Computational Thinking Practices Research Articles

Including neurodiversity in computational thinking

IntroductionThe foundational practices of Computational Thinking (CT) present an interesting overlap with neurodiversity, specifically with differences in executive function (EF). An analysis of CT teaching and learning materials designed for differentiation and support of EF show promise to reveal problem-solving strengths of neurodivergent learners.MethodsTo examine this potential, studies were conducted using a computer-supported, inclusive, and highly interactive learning program named INFACT that was designed with the hypothesis that all students, including neurodivergent learners, will excel in problem solving when it is structured through a variety of CT activities (including games, puzzles, robotics, coding, and physical activities) and supported with EF scaffolds. The INFACT materials were used in 12 treatment classrooms in grades 3–5 for at least 10  h of implementation. Pre-post assessments of CT were administered to treatment classes as well as 12 comparison classes that used 10  h of other CT teaching and learning materials. EF screeners were also used with all classes to disaggregate student results by quartile of EF.FindingsStudents using INFACT materials showed a significant improvement in CT learning as compared to comparison classes. Students with EF scores in the lower third of the sample showed the greatest improvement.DiscussionThis study shows promising evidence that differentiated activities with EF scaffolds situated across several contexts (e.g., games, puzzles, physical activities, robotics, coding) promote effective CT learning in grades 3–5.

Towards a Socio-Constructivist Didactic Model for Integrated STEM Education

AbstractAs science education shifts toward integrated STEM (Science, Technology, Engineering, and Mathematics) approaches, guidelines for designing teaching and learning episodes that integrate curricular content and procedures from multiple disciplines become increasingly in demand. The existing plethora of conceptualizations of STEM makes difficult such an endeavor, leading to ill-defined lesson plans focused on only two –mainly science and technology or science and mathematics– out of the four STEM disciplines. The question addressed, therefore, is how the integrated STEM approach could be translated into classroom practices that integrate the four STEM disciplines in a way that is consistent and coherent with elementary education curricula. This manuscript advances a theoretically informed didactic model for the design and implementation of integrated STEM in elementary education. The article discusses how the model uses socio-constructivist principles to establish intentional and explicit connections between STEM disciplines via scientific inquiry, engineering design, and computational thinking practices. The model is rooted in learning theories developed by Piaget, Vygotsky, Ausubel, and Bruner and could serve as a roadmap for educators and researchers designing integrated STEM lessons. Future empirical research testing the model is warranted.

Assessing implicit computational thinking in game‐based learning: A logical puzzle game study

AbstractTo date, extensive work has been devoted to incorporating computational thinking in K‐12 education. Recognizing students' computational thinking stages in game‐based learning environments is essential to capture unproductive learning and provide appropriate scaffolding. However, few reliable and valid computational thinking measures have been developed, especially in games, where computational knowledge acquisition and computational skill construction are implicit. This study introduced an innovative approach to explore students' implicit computational thinking through various explicit factors in game‐based learning, with a specific focus on Zoombinis, a logical puzzle‐based game designed to enhance students' computational thinking skills. Our results showed that factors such as duration, accuracy, number of actions and puzzle difficulty were significantly related to students' computational thinking stages, while gender and grade level were not. Besides, findings indicated gameplay performance has the potential to reveal students' computational thinking stages and skills. Effective performance (shorter duration, fewer actions and higher accuracy) indicated practical problem‐solving strategies and systematic computational thinking stages (eg, Algorithm Design). This work helps simplify the process of implicit computational thinking assessment in games by observing the explicit factors and gameplay performance. These insights will serve to enhance the application of gamification in K‐12 computational thinking education, offering a more efficient method to understanding and fostering students' computational thinking skills. Practitioner notesWhat is already known about this topic Game‐based learning is a pedagogical framework for developing computational thinking in K‐12 education. Computational thinking assessment in games faces difficulties because students' knowledge acquisition and skill construction are implicit. Qualitative methods have widely been used to measure students' computational thinking skills in game‐based learning environments. What this paper adds Categorize students' computational thinking experiences into distinct stages and analyse recurrent patterns employed at each stage through sequential analysis. This approach serves as inspiration for advancing the assessment of stage‐based implicit learning with machine learning methods. Gameplay performance and puzzle difficulty significantly relate to students' computational thinking skills. Researchers and instructors can assess students' implicit computational thinking by observing their real‐time gameplay actions. High‐performing students can develop practical problem‐solving strategies and exhibit systematic computational thinking stages, while low‐performing students may need appropriate interventions to enhance their computational thinking practices. Implications for practice and/or policy Introduce a practical method with the potential for generalization across various game‐based learning to better understand learning processes by analysing significant correlations between certain gameplay variables and implicit learning stages. Allow unproductive learning detection and timely intervention by modelling the reflection of gameplay variables in students' implicit learning processes, helping improve knowledge mastery and skill construction in games. Further investigations on the causal relationship between gameplay performance and implicit learning skills, with careful consideration of more performance factors, are expected.

