Promoting undergraduates’ computational thinking in a knowledge building environment

Problem-based learning integrated with Digital Argumentation (PBL-DA) is a learning strategy for optimizing innovative learning in the digital era. This research aimed to investigate whether the application of PBL-DA can foster the Computational Thinking (CT) and Higher Order Thinking Skills (HOTs). A quasi-experimental design measured three aspects: skill (decomposition, algorithm design, evaluation), attitude (confidence, communication, flexibility), and approach (tinkering, creating, collaborating). The students' HOTs were measured through eight aspects: critical thinking, argumentation, problem-solving, problem-identifying, understanding concepts, analysing, making decisions, and creative thinking. The students' CT and HOTs scores of control and experimental classes were analyzed using Hotelling’s T² test and Tukey’s post hoc test. The Hotelling’s T² test revealed a significant difference between the experimental and control classes for both CT and HOTs (T² = 0.340, p < 0.001 for CT; T² = 0.718, p < 0.001 for HOTs). Tukey’s test further showed that PBL-DA significantly impacted the CT skill and attitude aspects (p < 0.01), while the approach aspect was not significant (p > 0.05). For HOTs, critical thinking, argumentation, problem-identifying and analyzing were significantly improved (p < 0.01), but problem-solving, understanding concepts, making decisions, and creative thinking showed no significant improvement (p > 0.05). Pearson’s correlation analysis indicated a strong positive correlation (r = 0.651, p < 0.001) between students' CT and HOTs skills. These findings provide evidence of the effectiveness of the PBL-DA model in improving students' CT and HOTs, demonstrating its potential for fostering critical and higher-order thinking skills in the digital era.

This study aims to provide an overview of the computational mathematical thinking abilities of male and female students in solving mathematical problems and the aspects (abstraction, decomposition, algorithmic thinking, and generalization) that influence these differences. This study uses a qualitative method with a case study approach in a junior high school in Jakarta for the academic year 2023/2024. The participants in this study are 36 students. Data were collected through written examinations and interviews and analyzed using the triangulation technique. The results of the study showed different patterns of computational thinking skills between male and female students. Male students excel in decomposition and algorithmic thinking but are weak in abstraction and generalization. Female students excel in abstraction and decomposition but are weak in algorithmic thinking and generalization. Both male and female students master the context of decomposition for computational thinking skills but lack mastery in the context of generalization. In conclusion, gender differences influence specific aspects of computational thinking skills, indicating the need for tailored educational strategies to address these differences.

Educational Robotics (ER) is a tool that can favor teamwork, stimulate creativity, and the ability to solve students' problems through the process of assembling and programming robots. In this sense, ER has been used to improve educational practices. There are several initiatives that seek to stimulate Computational Thinking (CT) to stand out. Although ER being used to develop CT, there are still no guidelines based on scientific studies that support this use. The objective of this Research Full Paper is to identify: a) the main pedagogical approaches are applied in classes with ER focused on developing students' CT; b) the central difficulties are encountered in classes with ER focused on developing students' CT; c) the CT skills are presents in classes with ER focused on developing students' CT; d) the instruments are used to assess students' CT during classes with ER; e) the students' profile who participated in classes with ER focused o on developing students' CT; f) the educational robotics technologies are adopted in classes focused on developing students' CT. To achieve these goals, we planned and carried out systematic mapping of the literature. The results show that, through ER, CT is approached through the teaching of programming languages in a collaborative way in Early Childhood and High School. The most CT skills observed are related to programming, such as sequencing, algorithm, loop, generalization, decomposition, and debugging. The main instruments for assessing students are tests, and the most significant difficulty is the limitation of class hours. Finally, LEGO® is the most used technology in class.

