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The relationship between computational thinking performance and general achievement of secondary school students in Kazakhstan
Abstract
Computational thinking, a form of thinking and problem solving, is defined as a mental process for abstracting problems and formulating solutions. Computational thinking is considered to be an essential skill for everyone and has become the centre of attention in education settings. There is a limited number of tools to measure computational thinking skills by multiple-choice questions, and limited research on the relationship between computational thinking and other domains. The purpose of this research is to investigate the relationship between computational thinking performance, perception of computational thinking skills and school achievement of secondary school students. Computational thinking performance of secondary school students in Kazakhstan is measured by using a bespoke multiple-choice test, which focuses on the following elements of computational thinking: logical thinking, abstraction and generalisation. The perceptions of computational thinking skills are self-reported using a pre-existing questionnaire, which covers the following factors: creativity, algorithmic thinking, cooperation, critical thinking and problem solving. The General Knowledge Test results that contain scores for 14 different subjects are used as indicators of students’ school achievement, with further sub-scores for the science subjects, language subjects and humanities. The sample group of 775 grade eight students are drawn from 28 secondary schools across Kazakhstan. The validity and reliability of the multiple-choice questions are established by using Item Response Theory models. The item difficulty, discrimination and guessing coefficients are calculated; and the item characteristic curves for each question and test information functions for each quiz are obtained. As a result, the multiple-choice questions are concluded as a valid and reliable tool to measure the computational thinking performance of students. Multiple regression is used to examine the relationship between computational thinking performance, perception of computational thinking and school achievement sub-scores. The results of the data analysis show that science subjects, language subjects and perception of computational thinking skills are significant predictors for computational thinking performance, showing a moderate relationship between computational thinking performance and school achievement. However, no significant relationship is found between humanities subject scores and computational thinking performance. This study also adds to the literature for the studies that investigate the relationship between computational thinking skills and other variables. This research contributes to the development of validated tools to measure computational thinking performance by using multiple-choice questions. This study investigates the relationship between computational thinking performance and general school achievement of secondary school students, and its findings shed light on the measurement of children’s cognitive development. The findings can help in designing better curricula by adjusting subjects that enhance children’s higher-order thinking abilities. The findings obtained in this research also adds to the literature for the studies that investigate the relationship between computational thinking skills and other variables.
... The inclusion and integration of mathematical intuition, logic, and critical and computation thinking in the learning environment and educational system are one of the most discussed topics among educational institutes in Kazakhstan. Mindetbay [6] conducted research to determine the importance of computational thinking on the general school achievement of the students in Kazakhstan. The findings of Mindetbay [6] demonstrate that "the sciences subjects like physics and chemistry, and the overall perception of the students regarding the computational thinking is significantly correlated with the computational performance of the students. ...
... Mindetbay [6] conducted research to determine the importance of computational thinking on the general school achievement of the students in Kazakhstan. The findings of Mindetbay [6] demonstrate that "the sciences subjects like physics and chemistry, and the overall perception of the students regarding the computational thinking is significantly correlated with the computational performance of the students. Thus, computational thinking skills have a moderate association with the achievement of the school specifically in Kazakhstan." ...
Mathematics learning (ML) is a fundamental aspect of education that lays the groundwork for various academic disciplines and practical applications. Understanding the factors that propel ML is crucial for optimizing educational outcomes. This quantitative empirical study investigates the impact of logical reasoning (LR), critical thinking (CT), information technology (IT), and distance learning (DL) on ML. The study employs structural equation modeling (SEM) using SmartPLS 4 for data analysis and hypothesis testing. The findings reveal that LR, CT, IT, and DL positively influence ML. The results highlight the importance of fostering LR, CT, and the integration of IT in mathematics education. This study contributes to the existing body of knowledge by providing insights into the factors that promote effective ML. These findings have implications for educators, policymakers, and curriculum developers, aiding in the design of instructional strategies and the integration of technology to enhance ML outcomes.
This paper introduces a rubric for analyzing "mobile computational thinking" (MCT) as represented in App Inventor work products. To demonstrate its efficacy, this rubric was used to evaluate and compare student work from the CS and non-CS student cohorts in a mixed-major app design undergraduate course. Our analysis showed some significant differences between the cohorts, which were expected, as well as more subtle differences. The rubric demonstrated that it was sensitive to significant and subtle variations of MCT. The instrument is available for download and use.
