Computational Thinking Activities Research Articles

Why are some students “not into” computational thinking activities embedded within high school science units? Key takeaways from a microethnographic discourse analysis study

AbstractScience educators are integrating more and more computational thinking (CT) activities into their curricula. Proponents of CT offer two motivations: familiarizing students with a realistic depiction of the computational nature of modern scientific practices and encouraging more students from underrepresented backgrounds to pursue careers in science, technology, engineering, and mathematics. However, some studies show that increasing exposure to computing may not necessarily translate to the hypothesized gains in participation by female students and students of color. Therefore, paying close attention to students' engagement in computationally intense science activities is important to finding more impactful ways to promote equitable science education. In this paper, we present an in‐depth analysis of the interactions among a small, racially diverse group of high school students during a chemistry unit with tightly integrated CT activities. We find a salient interaction between the students' engagement with the CT activities and their social identification with publicly recognizable categories such as “enjoys coding” or “finds computing boring.” We show that CT activities in science education can lead to numerous rich interactions that could, if leveraged correctly, allow educators to facilitate more inclusive science classrooms. However, we also show that such opportunities would be missed unless teachers are attentive to them. We discuss the implications of our findings on future work to integrate CT across science curricula and teacher education.

What Emotions do Pre-university Students Feel when Engaged in Computational Thinking Activities?

Emotions affect how we acquire knowledge, being one of the causes of the demotivation generated at the time of studying a new field. Computer Science does not always pique the interest of young people, so we carry out an analysis of emotions that are present in primary and secondary school students, around 8-9 years old and 12-13 years old, who engage in Computational Thinking activities, considering the educational level, gender, and type of intervention, to understand why this lack of interest. The sessions were based on 1 hour of face-to-face class in which activities related to Computational Thinking were carried out. The instrument used to measure emotions was the Developmental Channels Questionnaire which includes 13 different emotions that students must answer using the Likert scale from 0 to 10. The emotions felt have been mostly positive and ambiguous, while negative emotions have a low intensity, particularly in primary education. Regarding the educational level, there are differences between girls and boys only in the secondary education, while in the primary they are no significant. Also, girls show an evolution when carrying out this type of activity, while boys do not change.

Computational Thinking Activities Among Mathematics Teachers: A Systematic Literature Review

Computational Thinking Activities Among Mathematics Teachers: A Systematic Literature Review

Who programs whom?—Computational empowerment through mastery and appropriation in young children’s computational thinking activities

This paper sheds light on 3–5-year-old children’s enactments of computational empowerment (CE) in activities with computational thinking (CT). CT is widely elaborated on as a universal problem-solving approach and a skill set necessary for thriving in today’s digitised societies. Scholars claim that CT for all should be ensured from an early age, and several studies develop and examine age-appropriate technological tools, as well as pedagogical approaches, for young children’s learning of CT. Based on 1.5 years of co-designing for children’s situated CT in two Danish kindergartens, the present study conducts a socioculturally informed analysis of video-observed interactions between children and educational robots. The findings display how children and robots engage in interactions that transcend children’s mastery of CT in any narrow sense. This is examined as situated enactments of CE; as children’s critical and informed decisions regarding the roles that technologies, in this case educational robots, can play in their institutionally situated social lives. The paper concludes that children’s various enactments of CE deserve scholarly and professional attention, both as an important prerequisite for, and as a necessary limitation to, the implementation of CT in kindergartens.

Integration of computational thinking activities in Grade 10 mathematics learning

This study explored integrating computational thinking (CT) activities in mathematics learning in Grade 10 classrooms in South African township, suburban and independent schools. The inquiry adopted a mixed method approach as part of an exploratory, descriptive survey design and involved purposively selected Grade 10 learners as participants. Quantitative data were collected through the administration of questionnaires among the participants. Qualitative data was collected through semi-structured interviews and activities involving integrating computational thinking activities in mathematics learning. The empirical investigation underpins the Cultural Historical Activity Theory (CHAT) as the theoretical framework. Key findings from the study revealed that the integration of computational thinking activities in mathematics learning promises to be an effective means to enhance learners’ understanding of mathematics content. In addition, the participants demonstrated a positive disposition towards computational thinking. The participants perceived computational thinking as a vital tool that can be harnessed to develop problem-solving skills in mathematics classrooms. The study findings provide critical theoretical implications for pedagogic innovation.