Computational thinking (CT) is a critical set of 21st century skills that young learners must develop to be successful in contemporary work and life. As more K-12 schools begin to integrate CT into the curriculum, elementary preservice teachers (EPSTs) must be prepared to teach CT to their future students. Therefore, elementary teacher preparation programs should explore ways to incorporate CT into their coursework, ensuring that EPSTs graduate with the necessary knowledge and skills to teach CT. This study investigates the impacts of a three-week CT module implemented in a technology integration course in an elementary teacher preparation program on EPSTs’ CT value beliefs, self-efficacy, and teaching efficacy. The purpose of the module was to introduce EPSTs to basic concepts and big ideas in CT, support their application of CT in block-based coding environments, and promote connection building between CT and authentic real-world scenarios that balance different types of CT activities. Guided by the Interconnected Model of Professional Growth (IMPG), this study examined EPSTs’ learning as a dynamic process of change across the personal and external domains. The module was located in the external domain as a stimulus for learning, while the Teacher Beliefs about Coding and Computational Thinking (TBaCCT) instrument was used to assess changes in value beliefs, self-efficacy, and teaching efficacy within the personal domain. A convergent parallel mixed-methods design was used to analyze pre- and post-surveys administered to 50 EPSTs and semi-structured interviews with four of the EPSTs. The results showed that the beliefs of the CT value of EPSTs evolved and their self-efficacy and teaching efficacy of CT significantly improved after participating in the module, suggesting that the interaction between external learning experiences and internal belief systems - facilitated by reflection and action - contributed to early professional growth. Notably, EPSTs also developed a more accurate understanding of CT, recognized the benefits of both plugged and unplugged CT activities, and expressed a desire for continued CT learning and professional development. Although EPSTs expressed concerns with the scarcity of physical computing toys in schools, they demonstrated a commitment to incorporating CT activities into their teaching and exploring alternative funding avenues to acquire such resources. Practical implications include potential approaches for elementary teacher preparation programs to embed CT into existing curricula.

Background and Aim: Based on relevant policies and literature, such as higher education planning at home and abroad, policies of the Chinese Ministry of Education, educational concepts, cognitive learning theories, project-based learning methods, teaching strategies, and teaching evaluations, researchers interviewed teachers and students on the current foundation of the programming design course. This research and development aimed 1 to study the background information focusing on the course components of the foundation of programming design course to enhance students’ computational thinking ability. 2) To develop the foundation of a programming design course based on Cognitive learning theory, combined with Project-based learning to enhance students’ computational thinking ability. 3) To determine the effectiveness of implementing the foundation of programming design course based on Cognitive learning theory combined with Project-based learning. Materials and Methods: The sample of this research was 30 first-year students (1 class) majoring in Network Engineering class 1, in the academic year 2024-2025 of Zhoukou Normal University, Henan Province, China. They are derived from using a cluster random sampling method. The experimental design adopted in this research was a group posttest-only design. The research instruments from each Phase of the study were as follows: Phase I: Interview forms for teachers and students on course-related questions. Phase II: 1) Foundation of programming design course based on Cognitive learning theory combined with Project-Based Learning. 2) 12 lesson plans for the foundation of the programming design course. 3) Evaluation form of computational thinking skills. 4) Learning achievement test. 5)Satisfaction questionnaire. The data were analyzed by using mean, standard deviation, and the one-sample t-test. Results: The results of this research were as follows: 1) The researcher reviewed the related documents about the Foundation of Programming Design Course and interviewed the 4 teachers and 30 students about problems of the Foundation of Programming Design Course, and the information gathered was used to develop the course. 2) The course development in six aspects: Course principles, Course objectives, Course content, Course instructional strategies, Course media and resources, and Course evaluation. 3) After implementing through Foundation of Programming Design Course based on Cognitive Learning Theory combined with Project-Based Learning, students’ computational thinking ability (Knowledge) was higher than the determined criterion of 70% at a significance level of 0.05; students’ computational thinking ability (Skills) was higher than the determined criterion of 70% at a significance level of .05. 4) The mean scores of students’ satisfaction after implementing the Foundation of Programming Design Course based on Cognitive Learning Theory combined with Project-Based Learning was 4.838 from a possible full mark of 5, and the standard deviation was 0.176, which was statistically higher than the criterion of 70% at the .05 level of statistical significance. Conclusion: This research confirms the effectiveness of the teaching model based on Cognitive learning theory combined with Project-Based Learning to enhance students' computational thinking ability.

This paper describes the challenges and approaches to introduce computational thinking to a large and diverse group of architecture students. Set up as an international one week workshop with 300 participating students from different cultural backgrounds and educational levels it also integrated a diverse group of tutors whose computational expertise ranged from not existent to high level expertise. The approach suggested to articulate a design task which enforced computational, systematic or algorithmic thinking but enabled different levels of engagement with actually using computer as tools. Hypothetically this would allow all students and tutors to engage with the computational thinking agenda regardless their computational affinity even whilst applying analogue methods. In the further course of the paper some of the approaches to the design task will be exemplified and discussed. In the larger perspective of the workshop it was evident that there was a great engagement with the computational agenda even from students and staff who rather avers to the use of computers. A key element in the conception of the workshop was the provision of predefined algorithms to ease the initial access to the use of the computational tools. The projects resulting from the one week workshop demonstrated different achievements in terms of computational thinking ranging from grid solutions, over simple continuous patterns, to the implementation of L-systems to overlapping and interconnected patterns creating a continuum with disruptions based on function, environmental conditions and topographic influences. Besides the intercultural experience the workshop was successful in exposing a large group of students and tutors to the concepts of computational design whilst accommodating different learning preferences and engagement with the computer as a device.