Performance in and perceptions of computational thinking (CT) are considered vital dimensions for comprehensively assessing CT skills of students. In this study, secondary school students’ CT performance and their perceptions were examined in terms of certain variables including gender, grade level, achievement and self‐efficacy. Casual‐comparative and correlational methods were used. The sample of the study consisted of a total of 328 fifth‐ and sixth‐grade (10–12 years old) secondary school students taking visual programming lessons. CT performance and perception tests were employed as data collection tools. The results show that CT performance of boys was higher than that of girls. A significant difference was found in both CT performance and perception depending on grades. The results show that achievement in math positively affected CT performance and perception. However, achievement in IT affected CT performance less than achievement in math. Implications are discussed in terms of theoretical insights, practices for improving CT skills in secondary schools and directions for further research.
Practitioner notes
What is already known about this topic Due to the complex structure of computational thinking (CT) in association with computers, cognition, learning and psychology, CT skills should be evaluated from a variety of perspectives.
CT performance and perception are considered vital dimensions for comprehensively assessing students’ CT skills.
What this paper adds This paper proposes a CT performance test and a CT perception scale for secondary school students to explore their skills in terms of certain variables including gender, grade level and achievements in math and information technology (IT) courses.
This paper provides some evidence that CT performance of boys is better than that of girls. A significant difference was found in both CT performance and perception depending on grades. The results of the study show that math course achievement positively affected CT performance and perception. However, IT course achievement affected CT performance less than math course achievement.
Implications for practice and/or policy CT performance is affected by different variables. Therefore, it may be beneficial to include specific topics in the curriculum that involve the use of more CT skills.
Girls’ interest and participation in practices such as programming can be encouraged.
Teachers should provide students with cognitive scaffolding to help them and to have them collaborate with each other during CT activities, especially at higher grades.
IT course content should include systematic and comprehensive CT activities to improve students’ CT skills. We suggest developing and implementing a holistic curriculum combined with IT and math lessons to improve students’ CT performance.
Computational Thinking (CT) has caught the attention of researchers, educators, and policymakers in many fields, and has been recognized as an important skill in this increasingly complex society. One challenge emerging in education is finding a way to embed computational thinking curricula into K-12 education. Researchers and educators are exploring ways to provide CT instruction. The study in this presentation investigates an innovative way to teach the CT skill abstraction. According to Grover & Pea’s article (2013), “abstraction involves defining patterns, generalizing from specific instances, and dealing with complexity.” This study explores the types of strategies students use when they play a game that requires multiple CT skills. Three hundred and sixty-five middle school students played two card games: Ghost Blitz vs. Sushi Go! and completed pre- and post-assessments which were designed based on the definition of abstraction to compare the participants’ performance. We analyzed students’ gameplay strategies to examine whether participants spontaneously utilized abstraction skills to make a plan to reach their goals when they were playing.
This Open Access book summarizes the key findings from the second cycle of IEA’s International Computer and Information Literacy Study (ICILS), conducted in 2018. ICILS seeks to establish how well schools around the globe are responding to the need to provide young people with the necessary digital participatory competencies. Effective use of information and communication technologies (ICT) is an imperative for successful participation in an increasingly digital world.
ICILS 2018 explores international differences in students’ computer and information literacy (CIL), namely their ability to use computers to investigate, create, and communicate at home, at school, in the workplace, and in the community. Participating countries also had an option to administer an assessment of students’ computational thinking (CT), focused on their ability to recognize aspects of real-world problems appropriate for computational formulation, and to evaluate and develop algorithmic solutions to those problems, so that the solutions could be operationalized with a computer.
The data collected by ICILS 2018 show how digital competencies can be assessed using instruments representing authentic contexts for ICT use, and how students’ CIL and CT skills relate to school learning experiences, out-of-school contexts, and student characteristics. Those data also show how learning technologies are used in classrooms around the world. Background questionnaires asked students about their use of ICT, and collected information from teachers, schools, and national education systems about the resourcing and teaching of CIL (and CT) within their countries. The results of ICILS 2018 will enable policymakers and education systems to develop a better understanding of the contexts and outcomes of CIL (and CT) education programs.
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.
This study investigates the measurement of computational
thinking performance of secondary school students using
multiple-choice questions. The sample group of 775 grade
eight students are drawn from 28 secondary schools across
Kazakhstan. Students responded to a Computational
Thinking Performance test of 50 multiple-choice questions.
