The ITALK project : A developmental robotics approach to the study of individual, social, and linguistic learning

This is the peer reviewed version of the following article: Frank Broz et al, “The ITALK Project: A Developmental Robotics Approach to the Study of Individual, Social, and Linguistic Learning”, Topics in Cognitive Science, Vol 6(3): 534-544, June 2014, which has been published in final form at doi: http://dx.doi.org/10.1111/tops.12099 This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving." Copyright © 2014 Cognitive Science Society, Inc.This article presents results from a multidisciplinary research project on the integration and transfer of language knowledge into robots as an empirical paradigm for the study of language development in both humans and humanoid robots. Within the framework of human linguistic and cognitive development, we focus on how three central types of learning interact and co-develop: individual learning about one's own embodiment and the environment, social learning (learning from others), and learning of linguistic capability. Our primary concern is how these capabilities can scaffold each other's development in a continuous feedback cycle as their interactions yield increasingly sophisticated competencies in the agent's capacity to interact with others and manipulate its world. Experimental results are summarized in relation to milestones in human linguistic and cognitive development and show that the mutual scaffolding of social learning, individual learning, and linguistic capabilities creates the context, conditions, and requisites for learning in each domain. Challenges and insights identified as a result of this research program are discussed with regard to possible and actual contributions to cognitive science and language ontogeny. In conclusion, directions for future work are suggested that continue to develop this approach toward an integrated framework for understanding these mutually scaffolding processes as a basis for language development in humans and robots.Peer reviewe

Grounding the curriculum: learning from live projects in architectural education

Abstract: For more than twenty years architects in the UK have advocated the use of ‘live’ projects in architecture schools as an alternative to the more traditional model of studio learning, but the educational establishment continues to marginalize community-based approaches to learning. Recent debate, focusing on shortcomings of the studio culture in architectural education, has condemned the isolation of students from real world contexts and teaching methods that cultivate values of individualism and competition. As an alternative, many claims have been made about the potential for enhancing student learning by adopting live briefs and involving clients and users in the education of architects. Yet much of the literature remains largely speculative or descriptive and so far has neglected to investigate participatory design processes to determine their precise pedagogic value. The aims of this paper are to examine the nature of learning in student projects outside the studio environment, to locate that learning within a range of categories of learning, and to develop a conceptual structure for further exploration of alternative pedagogies in architectural education. The study is based on evaluations of two participatory design projects carried out with students at Lincoln School of Architecture in the UK. Students’ perceptions of the learning they acquired are compared with the intended learning outcomes identified by tutors at the start of the projects, and these are further contrasted with the ‘competencies’ that are typical outcomes of the traditional curriculum. The findings, which reveal significant contingent and emergent learning in the live projects, are then discussed in relation to recognized theories of learning, such as experiential learning, social constructionism, situated learning and collaborative learning. The objective is to identify an appropriate theoretical framework that may be used to draw attention to the valuable contribution of live project learning in architectural education and support arguments in favour of a more expansive and socially grounded architecture curriculum

Developing Educational Software: a professional tool perspective

The selection, and use of educational software and its impact in schools are still controversial issues. In this paper we present an alternative conceptualisation of educational software based on considering the software as an instrument for teachers’ professional performance. We review previous work in the areas of the design, development and evaluation of educational software and of the process of educational innovation. The review of these four areas converges to demonstrate the need for knowing and considering the context of use of educational software and for understanding users' perspectives about its roles and possibilities and hence supports a consideration a perspective on educational software which sees it as a professional tool for teachers performance of their teaching role

Social robots in educational contexts: developing an application in enactive didactics

Due to advancements in sensor and actuator technology robots are becoming more and more common in everyday life. Many of the areas in which they are introduced demand close physical and social contact. In the last ten years the use of robots has also increasingly spread to the field of didactics, starting with their use as tools in STEM education. With the advancement of social robotics, the use of robots in didactics has been extended also to tutoring situations in which these \u201csocially aware\u201d robots interact with mainly children in, for example, language learning classes. In this paper we will give a brief overview of how robots have been used in this kind of settings until now. As a result it will become transparent that the majority of applications are not grounded in didactic theory. Recognizing this shortcoming, we propose a theory driven approach to the use of educational robots, centred on the idea that the combination of enactive didactics and social robotics holds great promises for a variety of tutoring activities in educational contexts. After defining our \u201cEnactive Robot Assisted Didactics\u201d approach, we will give an outlook on how the use of humanoid robots can advance it. On this basis, at the end of the paper, we will describe a concrete, currently on-going implementation of this approach, which we are realizing with the use of Softbank Robotics\u2019 Pepper robot during university lectures

The use of Artificial intelligence in school science: a systematic literature review

Artificial Intelligence is widely used across contexts and for different purposes, including the field of education. However, a review of the literature showcases that while there exist various review studies on the use of AI in education, missing remains a review focusing on science education. To address this gap, we carried out a systematic literature review between 2010 and 2021, driven by three questions: a) What types of AI applications are used in school science? b) For what teaching content are AI applications in school science used? and, c) What is the impact of AI applications on teaching and learning of school science? The studies reviewed (n = 22) included nine different types of AI applications: automated assessment, automated feedback, learning analytics, adaptive learning systems, intelligent tutoring systems, multilabel text classification, chatbot, expert systems, and mind wandering detection. The majority of the AI applications are used in geoscience or physics and AI applications are used to support either knkowledge construction or skills development. In terms of the impact of AI applications, this is found across the following: learning achievement, argumentation skills, learning experience, and teaching. Missing remains an examination of learners’ and teachers’ experiences with the use of AI in school science, interdisciplinary approaches to AI implementation, as well as an examination of issues related to ethics and biase