The purpose of this paper is to explore global trends in data science education and to derive research questions related to the curriculum design of data science education in Japan.

Data science is a systematic process for obtaining knowledge from data, and it is common for the focus of data science education to be on enabling students to carry out a series of processes (e.g. the ‘basic cycle of learning from data’), but we found that the positioning of data science education in school curricula is diverse. Based on these findings, we proposed guidelines for designing data science education curricula in Japan, and presented research issues that we considered necessary to realise curricula based on these guidelines. It is expected that designing diverse data science curricula that take into account the actual situation of each school will have a positive impact on learning guidance in other subjects as well.

This paper proposes a new educational model for data science, following an overview of the history of statistics education and the Shiga University model of data science education. In addition, this paper summarizes some proposals on data science education methods, introducing a case study of Shiga University. As a result, these proposals will be a foothold for the construction of the theory and practice of data science education in the future.

This study aimed to clarify the actual conditions of university students regarding the statistical inquiry process. To achieve this, we developed a survey and questionnaire focusing on the PPDAC cycle of the statistical inquiry process. We then conducted the survey with university students. The results suggested that university students found it difficult to answer questions related to “Information Ethics” and “Data Collection” correctly. However, questions related to “Plan,” such as selecting and grouping variables, were relatively easier for the university students in this study to answer correctly. Additionally, it was suggested that university students generally have little experience with the statistical inquiry process and a low perception of being proficient in it. Furthermore, the results of the correlation analysis between the comprehension survey and the questionnaire survey suggested that the correct response rate for the expression methods in the “Plan” phase was related to students’ self-perceived proficiency in representing data using statistical graphs, analyzing data using statistical methods, and interpreting graphed data.

STEAM education is being emphasized to foster students’ creativity in solving social issues and designing the future of society. “Period for Inquiry-Based Cross-Disciplinary Study” and other cross-curricular learning programs and STEAM education have been newly established in Japan. Despite the development of various evaluation methods, the lack of a universally applicable standard metric remains a pressing challenge in STEAM education. This study focused on developing a self-evaluation method for the STEAM-type inquiry-based learning program ‘UTokyoGSC-Next’ for high-school students, with the aim of establishing an effective evaluation method for inquiry-based learning. To evaluate the five competencies this program aimed for, we conducted a self-evaluation questionnaire for the students who participated. As a result, the self-assessment average scores after participating were higher than before. On the other hand, the self-assessment average score of passers of second selections tended to be lower than that of non-passers. It is possible that the passers evaluated themselves more harshly. Moreover, exploratory factor analysis was conducted to verify the evaluation indicators. The factor analysis confirmed that each of the five factors was strongly related to specific question items. These findings are expected to impact the design and evaluation of STEAM education programs.

This study aims to acquire the movement trajectories of players by using people flow analysis AI, taking futsal, a goal-type ball game, as an example. Furthermore, in order to implement it in a virtual environment, we reproduced a futsal match by importing the data on the players’ movement trajectories into game development integration software. The video footage from a futsal practice session was analyzed, and a framework was established to track the movement trajectories of ten players. In cases where player detection was interrupted, newly detected numbers were linked to the corresponding players to maintain continuous tracking. As a result, we were able to assign the same number to the same player for about 90% of the detected numbers. Next, we used perspective transformation technology to reproduce a futsal match in a 3D virtual environment. As a result, the sense of distance and positional relationships between the players were generally consistent.

Demands and expectations for data science education have been increasing in recent years. Data science education requires not just acquiring knowledge and skills, but also the ability to use them to solve real-world problems. To achieve this, it is recommended that project-based learning be conducted using realistic data. In this paper we reported on a PBL-type teaching practice carried out in collaboration among three universities. The classes were structured to allow communication between students with different knowledge and experience in data science education and between students with different fields of expertise. In addition, we provided opportunities for graduate students to answer questions from undergraduate students in order to develop consulting skills within the class. By analyzing real data, the students became more interested in data science and actively engaged in problem solving. Regarding consulting, the questioner was asked to confirm the knowledge he or she lacked in solving the problem, while the respondent made an effort to explain things in a way that suited the questioner. This paper provides an overview of the classes conducted collaboratively by the three universities and discusses the effects of these collaborative classes on student learning.

