Kong, S.C., Ogata, H., Arnseth, H.C., Chan, C.K.K., Hirashima, T., Klett, F., Lee, J.H.M., Liu, C.C., Looi, C.K., Milrad, M., Mitrovic, A., Nakabayashi, K., Wong, S.L., Yang, S.J.H. (eds.) (2009). Proceedings of the 17th International Conference on Computers in Education [CDROM]. Hong Kong: Asia-Pacific Society for Computers in Education. 162 Time Representation and Reasoning for a Story-telling Web Tool—the State of the Art Rosella GENNARI a , Tania di MASCIO b , and Giovanni de GASPERIS b a KRDB, Free University of Bozen-Bolzano, Italy b University of l’Aquila, gennari@inf.unibz.it {giovanni.degasperis, tania.dimascio}@ univaq.it Abstract: We are working on a story-telling web tool for primary-school classes. The tool should allow teachers to create or modify short stories, and elaborate temporal reasoning games that stimulate children to reason on the time dimension of stories. In this paper, we review the major theories and tools for qualitative temporal reasoning, studying two facets of time, relevant for such a tool: representation and reasoning. Keywords: artificial intelligence in education architectures (web-based), interaction design, knowledge modelling and representation. 1. Introduction Developing the cognitive capabilities of children to comprehend written texts is key to their development as young adults. In written stories, comprehension depends on the construction of a coherent mental representation of relations between the narrated events, e.g., see (Bamberg, 1987) and (Trabasso & van den Broek, 1985). Relations between events can be causal or temporal. Automated temporal reasoning is well studied in ICT, and off-the-shelf automated tools are available for it. We intend to exploit this body of knowledge, and develop it further by studying children’s causal-temporal and temporal reasoning on stories, in collaboration with psychologists and experts of usability. In this paper, we concentrate on temporal reasoning. According to child developmental studies, 8 olds are sensitive to the role of temporal relations in texts (such as before, while and after), and start using them in order to draw context-based deductions, e.g., see (McColgan & McCormack, 2008) and (Ge & Xuehong, 2002). Such reasoning capabilities develop further until the age of 11, when the concrete operational stage ends. 8 to 11 year old children are novice text comprehenders (novice comprehenders, henceforth). However, nowadays more and more novice comprehenders show problems in making global deductions on texts, as it seems to be the case of deaf children (Oakhill & Cain, 2000). Most educational material for novice comprehenders is mainly paper based, and educators cannot easily adapt it to the different types of novice comprehenders with text comprehension problems. The available electronic tools (e-tools, in brief) tend to concentrate on spelling, grammar, or highlighting passages of texts. Even when such e-tools tackle higher-level cognitive functions, they do not fully exploit artificial intelligence (AI) techniques or technologies. We are working on a story-telling web tool for primary-school classes, focussing on contemporary stories for children. The tool originates from LODE, a logic-based web system for deaf readers (Gennari & Mich, 2007). Our tool aims at being an AI system for novice comprehenders, focusing on those with problems in making global deductions on texts, and their educators. It will offer them: (1) hypertextual stories (h-stories, in brief); (2) smart temporal reasoning games; (3) visual interactions with the h-stories and games. The tool will adopt the qualitative temporal relations between events of stories that novice comprehenders should be able to master. In this paper, we review the major theories and tools for qualitative temporal representation and reasoning, in AI and HCI combined. As such, this paper paves the way for the design of our web tool.