Learning Robotics, with Robotics, by Robotics

Ilaria Gaudiello has a doctorate in Cognitive Psychology from Paris 8 University, and since 2008 her research in French and European projects (RASPO, PRISCINET, EDHHI, etc.) has been mainly devoted to educational technologies. She is also Subject Matter Expert for LEGO Education and consultant in pedagogical innovation based on digital switchover.Elisabetta Zibetti is Assistant Professor in Cognitive Psychology at Paris 8 University (CHART–LUTIN lab). She explores the psychological mechanisms allowing natural and artificial systems to understand, adapt to and to engage in interactions. She uses robotics as a "mindtool" to enhance the acquisition of human knowledge in theoretical and applied fields of research.

• Foreword ixPreface xiiiIntroduction xixChapter 1. Learning Robotics: Users’ Representation of Robots 11.1. Introduction: the ontological and pedagogical status of robots 11.2. What do we mean by robot representation? 31.2.1. The place of robots in our common-sense ontology 31.2.2. Categories: essentialist versus graded 41.2.3. The NOC hypothesis 61.2.4. Shifting between the different pedagogical roles of a robot 71.2.5. How do we investigate robot representations and the impact of learning robotics on these representations? 81.3. Study 1: Robot representation 91.3.1. Aims and rationale 91.3.2. Hypotheses 101.3.3. Method 121.4. Results 171.4.1. Which representation of robots for familiar and unfamiliar students? 171.4.2. The living and non-living items most frequently associated with robots (pre-questionnaire) 181.4.3. Gradation in robot categorization: essentialist versus non-essentialist stance (pre-questionnaire) 191.4.4. The educational roles most frequently envisaged for robots (pre-questionnaire) 201.4.5. Gradation in the educational roles envisaged for a robot (pre-questionnaire) 201.4.6. The impact of building and programming a robot on students’ judgment about the ontological status of robots 211.4.7. The impact of robot making on graded versus all-or-nothing categorization 231.4.8. Does familiarity with robots influence their categorization? 261.4.9. Dichotomous versus multiple categorization of robots 281.4.10. The impact of robot making on theeducational roles envisaged for robots 291.4.11. The impact of robot making on shift between the educational roles envisaged for robots 311.4.12. Does previous experience influence the educational role attributed to robots? 321.5. Discussion 341.6. Conclusions, limits and perspectives 38Chapter 2. Learning with Robotics: Functional and Social Acceptance of Robots 432.1. Functional and social acceptance of robots 432.2. Trust as a fundamental indicator of acceptance 492.2.1. Commonly used measures of human–robot trust 492.2.2. Conformation as an innovative measure of human–robot trust 512.2.3. Factors influencing robot trust 522.3. Study 2: robot acceptance 562.3.1. Aims and rationale 562.3.2. Method 592.4. Results 692.4.1. Do participants conform their answer more to iCub’s answer in the functional task than in the social task? (H1) 692.4.2. Do participants who conform to iCub in the social task also conform in the functional task? (H2) 712.4.3. Does the imagined HRI scenario influence trust in iCub? (H3) 712.4.4. Is there a correlation between negative attitudes to the robot’s social influence and the trust in the robot’s social savvy? (H4) 742.4.5. Is there a correlation between the human DFC and the trust in the robot’s functional and social savvy? 742.5. Discussion 762.6. Conclusions 83Chapter 3. Learning by Robotics: The Impact of Educational Robots on Learning 873.1. Combining RBI and inquiry-based science 873.2. IBSE and the four dimensions of learning 933.2.1. The cognitive dimension 953.2.2. The affective dimension 973.2.3. The social dimension 983.2.4. The meta-cognitive dimension 993.2.5. Self-regulation 1013.2.6. RBI and inquiry-based learning 1053.3. Study 3: impacts of ER on learning 1143.3.1. Aims and rationale 1143.3.2. The RObeeZ project 1153.3.3. Hypotheses 1223.3.4. Experimental design 1233.4. Results 1283.4.1. Are the subject-specific knowledge and competencies of pupils enhanced at the end of RObeeZ project? 1283.4.2. Are pupils’ transversal competencies enhanced at the end of the project? 1293.4.3. Does the combination of RBI and IBSE have an impact on the four dimensions of learning? 1303.5. Discussion 136Conclusion and Perspectives 143Appendices 153Appendix 1 155Appendix 2 159Appendix 3 163Appendix 4 169Appendix 5 177Bibliography 181Index 223