GLOBE: データ駆動型グループ学習支援システム

京都大学新制・課程博士博士(情報学)甲第24934号情博第845号京都大学大学院情報学研究科社会情報学専攻(主査)教授 緒方 広明, 教授 伊藤 孝行, 教授 田島 敬史学位規則第4条第1項該当Doctor of InformaticsKyoto UniversityDFA

Learning log-based automatic group formation: system design and classroom implementation study

Collaborative learning in the form of group work is becoming increasingly significant in education since interpersonal skills count in modern society. However, teachers often get overwhelmed by the logistics involved in conducting any group work. Valid support for executing and managing such activities in a timely and informed manner becomes imperative. This research introduces an intelligent system focusing on group formation which consists of a parameter setting module and the group member visualization panel where the results of the created group are shown to the user and can be graded. The system supports teachers by applying algorithms to actual learning log data thereby simplifying the group formation process and saving time for them. A pilot study in a primary school mathematics class proved to have a positive effect on students’ engagement and affections while participating in group activities based on the system-generated groups, thus providing empirical evidence to the practice of Computer-Supported Collaborative Learning (CSCL) systems

Efficacy and safety of transcutaneous electrical acupoint stimulation for the management of primary dysmenorrhoea: Protocol for a randomised controlled trial in China

INTRODUCTION: Primary dysmenorrhoea (PD) is a common menstrual concern with significant physical and psychosocial impacts. The effectiveness and safety of transcutaneous electrical acupoint stimulation (TEAS) in alleviating PD symptoms remain uncertain due to insufficient evidence. This single-centre, parallel, randomised controlled study intends to evaluate the efficacy and safety of TEAS for PD management. METHODS AND ANALYSIS: 60 participants aged 18-40 years diagnosed with moderate to severe PD will be recruited from Tai\u27an Hospital of Traditional Chinese Medicine (TCM) and randomly assigned to either a TEAS group or a TEAS-sham group (1:1). The TEAS group will undergo 12 sessions of TEAS treatment over two menstrual cycles, with 30 min per session, three sessions weekly. Participants in the TEAS-sham group will receive TEAS stimulation using identical devices and protocols but without current output. The primary outcome is the Visual Analogue Scale (VAS) for pain assessment. Secondary outcomes are Short-Form McGill Pain Questionnaire, total effective rate, uterine artery haemodynamics, prostaglandin and β-endorphin level, mental well-being and quality of life. Adverse events and their potential reasons and the use of analgesics will also be recorded. ETHICS AND DISSEMINATION: This study was approved by the Medical Ethics Committee of Tai\u27an Hospital of TCM. Written informed consent will be obtained from each participant. The results will be submitted for publication in a peer-reviewed journal. TRIAL REGISTRATION NUMBER: ChiCTR2300071686

Algorithmic group formation and group work evaluation in a learning analytics-enhanced environment: implementation study in a Japanese junior high school

In-class group work activities are found to promote the interpersonal skills of learners. To support the teachers in facilitating such activities, we designed a learning analytics-enhanced technology framework, Group Learning Orchestration Based on Evidence (GLOBE) using data-driven approaches. In this study, we implemented the algorithmic group formation and group work evaluation systems in a Japanese junior high school context. Data from a series of 12 collaborative learning activities were used to validate the difference in the measured heterogeneity of the formed homogeneous and heterogeneous groups compared to random grouping. Further, the peer rating and self-perception of the group work were compared for comparative reading and idea exchange tasks. We found algorithmically formed groups, considering the learner model data, either heterogeneously or homogeneously performed better than random grouping. Specifically, students in groups created by the homogeneous algorithm received higher peer ratings and more positive self-perception of group work in the idea exchange group tasks. We did not find significant differences in the comparative reading tasks. Along with the empirical findings, this work presents a paradigm of continuous data-driven group learning support by incorporating the peer and teacher evaluation scores as an input to the subsequent algorithmic grouping

Towards Predictable Process and Consequence Attributes of Data-Driven Group Work: Primary Analysis for Assisting Teachers with Automatic Group Formation