The test covers the concepts: logical thinking, generalisation
and abstraction. The validity and reliability of the multiple-choice questions are determined using an Item Response
Theory model. The item difficulty and discrimination
coefficients are calculated, and the item characteristic curves
for each question and test information functions for each
quiz are generated. The results of the study show that the
multiple-choice question assessment is a valid and reliable
tool to measure computational thinking performance of
students.
Although several investigations of spatial reasoning and mental rotation skills have been conducted in research areas linked to STEM education, to the best of our knowledge, few of these studies have examined the relationship between spatial reasoning and computational thinking. Given this gap in the literature, the present study investigates the role and action of spatial reasoning, and specifically the effects of mental rotation on computational thinking within an embodied and enacted perspective. To achieve this, we carried out a study involving 92 students in five primary-school classes (1st grade - 5th grade). The findings reveal a positive correlation between computational thinking skill and mental rotation ability.
The effectiveness of a pedagogical approach is directly related to whether it takes the characteristics of cognition into account (Sweller 2007). As such, a fundamental question that has strong implications for effective teaching and learning-- in the context of computational thinking (CT)--is what is its nature. Is it a domain-specific or domain-general cognitive capacity? The main objective of this article is to provide an initial introduction of generality/specificity issues to the CT literature from a cognitive psychology perspective. Specifically, it focuses on a critical appraisal of the domain-specific account of CT, which is subscribed by a considerable amount of existing conceptualisations and teaching practices. The article discusses educational implications under this account of CT, provides suggestions informed by learning theories, and presents a learning model for CT education.
An innovative, entry-level informatics course enables students to ponder CS problems in different ways, from different perspectives. Find the full text at ACM for dowload: https://dl.acm.org/citation.cfm?id=3342113.3329674
The recognition of middle grades as a critical juncture in CS education has led to the widespread development of CS curricula and integration efforts. The goal of many of these interventions is to develop a set of underlying abilities that has been termed computational thinking (CT). This goal presents a key challenge for assessing student learning: we must identify assessment items associated with an emergent understanding of key cognitive abilities underlying CT that avoid specialized knowledge of specific programming languages. In this work we explore the psychometric properties of assessment items appropriate for use with middle grades (US grades 6-8; ages 11-13) students. We also investigate whether these items measure a single ability dimension. Finally, we strive to recommend a "lean" set of items that can be completed in a single 50-minute class period and have high face validity. The paper makes the following contributions: 1) adds to the literature related to the emerging construct of CT, and its relationship to the existing CTt and Bebras instruments, and 2) offers a research-based CT assessment instrument for use by both researchers and educators in the field.
The European Commission Science Hub has been promoting Computational Thinking (CT) as an important 21st century skill or competence. However, "despite the high interest in developing computational thinking among schoolchildren and the large public and private investment in CT initiatives, there are a number of issues and challenges for the integration of CT in the school curricula". On the other hand, the Digital Competence (DC) Framework 2.0 (DigCom) is promoted in the same European Commission Science Hub portal. It shows that both topics have many things in common. Thus, there is the need of research on the relationship between CT and digital competence.
The goal of this paper is to analyse and discuss the relationship between DC and CT, and to help educators as well as educational policy makers to make informed decisions about how CT and DC can be included in their local institutions. We begin by defining DC and CT and then discuss the current state of both phenomena in education in multiple countries in Europe. By analysing official documents, we try to find the underlying commonness in both DC and CT, and discover all possible connections between them. Possible interconnections between the component groups of approaches are presented in Fig.
The development of students’ higher order learning is a critical component of education. For decades, educators and scientists have engaged in an ongoing debate about whether higher order learning can only be enhanced by building a base of factual knowledge (analogous to Bloom’s taxonomy) or whether higher order learning can be enhanced directly by engaging in complex questioning and materials. The relationship between fact learning and higher order learning is often speculated, but empirically unknown. In this study, middle school students and college students engaged in retrieval practice with fact questions, higher order questions, or a mix of question types to examine the optimal type of retrieval practice for enhancing higher order learning. In laboratory and K-12 settings, retrieval practice consistently increased delayed test performance, compared with rereading or no quizzes. Critically, higher order and mixed quizzes improved higher order test performance, but fact quizzes did not. Contrary to popular intuition about higher order learning and Bloom’s taxonomy, building a foundation of knowledge via fact-based retrieval practice may be less potent than engaging in higher order retrieval practice, a key finding for future research and classroom application.