Promoting computational thinking is a priority in CS education and other STEM and non-STEM disciplines. Our innovative, NSF-funded IC2Think project blends computational and creative thinking. In Spring 2013, we deployed Computational Creativity Exercises (CCE) designed to engage creative competencies (Surrounding, Capturing, Challenging and Broadening) in an introductory CSI course for engineering students. We compared this CCE implementation semester (80 students, 95% completing 3 or 4 CCEs) to the Fall 2013 semester of the same course (55 students) without CCEs. CCE implementation students had significantly higher scores on a CS concepts and skills knowledge test (F(1, 132) = 7.72, p < 01, partial Eta2 = .055; M=7.47 to M=6.13; 13 items) and significantly higher self-efficacy for applying CS knowledge in their field (F(1, 153) = 12.22, p < .01, partial Eta2 = .074; M=70.64 to M=61.47; 100-point scale). CCE implementation students had significantly higher study time (t(1, 136) = 2.08, p = .04; M=3.88 to M=3.29; 7-point scale) and significantly lower lack of regulation, which measures difficulties with studying (t(1, 136) = 2.82, p = .006; M=2.80 to M=3.21; 5-point scale). The addition of computational creativity exercises to CS courses may improve computational thinking and learning of CS knowledge and skills.

This study investigates the relationship between computational thinking performance and general school achievement and explores to see if computational thinking performance can be predicted by algebra and informatics achievement. The sample group of 775 grade 8 students was drawn from 28 secondary schools across Kazakhstan. The students responded to a Computational Thinking Performance test of 50 multiple-choice questions and Computational Thinking Scale questionnaire. The test covers the concepts: logical thinking, generalisation and abstraction. The validity and reliability of the multiple-choice questions are tested using the Item Response Theory. The Likert type questionnaire covers five factors: creativity, algorithmic thinking, cooperation, critical thinking and problem solving. School achievement results (secondary data) include scores for a number of school subjects. The results of the study showed that the multiple-choice questions are valid and a reliable tool to measure computational thinking performance of students. Algebra, general school achievement and students’ perception of their computational thinking skills were significant predictors of computational thinking performance. The results revealed no gender difference in computational thinking performance and perceptions of computational thinking. The findings regarding the relationship between computational thinking performance, the students’ general school achievement and perceptions of computational thinking skills are compared and discussed.

Objective: The benefits of computational thinking have become an increasingly acknowledged and popular subject of investigation among researchers. This research aims to gather detail and comprehensive information regarding the learning of computational thinking skills in mathematics at various educational levels through a systematic literature review approach. Methods: With a focus on education level, instructional media, mathematics content, and the components of computational thinking addressed by previous researchers, this paper applied the PRISMA Systematic Review Protocol to offer a comprehensive synthesis of sixteen empirical studies retrieved from the Scopus database on the implementation of computational thinking in mathematics education. Findings: Most research on fostering computational thinking in mathematics education is concentrated at the elementary and junior high school. To optimize the development of computational thinking in mathematics, teachers should be reminded of strategies to support students, particularly through activities involving simulations using various instructional media. Examples of such media include programming platforms, visualization tools, and interactive simulations and games. Number operations and geometry are the mathematical content most widely used for fostering computational thinking. Algorithmic thinking, a crucial component in fostering computational thinking among elementary school students, helps them develop a strong foundation for understanding higher mathematical concepts. Conclusion: A systematic review of computational thinking in learning mathematics at the various education level is conducted in this study. The chosen studies were systematically analyzed for the advancement of computational thinking in learning mathematics to provide new an insight information for educators and stakeholders. Keywords: computational thinking, mathematics, systematic literature review. DOI: http://dx.doi.org/10.23960/jpmipa/v25i1.pp34-52

There is little empirical research related to how elementary students develop computational thinking (CT) and how they apply CT in problem-solving. To address this gap in knowledge, this study made use of learning trajectories (LTs; hypothesized learning goals, progressions, and activities) in CT concept areas such as sequence, repetition, conditionals, and decomposition to better understand students’ CT. This study implemented eight math-CT integrated lessons aligned to U.S. national mathematics education standards and the LTs with third- and fourth-grade students. This basic interpretive qualitative study aimed at gaining a deeper understanding of elementary students’ CT by having students express and articulate their CT in cognitive interviews. Participants’ (n= 22) CT articulation was examined usinga prioricodes translated verbatim from the learning goals in the LTs and was mapped to the learning goals in the LTs. Results revealed a range of students’ CT in problem-solving, such as using precise and complete problem-solving instructions, recognizing repeating patterns, and decomposing arithmetic problems. By collecting empirical data on how students expressed and articulated their CT, this study makes theoretical contributions by generating initial empirical evidence to support the hypothesized learning goals and progressions in the LTs. This article also discusses the implications for integrated CT instruction and assessments at the elementary level.

