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Computer Science Education, Programming, Kindergarten, Elementary Secondary Education, Masters Theses, Psychometrics, Sampling, Educational Technology, Computer Assisted Instruction, Trend Analysis, Departments, Universities, Doctoral Dissertations, Thinking Skills, Teaching Methods, Learning Processes, Information Retrieval, Research Methodology, Validity, Reliability, Foreign Countries, and Turkey

This study is designed to reveal the research trends of graduate theses published in the field of computer programming in K-12 between 2018 and 2022. Document analysis was used for data collection in this study. The data was divided into 9 categories, and the results demonstrated that the scholars in the Departments of Computer Educational and Instructional Technologies (CEIT) at Atatürk University and Ondokuz Mayis University of Türkiye mainly published master's theses in this field in 2019. Another result was that though CEIT is also the main department for doctoral theses, no difference exists in terms of years or universities. "Teaching, learning, and training programming" and "computational thinking" are the most frequently used keywords in graduate programs, respectively. While quantitative and mixed method (parallel, convergent), convenience sampling, and psychometric scales are preferred in master's theses, mixed method (explanatory, mixed), purposive sampling, interviews/focus group interviews, and psychometric scales are preferred in doctoral theses, respectively. Observation and semi-structured interview forms are used as data collection tools in the theses. Although quantitative methods are mainly utilized in data analysis, parametric and non-parametric statistical tests are also used, and content analysis is resorted to as part of qualitative methods. Whilst validity and reliability studies have been carried out measurement tools are employed in master's theses, scales have been developed in doctoral theses. The present study also offers some suggestions for future research on teaching computer programming.

Programming, Computer Science Education, Student Attitudes, Computation, Middle School Students, Instructional Effectiveness, Thinking Skills, Educational Games, Foreign Countries, Self Efficacy, Access to Computers, and Turkey

The aim of this study is to examine the effect of block-based coding education on middle school students' computational thinking skills and attitudes towards coding with Blocky example. The training phase of the implementation process was planned and implemented by subject experts in 4 weeks and 2 hours a week. In the research, both quantitative and qualitative research methods and exploratory sequential design were used as mixed methods. In this study, quantitative research method and pretest- post-test control group semi-experimental pattern model was used as the research model. The universe of the study consists of 5th grade students studying at a secondary school in Aksaray province Eskil district of Türkiye in the 2019-2020 academic year. Within the scope of the research, the research participant group was determined considering that 5th grade students will receive coding training for the first time. In addition to the total number of students to be reached is 38, including 19 control and 19 experimental groups. While the "blocky" application used in block-based coding education was determined as the independent variable in the research, the students' computational thinking skills and their attitudes towards learning to code were determined as dependent variables. As a result of the applications and analysis, the difference between the values of students' computational thinking skills self-efficacy and attitudes towards learning coding before and after education is statistically significant. In order to determine the effect size of the Blocky block-based coding environment on the Information Computational Thinking Skills Self-Efficacy Scale (CTSES) and the Attitudes Toward Learning Coding Scale (ATLCS), the eta squared value was examined. It can be said that the Blocky block-based coding environment has a "large" effect size on computational thinking skills, self-efficacy perception and on the attitude towards learning coding.

Educational Planning, Flipped Classroom, Meetings, Budgeting, Program Evaluation, Programming, Efficiency, Program Effectiveness, Educational Benefits, Higher Education, and Secondary Education

The purpose of this paper is to recognize the special features of the flipped classroom and to explore the aspects of opportunities that the flipping concept can be applied to educational planning. The essential elements of the flipping concept are identified. A brief review of the key studies on flipped classrooms at both the college and high school levels was presented. Analysis is made on the basic flipping concept as it applies to educational planning meetings. Then, the flipping concept is incorporated with the stages of the Planning, Programming, Budgeting and Evaluation System (PPBES) to perceive how the flipping concept can help with strengthening the efficiency and effectiveness of the planning system. The authors conclude by confirming the key elements of the flipping concept, "increased interaction" and "practical application," as clear benefits to the educational planning process.