The purpose of this study is to identify whether computational thinking skills among secondary school students differ depending on the type of digital games they play. The participants of this study were 202 secondary school students at 5 th , 6 th , 7 th and 8 th grades during 2016-2017 academic year. Correlational survey method was used during this study. Furthermore, there were three different data collection instruments used. The first one was "Personal Information Form". The second one was "Computational Thinking Skills Scale" and the third data collection instrument was "Questionnaire for Type of Games Played with Digital Tools". Results indicated that students scored higher compared to other sub-scales while their scores from the critical thinking sub-scale was the lowest. The most frequently played game category of the students was found to be dress up/make-up games.
Multiple-choice testing is considered one of the most effective and enduring forms of educational assessment that remains in practice today. This study presents a comprehensive review of the literature on multiple-choice testing in education focused, specifically, on the development, analysis, and use of the incorrect options, which are also called the distractors. Despite a vast body of literature on multiple-choice testing, the task of creating distractors has received much less attention. In this study, we provide an overview of what is known about developing distractors for multiple-choice items and evaluating their quality. Next, we synthesize the existing guidelines on how to use distractors and summarize earlier research on the optimal number of distractors and the optimal ordering of distractors. Finally, we use this comprehensive review to provide the most up-to-date recommendations regarding distractor development, analysis, and use, and in the process, we highlight important areas where furt
The continued call for twenty-first century skills renders computational thinking a topical subject of study, as it is increasingly recognized as a fundamental competency for the contemporary world. Yet its relationship to academic performance is poorly understood. In this paper, we explore the association between computational thinking and academic performance. We test a structural model—employing a partial least squares approach—to assess the relationship between computational thinking skills and academic performance. Surprisingly, we find no association between computational thinking skills and academic performance (except for a link between cooperativity and academic performance). These results are discussed respecting curricular mandated instruction in higher-order thinking skills and the importance of curricular alignment between instructional objectives and evaluation approaches for successfully teaching and learning twenty-first-century skills.
Game-based learning using interactive environments to impart theoretical and applied knowledge for introductory programming courses is divided in two popular approaches: " game making " and " game playing ". Various studies have been conducted following greatly the former approach in secondary and tertiary education with controversial results. However, there has been relatively little research shown about how game playing can be associated with the development of computational thinking and how fundamental programming concepts can be supported by playing games. This work investigates how a simulation game should be designed to support the development of computational problem-solving strategies through the medium of learning fundamental computer science concepts, by proposing a theoretical game playing framework.
https://doi.org/10.1145/3012430.3012496
Computational thinking (CT) is being considered as a key set of problem-solving skills to be acquired by the new generations of digital citizens and workers in order to thrive in a computer-based world. However, from a psychometric point of view, CT is still a poorly defined psychological construct: there is no full consensus on a formal definition of CT or how to measure it; and its correlations with other psychological constructs, whether cognitive or non-cognitive, have not been completely established. In response to the latter, this paper aims to study specifically the correlations between CT and the several dimensions from the ‘Big Five’ model of human personality: Conscientiousness, Openness to Experience, Extraversion, Agreeableness, and Neuroticism. To do so, the Computational Thinking Test (CTt) and the Big Five Questionnaire-Children version (BFQ-C) are administered on a sample (n = 99) of Spanish students from 5th to 10th grade. Results show statistically significant correlations between CT and: Openness to Experience (r = 0.41), Extraversion (r = 0.30), and Conscientiousness (r = 0.27). These results are partially consistent with the literature about the links between cognitive and personality variables, and corroborate the existence of a non-cognitive side of CT. Hence, educational interventions aimed at fostering CT should take into account these non-cognitive issues in order to be comprehensive and successful.
Many economics students believe that multiple‐choice (MC) exams are easier than constructed‐response (CR) exams. If true understanding of economics is reflected by performance on CR exams, then easier MC exams would give rise to misleading measures of student understanding of economics, creating a false sense of complacency among both instructors and students. This article investigates this issue by comparing student scores on MC and “equivalent” CR questions. Our results show that, for certain types of MC questions, students do indeed score better, even after correcting for guessing, and on other types of questions, they produce similar scores. These results are unaffected by comparing males versus females or “good” versus “poor” students.
