Abstract:

Artificial Intelligence invites us to interpret technologies within the broader network of human relationships: in educational ecologies, it reshapes knowledge-construction processes into interwoven biographies, symbols, artefacts, and languages. When embedded presences such as robots enter these contexts, they contribute to redefining the meanings of experience by stimulating self-exploration of social, ethical, and epistemological dimensions. Imaginaries, therefore, become a key lens for understanding how the artificial is conceived, narrated, and situated by young people.

This contribution integrates a qualitative exploratory–descriptive design with quantitative descriptive analyses to investigate the perceptions of children and pre-teens regarding robots. Within Italian STEM-in-education projects (school year 2024/25), spontaneous written and graphic responses were collected from 761 pupils aged 6–13, prompted by the question: “What is a robot for you?”. While this question introduced the educational intervention conducted by expert researchers, the resulting corpus (short texts, text–drawing productions, and 145 drawings) allowed qualitative analyses aimed at identifying the most prevalent dimensions and scenarios at these ages.

A reflective thematic analysis was conducted through iterative phases of data familiarisation, generation of initial codes, and development and refinement of themes. After an inductive phase intended to capture recurring meaning units, abductive reasoning guided their organisation into a hierarchical categorical system (macro-categories and subcodes) distinguishing ontological dimensions (what it is), agency (what it does and how it works), purposes and contexts of use, relational and value-related dimensions, sources of imagery, and graphic material. The system was tested through an initial coding of a random sample of 200 responses to verify internal consistency, saturation, and semantic clarity.

To enhance interpretative reliability, the procedure included multiple rounds of inter-researcher comparison, discussion of discrepancies, and refinement of the categorisation. Triangulation occurred on three levels: data (texts and drawings), researchers (inter-subjective comparison), and methodology (integration of qualitative analysis with descriptive frequencies). Although the sample cannot be generalised, the size of the corpus and the transparency of the analytical process support the transferability of findings and the replicability of the study.

Initial results from the random sample show a predominance (42%) of responses related to robotic agency, especially generic descriptions of actions or tasks (35%). These are followed by statements referring to the robot’s nature (39%), including characterisations involving software and artificial intelligence (16%) and physical components (11%). Educationally relevant are the responses (19%) addressing purposes and contexts of use (help, care, play) and those involving relational and value dimensions (robots as friends, social implications, risks), which overall reflect an ambivalent narrative positioning technologies between opportunity and threat.

Despite the inherent limitations of context-based research, this study highlights the importance of examining the forms, contents, and languages of the collective imagination to support the teaching of New Literacies that accompany young people in their encounter with technology.

Keywords:

Perceptions, Artificial, Education.