Gender equity and motivational readiness for computational thinking in early childhood

Learning coding during early childhood is an effective way for children to practice computational thinking. Aspects of children's motivation can increase the likelihood that children approach computational thinking activities with enthusiasm and deep engagement. Gender inequities may interfere with children's readiness to take advantage of opportunities to build computational thinking skills through activities such as coding. Societal stereotypes can reduce young girls’ motivation to engage with computer science, preventing them from gaining benefits from coding activities designed to support computational thinking. This study examined children's gender stereotypes as well as children's own motivation for computer coding in 363 first- through third-grade children. We assessed gender differences in both stereotypes and motivation, as well as links between the stereotypes that individual children held and their own motivation. Children generally endorsed stereotypes about interest and ability for computer coding that favored their own-gender group, although third-grade girls reported gender-egalitarian beliefs about interest in coding. There were no gender differences in children's motivation for computer coding in terms of their own interest, sense of belonging, or ability self-concepts. Children's stereotypes about their own-gender group were significantly positively correlated with their own motivation for computer coding. These findings suggest that early childhood represents an excellent age for children to begin building computational thinking skills, before girls endorse negative stereotypes about their gender's interest in computer science.

An Investigation of Affective Factors Influencing Computational Thinking and Problem-Solving

This study investigated the effects of affective factors on computational thinking and problem-solving. Computer science subjects are becoming part of the regular curricula in K-12 and higher education to enhance computational problem-solving skills. However, affective factors influencing computational thinking skills and computational thinking components predicting problem-solving skills have yet to be fully explored. This paper proposed a conceptual model to predict (a) four affective factors that influence computational thinking self-efficacy and (b) six computational thinking components that affect problem-solving self-efficacy. Structural equation modeling was used to analyze self-report data from college students to examine the direct relationships among study variables. The findings showed that two affective factors (i.e., programming self-efficacy and computer science usefulness) significantly predicted computational thinking self-efficacy and influenced problem-solving self-efficacy. Also, two computational thinking components (i.e., algorithm and debugging) were the significant determinants of problem-solving self-efficacy. The results validate the importance of affective factors in computer science education and suggest specific computational thinking activities that should be emphasized in computer science curricula to facilitate problem-solving skills.

Engaging Primary and Secondary School Students in Computer Science Through Computational Thinking Training

Although Computer Science has grown to become one of the most highly demanded professional careers, every year, only a small percentage of students choose a degree directly related to Computer Science. Perhaps the problem lies in the lack of information that society has about Computer Science itself, and particularly about the work computer scientists do. No one doubts the role of Mathematics or Languages as core subjects in every primary and secondary education syllabus; however, Computer Science plays a negligible role in most current syllabuses. Only in a few countries have governments paid special attention to content related to Computer Science and to learning to analyze and solve problems the way computer scientists do (Computational Thinking). In this article, we present <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Piens@ Computacion@ULLmente</i> , a project that provides a methodology to promote Computer Science through Computational Thinking activities among primary and secondary education students. The results obtained from an exhaustive statistical analysis of the data we collected demonstrate that the perception of Computer Science that pre-university students have can be improved through specific training. Moreover, we can also confirm that the performance of pre-university students involving Computational Thinking skills is independent of gender, particularly at the primary education level.

