Computational thinking in early childhood education
The impact of programming a tangible robot on developing debugging knowledge
Bibliographic Data
| ID | 12138022 |
|---|---|
| Authors | Anastasia Misirli (0000-0003-2943-9490, University of Patras), Vassilis Komis (0000-0001-6909-2765, University of Patras, corresponding author) |
| Year | 2023 |
| Volume | 65 |
| Pages | 139-158 |
| Publication date | 2023-01-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Early Childhood Research Quarterly (JOURNAL) |
| Journal identifiers | ISSN: 0885-2006 • E-ISSN: 1873-7706 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.ecresq.2023.05.014 |
| OpenAlex | W4381888487 |
| Language | EN |
| Citations received | 13 |
| References cited | 41 |
The present study investigates the debugging process of 526 children in preschool (4–6 aged) when programming a tangible robot. When a child is involved in programming, it is needed to identify and correct errors, or in other words, debug a program. Debugging is a high-level thinking skill and is an essential component closely related to developing Computational Thinking in early childhood education. Though the debugging process is a cognitive function in programming investigated by many researchers in recent decades, most studies are conducted either in primary, secondary education, or higher education concerning beginners or experts in programming. Very few reviews, and some focus on preschool education. Our study set out the following objectives: 1) How do children identify the existence of error and locate it? 2) What types of errors emerge when coding? 3) What type of error is complex for novice programmers? 4) What strategies are developed by novice programmers to debug effectively? and 5) What types of knowledge do novice programmers construct by debugging the tangible robot Bee-Bot? The study follows an iterative model of a design-based research approach. It uses multiple case studies to collect qualitative and quantitative data. The programming intervention was implemented by 30 educators in their classrooms and was based on a scenario-based teaching design. The debugging process was analysed using Klahr & Craven's framework (1988): 1) test and evaluate program, 2) identify bug, 3) represent program, 4) locate bug and 5) correct bug. The main finding is the construction and development of syntactic and semantic knowledge
Algorithmic program debugging · Computational Thinking · Construct (python library · Debugging · Human–computer interaction · Process (computing · Programming language · Software engineering · Computer Science · Software Testing and Debugging Techniques · Teaching and Learning Programming · Artificial Intelligence
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| Citations per year | 6.5 |
|---|---|
| Citation span | 2024 - 2026 (3) |
| Highly cited | No |