Since 2012, the authors have been integrating traditional face-to-face STEM education at universities with e-Learning platforms such as Moodle, aiming to empower students to learn autonomously outside the classroom. This effort is part of their broader strategy to digitize university education. The onset of the COVID-19 pandemic in 2020 accelerated the shift towards ”new normal” educational practices, emphasizing remote and contactless learning in higher education. This highlighted the critical role of digital transformation (”EduTech”) in adapting to new teaching paradigms. In response to these challenges, the authors have continued their research and development in EduTech, with a specific focus on enhancing mathematical education through innovative tools embedded within their e-Learning system. Key functionalities like ”STACK” and ”Maxima” play pivotal roles in this system, facilitating interactive and personalized learning experiences for students. Their work has been supported by grants from the Moodle Association of Japan, enabling them to develop plugins and present their findings at prestigious conferences such as Moodle Moot Japan 2020. Their ongoing research has evolved to include sophisticated features such as generating scatter plots to analyze attention coefficients and grades (”S-P table analysis”). These advancements underscore their dedication to improving the quality and effectiveness of mathematics education in higher learning institutions. By leveraging technology and educational research, the authors are actively contributing to the ongoing digital transformation of university education, ensuring its relevance and resilience in the face of evolving global challenges.

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The course "Introduction to Biology," a required course for basic education at Obihiro University of Agriculture and Veterinary Medicine, is facilitated using Moodle. The total number of students in the course is about 260, including approximately 250 first-year students and students who took the course in previous years. Grades for this course are determined by the total score out of 100 points, which is the sum of a preparatory test given one week before each lecture, a review test given one week after the lecture, a mid-term exam, and a final exam. Among students who scored 60 or more points, which is considered a passing score, the trend of high average scores and low variance continued after the school year of 2020. Therefore, in the current (2023) school year, the settings were adjusted to allow students to take each of the preparation/review tests only once, while the mid-term exam was abolished, leaving only the final exam. Consequently, the variance of the scores increased and the mean score decreased, resulting in improved discrimination of the studentsʼ performance. The reliability of this assessment was sufficient, and its validity was generally assured. No direct correlation was found between the time taken to answer the questions and the scores. While these findings imply the enhanced effectiveness of the grading methods, the results also suggest that the question bank needs to be expanded for the sustainability of this practice and the quality of student learning.

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We report on methods to obtain learning logs from Dynamic Geometry Software (DGS) content embedded in Moodle using JavaScript. We utilized GeoGebra and Cinderella as examples of DGS. We obtained the time, coordinates, and values of variables defined upon user interaction with the content, triggered through mouse and/or touch events. We implemented a flow for obtaining data from the interaction and automatically sending and storing it in a database activity module prepared in a Moodle course once the user completes the interaction by utilizing the method developed in Saito (2023). As a result of this implementation, we clarified that it is possible to build a learning analytics (LA) environment capable of obtaining log data from DGS without relying on admin privilege or plugins. It is anticipated that, by applying our methods, it will be possible not only to obtain information to improve DGS content but also to evaluate learning outcomes that are difficult to assess with other learning data, such as usual grading scores.

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A simple method of connecting Moodle and the Jupyter environment through frontend JavaScript is reported. If the Jupyter environment is located outside the site where Moodle is hosted, connections using only a frontend API, unless CORS (Cross-Origin Resource Sharing) is appropriately allowed, are generally prohibited. However, by using the Web Messaging API, our method enables establishing a cross-origin connection with the Jupyter environment—for example, to extract logs—without any admin privilege, special plugins, or server settings, although it requires students to make some small arrangements, like executing initial JavaScript code. As a particular instance in data science education within an undergraduate curriculum, we report an attempt to obtain learning logs from the Jupyter environment known as the JDCat analysis tool, operated by NII (National Institute of Informatics) and launched using the free-of-charge Binder service. We explore the possibilities and issues related to connecting Moodle with the Jupyter environment.

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Learner reflection is one of the key elements in higher education. As tools to support the reflection, tools such as minute papers and Daifuku-Cho exist. In this study, a comparison was made as to what kind of activity modules are available for using Moodle as a reflection support tool. Quizzes and questionnaires can be used if the learner writes and submits a reflection, and no individual feedback is given. If comments and evaluations are to be added to the written content, it will be necessary to utilize functions such as forums and databases. Although the digitization of minute papers, etc., which used to be paper-based media, offers various advantages, it is necessary to carefully consider how the different activity modules should be used, depending on how the features are to be utilized and how they are to be used for education.

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