Offline and online user experience of gamified robotics for introducing computational thinking: Comparing engagement, game mechanics and coding motivation

As we begin to identify essential skills for the future, there has been an increased focus on how to define and implement computational thinking within education. However, the question of how to engage children with coding activities within the context and limitations of the curriculum remains relatively explored. In our study, a human-centered design approach was followed to guide a small group of children through the co-design, implementation and evaluation of a board game. The board game had two versions: an offline version involving a robotic agent and an online version with its digital equivalent. A mixed-method approach was used to understand and compare levels of engagement, usability, and collaboration in both versions of the game. The tangible aspect of working with a robotic agent in the offline version led to greater levels of motivation and involvement with the game mechanics. Tangible robotics games tend to be more approachable for children. Our study shows that using such games by connecting the mathematics curriculum with coding problems can successfully engage participants in collaborative computational thinking activities. We contribute to the field by providing human-centered guidance for the creation of educational tools to develop computational thinking. Such guidance is not only applicable in technologically rich environments; it can also be applied in educational communities with limited access to technology.

Supporting Future Teachers to Promote Computational Thinking Skills in Teaching STEM—A Case Study

In recent years, teachers in various fields, such as science, mathematics, linguistics and others, have been interested in alternative learning strategies as opposed to traditional activities, in order to help students to examine their learning progress. The integration of computational thinking in teaching activities, after returning to face-to-face activities, can meet the needs of students during the COVID-19 pandemic. In this research, two samples of students in their first year of study were recruited for the teacher training program validation for computational skills in STEM education. The training model offers an explanation for the differences between the following two sets of data: the CT modules used in a substantial number of teacher workshops, and the results obtained, which are closely related to the argument that teachers can support students’ lifelong learning by developing computational thinking activities. The results related to the students’ scores may have contributed to their improvement in computational thinking skills and it could be one of the best examples of how to change the ways of learning about 21st century skills and sustainable education.

Developing Student’s Comprehensive Knowledge of Physics Concepts by Using Computational Thinking Activities: Effects of a 6-Week Intervention

Computational thinking has been identified as an important approach for enabling students' better comprehension of science concepts as well as scientific procedures. Computation is useful in physics because it permits physics theories to be applied to issues that are complicated to fix analytically. Visual Python provides a 3D environment where learners may design 3D objects, apply a physical framework, and study the effects of altering parameters. The implementation and outcomes of a 6-week teacher-led computational thinking intervention with groups of 12th graders (n=60) are described in this study. Two research questions are being addressed using quantitative analysis and a quasi-experimental approach involving a pre- and post-test. The participants who received the six-week implementation on the experimental group performed significantly better on the post-test than the control group, which received only standard teaching lectures. The results indicated a statistically significant difference in mean scores between the experimental group (M = 24.03, SD = 4.68) and the control group (M = 20.3, SD = 5.38). The findings indicate that implementing computational thinking activities not only improves students' knowledge of physics concepts, but it also improves visual thinking, allowing students to better cognitively comprehend the problem.

Exploring Design Principles in Computational Thinking Instruction for Multilingual Learners

Background: Multilingual learners have been overlooked and understudied in computer science education research. As the CS for All movement grows, it is essential to design integrated, justice-oriented curricula that help young multilingual learners begin to develop computational thinking skills and discourses. Purpose: We present a conceptual framework and accompanying design principles for justice-centered computational thinking activities that are language-rich, with the aim of supporting learners’ agency and building their capacity over time to use computing for good in their communities. Setting: Our work takes place in a research–practice partnership centered in an elementary school in California with a significant multilingual Latinx population. Research Design: We have engaged in two cycles of design-based research with preservice and in-service teachers at an elementary school. Through analysis of one case study during the second and most recent cycle, we examined the potential of teachers using our design principles for supporting multilingual learners’ language development through engagement in computational thinking. Conclusions: Our findings suggest that multilingual learners will engage in productive discourse when computational thinking lessons are designed to (1) be meaningfully contextualized, (2) position students as agentic learners, and (3) promote coherence over time. However, more research is needed to understand how teachers use these principles over time, and what additional supports are needed to ensure coordination between stakeholders to develop and effectively implement coherent learning progressions.

