atlas

Research map / Large language models / AI and society

Does Any AI-Based Activity Contribute to Develop AI Conception? A Case Study with Italian Fifth and Sixth Grade Classes

AAAI 2024 · Large language models › AI and society · approach: Teacher needs and AI curricula · 7 citations (OpenAlex)

Read the paperCheck your idea against 108,967 papers

AI-extracted summary. Written by AI from the paper's full text. Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.

The paper reports a quasi-experimental study comparing a programming-only course with a programming plus block-based AI course (using a Codey Rocky robot) for 192 Italian fifth and sixth graders, measuring computational thinking and conceptions of artificial and human minds.

Problem

Whether block-based AI courses complementing school curricula effectively develop computational thinking and a correct AI conception (understanding of artificial and human minds) in primary school children.

Approach

A controlled two-group school study in which one group received an extra four-lesson AI block-based course with an educational robot on top of a shared programming curriculum, with pre/post tests on computational thinking, the AMS artificial-mind scale, and AMOS human-mind beliefs questionnaires.

Key results

Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add four AI block-based lessons and educational robot activities to programming lessonsProgramming&AI group compared with Programming group · Computational thinking testscore: 8.21 (SD = 2.32) -> 9.00 (SD = 2.11); 8.00 (SD = 2.57) -> 8.73 (SD = 2.10)No clear effect
Add four AI block-based lessons and educational robot activities to programming lessonsProgramming&AI group compared with Programming group · AMS scaletotal score: 20.77; SD = 9.28 -> 19.78 (SD = 10.43); 22.01; SD = 9.03 -> 20.43 (SD = 10.29)No clear effect
Add four AI block-based lessons and educational robot activities to programming lessonsProgramming&AI group compared with Programming group · Theory and Beliefs of Intelligence Questionnairescore: 12.50, SD = 2.71 -> 12.56, SD = 2.69; 11.74, SD = 2.55 -> 11.72, SD = 2.85No clear effect
Add four AI block-based lessons and educational robot activities to programming lessonsProgramming&AI group compared with Programming group · Self-Confidence Questionnairescore: 8.71, SD = 2.61 -> 8.64, SD = 2.46; 8.94, SD = 1.90 -> 8.60, SD = 2.15No clear effect
Add four AI block-based lessons and educational robot activities to programming lessonsProgramming&AI group compared with Programming group · Mastery Goals Questionnairescore: 15.18, SD = 3.19 -> 15.50, SD = 3.27; 15.76, SD = 3.09 -> 15.48, SD = 3.12No clear effect

Surprising findings

Limitations

Experimental setup

Datasets: AMS scale (Manzi et al. 2020) AMOS 8-15 questionnaires (Cornoldi et al. 2005) Bebras-based computational thinking test

Benchmarks: computational thinking test AMS scale AMOS 8-15 questionnaires

Metrics: mean score change pre to post test F statistic partial eta squared p-value

Baselines: programming-only course group

Builds on: AI4K12 AI for Kids PopBots

Closest papers by meaning

Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.

Open scime draft

Get the next scime Dispatch and a monthly field update

Free. We send a confirmation link first; every email has a one-click unsubscribe. Privacy