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arxiv: 2606.02175 · v1 · pith:6MFBFERPnew · submitted 2026-06-01 · 💻 cs.CY

The Use of Computational Thinking Skills, Difficulties, and Strategies of Introductory Programming Students Solving Bebras Tasks

Enrico Benedetti , Isaac Alpizar-Chacon , Johan Jeuring This is my paper

Pith reviewed 2026-06-28 12:28 UTC · model grok-4.3

classification 💻 cs.CY
keywords computational thinkingintroductory programmingBebras tasksproblem solvingdifficultiesstrategiesnon-CS majorsalgorithmic thinking
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The pith

Introductory programming students apply computational thinking skills like algorithmic thinking and abstraction when solving Bebras tasks, but struggle to plan systematically and explain their reasoning.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper examines how students in an introductory programming course for non-majors use computational thinking skills on five Bebras tasks. It collected 241 submissions from 58 students, coded them for skills using an existing scheme, and performed thematic analysis on difficulties and strategies reported in reflections. Algorithmic thinking, abstraction, and decomposition appeared most often and correlated with correct answers, while evaluation and generalization appeared rarely. Students reported challenges understanding tasks and creating plans, along with various problem-solving approaches. The findings indicate that Bebras tasks provide a setting for these students to engage computational thinking skills.

Core claim

Students in introductory programming apply computational thinking skills when solving Bebras tasks, with algorithmic thinking, abstraction, and decomposition appearing most frequently and evaluation and generalization appearing much less frequently; the presence of these skills is positively associated with correct answers, yet students face challenges understanding tasks and making plans and report various strategies for problem solving.

What carries the argument

Application of an existing coding scheme for computational thinking skills to student plans and solutions on Bebras tasks, paired with thematic analysis of post-task comments on difficulties and strategies.

If this is right

  • Presence of computational thinking skills correlates with correct answers on the tasks.
  • Students encounter four main areas of difficulty, including task understanding and plan creation.
  • Bebras tasks can serve as opportunities for introductory programming students to engage computational thinking skills.
  • These tasks could be incorporated into future research on computational thinking development in this population.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Similar submissions from computer science majors could be compared to test whether the same skill patterns and difficulties hold.
  • Instructional interventions targeting evaluation and generalization might increase their frequency in student work.
  • Bebras tasks could be sequenced by difficulty to scaffold systematic planning in introductory courses.

Load-bearing premise

The existing coding scheme for computational thinking skills can be applied reliably to these students' submissions and the thematic analysis of difficulties and strategies accurately reflects their experiences.

What would settle it

An independent replication in which multiple coders fail to agree on the computational thinking skills present in the same set of submissions or find no association between skill presence and solution correctness.

Figures

Figures reproduced from arXiv: 2606.02175 by Enrico Benedetti, Isaac Alpizar-Chacon, Johan Jeuring.

Figure 1
Figure 1. Figure 1: The third Bebras task, “Railway Network”. [PITH_FULL_IMAGE:figures/full_fig_p004_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Diagram of the study design and collected data after cleaning. [PITH_FULL_IMAGE:figures/full_fig_p006_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: Use of CT skills by each student (𝒏 = 58) in the five tasks. Each of the five symbols denotes the presence of the corresponding CT skill; that is, at least one of its subskills was observed. In contrast, we could not identify the use of CT skills in submis￾sions that did not provide information about plans or solution steps. Additionally, certain tasks made it possible to observe certain CT skills more tha… view at source ↗
read the original abstract

Computational thinking (CT) is regarded as a fundamental skill set everyone should learn. Identifying when and how CT skills are used is challenging but important to inform interventions supporting their development. Previous research has examined how students and experts apply CT skills when solving introductory computational problems. However, the extent to which higher education students in introductory programming courses do so in depth is underexplored. We address this gap by examining how those students apply CT skills when solving computational problems, the difficulties they encounter, and the strategies they employ. We collected plans and solutions to Bebras tasks (short problems introducing CS concepts and considered effective for eliciting CT skills) in an introductory programming course for non-CS majors. We gathered 241 submissions from 58 students across five tasks, along with post-task comments and reflections on strategies. We analyzed the data using descriptive statistics, applied an existing coding scheme to identify CT skills, and conducted thematic analysis to identify difficulties and strategies. Submissions varied in structure and level of detail. The most prevalent CT skills were algorithmic thinking, abstraction, and decomposition, while evaluation and generalization appeared much less frequently. CT skill presence was positively associated with correct answers. Students faced challenges in four areas, including understanding the tasks and making a plan, and reported various problem-solving strategies. Consolidating and extending prior research on CT skills and problem solving, our findings show that students in introductory programming apply CT skills but can struggle to solve problems systematically and explain their reasoning. Furthermore, Bebras tasks create opportunities for this population to engage CT skills and could be used in future research.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The paper investigates how 58 non-CS major students in an introductory programming course apply computational thinking (CT) skills when solving five Bebras tasks. It collects 241 submissions (plans, solutions, and reflections), applies an existing CT coding scheme via descriptive statistics to quantify skill prevalence (algorithmic thinking, abstraction, and decomposition most common; evaluation and generalization rare), reports a positive association between CT skill presence and correct answers, and uses thematic analysis to identify four areas of difficulty (e.g., task understanding and planning) plus problem-solving strategies. The central claim is that these students engage CT skills but struggle with systematic problem-solving and explanation, and that Bebras tasks are suitable for future CT research with this population.