Since test items are the building blocks of any test, learning how to develop and validate test items has always been critical to the teaching-learning process. As they grow in importance and use, testing programs increasingly supplement the use of selected-response (multiple-choice) items with constructed-response formats. This trend is expected to continue. As a result, a new item writing book is needed, one that provides comprehensive coverage of both types of items and of the validity theory underlying them. This book is an outgrowth of the author's previous book, Developing and Validating Multiple-Choice Test Items, 3e (Haladyna, 2004). That book achieved distinction as the leading source of guidance on creating and validating selected-response test items. Like its predecessor, the content of this new book is based on both an extensive review of the literature and on its author's long experience in the testing field. It is very timely in this era of burgeoning testing programs, especially when these items are delivered in a computer-based environment. Key features include. Comprehensive and Flexible -No other book so thoroughly covers the field of test item development and its various applications. Focus on Validity -Validity, the most important consideration in testing, is stressed throughout and is based on the Standards for Educational and Psychological Testing, currently under revision by AERA, APA, and NCME. Illustrative Examples -The book presents various selected and constructed response formats and uses many examples to illustrate correct and incorrect ways of writing items. Strategies for training item writers and developing large numbers of items using algorithms and other item-generating methods are also presented. Based on Theory and Research -A comprehensive review and synthesis of existing research runs throughout the book and complements the expertise of its authors.
It has been more than a decade since Jeanette Wing's (2006) influential article about computational thinking (CT) proposed CT to be a “fundamental skill for everyone” (p. 33) and that needs to be added to every child's knowledge and skill set like reading, writing and arithmetic. Wing suggested that CT is a universal skill, and not only for computer scientists. This call resonated with many educators leading to various initiatives by the International Society for Teacher in Education (ISTE) and Computer Science Teachers Association (CSTA) provided the groundwork to integrate CT into the K-12 curriculum. While CT is not a new concept and has been taught in computer science departments for decades, Wing's call created a shift towards educational computing and the need for integrating it into curriculum for all. Since 2006, many scholars have conducted empirical or qualitative research to study the what, how and why of CT. This chapter reviews the most current literature and identifies general research patterns, themes and directions for the future. The purpose of the chapter is to emphasize future research needs by cumulatively looking at what has been done to date in computational thinking research. Consequently, the conclusion and discussion section of the paper presents a research agenda for future.
Considering what we know about computational thinking, how much of this cognitive domain hangs on one's ability to think spatially? Is spatial thinking a hidden foundational property for developing strong computational thinking skills? If coding is the new literacy for 21st century thinking, educators must diversify their methodology of instruction. Mathematics must not be the only pathway to computational thinking, computer science, and coding. This book chapter opens up new insight into spatial reasoning, showing it as a new viable method to give students the computational thinking skills necessary to thrive in STEM fields. Finally, this chapter presents concepts found in shape grammars as a methodology used to teach students how to approach art and design computationally. With shape, grammars we find computational thinking at the center of creative activities.
The purpose of this study is to analyze the effects of flipped learning on students' academic achievements in the subject of science at Bilim Innovation Lyceums (BIL) in Kazakhstan. For this purpose, pre and post surveys were conducted on 168 students who were divided into two groups; the experimental group consisting of 84 students who took part in flipped learning classes for seven weeks and the control group consisting of 84 students who experienced the traditional method of classroom instruction at the same period. To achieve the objectives of the study, a final placement test score was used before and after the introduction of the flipped classroom model. The results of the study are summarized as follows. There were a significant difference between the two groups in terms of academic achievement when it measured by test scores before and after the concerned semester. On the basis of these findings, several suggestions were made for the schools to utilize innovative instructional methods including flipped learning for sustainable education in the future.