Assessing the Efficacy of an Accessible Computing Curriculum for Students with Autism Spectrum Disorders

There is a limited amount of research dedicated to designing and developing computing curricula specifically tailored for students with autism spectrum disorder (ASD), and thus far, no study has examined the effectiveness of an accessible computing curriculum designed specifically for students with ASD. The goal of this study is to evaluate the effectiveness of an accessible curriculum in improving the learning of computational thinking concepts (CTCs) such as sequences, loops, parallelism, conditionals, operators, and data, as well as the development of proficiency in computational thinking practices (CTPs) including experimenting and iterating, testing and debugging, reusing and remixing, and abstracting and modularizing. The study involved two groups, each comprising twenty-four students. One group received instruction using the accessible curriculum, while the other was taught with the original curriculum. Evaluation of students’ CTCs included the analysis of pretest and posttest scores for both groups, and their CTPs were assessed through artifact-based interview scores. The results indicated improvement in both groups concerning the learning of CTCs, with no significant difference between the two curricula. However, the accessible computing curriculum demonstrated significant enhancements in students’ proficiency in debugging and testing, iterating and experimenting, modularizing and abstracting, as well as remixing and reusing. The findings suggest the effectiveness of accessible computing curricula for students with ASD.

“So, we kind of started from scratch, no pun intended”: What can students learn from designing games?

AbstractMuch research attention has been focused on learning through game playing. However, very little has been focused on student learning through game making, especially in science. Moreover, none of the studies on learning through making games has presented an account of how students engage in the process of game design in real time. The present study seeks to address that gap. We report an exploratory embedded case study in which three groups of students in one classroom created a computer game designed to teach peers about climate science, while drawing on scientific knowledge, principles of game design, and computational thinking practices. Data sources were student design sheets, computer video, and audio screen capture while students created their game, and interviews after completing the curriculum unit. A theme‐driven framework was used to code the data. A curricular emphasis on systems across climate systems, game design, and computational thinking practices provided a context designed to synergistically supported student learning. This embedded case study provides a rich example of what a collaborative game design task in a constructionist context looks like in a middle school science classroom, and how it supports student learning. Game design in a constructionist learning environment that emphasized learning through building a game allowed students to choose their pathways through the learning experience and resulted in learning for all despite various levels of programming experience. Our findings suggest that game design may be a promising context for supporting student learning in STEM disciplines.

Teacher Candidates’ Conceptions and Practices of Computational Thinking for Equity

This study documents novice science and math teachers’ developing pedagogical approaches to integrating computational thinking (CT) and data into their courses to support educational equity and social justice. The 10 novice teacher candidates (TCs) studied were part of an urban teacher residency program that empowered them with an asset-based pedagogy we describe as “CT for Equity.” Drawing on coursework and interviews as data, we asked three questions: What are teachers’ conceptions of CT? What are their CT instructional practices? And how did their students respond to those practices? To explore conceptions of CT, we used Kafai et al.’s (2020) articulation of three frames of CT – cognitive, situated, and critical approaches – and found that the TCs’ conceptions do not narrowly fit into one of the three frames, but rather they mix and match components of the perspectives to support a range of student outcomes, from transferable skills to preparing youth to explore social justice issues. We also identified a small but powerful set of core practices that the teachers used to support learning outcomes, including integrating data on locally and socially relevant issues. We present group-level trends and three classroom stories, or profiles of practice, to illustrate the generative ways TCs blended priorities from the three frames in instruction. The diversity in the TCs’ conceptions and practices deepens understandings of asset-based pedagogies in CT by shining light on the rich and varied ways that math and science teachers meet the needs of their minoritized students.

