Computational creativity: an interdisciplinary approach to sequential learning and creative generations

Creativity seems mysterious; when we experience a creative spark, it is difficult to explain how we got that idea, and we often recall notions like ``inspiration" and ``intuition" when we try to explain the phenomenon. The fact that we are clueless about how a creative idea manifests itself does not necessarily imply that a scientific explanation cannot exist. We are unaware of how we perform certain tasks, such as biking or language understanding, but we have more and more computational techniques that can replicate and hopefully explain such activities. We should understand that every creative act is a fruit of experience, society, and culture. Nothing comes from nothing. Novel ideas are never utterly new; they stem from representations that are already in mind. Creativity involves establishing new relations between pieces of information we had already: then, the greater the knowledge, the greater the possibility of finding uncommon connections, and the more the potential to be creative. In this vein, a beneficial approach to a better understanding of creativity must include computational or mechanistic accounts of such inner procedures and the formation of the knowledge that enables such connections. That is the aim of Computational Creativity: to develop computational systems for emulating and studying creativity. Hence, this dissertation focuses on these two related research areas: discussing computational mechanisms to generate creative artifacts and describing some implicit cognitive processes that can form the basis for creative thoughts.

Weak reasoning argumentative theory. A dialogical approach for the discovery of philosophy in high schools

In the literature on philosophical practices, despite the crucial role that argumentation plays in these activities, no specific argumentative theories have ever been proposed to assist the figure of the facilitator in conducting philosophical dialogue and to enhance student’s critical thinking skills. The dissertation starts from a cognitive perspective that challenges the classic Cartesian notion of rationality by focusing on limits and biases of human reasoning. An argumentative model (WRAT – Weak Reasoning Argumentative Theory) is then outlined in order to respond to the needs of philosophical dialogue. After justifying the claim that this learning activity, among other inductive methodologies, is the most suitable for critical thinking education, I inquired into the specific goal of ‘arguing’ within this context by means of the tools provided by Speech Act Theory: the speaker’s intention is to construct new knowledge by questioning her own and other’s beliefs. The model proposed has been theorized on this assumption, starting from which the goals, and, in turn, the related norms, have been pinpointed. In order to include all the epistemic attitudes required to accomplish the complex task of arguing in philosophical dialogue, I needed to integrate two opposed cognitive accounts, Dual Process Theory and Evolutionary Approach, that, although they provide incompatible descriptions of reasoning, can be integrated to provide a normative account of argumentation. The model, apart from offering a theoretical contribution to argumentation studies, is designed to be applied to the Italian educational system, in particular to classes in technical and professional high schools belonging to the newly created network Inventio. This initiative is one of the outcomes of the research project by the same name, which also includes an original Syllabus, research seminars, a monitoring action and publications focused on introducing philosophy, in the form of workshop activities, into technical and professional schools.

Bridging the gap:exploring the cognitive impact of InterpretBank on Chinese interpreting trainees

This exploratory research project developed a cognitive situated approach to studying aspects of simultaneous interpreting with quantitative, confirmatory methods. To do so, it explored how to determine the potential benefits of using a computer-assisted interpreting tool, InterpretBank, among 22 Chinese interpreting trainees with Chinese L1 and English L2. The informants were mostly 2nd-year female students with an average age of 24.7 enrolled in Chinese MA interpreting programs. The study adopted a pretest and posttest design with three cycles. The independent variable was using Excel or InterpretBank. After Cycle I (pre-test), the sample split into control (Excel) and experimental (InterpretBank) groups. Tool choice was compulsory in Cycle II but not Cycle III. The source materials for each cycle were pairs of matching transcripts from popular science podcasts. Informants compiled glossaries out of one transcript, while the other one was edited for simultaneous interpreting, with 39 terms as potential problem triggers. Quantitative profiling results showed that InterpretBank informants spent less time on glossary compilation, generated more terms faster than Excel informants, but their glossaries were less diverse (personal) and longer. The booth tasks yielded no significant differences in fluency indicators except for more bumps (200-600ms silent time gaps) for InterpretBank in Cycle II. InterpretBank informants had more correct renditions in Cycles II and III but there was no statistically significant difference among accuracy indicators per cycle. Holistic quality assessments by PhD raters showed InterpretBank consistently outperforming Excel, suggesting a positive InterpretBank impact on SI quality. However, some InterpretBank implementations raised cognitive ergonomic concerns for Chinese, potentially undermining its utility. Overall, results were mixed regarding InterpretBank benefits for Chinese trainees, but the project was successful in developing cognitive situated interpreting study methods, constructs and indicators.