This study explored the ways that the Computational Thinking (CT) process can be evaluated in a classroom environment. Thirty Children aged 10–11 years, from a primary school in London took part in a game-making project using the Scratch and Alice 2.4 applications for eight months. For the focus of this specific paper, data from participant observations, informal conversations, problem-solving sheets, semi-structured interviews and children's completed games were used to make sense of elements of the computational thinking process and approaches to evaluate these elements in a computer game design context. The discussions around what CT consists, highlighted the complex structure of computational thinking and the interaction between the elements of artificial intelligence (AI), computer, cognitive, learning and psychological sciences. This also emphasised the role of metacognition in the Computational Thinking process. These arguments illustrated that it is not possible to evaluate Computational Thinking using only programming constructs, as CT process provides opportunities for developing many other skills and concepts. Therefore a multiple evaluation approach should be adopted to illustrate the full learning scope of the Computational Thinking Process. Using the support of literature review and the findings of the data analysis I proposed a multiple approach evaluation model where ‘computational concepts’, ‘metacognitive practices’, and ‘learning behaviours’ were discussed as the main elements of the CT process. Additionally, in order to investigate these dimensions within a game-making context, computer game design was also included in this evaluation model.
Computational Thinking represents a terminology that embraces the complex set of reasoning processes that are held for problem stating and solving through a computational tool. The ability of systematizing problems and solve them by these means is currently being considered a skill to be developed by all students, together with Language, Mathematics and Sciences. Considering that Computer Science has many of its roots on Mathematics, it is reasonable to ponder if and how Mathematics learning can be influenced by offering activities related to Computational Thinking to students. In this sense, this article presents a Systematic Literature Review on reported evidences of Mathematics learning in activities aimed at developing Computational Thinking skills. Forty-two articles which presented didactic activities together with an experimental design to evaluate learning outcomes published from 2006 to 2017 were analyzed. The majority of identified activities used a software tool or hardware device for their development. In these papers, a wide variety of mathematical topics has been being developed, with some emphasis on Planar Geometry and Algebra. Conversion of models and solutions between different semiotic representations is a high level cognitive skill that is most frequently associated to educational outcomes. This review indicated that more recent articles present a higher level of rigor in methodological procedures to assess learning effects. However, joint analysis of evidences from more than one data source is still not frequently used as a validation procedure.
Computational thinking – the ability to solve problems using concepts from computer science – has been widely discussed in the computer science education field. However, the relationship of computational thinking to intelligence – seen as the general ability to understand and solve complex problems – is contestable and has not been extensively explored. The present study addressed the question of how computational thinking is related to intelligence. To find an answer to this question, 71 pre-service teacher students completed a survey with 20 Bebras tasks as a measure of computational thinking and a non-verbal intelligence test (TONI-3) to assess their general problem-solving ability. The large and significant correlation of r(70) = .53, p
This important text synthesizes the state of knowledge related to thinking and technology and provides strategies for helping young people cultivate thinking skills required to navigate the new digital landscape. The rise of technology has resulted in new ways of searching and communicating information among youth, often creating information “overload”. We do not know how the new technologies will affect the ways young people learn and think. There are plenty of warnings about the dangers of information technology, but there is also enormous potential for technology to aid human thinking, which this book explores from an open-minded perspective.
Coverage Includes:
- An up to date review of the literature on thinking skills in general, and in relation to technology.
- Practical guidelines for thinking with technology.
- A scholarly review of the characteristics of the digital generation.
- A discussion of the various steps involved in the thinking process.
- A historical context of the Information Age and the transition from oral history, to printing press, to the Internet.
Thinking Skills for the Digital Generation: The Development of Thinking and Learning in the Age of Information is an invaluable reference for educators and research professionals particularly interested in educational technology, and improving thinking and problem-solving skills.
Computational thinking (CT) is being consolidated as a key set of problem-solving skills that must be developed by the students to excel in our software-driven society. However, in psychological terms, CT is still a poorly defined construct, given that its nomological network has not been established yet. In a previous paper, we started to address this issue studying the correlations between CT and some fundamental cognitive variables, such as primary mental abilities and problem-solving ability. The current work deepens in the same direction as it aims to extend the nomological network of CT with non-cognitive factors, through the study of the correlations between CT, self-efficacy and the several dimensions from the ‘Big Five’ model of human personality: Openness to Experience, Conscientiousness, Extraversion, Agreeableness, and Neuroticism. To do so, the Computational Thinking Test (CTt) and some additional self-efficacy items are administered on a sample of 1251 Spanish students from 5th to 10th grade (N = 1251), and the Big Five Questionnaire-Children version (BFQ-C) is also taken by a subsample from the above (n = 99). Results show statistically significant correlations between CT and self-efficacy perception relative to CT performance (rs = 0.41), in which gender differences in favor of males are found (d = 0.42). Moreover, results show statistically significant correlations between CT and: Openness to Experience (r = 0.41), Extraversion (r = 0.30), and Conscientiousness (r = 0.27). These findings are consistent with the existing literature except for the unexpected correlation between CT and the Extraversion factor of personality, which is consequently discussed in detail. Overall, our findings corroborate the existence of a non-cognitive side of CT that should be taken into account by educational policies and interventions aimed at fostering CT. As a final contribution, the extended nomological network of CT integrating cognitive and non-cognitive variables is depicted.