Understanding computational thinking in the gameplay of the African Songo board game

AbstractComputational thinking is a necessary skill for the 21st century. While previously examined in computer‐rich settings, researchers are increasingly studying computational thinking in unplugged environments such as board games. Focusing on the African board game Songo, this study shows that computational thinking practices are embedded in Songo board gameplay and interact with the cultural context. The study also reveals a computing practice peculiar to Songo gameplay, songoputation. This paper suggests that researchers can benefit from exploring computational thinking and computing practices beyond board games in western contexts. Practitioner notesWhat is already known about this topic Computational thinking can be cultivated in non‐digital environments. Board games are spaces where computational thinking can be developed. The relationship between African board games and computational thinking is still unknown. What this paper adds African board games such as Songo are spaces where players engage with computational thinking and songoputation Culture informs computational thinking practices players engaging in when playing Songo. Computational thinking is not a new practice and should be explored in different culture contexts and settings. Implications for practice and/or policy African board games should be used to develop computational thinking skills. Board games should be used to foster computational thinking skills among students in context with limited access to digital technology.

School and Community Practices of Computational Thinking in Mathematics Education through Diverse Perspectives

In the 21st century, computational thinking (CT) has emerged as a fundamental skill. Building on this momentum and recognizing the importance of exploring the use of computational thinking (CT) concepts and tools in teaching and learning, this study conducted a qualitative content analysis to investigate online resources for school and community outreach practices related to integrating CT and coding into mathematics education. The data set was selected from sample websites hosting a community of practice and interpreted through Kafai et al.’s (2020) framings of CT and a combination of three theories of learning and teaching (i.e., constructionism, social constructivism, and critical literacy). The study found that in mathematics, more attention is given to the cognitive approach of CT, which focuses on acquiring CT skills and concepts, rather than the situated approach that emphasizes participation during learning. Additionally, there is not enough emphasis on the critical framing of CT, which examines how learning reflects values and power structures. The study’s significance is grounded in enhancing the perspectives of researchers, educators, and policymakers by providing insights into the wide affordances of CT which meet and exceed the expectations of curriculum content and skills. In light of the recent attention paid to adding coding to the new mathematics curriculum, this study contributes to the literature, practice, and curriculum development on the integration of CT into school mathematics and serves as a basis for future research in the field.

Interactions between self‐regulated learning and assessment for learning in an undergraduate introductory computer science course

AbstractMany introductory computer science (CS) courses are intended to address the increased demand for computer literacy and the development of cross‐cutting concepts and practices of computational thinking (CT). Colleges and universities offer introductory CS courses every semester toward this end. The issue is centered on how to support CT learning in a large introductory CS course. To do it, an introductory CS course was designed to enrich CT by embedding short episodes of assessments to facilitate learning (AfL) and to support students’ self‐regulated learning (SRL). This chapter begins by articulating the intricacies of the underlying processes of SRL, principles of AfL, and computational thinking practices in CS. Using the undergraduate introductory CS course referred to above, key practices of SRL and AfL will be illustrated to demonstrate how student learning of CS programming is structured with various online and offline supports. The chapter then concludes by appraising aspects of this CS course with practical suggestions for supporting student SRL and their learning of CS programming.

Monitoring cognitive development through the assessment of computational thinking practices: A longitudinal intervention on primary school students

Computational thinking (CT) practices is a critical cognitive tool for students to overcome challenges in this technological era. Few studies investigated CT practices from a development perspective. A two-year intervention was implemented in 30 intervention and 22 control schools in Hong Kong to promote CT education (T1baseline: N = 13,056; T2: N = 16,367; and T3: N = 15,269). Senior primary students (grades 4 to 6) around 8–12 years old were targeted. Among them, 34% were girls at T1baseline. Their learning progression of cognitive development was assessed with a CT practices test. Data were analyzed using item response analysis. Learning trajectories of CT practices were modeled to understand how students’ cognitive development differed between schools. Insights of findings were discussed in bringing CT practices to life.

