Towards a synthetic tutor assistant: The EASEL project and its architecture

Robots are gradually but steadily being introduced in our daily lives. A paramount application is that of education, where robots can assume the role of a tutor, a peer or simply a tool to help learners in a specific knowledge domain. Such endeavor posits specific challenges: affective social behavior, proper modelling of the learner’s progress, discrimination of the learner’s utterances, expressions and mental states, which, in turn, require an integrated architecture combining perception, cognition and action. In this paper we present an attempt to improve the current state of robots in the educational domain by introducing the EASEL EU project. Specifically, we introduce the EASEL’s unified robot architecture, an innovative Synthetic Tutor Assistant (STA) whose goal is to interactively guide learners in a science-based learning paradigm, allowing us to achieve such rich multimodal interactions

The EASEL project: Towards educational human-robot symbiotic interaction

This paper presents the EU EASEL project, which explores the potential impact and relevance of a robot in educational settings. We present the project objectives and the theorectical background on which the project builds, briefly introduce the EASEL technological developments, and end with a summary of what we have learned from the evaluation studies carried out in the project so far

Common breast cancer susceptibility alleles are associated with tumor subtypes in BRCA1 and BRCA2 mutation carriers : results from the Consortium of Investigators of Modifiers of BRCA1/2.

Abstract Introduction Previous studies have demonstrated that common breast cancer susceptibility alleles are differentially associated with breast cancer risk for BRCA1 and/or BRCA2 mutation carriers. It is currently unknown how these alleles are associated with different breast cancer subtypes in BRCA1 and BRCA2 mutation carriers defined by estrogen (ER) or progesterone receptor (PR) status of the tumour. Methods We used genotype data on up to 11,421 BRCA1 and 7,080 BRCA2 carriers, of whom 4,310 had been affected with breast cancer and had information on either ER or PR status of the tumour, to assess the associations of 12 loci with breast cancer tumour characteristics. Associations were evaluated using a retrospective cohort approach. Results The results suggested stronger associations with ER-positive breast cancer than ER-negative for 11 loci in both BRCA1 and BRCA2 carriers. Among BRCA1 carriers, single nucleotide polymorphism (SNP) rs2981582 (FGFR2) exhibited the biggest difference based on ER status (per-allele hazard ratio (HR) for ER-positive = 1.35, 95% CI: 1.17 to 1.56 vs HR = 0.91, 95% CI: 0.85 to 0.98 for ER-negative, P-heterogeneity = 6.5 × 10-6). In contrast, SNP rs2046210 at 6q25.1 near ESR1 was primarily associated with ER-negative breast cancer risk for both BRCA1 and BRCA2 carriers. In BRCA2 carriers, SNPs in FGFR2, TOX3, LSP1, SLC4A7/NEK10, 5p12, 2q35, and 1p11.2 were significantly associated with ER-positive but not ER-negative disease. Similar results were observed when differentiating breast cancer cases by PR status. Conclusions The associations of the 12 SNPs with risk for BRCA1 and BRCA2 carriers differ by ER-positive or ER-negative breast cancer status. The apparent differences in SNP associations between BRCA1 and BRCA2 carriers, and non-carriers, may be explicable by differences in the prevalence of tumour subtypes. As more risk modifying variants are identified, incorporating these associations into breast cancer subtype-specific risk models may improve clinical management for mutation carriers

The potential of learning from erroneous models: comparing three types of model instruction

Learning from computer models is a promising approach to learning. This study investigated how three types of learning from computer models can be applied to teach high-school students (aged 14–17) about the process of glucose–insulin regulation. Two traditional forms of learning from models (i.e. simulating a predefined model and constructing a model) were compared to learning from an erroneous model. In this innovative form of learning from computer models, students are provided with a model that contained errors to be corrected. As such, students do not have to engage in the difficult task of constructing a model. Rather, they are challenged to work with and correct the model in order for the simulation to generate correct output. As predicted, learning from erroneous models enhances learning of domain-specific knowledge better than running a simulation or constructing a model

Design challenges for long-term interaction with a robot in a science classroom

This paper aims to present the main challenges that emerged during the process of the research design of a longitudinal study on child-robot interaction for science education and to discuss relevant suggestions in the context. The theoretical rationale is based on aspects of the theory of social constructivism and we use the collaborative inquiry as a framework to examine children's learning process who interact with a robotic learning companion. We identify two main challenges; (i) the development of robust on-demand systems for long-term interaction; and (ii) the design of developmentally appropriate scaffolding in embodied, semi-structured learning tasks. To address these challenges, we suggest (i) the development of a system for the detection of child's intention for interaction in the context of a classroom and (ii) the design of sensorized learning materials for the support of developmentally appropriate embodied learning experience

Measuring Children’s Perceptions of Robots’ Social Competence: Design and Validation

This paper presents the design and validation of a measurement instrument for children’s perceptions of robots’ social competence. The need for a standardized validated instrument has emerged as a requisite for meta-analyses and comparisons among various studies in the field of child-robot interaction. We report on the development of the instrument and its validation, which adopted a design-based method with two iterations. We used construct validity, which was formed by divergent and convergent validity. Children’s perceptions of three different robotic platforms were examined in two empirical studies with 78 children aged 7-9 years, which was based on semi-structured interviews with qualitative thematic content analysis. The results indicated that children differentiate their perception of social competence depending on the perceived intentionality of the robot and they ascribe discrete categorizations to the robot such as a machine, social artifact and social agent. The findings are discussed in relation to existing literature