Evidence map›Paper›PMID 37362587›Full record

ArticleTechTrends : for leaders in education & training2023

Educational Robotics for Developing Computational Thinking in Young Learners: A Systematic Review.

Yu-Hui Ching, Yu-Chang Hsu

Abstract read
In one paragraph

Article in TechTrends : for leaders in education & training, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Yu-Hui ChingBoise State University, Boise, ID USA.ORCID 0000-0002-6382-9903
Yu-Chang HsuBoise State University, Boise, ID USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Educational robotics has been adopted to create interactive and engaging learning environments to develop computational thinking (CT) in K-12 learners. This study systematically examined 22 peer-reviewed empirical research articles on the use of educational robotics to develop CT in young learners (pre-kindergarten to 6th grade) published between 2012 and 2021. The findings revealed that using robotics activities to develop CT has mostly been studied in the formal education settings with the duration of robotics curricular activities ranging from 80 minutes to 24 hours. The five CT skills studied most often include Sequencing, Conditionals, Loops, Debugging, and Algorithmic Thinking. The different versions of LEGO Mindstorms are the most frequently adopted robotic kits in the examined studies. The most frequently adopted learning and instructional strategies in the robotics activities include collaborative learning, project-based learning, and embodied learning. This paper identified and discussed developmentally appropriated CT skills, robotics kits, and pedagogical approaches suitable for supporting CT development in young learners. The findings can guide educators and instructional designers for future robotics activity design and development endeavors. This paper also identified gaps in the current research and recommended directions for advancing research in adopting robotics to develop CT in young learners.

Indexed as

Computational thinkingEducational roboticsSTEM educationSystematic reviewYoung learners

Identifiers

PMID37362587
PMCPMC10078047

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.