Computational thinking skill is an important skill individuals should acquire to meet the requirements of the digital age. The aim of the study is to predict the computational thinking skills of middle school students through ANFIS approach, which is an adaptive neural network-based fuzzy logic. Students' computational thinking skill scores were predicted by creating a model based on grade level and academic achievement variables. Grade level and academic achievement served as the model's input variables, and computational thinking skill scores served as the model's output variable. Data were collected using personal information form and computational thinking scale. A comparison was made between students' real and artificial computational thinking skill scores using statistical methods. In the study, a strong and favorable association between the artificial scores produced using the ANFIS technique and the actual scores was discovered. Furthermore, there was no statistically significant difference between the real and artificial scores for computational thinking skills. These results indicate that the ANFIS approach is a suitable alternative analysis method for predicting students' computational thinking skills. The study provides a good example in the field of education where artificial intelligence can be used to predict students' educational characteristics.

&lt;span lang="EN-US"&gt;Based on the study, computational thinking skills are influenced by science, technology, engineering and mathematics (STEM) skills, and there is a relationship between computational thinking skills and 21st-century skills. However, studies related to STEM attitudes, computational thinking and their impact on 21st-century skills are still very few and limited. The purpose of our study was to examine the impact of STEM attitudes and computational thinking on 21st-century. This research uses a quantitative approach. The participants of this study were students of a vocational school in Bantul Regency, Yogyakarta, Indonesia (N=290). Research data in STEM attitude, computational thinking, and 21st-century skills using a questionnaire. The data were analyzed using structural equation modeling techniques using the Smart PLS application. The results of the study obtained several findings, including: the model proposed in this study was valid; STEM attitude has a positive and significant effect on computational thinking; and computational thinking has a positive and significant effect on 21-st century skills. It can be argued that when STEM attitudes and computational thinking are more positive, 21-st century skills will improve. These findings have implications that curriculum development and STEM learning practices have to develop students’ computational thinking skills and 21st-century skills, especially in vocational schools.&lt;/span&gt;

In 2018, the Ministry of Education released the Action Plan for Education Informatization 2.0, which puts forward new requirements for modern education and teaching. Under the influence of the computer Internet, modern teaching has not only changed the way of teaching and learning, but also promoted the improvement of educational concept. In the face of the current new trend, how to cultivate students' computer thinking ability in the teaching of computer courses has gradually become a hot topic in the field of computer education at home and abroad. This paper mainly describes the concept of computer thinking, characteristics and research status at home and abroad, at the same time, comprehensive description of the specific significance of the development of computer thinking, as well as how to cultivate students' computer thinking, finally do a whole summary of computer thinking, and add their own thinking. Under the new situation, we should advocate the development of computer thinking, keep up with the pace of The Times, and attach importance to the cultivation of students' computer thinking, so that students can better deal with the problems in life by the course learning.

Computational thinking involves using computer science concepts to design systems, find solutions to problems, and understand human behavior. Recent reports recommend the addition of computational thinking into K-6 education, and computational thinking has been taught in different learning environments, including formal and informal environments, and has also been taught alongside engineering design thinking. The CDIO Initiative includes a Conceive-Design-Implement-Design process, which can be adapted for use in guiding computational thinking activities at the elementary (K-6) level. This chapter draws on a phenomenological approach to computational thinking to provide the justification and method for adapting the C-D-I-O design process for teaching K-6 computational thinking. It also describes the design requirements and methods for creating four scaffolded computational thinking activities, which are discussed in detail. For each design, the connection with computational thinking concepts and the proposed framework are provided. This chapter also includes a discussion of the scaffolding techniques between the activities, and how the fading of scaffolding was used to improve learning and confidence. By drawing upon a phenomenological approach to computational thinking, we can make rooms for different ways of knowing and representation in computational thinking education to better connect with students’ lived experiences.

Computational thinking for teachers: Development of a localised E-learning system