Daisuke Saito

Although programming is part of primary school curricula in many countries, barriers persist for elementary students learning programming such as an insufficient understanding of the underlying mathematics, complex concepts, and purpose of programming. These challenges often lead to disinterest. Herein we present an innovative game-design-based programming education tool. Students progressively enhance a classic game, Puyo Puyo, using fundamental programming concepts and selecting the appropriate code. This engaging approach improves students' computational thinking abilities as they transform code into a functional game. Here, we describe the tool's background and structure. Then we detail a workshop using the tool, including analyzing the changes in students' programming skills, computational thinking, and interest in programming. Finally, we summarize the findings and future research directions.

Visual programming languages are popular because they can be learned at an early age. Unlike text-based languages, they do not require linguistic knowledge. Visual programming languages are diverse and include block programming, flow programming, AR-based programming, and robot-based programming. Scratch and Viscuit are common visual programming tools. Because effective learning methods for these languages have yet to be clarified, we proposed a method and evaluated its learning effectiveness using Chuggington Programming, which is a visual programming game application. Although the questionnaire responses for five workshops at educational institutions were positive, quiz results for one- to two-hour workshops did not show significant differences based on Wilcoxon's signed rank test. Herein we focus on complexity in visual programming to assess the feasibility of a new evaluation method similar to a text-based evaluation method using turtle graphics. We compare traditional text-based evaluation methods such as Cyclomatic Complexity, Halstead Complexity, etc. with turtle graphics. Then we examine the relationship between data for student performance in the workshop and the complexity level. The solution time and complexity are positively correlated, while the percentage of correct responses and complexity are negatively correlated, validating the complexity has potential as an effective learning measure.

This study explores the potential application of program complexity as a tool for assessing children’s logical thinking abilities within the context of programming education. We conducted a programming workshop for children and assessed their logical thinking capabilities. The correlation between their test results and the complexity of the programs they developed during the workshop was examined. Results suggest that program complexity is a viable indicator for assessing logical thinking skills in children.

The Computer Science industry suffers from a vivid gender gap. To understand this gap, Computational Thinking skills in Computer Science education are analyzed by binary gender roles using block-based programming languages such as Scratch since they are intuitive for beginners. Platforms such as Dr. Scratch, aid learners in improving their coding skills by earning a Computational Thinking score while supporting effective assessments of students' projects and fostering basic computer programming. Although previous studies have examined gender differences using Scratch programs, few have analyzed the Scratch project type's impact on the evaluation process when comparing genders. Herein, the influence of project type is analyzed using instances of 124 (62 male, 62 female) projects on the Scratch website. Initially, projects were categorized based on the user's gender and project type. Hypothetical testing of each case shows that the scoring system has a bias based on the project type. As gender differences appear by project type, the project type may significantly affect the gender gap in Computational Thinking scores. This study demonstrates the importance of incorporating the project type's effect into the Scratch projects' evaluation process when assessing gender differences.

This study investigates the Computational Thinking skill differences among novice programmers in relation to gender. Block-based visual programming languages such as Scratch particularly benefit K-12 programmers because they learn how to code intuitively. Our study analyzed 124 (62 males, 62 females) Scratch projects on the Scratch website, categorized projects on the basis of each user's gender and project type, and compared their Computational Thinking scores. The results of this study suggest that project types preferred by males require more programming construct reflected in the Computational Thinking score than that of females. Because gender differences appear by project type, project type presumably influences the gender gap in scores.

In evaluating the learning achievement of programming-thinking skills, the method of using a rubric that describes evaluation items and evaluation stages is widely employed. However, few studies have evaluated the reliability, validity, and consistency of the rubrics themselves. In this study, we introduced a statistical method for evaluating the characteristics of rubrics using the goal question metric (GQM) method. Furthermore, we proposed a method for measuring four evaluation results and characteristics obtained from rubrics developed using this statistical method. Moreover, we showed and confirmed the consistency and validity of the statistical method using the GQM method of the resulting developed rubrics. We show how to verify the consistency and validity of the rubric using the GQM method.

To guide practitioners and researchers to design and research Machine Learning (ML) system development processes, we conduct a preliminary literature review on ML system development practices. We identified seven papers and two other papers determined in an ad-hoc review. Our findings include emphasized phases in ML system developments, frequently described ML-specific practices, and tailored traditional practices.

There are many lectures for students or working adults. Educational institutions have created a table that associates educational courses with learning standards in order to understand the content of these courses. Learning standards such as SFIA (Skills Framework for an Information Age) indicate the skills that learners should learn. The mapped table can make contents clear for students or other educational institutions.

Participants’ feelings and impressions utilizing electroencephalography (EEG) and the effectiveness of code are compared for different types of programming sessions. EEG information is obtained as an alternate viewpoint during three programming sessions (solo, pair, and mob programming). MindWave Mobile 2 (brainwave detector) is equipped to collect the attention levels, meditation levels, and EEG brainwaves. These data are utilized to distinguish efficiencies, weaknesses, and points of interest by programming session. The results provide preliminary information to distinguish between the three sessions, but further studies are necessary to make firm conclusions. Additionally, alternative methods or systems are required to analyze the collected data.

Extreme programming (XP) approaches such as pair and mob programming (PP and MP, respectively) have been introduced to the educational sector. However, higher education curricula have started implementing online courses as a method for teaching programming, which poses challenges when conducting XP. Because social factors are vital to learning, we examine a project-based learning method using online MP that introduces a high level of communication. It also maintains the advantages of PP through the “driver” and “navigator” approach. However, there are multiple complications, including discomfort, slow code generation, and interpersonal issues, when using conventional MP. Accordingly, we introduce a mentoring approach to the MP setup and examine the differences compared to conventional MP sessions. We create and analyze co-occurrence networks of codes found via open coding. In this paper, we explain our method and show its advantages based on the results of our analysis.