This study examined the relationship between self-evaluated academic achievement based on the viewpoint assessment via an evaluation in the specialized subject taught at the Electrical Department of Technical Upper Secondary School and the self-adjustment learning ability. A total of 676 students at the T prefectural Electrical Department of Technical Upper Secondary School completed self-reported questionnaires. A series of surveys were conducted, followed by a covariance structure analysis. We found and interpreted the five following factors: “metacognition,” “learning strategies,” “self-evaluation of academic achievement,” “recognition of task value,” and “proactive learner attitude as a member of society.” “Self-evaluation of academic achievement” and “proactive learner attitude as a member of society” were correlated with .64. “Metacognition” showed a high positive path to “self-evaluation of academic achievement” and “proactive learner attitude as a member of society.” “Learning strategies” showed a positive path to “proactive learner attitude as a member of society.” “Recognition of task value” showed a positive path to “self-evaluation of academic achievement” and “proactive learner attitude as a member of society.” The findings suggested that learning strategies played important roles in increasing learning independence. As a result of comparing the average values of each school year within each of the five factors via analysis of variance, the average value of metacognition was lower than those of the other factors. The guidance and support of learning activities that exercise metacognition was the academic ability of Technical Upper Secondary School students. This finding may help improve their learning strategies.

There is an increasing need to attract students to information technology education programs, especially given the imperative to secure and train talented domestic engineers in information technology (e.g., computer and machine learning programmers). Accordingly, various teaching materials have been developed for programming education in recent years. However, research reports on teaching materials regarding machine learning are scarce. We newly developed a teaching material for learning and understanding how machine learning works using the NVIDIA Jetson Nano device. This study investigated the educational effects of these machine learning teaching materials based on lesson practice. To this end, we recruited a sample of 112 third grade junior high school students. Our results suggest that the teaching materials are valid for learning activities and understanding how machine learning works in technical departments at junior high schools.

The purpose of this study was to develop a teaching material in which students choose agricultural chemicals that adapt to different condition, and we investigated how this teaching material affected the construction of risk perception. The students were able to understand the knowledge and skills of agricultural chemicals through this teaching material. However, the understanding of how to use agricultural chemicals before the harvest season was insufficient. In the risk perception of agricultural chemicals, the students realized that it is necessary to select appropriate agricultural chemicals from economic, environmental, and social perspectives, which led to a multifaceted understanding of agricultural chemicals. This suggests that this teaching material contributed to the risk perception of agricultural chemicals; in particular, the activity of selecting one from multiple prepared options was produced based on the viewpoint or idea of ??technology and the concept of technology. It was thought that this would lead to the development of the judgment ability to select the most suitable option considering productivity, environmental load, safety, et al.

The purpose of this study was to elucidate the structure of students’ optimization thinking in "technological problem solving” at junior high school technology education. A survey was conducted on 349 8th grade students in junior high school who were engaged in learning about technological problem solving in the Content A, "Materials and Processing Technology," using the questionnaire for understanding optimization thinking (Yamashita and Moriyama 2020), which was constructed based on the concept of systems engineering. As a result, four factors were extracted as students' optimization thinking: F1 "Modeling the Problem," F2 "Searching for Comprehensive Solution," F3 "Considering User Needs," and F4 "Considering Constraints.” Multiple-group structural equation modeling was conducted to examine the effects of problem-solving experience on these four factors by project type. As a result, the students who experienced free design projects (students designed their own products) was characterized by the influence of "design process experience" and "troubleshooting experience" on optimization thinking compared to students who experienced the project by choosing only the design model.

The purpose of this study was to verify the effect of group learning activities on the consciousness of information morals considering personal traits, and to obtain basic knowledge for the enhancement of information morality education. In this study, 98 fifth-graders were organized into groups based on their self-efficacy level, and trial lessons were conducted to develop awareness of information morals about health maintenance. The group comprising only learners with low self-efficacy rated their consciousness of information morals about health maintenance lower than the group comprising only learners with high self-efficacy levels. This suggests that it is crucial for learners with low self-efficacy to adjust their learning environment so that they can interact with learners with high self-efficacy.

The study clarified the semantic structure of practical knowledge aimed at achieving proactive, interactive, and deep learning through a lesson on evaluating the technology of nurturing living things. The researchers based this study around the reflections of a surveyed teacher via stimulated recall. The teacher practiced the aforementioned lesson with a wearable camera, then discussed his reflections on the lesson while viewing the video, which integrated the subjective images recorded by the wearable camera with the objective images that were recorded in the classroom by a video camera. Following this, the researchers qualitatively analyzed text data that were derived from the teacher’s discussion and created a relevant model based on practical knowledge. Thus, the researchers clarified the concept constructing the practical knowledge with the context in the lesson. The externalization of this practical knowledge should facilitate the ability to share it with others. In addition, the results of this study suggest the need to accumulate case studies based on learning contents and consider strategies for inheriting practical knowledge.

This study investigated the practice of foreign language activity classes at the elementary-school level, with a focus on the incorporation of programming to nurture the foundation of English characters and relevant learning effects. A total of 34 elementary school fourth graders participated in a trial lesson for foreign language activities using the visual programming language Scratch, wherein the subject was used as a guide. Based on the analysis, students who were subjected to learning that incorporated programming could connect English voices with letters and meanings; in addition to listening and speaking, they also developed a foundation for letters. Further, as a side effect, this suggests that a link with tasks that require the use of programming can lead to more awareness of programming and further motivate students to learn programming.

This study developed and applied a four-hour training course on programming, data science, and machine learning, which are new subjects for a high-school level “Information” course. The training targets the teaching faculty in charge of information education at high schools and supervisors in charge of information education. The training contents feature actual situations involving programming instructions offered in elementary, junior high, and senior high schools, including basic programming exercises, the effective use of data, programming learning that incorporates data science and machine learning, and how to teach programming in senior high schools. As for the teacher training, we developed and used an automatic sorting machine for mini tomatoes in order to experience the effective use of data and machine learning through programming. As a result of the training, the participants were able to assess specific methods for the effective use of data and enhanced their understanding of the training contents.

In November 2020, the National Center for University Entrance Examinations provided the Common Test for University Admissions “Information Study” Trial Problem to boards of education and related organizations. The “Information Study” Sample Problem was released in March 2021. In each problem, the test tends to instill the feeling that the thinking, judgment, and expressive abilities are more important than knowledge and skill. In this study, we investigated the fourth question “Traffic Congestion Simulation”” Trial Problem in simulation classes. Students were asked to answer the fourth question of the Trial Problem twice before and after classes. After analyzing the answers given by these students, it was clear that the “reading ability to accurately read and understand what is being asked” and “analytical ability to compare multiple graphs and accurately read information therein” were required to solve the fourth question of the Trial Problem. Our findings also suggest that it is necessary to cultivate these abilities under a design that considers appropriate curriculum management and cross-curricular engagement.