Programming, Play, Young Children, Robotics, Spatial Ability, Problem Solving, Psychomotor Skills, Kindergarten, and Interpersonal Competence

We propose the results of a research that combines the educational and psychological media approach, to verify the pedagogical potential of coding and robotics in the learning processes of 4-year-old children at the cognitive and socio-relational level. The study investigated the impact of unplugged and plugged coding on the skills of spatiality, movement and problem-solving skills, storage and decoding of progressively more complex indications, and single-group interaction of 51 children and three kindergartens using storytelling and the educational robot Cubetto. The work is based on the research carried out by Lee (2020) on the inclusion of coding in early childhood, the theoretical references of Wing (2010) about computational thinking and the theoretical frameworks proposed by Bers (2020) regarding coding as a playful dimension. The data collected through the quantitative and qualitative tools of a pre- and post-intervention questionnaire to educators and a checklist of observations on children recorded the following: (1) an increase in children's space, motor and information-storage/decoding skills; (2) a change in children's collaborative skills when comparing the results of the plugged and unplugged coding workshops; and (3) the impact of coding to increase children's performance skills through narrative dimension and play.

Graduate Students, Foreign Countries, Programming, Models, Land Use, Ecology, Systems Approach, Research Projects, and Germany

Agent-based modeling is a promising tool for familiarizing students with complex systems as well as programming skills. Human-environment systems, for instance, entail complex interdependencies that need to be considered when modeling these systems. This complexity is often neglected in teaching modeling approaches. For a heterogeneous group of master's students at a German university, we pre-built an agent-based model. In class, this was used to teach modeling impacts of land use policies and markets on ecosystem services. As part of the course, the students had to perform small research projects with the model in groups of two. This study aims to evaluate how well students could deal with the complexity involved in the model based on their group work outcomes. Chosen indicators were, e.g., the appropriateness of their research goals, the suitability of the methods applied, and how well they acknowledged the limitations. Our study results revealed that teaching complex systems does not need to be done with too simplistic models. Most students, even with little background in modeling and programming, were able to deal with the complex model setup, conduct small research projects, and have a thoughtful discussion on the limitations involved. With adequate theoretical input during lectures, we recommend using models that do not hide the complexity of the systems but foster a realistic simplification of the interactions.

Programming, Academic Achievement, Logical Thinking, Thinking Skills, Learning Motivation, College Students, Programming Languages, and Instructional Effectiveness

Background: Studies on the effectiveness of block-based environments continue to produce inconsistent results. A strong reason for this is that most studies compare environments that are not equivalent to each other or to the level of learners. Moreover, studies that present evidence of the effectiveness of block-based environments by comparing equivalent environments are limited. Objectives: This study aims to scrutinize the effects of programming training to be held in equivalent environments (block-based and text-based) with university students who do not have prior programming knowledge and experience on achievement, logical thinking, and motivation. Methods: The study was conducted by using an experimental pretest-posttest control group design. The study was conducted with 60 students, the total consisting of 30 students in the experimental group and 30 students in the control group. In the experimental group, block-based visual programming training with Scratch was conducted and the control group received text-based programming training with Small Basic. The training was maintained for 10 weeks, for 4 h a week in each group. The programming achievement test, the logical thinking skills test, and the motivation scale were used to collect the data. Results and Conclusions: The results showed that the use of a block-based environment in programming training contributed positively to the development of students' logical thinking skills, and motivation for learning programming. In contrast, there was evidence that this training did not make a difference on programming success. Implications: The findings of the study provided evidence of the effectiveness of block-based training in comparisons made in equivalent environments. Focusing research on this issue may contribute to the improvement of the current understanding.