Lesson plans are an externalization of lesson design. This study analyzes how pre-service teachers apply their knowledge toward their lesson plans as they revised their lesson plans for trial science lessons. Further, it examines teachers’ ability to plan suitable lessons. At the end of the semester in third year, the teachers were required to revise the lesson plans they prepared for the first trial lesson, after which a science teacher T and education researcher P analyzed what types of “teachers’ knowledge” were used and assessed teachers’ ability to plan appropriate lessons. The study identified five key points. First, when revising the lesson plans, the pre-service teachers utilized three complex teacher knowledge groups, namely, “domains A to C” frequently, especially “domain C.” Second, the higher their achievement level, the more teacher knowledge they incorporated into their lesson plan revisions. Third, pre-service teachers in high-performing groups were thought to have used and constructed their knowledge without bias. Fourth, the middle-performing group, in particular, used “Domain C” more often and examined it in relation to teaching methods and students. Fifth, the lack of bias in teachers’ knowledge areas in the lower-performing groups suggests that improvements in lesson plans needed to be made across all teachers’ knowledge areas, rather than in specific teachers’ knowledge areas.

With the increasing complexity of society, the importance of quantifying uncertainty in decision-making is growing. Alongside the development of technologies such as TinkerPlots and CODAP, and the spread of mathematical modeling research in general, there has been a recent proposal that school education should foster problem-solving skills and abilities by engaging students in real-world problem-solving using probability (probabilistic modeling). However, teaching probabilistic modeling in school education is not easy. In this paper, we aim to clarify whether students can engage in the probabilistic modeling process through solving word problems. The results demonstrate that students can indeed engage in probabilistic modeling through word problem-solving, provided that the class includes at least the following three instructional innovations: (1) Designing teaching materials in a way that causes students to make errors or diverge in their thinking. (2) Creating tasks where students’ expectations differ from simulation results, or where students can intuitively sense the correct outcome but struggle to quantify and explain the degree of accuracy. (3) Including activities that allow students to change the conditions of the problem.

The purpose of this study was to investigate teachers’ initial attitudes and perceptions toward the introduction and practice of STEAM education in Japanese junior high schools. This is essential in understanding how best to introduce STEAM education into Japanese public education. Therefore, the authors conducted a semi-structured interview with one junior high school science teacher about implementing STEAM classes for the first time and analyzed the data using SCAT. As a result, it was revealed that the teacher actively embraced the teaching practice after being initially confused by STEAM education when she first encountered it. In addition, the teacher’s understanding of STEAM education deepened by observing students’ behavior during class, and it was shown that the teacher could see the positives of problem-solving in a real-world context, creative activities based on divergent thinking, and inquiry activities. Furthermore, it was shown that the teacher could see the positives of STEAM education firsthand such as how it aligns with her core beliefs, a positive impact on students not experienced before, and a sense of enjoyment and accomplishment in STEAM education.

The Super Science High School Project was not simply established and changed due to the need to develop human resources in science and technology. In this paper, I have examined the transition of the project using the “Policy Window Model.” The project was not realized simply because of a declining interest in the natural sciences among youth, namely, a “problem stream.” The project was established when the “political stream” of government ministry reorganization was added to this problem stream. Furthermore, recent reviews of the project were a response to the larger “political stream” of budget rationalization

Students’ interest in chemical experiments is caused by observing changes through chemical reactions. The author investigated three types of experiments using agar gel, which allows observing the reaction process over a relatively long period of time. Firstly, the process by which acidity, neutrality, and basicity are determined by the properties of salt produced in the neutralization reaction between acid and base was investigated. Secondly, the appearance of precipitate lines formed by the reaction of calcium and barium ions with carbonate and sulfate ions was observed. Thirdly, it is observed that precipitates are formed depending on the strength of alkalinity due to the reaction between metal ions and an aqueous sodium hydroxide solution.