How a child entangles empathy and computational thinking in reasoning about fairness

In this work, we argue for expanding the scope of K-12 computational thinking (CT) integration contexts to include everyday scenarios involving moral reasoning. Epistemic overlap between computational thinking practices and moral reasoning suggest that these contexts are potentially rich sites to see “seeds of CT” in children's reasoning and can provide rich educational pathways for children into CT. Taking a case-study approach, we examine the reasoning of a second-grader, Ollie, on a task involving fair allocation of resources to victims of a natural disaster. Our analysis finds that Ollie's reasoning was rich with seeds of CT (e.g., problem formulation, abstraction, complex-systems thinking) and that empathy served as an important supporting role to the CT. This work has implications for curricular design, suggesting that fairness and resource allocation scenarios with built-in opportunities for empathy might provide rich sandboxes for CT integration.

Computational thinking practices as tools for creating high cognitive demand mathematics instruction

Computational thinking practices as tools for creating high cognitive demand mathematics instruction

Computational thinking as part of compulsory education: How is it represented in Swedish and Norwegian curricula?

In recent years, many countries have revised their school policy documents to incorporate digital competence, computational thinking and programming. This study examines and compares how and in what contexts Nordic curricula, Swedish and Norwegian in particular, embody aspects of computational thinking. Results show that only parts of the practices defined in the computational thinking framework used for analysis could be explicitly identified in the curriculum documents. The most salient computational thinking practice represented in both the Swedish and Norwegian curricula is programming, and programming is primarily recognized as a method and tool for learning other subject content and not as a knowledge domain in its own right. Implicitly both curricula leave leeway for teachers to implement a broader approach to computational thinking. However, this would need much time, teacher competence and effort, and what it requires seems to be under-communicated in the curricula, leaving schools and teachers with major challenges.

Computational Thinking and Coding for Kids Training for Elementary School Teachers

Computational thinking and coding are thinking skills that are recently expected to be acquired by elementary school children as the era of the industrial revolution 4.0 requires students to be familiar with the use of technology. In some developed countries, the two skills have been included in elementary school curriculum. However, the situation is different in the context of Indonesia since teachers or instructors who are able to provide these skills are inadequate. Therefore, this training was intended to socialize and educate the application of coding and computational thinking, especially to elementary school teachers so that they have the ability to equip their students with those skills. The participants of this training were teachers of Labschool UPI Purwakarta. The training was conducted in one day containing the concepts and practices of ICT and computational thinking as well as coding for kids. The result of satisfaction questionnaire distributed to the participants after the training shows a good level of satisfaction in terms of training materials, delivery of materials, and the usefulness of activities as much as 71,4%, 57,1% and 92,9% consecutively. The teachers hope that follow-up trainings are carried out to increase their knowledge and ability in developing technology-based learning.

Effects of voice assistant creation using different learning approaches on performance of computational thinking

Designing artificial intelligence (AI) artefact learning has gone beyond command-line-based instruction, to include a low-barrier threshold with block-based programming. Such instructional design must not solely emphasise AI workings. Rather, it must offer students computational thinking (CT) practice to support their AI-related artefact creation while reducing their AI anxiety about future job replacement or sociotechnical blindness. In this study, this research explored an experiential learning approach to improve CT along with AI application capabilities when engaging undergraduate students in creating a voice assistant application (VA app). A total of 56 students participated in the study. The control group (CG) of 26 students used a conventional subject-based learning method, while the experimental group (EG) of 30 students adopted an experiential learning method. This study aimed to examine the differences in the learning achievement of CT and AI concept, as well as the perspectives of AI anxiety, and CT; in the meanwhile, this study analysed the students' learning behaviours using sequential behavioural analysis to discuss the learning process. Results showed that the CT ability of the EG was better than that of the CG, although no significant difference was found between the two groups’ AI concepts and anxiety. The behaviour analysis also revealed that the EG students were willing to ask more questions, and conducted their VA evaluation, whereas the CG students were inclined to focus on the input and output of knowledge, and replicated what the teacher presented. Suggestions and implications are given for future research.