Intelligent Tutoring Systems, Coding, Programming, Skill Development, Instructional Design, Educational Technology, Mastery Learning, and STEM Education

Background: Skill integration is vital in students' mastery development and is especially prominent in developing code tracing skills which are foundational to programming, an increasingly important area in the current STEM education. However, instructional design to support skill integration in learning technologies has been limited. Objectives: The current work presents the development and empirical evaluation of instructional design targeting students' difficulties in code tracing particularly in integrating component skills in the Trace Table Tutor (T3), an intelligent tutoring system. Methods: Beyond the instructional features of active learning, step-level support, and individualized problem selection of intelligent tutoring systems (ITS), the instructional design of T3 (e.g., hints, problem types, problem selection) was optimized to target skill integration based on a domain model where integrative skills were represented as combinations of component skills. We conducted an experimental study in a university-level introductory Python programming course and obtained three findings. Results and Conclusions: First, the instructional features of the ITS technology support effective learning of code tracing, as evidenced by significant learning gains (medium-to-large effect sizes). Second, performance data supports the existence of integrative skills beyond component skills. Third, an instructional design focused on integrative skills yields learning benefits beyond a design without such focus, such as improving performance efficiency (medium-to-large effect sizes). Major Takeaways: Our work demonstrates the value of designing for skill integration in learning technologies and the effectiveness of the ITS technology for computing education, as well as provides general implications for designing learning technologies to foster robust learning.

Elementary School Students, Secondary School Students, Robotics, Programming, Programming Languages, Skill Development, Instructional Effectiveness, Instructional Design, Academic Ability, Mathematics Activities, Kindergarten, and Young Children

Background: As one of the mainstream forms of programming education, educational robotics (ER) have been a crucial way to develop K-12 students' programming ability. Objectives: The purpose of this study is to clarify the content of programming ability, to verify the effectiveness of ER as a teaching method to improve students' programming abilities and the conditions for more effective instructional design. Methods: The method of meta-analysis was adopted to conduct this study. 4180 K-12 students from 36 studies with a total of 85 effect sizes were captured. Based on the contents of included literature, an ER programming ability model was put forward, which was composed of essential ability and generative ability. The meta-analysis of essential ability (N = 22) and generative ability (N = 64) was carried out respectively. Results and conclusion: The results showed that ER activity has a positive effect on the essential ability (Hedges' g = 0.539 CI [0.327, 0.752], p < 0.001) and generative ability (Hedges' g = 0.535 CI [0.426, 0.643], p < 0.001). Additionally, the results of moderator analysis showed that utilizing ER to solve mathematics problems is able to more effectively develop students' essential ability, while the STEM interdisciplinary ER instruction had the largest effect on generative ability. Simultaneously, the individual programming form is conducive to students' essential ability, while the generative ability is significantly affected by the cooperative programming form. No matter for the evaluation of essential ability or generative ability, ER had the greatest effect on kindergarten children' programming ability. Moreover, the intervention duration ranging from 1 to 5 weeks, the samples size less than 50 and the choice of measurement scale can effectively improve students' programming ability. Implications: This research enriched the theoretical basis of programming ability, and provided reference and guidance for K-12 programming teaching practitioners and researchers in ER teaching design and practise.

Learning Strategies, Programming, Computer Science Education, Metacognition, Online Courses, Learning Processes, Introductory Courses, Correlation, In Person Learning, Student Attitudes, Undergraduate Students, Help Seeking, and Teaching Methods

The autonomy and flexibility that online learning contents provide students in a traditional face-to-face course require them to pick up newer strategies for regulating their learning process. This study focuses on identifying how students' self-reported traits of self-regulated learning may relate to the task value of the learning contents of an introductory programming course. This study explores the distribution of self-regulated learning and task value components reported by students. A moderately positive correlation is seen between the task value and perceived self-regulated learning traits of students. The findings of this study demonstrate how some of the online learning components and facilitation methods that students value the most could be incorporated into a traditional face-to-face course to promote self-regulated learning skills.