Survey: Artificial Intelligence, Computational Thinking and Learning

Learning is central to both artificial intelligence and human intelligence, the former focused on understanding how machines learn, the latter concerned with how humans learn. With the growing relevance of computational thinking, these two efforts have become more closely connected. This survey examines these connections and points to the need for educating the general public to understand the challenges which the increasing integration of AI in human lives pose. We describe three different framings of computational thinking: cognitive, situated, and critical. Each framing offers valuable, but different insights into what computational thinking can and should be. The differences between the three framings also concern the views of learning that they embody. We combine the three framings into one framework which emphasizes that (1) computational thinking activities involve engagement with algorithmic processes, and (2) the mere use of a digital artifact for an activity is not sufficient to count as computational thinking. We further present a set of approaches to learning computational thinking. We argue for the significance of computational thinking as regards artificial intelligence on three counts: (i) Human developers use computational thinking to create and develop artificial intelligence systems, (ii) understanding how humans learn can enrich artificial intelligence systems, and (iii) such enriched systems will be explainable. We conclude with an introduction of the articles included in the Special Issue, focusing on how they call upon and develop the themes of this survey.

The CT-cube: A framework for the design and the assessment of computational thinking activities

Computational thinking is a fundamental competence that is being introduced in K-12 and succeeding curricula worldwide. Despite this huge effort, many computational thinking models in the literature do not explicitly take into consideration the pupils’ age and the developmental nature of computational thinking skills. Furthermore, many existing computational thinking models are focused on the internal thinking processes of the individuals, failing to explicitly consider the situated nature, in terms of social context and artefactual environment, that usually characterise tasks that require computational thinking to be solved. In this paper, we present a framework for the design, realisation, analysis, and assessment of computational thinking activities, called CT-cube. The CT-cube allows to extend existing computational thinking models to consider the life-long development of computational thinking skills in individuals, from childhood to adult age, and to take into consideration the situated nature of computational thinking activities. We use the CT-cube to design an unplugged task, called Cross Array Task (CAT), allowing to assess the algorithmic skills of K-12 pupils and we show how the CT-cube can be used in this case to illustrate the development of this competence along the entire compulsory school path, considering a sample of 109 pupil aged 3 to 16 in Switzerland.

A proposal to introduce STEM and educational robotics in kindergarten through an educational scenario for the global food system with resources from Europeana

In recent years, increasing attention has been focused on developing Kindergarten children's acquisition of 21st-century digital skills and competencies. New educational technologies have been created to engage students in computational thinking activities. In addition, the use and teaching of robotics have been increasingly studied in recent years, as research data has shown recommendations and positive outcomes for students and teachers. As global demand for food and non-food products continues to grow, primarily driven by population and income growth, the challenge of addressing resource depletion and climate change is also expected to increase. This intervention aims to present the global food system and food waste phenomenon to toddlers through an educational scenario for kindergarten using educational robotics and STEM methodology.

Marine plastic pollution in kindergarten as a means of engaging toddlers with STEM education and educational robotics

In recent years, education has increasingly focused on children's acquisition of digital skills and abilities, which leads to the need to create new educational methodologies capable of engaging students in computational thinking activities. The research interest of this paper focuses on how preschool children can be more involved in STEM and educational robotics through authentically experiential learning on the topic of marine plastic pollution. It examines toddler engagement through an integrated STEM scenario using the programmable robot Bee-Bot and encourages children to solve problems in many possible ways, assessing the strengthening of their necessary skills. The teaching intervention took place during the 2021-22 school year in a Kindergarten in the city of Ioannina. During the planning and implementation phase of the program, action research and field study are applied, while the sociocultural approach to teaching natural sciences, educational robotics, new technologies, engineering, the arts and mathematics. The research framework is completed with the evaluation process and the students disseminating the project learning outcomes.