The aim of this study is to determine how much various variables explain students' computational thinking (CT) skills. Furthermore, it was aimed to produce a model that explains and predicts the relations between computational thinking skills and various variables. Study group consists of 156 students who were studying in 5e12. Class in 2015 e2016 academic year in different schools in Ankara. Relational screening model was used in this research. Two different data collection instruments were used in this research. The first one is “Personal Information Form”. The second one is “Computational Thinking Skills Scale”. Structural Equation Model was used in data analysis so as to produce a model that explains and predicts the relations between computational thinking skills and various variables. According to research results, it was found that computational thinking skill was highly predicted by variables, respectively; “thinking styles, academic success in mathematic class, attitude against mathematic class”.
Most research in primary and secondary computing education has focused on understanding learners within formal classroom communities, leaving aside the growing number of promising informal online programming communities where young users contribute, comment, and collaborate on programs to facilitate learning. In this article, we examined trends in computational participation in Scratch, an online community with over 1 million registered youth designers. Drawing on a random sample of 5,004 youth programmers and their activities over 3 months in early 2012, we examined programming concepts used in projects in relation to level of participation, gender, and length of membership of Scratch programmers. Latent class analysis results identified the same four groups of programmers in each month based on the usage of different programming concepts and showed how membership in these groups shifted in different ways across time. Strikingly, the largest group of project creators (named Loops) used the simplest and fewest programming concepts. Further, this group was the most stable in membership and was disproportionately female. In contrast, the more complex programming groups (named Variables, Low Booleans, and High Booleans) showed much movement across time. Further, the Low Booleans and High Booleans groups, the only groups to use “and,” “or,” and “not” statements in their programs, were disproportionately male. In the discussion, we address the challenges of analyzing young learners’ programming in informal online communities and opportunities for designing more equitable computational participation.
Addressing unresolved questions concerning computational thinking.
One of the major hurdles toward automatic semantic understanding of computer programs is the lack of knowledge about what constitutes functional equivalence of code segments. We postulate that a sound knowledgebase can be used to deductively understand code segments in a hierarchical fashion by first de-constructing a code and then reconstructing it from elementary knowledge and equivalence rules of elementary code segments. The approach can also be engineered to produce computable programs from conceptual and abstract algorithms as an inverse function. In this paper, we introduce the core idea behind the MindReader online assessment system that is able to understand a wide variety of elementary algorithms students learn in their entry level programming classes such as Java, C++ and Python. The MindReader system is able to assess student assignments and guide them how to develop correct and better code in real time without human assistance.
It is possible to define Computational Thinking briefly as having the knowledge, skill and attitudes necessary to be able to use the computers in the solution of the life problems for production purposes. In this study, a scale has been developed for the purpose of determining the levels of computational thinking skills (CTS) of the students. CTS is a five-point likert type scale and consists of 29 items that could be collected under five factors. The study group of this work consists of 726 students educated at the levels of associate degree and undergraduate degree with formal education in Amasya University for the first application. For the second application 580 students who were educated in pedagogical formation education via distance education in Amasya University. The validity and reliability of the scale have been studied by conducting exploratory factor analysis, confirmatory factor analysis, item distinctiveness analyses, internal consistency coefficients and constancy analyses. As a result of the conducted analyses, it has been concluded that the scale is a valid and reliable measurement tool that could measure the computational thinking skills of the students. In addition; the digital age individuals are expected to have the computational thinking skill, and at what degree they have these skills, the revelation of whether the levels they have are sufficient or not are a requirement. Within this frame, it could be said that the scale could make significant contributions to the literature.