Summer Programs, Programming, Camps, Active Learning, Student Projects, Informal Education, Computer Science Education, Rural Areas, Student Motivation, Student Interests, Middle School Students, and Washington

Current research has not fully explored how summer programming camps can help students increase motivation and interest to pursue computing career, and their programming knowledge. Informal CS education through summer programming camps provides K-12 students the opportunity to learn how to code through fun and interactive activities outside of their typical classroom experiences. In this study, we examined the effectiveness of a weeklong summer programming camp for promoting students' motivation and interest in programming, and their programming knowledge. Participants were 19 middle school students from rural Washington. Students participated in a project-based learning approach through game development in Python. Using a within-subjects design, we analyzed students' pre and post motivation and knowledge assessment scores. Results from the analysis indicated a significant improvement in post-test programming knowledge scores (d = 0.93). The findings also indicated that students were able to achieve basic abstraction and algorithmic thinking but not code analysis and debugging skills. On their motivation to pursue computing careers, the results did not show any difference before and after the camp due to their prior existing interest in attending the camp.

Information Systems, Educational Quality, Computer Software, Visual Aids, Programming, Models, Program Evaluation, Program Costs, Audits (Verification), Resource Allocation, Information Management, Accreditation (Institutions), Benchmarking, and Evaluation Criteria

The study develops a method for monitoring and management of the quality of educational programs using software instruments. The method describes each of the monitoring implementation stages in detail specifying the input and output data, as well as the controls that affect the time and quality of the implementation of the corresponding stage. Algorithm programs in the form of flowcharts reflecting all the content aspects are developed and formalized for the automatization of monitoring. The presented algorithm models allow implementing the program complex of the system for monitoring and management of the quality of educational programs using the modern object-oriented design and programming environments. The goal of the study is to develop a model of algorithms for the organization of monitoring and managing the quality of educational programs, which allow reducing the time costs of these processes while increasing the objectivity of quality assessment. The obtained results are intended for the audit of educational services, public control over the implementation of educational activities, accreditation of directions of training, or licensing of educational organizations. The developed algorithms provide for evaluating the content of each stage of the audit of an educational program, generate a list of notes ranked by importance, and ensure the rational allocation of resources for the implementation of each stage of the educational process.

Programming, Foreign Countries, Computer Science, Peer Teaching, Adult Students, Postsecondary Education, Communities of Practice, Young Adults, Program Evaluation, and Ireland

Access Foundation Programmes are a widening-participation initiative designed to encourage engagement in higher education among underrepresented groups, including those with socioeconomic and educational disadvantage. In particular, mature students enrolled in these programmes experience greater difficulties making the transition to tertiary education, especially when they opt to study disciplines traditionally considered difficult. Computer programming is perceived as a traditionally difficult subject with typically lower pass rates and progression rates than other subjects. This paper describes the first of a three-cycle action research study examining the perceived effects of a structured Peer Assisted Learning (PAL) Programme for mature students enrolled in a computer science programming module for an Access Foundation Programme in an Irish University. The focus of this qualitative study was to evaluate the perceived effect of a PAL programme on learning and whether it offered a positive learning support structure. Findings from our study suggest that PAL programmes have an overall positive effect on subject comprehension as well as enhanced learner confidence for mature Access Foundation students. Furthermore, PAL sessions offered students a support structure that helped with their transition and acculturation to tertiary education. This study also highlights the importance the PAL leader's role has on the perceived effectiveness of the PAL sessions as well as the impact of the students' shared history on the near-peer bond. The study concludes that the implementation of PAL programmes for Access Foundation Programmes has the potential to offer mature students a supportive learning environment and to improve their learning experience.

Programming, Time Management, Computer Science Education, Integrated Learning Systems, Distance Education, COVID-19, Pandemics, Learning Analytics, Introductory Courses, Undergraduate Students, Online Courses, Learning Activities, Assignments, Learner Engagement, Educational Change, Comparative Analysis, Student Attitudes, Tests, Foreign Countries, and Turkey

Time management is an important self-regulation strategy that can improve student learning and lead to higher performance. Students who can manage their time effectively are more likely to exhibit consistent engagement in learning activities and to complete course assignments in a timely manner. Well planning of the study time is an essential part of online learning and has been particularly critical in remote education during the COVID-19 pandemic. During this period of crisis, programming courses have been exceptionally challenging since students needed to devote sufficient time in the practice of code-writing besides studying the theoretical foundations, while, at the same time, working on the learning tasks for other online courses. Therefore, students' time management skills have been a determining factor in how they engaged in programming courses during the emergency remote education. In this regard, this study explores the association between students' time management skills and their course engagement (extracted from the LMS log data) in an undergraduate-level programming course taught fully online during the pandemic. Results show varying levels of participation and different temporal patterns of engagement depending on the students' ability to manage their time. Additionally, students with strong time management skills performed slightly better than those with poor time management skills. Implications for future research and practice are shared.

