The Interplay Between Mathematical and Computational Thinking in Primary School Students’ Mathematical Problem-Solving Within a Programming Environment

Abstract

In this paper, we explore the challenges experienced by a group of Primary 5 to 6 (age 12–14) students as they engaged in a series of problem-solving tasks through block-based programming. The challenges were analysed according to a taxonomy focusing on the presence of computational thinking (CT) elements in mathematics contexts: preparing problems, programming, create computational abstractions, as well as troubleshooting and debugging. Our results suggested that the challenges experienced by students were compounded by both having to learn the CT-based environment as well as to apply mathematical concepts and problem solving in that environment. Possible explanations for the observed challenges stemming from differences between CT and mathematical thinking are discussed in detail, along with suggestions towards improving the effectiveness of integrating CT into mathematics learning. This study provides evidence-based directions towards enriching mathematics education with computation.

Current trends and developments in the application of digital tools and implementation of environmental awareness and sustainability in PBL-based STEM education: a dual systematic literature review

“…These allow younger students (primary and secondary school) or beginners in programming to succeed in robotics. We could see an example of this in Hooke's Law experiment (Major et al, 2021), in collecting and processing sensor data for robotics electronics integration (Wang et al, 2021), in building a room capacity detector and a thermometer (Cui et al, 2021), or in such a real-world problem, like helping hospitals prioritize patients (Shahin et al, 2021).…”

“…Based on the studies reviewed, using robotics seems to provide an appropriate problem-based STEM learning environment for all ages. Robotic devices, like Arduino, Micro: bit, or Raspberry PI are based on more straightforward block-based programming; therefore, they are suitable for elementary or secondary school students (Weng et al, 2022;Cui et al, 2021) and beginners (Major et al, 2021;Wang et al, 2021). For high school students with programming backgrounds or university students, robotic tools based on a text-based programming language (like Python or C++) are more common.…”

A Novel Three-Way Decision Model for Improving Computational Thinking Based on Grey Correlation Analysis

“…Vesikivi et al [10] focused on teaching computational thinking and the teaching methods and research design under different types on the impact of the development of computational thinking. Cui and Ng [11] studied evidence-based directions towards enriching mathematics education with computational thinking. Grover et al [12] tapped into the existing relationship between cognitive level and computational thinking through student's programming behaviors, thus showing the superiority of programming instruction as a means of computational thinking development.…”

“…(8) k � 0// Initialize the maximum number of similar classes among experts. ( 9) if find S max ←S and S max ≠ 0 then (10) Gr←S max corresponding two experts (11) sim AiBj ←0 (12) Dr←Gr ∪ S max (13) Repeat the above steps until S � ∅. (14) C←∅ // Initialize the expert collection.…”

“…In this study, the top 30% of students were selected as the excellent category, i.e., category A, the bottom 20% as the average category, i.e., category C, and the rest as the medium category, i.e., category B. us, the initial category classification of the evaluated subjects was completed. e initial classification of the three categories of students, that is, the tripartition, is A � [10,7,24,23,20,5,6,22,18], B � [9,19,4,25,13,8,21,12,28,11,15,3,17,14,29], and C � [1, 26, 27, 16, 2, 0], respectively.…”