Some researchers consider that the benefits of Computational Thinking (CT) in education are unclear, and therefore a quantitative study to understand the effects of CT skills in the basic levels of formal education is needed. The present study aims to analyze the effects of CT on the academic performance of students in high school. We seek to answer the following research questions: (RQ1) Can CT increase the problem-solving skills of students in high school? (RQ2) Is CT related to the performance of students in high school? (RQ3) Can CT improve the performance of students in high school? We conducted an analysis between two groups of students with similar profiles belonging to the same population, where the factor CT proficiency is the only feature that distinguishes both groups. The results show that there is a moderate correlation between the performance of evaluated students and their skills of CT developed by computer programming. In addition, we found that students proficient in computer programming have superior performance up to 10.2% in ENEM (National Exam of High School) assessment compared to those with little or no experience level and even better performance 21% in the WASI test problem-solving in students on attending high school.
Computer science is becoming ever increasingly important to our society. Computer science content has, however, not traditionally been considered a natural part of curricula for primary and secondary education. Computer science has traditionally been primarily a university level discipline and there are no widely accepted general standards for what computer science at K-12 level entails. Also, as the interest in this area is rather new, the amount of research conducted in the field is still limited. In this paper we review how 10 different countries have approached introducing computer science into their K-12 education. The countries are Australia, England, Estonia, Finland, New Zealand, Norway, Sweden, South Korea, Poland and USA. The studied countries either emphasize digital competencies together with programming or the broader subject of computer science or computing. Computational thinking is rarely mentioned explicitly, but the ideas are often included in some form. The most common model is to make computer science content compulsory in primary school and elective in secondary school. A few countries have made it compulsory in both, while some countries have only introduced it in secondary school.
Responding to a groundswell of researcher and practitioner interest in developing students' interpersonal and intrapersonal skills, we evaluated three measurement approaches for creativity and global citizenship. We designed a 10-criteria evaluative framework from seminal and cutting-edge research to compare extant self-reports and situational-judgment tests (SJTs) from each construct and to design two discrete-choice experiments (DCEs). Our evaluation detailed opportunities, challenges, and tradeoffs presented by each approach's design considerations, possibilities for bias, and validity-related issues. We found that researchers rely heavily upon self-report instruments to measure constructs, such as creative thinking and global citizenship. We found evidence that the self-report instruments evaluated were susceptible to some biases more than others. We found that SJTs and DCEs may mitigate some concerns of bias and validity present in self-report when measuring interpersonal and intrapersonal skills. We make recommendations for future development of these formats.
Computational thinking (CT) is a popular phrase that refers to a collection of computational ideas and habits of mind that people in computing disciplines acquire through their work in designing programs, software, simulations, and computations performed by machinery. Recently a computational thinking for K-12 movement has spawned initiatives across the education sector, and educational reforms are under way in many countries. However, modern CT initiatives should be well aware of the broad and deep history of computational thinking, or risk repeating already refuted claims, past mistakes, and already solved problems, or losing some of the richest and most ambitious ideas in CT. This paper presents an overview of three important historical currents from which CT has developed: evolution of computing's disciplinary ways of thinking and practicing, educational research and efforts in computing, and emergence of computational science and digitalization of society. The paper examines a number of threats to CT initiatives: lack of ambition, dogmatism, knowing versus doing, exaggerated claims, narrow views of computing, overemphasis on formulation, and lost sight of computational models.
The purpose of this study is to design a computational thinking curriculum standard for K-12 education. The Delphi technique was employed to collect different views and derive consensus from a panel of thirteen experts, including computer scientists, computer science educators, K-12 computer teachers, and industry experts. The first draft of Delphi survey questionnaire, consisting of nine themes (problem solving, problem decomposition, algorithms, data representation, data analysis, modeling and simulation, abstraction, automation, and others) and 60 competence indicators, was developed based on our investigation of the nature of computational thinking. After three rounds of survey and a final round-table discussion, the expert panel derived 49 essential competence indicators (13 for grades K to 6, nine for grades 7 to 9 and 27 of grades 10 to 12) and eight optional competence indicators (one for grades 7 to 9 and seven for grades 10 to 12). According to the results, the core ability and training of computational thinking are different in grades. In grades K to 6, students develop logical thinking and problem solving skills in personal and family life. In grades 7 to 9, students must understand the basic concepts of programming and write basic programs. Finally, in grades 10 to 12, they will use high-level skills to apply the concepts of abstraction, modeling, and structured problem decomposition to solve problems in different fields. The results serve as useful references for developing Taiwan's new K-12 computing curriculum.