Computer Simulation, Animation, Educational Technology, Technology Uses in Education, Student Motivation, Academic Achievement, Student Attitudes, High School Students, Programming, Foreign Countries, Correlation, Tests, Scores, Student Interests, and Turkey

This study examines the effect of using animation-based worked examples (ARAWEs) that are prepared using Augmented Reality (AR) technology instead of using traditional paper-based worked examples (TWEs) on the achievement, motivation, and attitude of high school students during their programming education. The research was designed through the "Nonequivalent Control Group Model", one of the quasiexperimental models. The participants consisted of second year students (N=94) who were taking the "Basics of Programming" course in the Department of Information Technologies a vocational and technical Anatolian high school in Turkey. An achievement test was applied to the participants as pre-test and final test. Motivation of the students was measured by means of the "Instructional Materials Motivation Survey" developed by Kutu and Sözbilir (2011), and participant attitudes towards using AR was measured by means of the "AR Attitude Scale" developed by Küçük, Yilmaz, Baydas and Göktas (2014). According to the results, both the achievement and motivation levels of the students studying on ARAWEs increased significantly compared to those studying on TWEs. There was a high level of correlation between the final test scores and the attitude levels of the students studying on ARAWEs. Considering that instructional materials containing animation-based worked examples prepared using AR technology increase students' interest and motivation in the subject, their use in lessons that include teaching problem solving skills, such as mathematics, physics, and chemistry, can be implemented in future studies.

Problem Solving, Preschool Children, Computer Science Education, Programming, Learning Activities, and Student Experience

This study aims to explore the influences of the CS-unplugged activities in developing problem solving skills of preschool children. The participants were 11 children (4-5 aged) enrolled in a public preschool and Code.org activities were used as an instructional package. Activity evaluation form and interviews were used to understand children's problem solving processes. In order to determine the problem solving performances, the tasks were divided into the meaningful sub-tasks with regard to problem steps of Nance' problem solving model. The results indicated that CS-unplugged activities positively influenced students' understanding and planning performances more than doing and evaluation skills. Preschool children developmental characteristics and the nature of the problems somewhat hampered the development of their performances in doing and evaluation steps. It is hoped that the study may provide insights for the efforts on enhancing preschool children's problem solving processes.

Difficulty Level, Computation, Thinking Skills, Programming, Undergraduate Students, Computer Science Education, and Electronic Learning

To help novice learners overcome the obstacles of learning computational thinking (CT) through programming, it is vital to identify difficult CT components. This study aimed to determine the computational concepts and practices that learners may have difficulties acquiring and discuss how programming instructions should be designed to facilitate learning CT in online learning environments. Participants included 92 undergraduate students enrolled in an online course. Data were collected from a CT knowledge test and coding journals. Results revealed that four computational concepts (i.e., parallelism, conditionals, data, and operators) and two computational practices (i.e., testing and debugging and abstracting and modularizing) were identified as CT components that were difficult to learn. The findings of this study imply that CT instructions should offer additional instructional supports to enhance the mastery of difficult computational concepts and practices. Further research is necessary to investigate instructional approaches to successful CT learning.

Anxiety, Undergraduate Students, Student Attitudes, Factor Analysis, Programming, Measures (Individuals), Factor Structure, Reliability, Validity, Correlation, Psychometrics, Self Esteem, Comparative Analysis, Foreign Countries, Item Analysis, Computer Science Education, and Turkey