Significance. If the coding reliability holds, the work offers a concrete empirical snapshot of CT skill use in a non-CS introductory population, extends prior expert/student comparisons, and provides actionable evidence that Bebras tasks can surface both strengths and gaps. The positive association finding, if robust, could inform curriculum design; the thematic difficulties add practical detail on barriers to systematic reasoning.

major comments (2)
  1. [Methods / Data Analysis] Methods / Data Analysis: The paper applies an existing CT coding scheme to 241 submissions and reports prevalence plus a positive association with correct answers, yet provides no inter-rater reliability statistic (Cohen’s kappa, percentage agreement, or similar) and no validation or adaptation details for non-CS majors. Because the prevalence figures and the skill–correctness association are load-bearing for the central claim, this omission leaves the quantitative results sensitive to single-coder interpretation.
  2. [Methods / Thematic Analysis] Methods / Thematic Analysis: The thematic analysis of difficulties and strategies is described only as “thematic analysis” with no mention of multiple independent coders, member checking, audit trail, or saturation criteria. Given that the four difficulty areas and reported strategies are presented as findings, the absence of these standard safeguards is a load-bearing concern for the qualitative component.
minor comments (2)
  1. [Abstract and §3] Abstract and §3: Sample demographics (e.g., prior programming experience, gender distribution, exact course level) are not summarized, making it hard to assess generalizability to other introductory cohorts.
  2. [Results] Results: The exact statistical test used for the “positive association” between CT skill presence and correct answers is not named (chi-square, logistic regression, etc.), and effect sizes or confidence intervals are not reported.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive feedback. We address the two major comments on methods below and will revise the manuscript to increase transparency in both the quantitative coding and qualitative analysis sections.

read point-by-point responses

  1. Referee: [Methods / Data Analysis] Methods / Data Analysis: The paper applies an existing CT coding scheme to 241 submissions and reports prevalence plus a positive association with correct answers, yet provides no inter-rater reliability statistic (Cohen’s kappa, percentage agreement, or similar) and no validation or adaptation details for non-CS majors. Because the prevalence figures and the skill–correctness association are load-bearing for the central claim, this omission leaves the quantitative results sensitive to single-coder interpretation.

    Authors: We agree that the absence of inter-rater reliability reporting is a limitation. The coding followed an existing published scheme applied by the first author (with prior CT research experience) without modification for this population. In revision we will expand the methods to detail the exact application steps, any pilot coding performed, and explicitly state the single-coder nature of the analysis, thereby addressing sensitivity concerns while preserving the descriptive findings. revision: yes

  2. Referee: [Methods / Thematic Analysis] Methods / Thematic Analysis: The thematic analysis of difficulties and strategies is described only as “thematic analysis” with no mention of multiple independent coders, member checking, audit trail, or saturation criteria. Given that the four difficulty areas and reported strategies are presented as findings, the absence of these standard safeguards is a load-bearing concern for the qualitative component.

    Authors: We acknowledge that the thematic analysis description is insufficiently detailed. The analysis followed an inductive thematic approach on the 241 submissions and reflections; we will revise the methods to specify the steps taken (familiarization, initial coding, theme development), note that a single researcher led the process with team discussion of emerging themes, and add a limitations paragraph on the lack of independent coders or member checking. revision: yes

Circularity Check

0 steps flagged

No circularity: purely empirical observational study

full rationale

The paper collects 241 student submissions to Bebras tasks, applies an existing (non-self-authored) coding scheme for CT skills, performs descriptive statistics and thematic analysis, and reports associations. No equations, fitted parameters, derivations, predictions from inputs, or self-referential definitions appear. The central claims rest on direct data analysis rather than any reduction to prior self-citations or constructed equivalences. Self-citation, if present for the coding scheme, is not load-bearing as the scheme is described as existing and external.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

Empirical education study with no mathematical derivations, fitted parameters, or postulated entities; relies on standard qualitative methods and an existing coding scheme from prior work.

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