Learning number patterns through computational thinking activities: A Rasch model analysis

Despite the increasing presence of computational thinking (CT) in the mathematics context, the connection between CT and mathematics in a practical classroom context is an important area for further research. This study intends to investigate the impact of CT activities in the topic of number patterns on the learning performance of secondary students in Singapore. The Rasch model analysis was employed to assess differences of ability between students from the experimental group and control group. 106 Secondary One students (age 13 years old) from a secondary school in Singapore took part in this study. A quasi-experimental non-equivalent groups design was utilized where 70 students were assigned into the experimental group, and 36 students were assigned into the control group. The experimental group was given intervention with CT-infused activities both on- and off-computer, while the control group received no such intervention. Both groups were administered the pretest before the intervention and the posttest after the intervention. The data gathered were analyzed using the partial credit version of the Rasch model. Analysis of pretest and posttest results revealed that the performance of the experimental group was similar to the control group. The findings did not support the hypothesis that integrating CT in lessons can result in improved mathematics learning. However, the drastic improvement was observed in individual students from the experimental group, while there is no obvious or extreme improvement for the students from the control group. This study provides some new empirical evidence and practical contributions to the infusion of CT practices in the mathematics classroom.

Improving Computational Thinking in Secondary Students with Unplugged Tasks

The teaching-learning of programming fundamentals is increasing in secondary schools, however, it is a very difficult task for the teacher because the student has not yet achieved full development of their computational thinking, so they have difficulty in learning programming fundamentals. In this article, we describe the development of computational thinking activities prior to the teaching of programming fundamentals and we analyze the data obtained from a pre- and post-test of computational thinking applied to a control group and an experimental group. Afterwards, we analyze the results obtained from a test of programming fundamentals to both the control group and the experimental group.The activity has been evaluated during the academic year 2017-2018 by 80 high school students from 10th grade (15 and 16 years old), our results indicate that the development of activities of Computational Thinking previous to the teaching of programming fundamentals has allowed the students to assimilate in a better way the learning in the mentioned subject, that is to say, they extended their mathematical logical reasoning to develop the respective flow charts without any difficulty. That is, they expanded their mathematical logical reasoning to develop the respective flow diagrams without any difficulty.

How do Teachers Apply Computational Thinking Activities in Elementary School? From Continuing Education to the classroom

INTRODUCTION: There is no consensus of what skills can be developed from the learning of Computation Thinking (CT). However, teachers and researchers agreed that by the learning of CT individuals can acquire and expand many abilities. Courses have been carried out in Brazil and in other countries with the aim of motivating teachers on adding CT to classroom practices. OBJECTIVE: This article to present a case study that investigated the feasibility of introducing activities of CT for primary school children. Such activities were created and mediated by the teachers of Primary School. METHOD: First, a continuing education course about Computational Thinking was conducted with the participation of 14 teachers. The participants could understand the fundamentals of CT, and consequently, became able to planning and conducting CT activities by themselves in their classrooms. After, we analyzed the data gathered during the course under the quantitative and qualitative lenses. RESULTS: The results showed that the participants had a degree of agreement between 56% and 71% regarding the understanding and applicability of CT to developing skills in Primary School. The qualitative findings revealed that the participants could prepare activities that linked CT to topics presented in the subjects of Primary School. Besides, we could identify three patterns of shaping the activities in which this "computational think" were incorporated. CONCLUSION: Practices to stimulate the CT in students are mediated by using different teaching strategies as such Gamification and Culture Maker. These activities also enable the development of skills related to the National Curricular Common Base

Modeling and Measuring High School Students’ Computational Thinking Practices in Science

Despite STEM education communities recognizing the importance of integrating computational thinking (CT) into high school curricula, computation still remains a separate area of study in K-12 contexts. In addition, much of the research on CT has focused on creating generally agreed-upon definitions and curricula, but few studies have empirically tested assessments or used contemporary learning sciences methods to do so. In this paper, we outline the implementation of an assessment approach for a 10-day high school biology unit with computational thinking activities that examines student pre-post responses as well as responses to embedded assessments throughout the unit. Using pre-post scores, we identified students with both positive and negative gains and examined how each group’s CT practices developed as they engaged with the curricular unit. Our results show that (1) students exhibited science and computational learning gains after engaging with a science unit with computational models and (2) that the use of embedded assessments and discourse analytics tools reveals how students think differently with computational tools throughout the unit.