The main goal of the current study is to develop a reliable instrument to measure programming anxiety in university students. A pool of 33 items based on extensive literature review and experts' opinions were created by researchers. The draft scale comprised three factors applied to 392 university students from two different universities in Turkey for exploratory factor analysis. The number and character of the underlying components in the scale were determined using exploratory factor analysis. After exploratory factor analysis, confirmatory factor analysis was conducted on the draft scale using a sample of 295 university students. Confirmatory factor analysis was carried out to ensure that the data fit the retrieved factor structure. The internal consistency coefficient (Cronbach's alpha) was calculated for the full scale and each dimension for reliability analysis. For convergent validity, the factor loading of the indicator, the average variance extracted, composite reliability, and maximum share variance values were calculated. Additionally, convergent validity was tested through (1) comparison of mean values of factors and total programming anxiety depending on gender and (2) correlation analysis of factors, total programming anxiety, and course grade of students. The Fornell & Larcker criterion and the Heterotrait-Monotrait correlation ratio were utilized to assess discriminant validity. According to analysis results, the Programing Anxiety Scale (PAS) comprised 11 items in two factors: classmates and self-confidence. Similarly, results revealed that The PAS has good psychometric properties and can be used to assess the programming anxiety of university students.

Coding, Programming, Program Length, Student Satisfaction, Computer Science Education, Student Attitudes, Web Sites, and Opinions

This study aims to shed light on what students like and dislike in coding bootcamps. A qualitative content analysis of student reviews for coding bootcamps was conducted, resulting in a research model and survey instrument consisting of fourteen factors that are proposed to affect coding bootcamp satisfaction. The proposed satisfaction factors include quality of instructors, value of mentors, availability of TAs, access to support staff, provision of career services, rigor of curriculum, appropriateness of pedagogy, development of peer connections, conduciveness of atmosphere, use of appropriate technology, affordability, openness of communication, quality of prep course, and level of post-bootcamp support. Each of the proposed satisfaction factors is measured with three to ten Likert-style variables. The proposed research model and survey instrument can be used by administrators and educators in coding bootcamps and traditional universities alike to better understand and ultimately improve student satisfaction in computing education.

Teaching Methods, Introductory Courses, Computer Science Education, Assignments, Programming, Learning Motivation, Scaffolding (Teaching Technique), Achievement Gains, Instructional Effectiveness, Natural Language Processing, Student Attitudes, Study Habits, Computer Software, Intelligent Tutoring Systems, Tests, Scores, Cognitive Ability, and Undergraduate Students

Learning computer programming is a challenging task for most beginners. Demotivation and learned helplessness are pretty common. A novel instructional technique that leverages the value-expectancy motivational model of student learning was conceptualized by the author to counter the lack of motivation in the introductory class. The result was a frequency adherent scaffolded instructional technique called An Assignment A Day (AAAD). Instead of writing an assignment and a lab for each module/chapter, students were asked to complete one assignment a day, not exceeding four assignments a week. The assignments were incrementally difficult and had to be done almost every day. With the application of AAAD for two consecutive semesters, there was a meaningful improvement in the final grades. This technique, though initially encouraging, created a significant load on the instructor in terms of assignments graded and questions answered every day. A natural language processing (NLP) based conversational agent was designed and integrated with AAAD to counter this overload. The idea was simple -- relay commonly asked course questions to an NLP based chatbot and let the instructor handle the complex queries. This integrated system was named Conversational Agent Supported Scaffolded Approach (CASSA). The main contribution of this work is the construction of a conversational agent and its integration with AAAD. The conversational agent is currently being assessed for overall efficacy, though preliminary results are discussed. The vision is to create a generic virtual assistant template that can be re-used across multiple courses to assist instructors.

Skills, Achievement Gap, Employment Qualifications, Information Technology, Career Readiness, Education Work Relationship, Employer Attitudes, Expectation, Job Skills, College Graduates, Computer Security, Computer Software, Programming, Computer Networks, Technological Advancement, and Knowledge Level

Information Technology (IT) skills gap discourse suggests a mismatch between what students are acquiring in terms of knowledge and skills in their education versus what employers believe are useful skills for doing day to day tasks. This study builds upon previous research (analyzing the skills of college students in IT-related majors) by surveying industry professionals to determine the skills their organization requires and offering suggestions that can benefit the educational institutions and create a better educated workforce. Implications are drawn and a conclusion is presented.