Development and illustration of a framework for computational thinking practices in introductory physics

Development and illustration of a framework for computational thinking practices in introductory physics

Learning Computational Thinking Practices Through Agent-Based Modeling in an Informal Setting

In this qualitative study, I investigated the form of interaction when learners co-constructed computational thinking practices in an informal setting. This study focuses on the roles of five youth, three adult mentors, and a facilitator during a summer camp and documents how learners interacted to exchange ideas, collaborate, and accommodate other perspectives. Participants used questions that promote deep thinking to engage in computational thinking practices during the interactions. Analysis of data shows that learners developed computational thinking practices including interpreting, modeling connections to the real-world, manipulating parameters, discovering ideas to explore models, prompting, conjecturing, and making predictions when working on agent-based modeling and writing codes in NetLogo. These practices are further grouped together as model interpretation and connection to the real world, parameter manipulation and discovery, prompting and exploring, and making predictions/conjectures and generalizing. This study also finds some community-based practices such as practical wisdom, trying something and adjusting, and the use of network of resources relevant during interaction to develop computational thinking practices.

Toward a Holistic Pedagogical Approach in K-6 Education: Evidence From a Multiple-Case Study in Spain

ABSTRACT This article examines how a multidimensional, skill-driven curricular framework plays out in diverse primary school settings toward a holistic K-6 curriculum framework. Particularly, it explored how unplugged tasks involve imaginative pedagogies, computational thinking skills, new media literacy skills, and social-emotional skills across three different primary schools by fulfilling two learning conditions, without coding/programming and without using digital devices. Within-case and cross-case analyses were conducted by following the qualitative multiple-case study research design. The evidence stems from lesson analysis, observation field notes, and interview transcripts with 152 participants. We collected 94 lessons from the three schools and we analyzed the data by using a predefined coding scheme grounded upon four frameworks. We conclude that the detected teaching practices uncover promising trajectories by demonstrating a great potential to consider the proposed framework as an effective and age-appropriate pedagogical approach applicable to low-technology and coding-free learning environments. The study highlights the need of teacher professional development, especially on computational thinking in reference to cognitive/intellectual, emotional/affective, social, creative/imaginative, and material dimensions for conscious computational thinking practice implementation. Given the paucity of research on unplugged and, especially, non-programming/coding methods at primary education level, this study can open up prominent issues for further examination and validation.

Computational thinking for using models of water flow in environmental systems: Intertwining three dimensions in a learning progression

AbstractNearly a decade ago, the Framework for K‐12 Science Education argued for the need to intertwine science and engineering practices, disciplinary core ideas, and crosscutting concepts in performance expectations. However, there are few empirical examples for how intertwining three dimensions facilitates learning. In this study, we used a learning progressions approach to examine how student engagement in computational thinking (science and engineering practice) intertwines with learning about the flow of water through environmental systems (disciplinary core ideas) and understanding of systems and system models (crosscutting concept). We developed three secondary‐level curriculum units situated in current groundwater contamination and urban flooding contexts. Units included specially designed NetLogo computational models. Post‐assessments measured student performances in computational thinking processes and understanding of hydrologic systems. Using item response theory in our analysis, we identified distinct levels of performance on a learning progression. At the lower end, literal model users interacted with models and manipulated model interfaces to achieve a specified goal. In the middle, Model Technicians used computational models to solve real‐world problems. At the upper end, principle‐based model users used computational thinking processes and principles related to systems modeling and hydrology to explain how the models worked to predict water flow. Differences between performances of literal model users, model technicians, and principle‐based model users reflected shifts in how students made sense of the systems and system models crosscutting concept. These shifts in performances aligned with progress in computational thinking practices and finally with use of hydrology disciplinary core ideas. These findings contribute to understanding of how science and engineering practices, disciplinary core ideas, and crosscutting concepts intertwine during learning; how computational thinking practices develop; and how computational thinking about system models facilitates learning for environmental science literacy.

Leveraging Prediction and Reflection in a Computational Setting to Enrich Undergraduate Students’ Combinatorial Thinking

In this paper, I discuss undergraduate students’ engagement in basic Python programming while solving combinatorial problems. Students solved tasks that were designed to involve programming, and they were encouraged to engage in activities of prediction and reflection. I provide data from two paired teaching experiments, and I outline how the task design and instructional interventions particularly supported students’ combinatorial reasoning. I argue that emergent computational representations and the prompts for prediction and reflection were especially useful in supporting students’ reasoning about fundamental combinatorial ideas. I argue that this particular mathematical example informs broader notions of disciplinary reflexivity and representational heterogeneity, providing insight into computational thinking practices in the domain of mathematics. Ultimately, I aim to explore the nature of computing and enumeration, shedding light on why the two disciplines are particularly well-suited to support each other. I conclude with implications and avenues for future research.