteristics of the system as they were able to recognize the genuine social aspects and the realism represented in the game. Finally, the evaluation showed indications for developing new lines of thinking for some participants to the extent that some of them were ready to carry the experience forward to the real world. However, the evaluation also suggested possible improvements, such as the use of 3D interface and free text natural language

A Formal Architecture of Shared Mental Models for Computational Improvisational Agents

This paper proposes a formal approach of constructing shared mental models between computational improvisational agents (improv agents) and human interactors based on our socio-cognitive studies of human improvisers. Creating shared mental models helps improv agents co-create stories with each other and interactors in real-time interactive narrative experiences. The approach described here allows flexible modeling of non-Boolean (i.e. fuzzy) knowledge about scene and background concepts through the use of fuzzy rules and confidence factors in order to allow reasoning under uncertainty. It also allows improv agents to infer new knowledge about a scene from existing knowledge, recognize when new knowledge may be divergent from the other actor’s mental model, and attempt to resolve this divergence to reach cognitive consensus despite the absence of explicit goals in the story environment

Reaching Cognitive Consensus with Improvisational Agents

A common approach to interactive narrative involves imbuing the computer with all of the potential story pre- authored story experiences (e.g. as beats, plot points, planning operators, etc.). This has resulted in an accepted paradigm where stories are not created by or with the user; rather, the user is given piecemeal access to the story from the gatekeeper of story knowledge: the computer (e.g. as an AI drama manager). This article describes a formal process that provides for the equal co-creation of story-rich experiences, where neither the user nor computer is in a privileged position in an interactive narrative. It describes a new formal approach that acts as a first step for the realtime co-creation of narrative in games that rely on the negotiated shared mental model between a human actor and an AI improv agent

A Hybrid Expert System Supporting Diagnosis of Heart Diseases

In this paper, we have developed a hybrid expert system prototype used for supporting diagnosis of heart diseases. The system merges uncertainty management techniques and case-based reasoning. The system is able to give appropriate diagnosis for 4 heart diseases namely; mitral stenosis, left-sided heart failure, stable angina pectoris and essential hypertension with the corresponding certainty factor. The system has been implemented in visual prolog for windows and has trained set of 42 cases for Egyptian cardiac patients and has been tested by another 13 different cases. Each case contains 33 significant attributes resulted from the statistical analysis performed to 110 cases

Teaching in Ill-Defined Domains Using ITS and AI Appraoches

Ill-defined domains offer many challenges to computer scientists. Developing intelligent tutoring systems (ITSs) in these domains is a very challenging task due to the difficulty in modeling these domains, answers to ill-defined problems are ambiguously identified as right or wrong, and no generally accepted architecture is currently existed. This paper presents general guidelines for the development of ITSs in ill-defined domains, such as Argumentation and Ethics. This is instantiated in the two example systems AEINS and ALES. These systems offer adaptive learning processes and personalized feedback aiming to transfer the required skills to the learners and develop their reasoning

Cultivating intelligent tutoring cognizing agents in ill-defined domains using hybrid approaches

Cognizing agents are those systems that can perceive information from the external environment and can adapt to the changing conditions of that environment. Along the adaptation process a cognizing agent perceives information about the environment and generates reactions. An intelligent tutoring cognizing agent should deal not only with the tutoring system’s world but also with the learner-it should infer and predict new information about the learner and tailor the learning process to fit this specific learner. This paper shows how intelligent tutoring cognizing agents can be cultivated in ill-defined domains using hybrid techniques instantiated in the two example agents AEINS-CA and ALES-CA. These agents offer adaptive learning process and personalized feedback aiming to transfer certain cognitive skills, such as problem solving skills to the learners and develop their reasoning in the two ill-defined domains of ethics and argumentation. The paper focuses on the internal structure of each agent and the reasoning methodology, in which, the cognizing agent administration and construction along with the pedagogical scenarios are described

Educational Narrative-Based Environment to Teach Ethics

This paper presents AEINS, an educational system to teach ethics using the Socratic Method pedagogy [1]. AEINS is based on an architecture that marriages interactive narrative and intelligent tutoring. The idea is centered around involving students in different moral dilemmas (teaching moments). AEINS provides individualized story-paths and a personalized learning process. AEINS early evaluation shows promising results

Character Education using Pedagogical Agents and Socratic Voice

Promoting ethical, responsible, and caring young people is a perennial aim of education. Schools are invited to include moral teaching in every possible curriculum, such as the core subjects and sports teams and clubs. Efforts have been done to find other teaching ways other than traditional ones such as games or role play or engaging students in moral dilemmas. Computer games have been always found as one of the most engaging learning platforms. This paper introduces AEINS, a learning environment that is designed and implemented based on the learning theories such as: Bloom’s Taxonomy, Keller’s ARCS model and Gagné’s Nine Principles. The learning environment allows the students to interact with different moral dilemmas and see the effect of their choices on themselves and others. AEINS makes use of the Socratic Method as its predominant teaching pedagogy and employs pedagogical agents to supply the educational process. AEINS evaluation results indicated development of moral reasoning and transfer of moral virtues to its users

Adaptive Augmented Reality Serious Game to Foster Problem Solving Skills

This paper describes the design of an adaptive intelligent augmented reality serious game which aims to foster problem solving skills in young learners. Studies show that our students lack computational thinking skills in high school, which raises the need to establish new methods to develop these skills in our younger learners. We believe that problem solving skills are the fundamental skills of computational thinking and are critical for STEM, in addition to a broad range of other fields. Therefore we decided to focus on those meta-cognitive skills acquired to foster problem solving, such as strategic knowledge. The game described in this paper provides a unique adaptive learning environment that aims to develop learners’ meta-cognitive skills by utilizing augmented reality technology, believable pedagogical agents and intelligent tutoring modules. It offers a great user experience and entertainment which we hope will encourage learners to invest more time in the learning process. This paper describes the architecture and design of the game from the viewpoint of educational pedagogies and frameworks for serious game design

Serious Games to Teach Ethics

In this paper, we are focusing on digital serious games (edugames) and how they can be utilized in teaching in the ethics and citizenship domain. Our aim is to combine narrative techniques with intelligent tutoring techniques in a single model that adopts and based on educational theories and classroom educational strategies. The model has been used to implement an adaptive educational interactive narrative system (AEINS). AEINS is an inquiry based edugame to support teaching ethics. The AEINS version presented in this paper targets students between the age of 8 and 11. The idea is centered around presenting and involving students in different moral dilemmas (called teaching moments) within which the Socratic Method is the used pedagogy in the teaching process. AEINS monitors and analyzes the students actions in order to provide an individualized story-path and an individualized learning process. The student is an active participant in the educational process and is able to interact with the edugame as a first person player. We claim that such interaction can help in developing new or deeper thoughts about different moral situations. Our aim is to contribute to the design of serious games and help raise awareness of ethics and citizenship in children