Data-driven platforms with rich data and learning analytics applications provide immense opportunities to support collaborative learning such as algorithmic group formation systems based on learning logs. However, teachers can still get overwhelmed since they have to manually set the parameters to create groups and it takes time to understand the meaning of each indicator. Therefore, it is imperative to explore predictive indicators for algorithmic group formation to release teachers from the dilemma with explainable group formation indicators and recommended settings based on group work purposes. Employing learning logs of group work from a reading-based university course, this study examines how learner indicators from different dimensions before the group work connect to the subsequent group work processes and consequences attributes through correlation analysis. Results find that the reading engagement and previous peer ratings can reveal individual achievement of the group work, and a homogeneous grouping strategy based on reading annotations and previous group work experience can predict desirable group performance for this learning context. In addition, it also proposes the potential of automatic group formation with recommended parameter settings that leverage the results of predictive indicators

New insights into bacterial mechanisms and potential intestinal epithelial cell therapeutic targets of inflammatory bowel disease

The global incidence of inflammatory bowel disease (IBD) has increased rapidly in recent years, but its exact etiology remains unclear. In the past decade, IBD has been reported to be associated with dysbiosis of gut microbiota. Although not yet proven to be a cause or consequence of IBD, the common hypothesis is that at least some alterations in the microbiome are protective or pathogenic. Furthermore, intestinal epithelial cells (IECs) serve as a protective physical barrier for gut microbiota, essential for maintaining intestinal homeostasis and actively contributes to the mucosal immune system. Thus, dysregulation within the intestinal epithelium increases intestinal permeability, promotes the entry of bacteria, toxins, and macromolecules, and disrupts intestinal immune homeostasis, all of which are associated with the clinical course of IBD. This article presents a selective overview of recent studies on bacterial mechanisms that may be protective or promotive of IBD in biological models. Moreover, we summarize and discuss the recent discovery of key modulators and signaling pathways in the IECs that could serve as potential IBD therapeutic targets. Understanding the role of the IECs in the pathogenesis of IBD may help improve the understanding of the inflammatory process and the identification of potential therapeutic targets to help ameliorate this increasingly common disease

Study of the Durability of Membrane Electrode Assemblies in Various Accelerated Stress Tests for Proton-Exchange Membrane Water Electrolysis

In this work, we focus on the degradation of membrane electrode assemblies (MEAs) in proton-exchange membrane water electrolysis (PEMWE) induced by different accelerated stress tests (ASTs), including constant-current mode, square-wave mode, and solar photovoltaic mode. In constant-current mode, at continuous testing for 600 h at 80 °C, a degradation of operating voltage increased by the enhanced current density from 22 µV/h (1 A/cm2) to 50 µV/h (3 A/cm2). In square-wave mode, we found that in the narrow fluctuation range (1–2 A/cm2), the shorter step time (2 s) generates a higher degradation rate of operating voltage, but in the wide fluctuation range (1–3 A/cm2), the longer step time (22 s) induces a faster operating voltage rise. In the solar photovoltaic mode, we used a simulation of 11 h sunshine duration containing multiple constant-current and square-wave modes, which is closest to the actual application environment. Over 1400 h ASTs, the solar photovoltaic mode lead to the most serious voltage rise of 87.7 µV/h. These results are beneficial to understanding the durability of the PEM electrolyzer and optimizing the components of MEAs, such as catalysts, membranes, and gas diffusion layers

Control of local ion transport to create unique functional nanodevices based on ionic conductors

The development of nanometer-scale devices operating under a new principle that could overcome the limitations of current semiconductor devices has attracted interest in recent years. We propose that nanoionic devices that operate by controlling the local transport of ions are promising in this regard. It is possible to control the local transport of ions using the solid electrochemical properties of ionic and electronic mixed conductors. As an example of this concept, here, we report a method of controlling the transport of silver ions of the mixed-conductor silver sulfide (Ag2S) crystal and basic research on nanoionic devices based on this mixed conductor. These devices show unique functions such as atom deposition, resistance switching, and quantum point contact switching. The switches operate through the formation and dissolution of an atomic bridge between the electrodes, and the behavior is realized by control of the local solid-state electrochemical reaction. Potential nanoionic devices utilizing the unique functions and characters that do not exist in conventional semiconductor devices are discussed