学習・運動データを用いた学生の自主学習スキルの向上

京都大学新制・課程博士博士(情報学)甲第23315号情博第751号新制||情||128(附属図書館)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 黒田 知宏, 教授 楠見 孝学位規則第4条第1項該当Doctor of InformaticsKyoto UniversityDFA

A Novel Task of Loading and Computing Resource Scheduling Strategy in Internet of Vehicles Based on Dynamic Greedy Algorithm

Focus on the scheduling problem of distributed computing tasks in Internet of Vehicles. Firstly, based on the computing-aware network theory, a distributed computing resource model of the Internet of Vehicles is established, and the seven-dimensional QoS attributes of the computing resources in the Internet of Vehicles (reliability between computing resources, communication costs, computing speed and computing costs of the computing resources themselves , computing energy consumption, computing stability, and computing success rate) are grouped and transformed into two-dimensional comprehensive attribute priorities: computing performance priority and communication performance priority. Secondly, the weighted directed acyclic graph model of distributed computing tasks in the Internet of Vehicles and the seven-dimensional QoS attribute weighted undirected topology graph model of distributed computing resources in the Internet of Vehicles are respectively established. Moreover, a dynamic greedy algorithm-based task of loading and computing resource scheduling algorithm is proposed. Finally, the example analysis shows that the overall performance of this dynamic greedy algorithm-based task of loading and computing resource scheduling algorithm is better than the classic HEFT scheduling algorithm and round robin scheduling algorithm

Nuclei micro-array FISH, a desirable alternative for MCL diagnosis

Mantle cell lymphoma (MCL) is a rare, specific lymphoma subtype. Though the morphologic and immunophenotypic features of MCL have been well described in recent literatures, it is still a diagnostic dilemma because of its frequent confusion with other small B cell lymphomas (SBCLs). In the present study, we primarily focus on establishing a sensitive and specific method for the diagnosis of MCL, which is efficient to distinguish this disease from other SBCLs. We carried out our investigation for MCL and other SBCLs (including SLL, FL, MZL, and MALT) on their feature of morphology, immunophenotype, and t(11;14)(q13;q32) translocation analysis based on polymerase chain reaction (PCR) and interphase nuclei micro-array fluorescence in situ hybridization (FISH). The morphologic and immunologic analysis showed the positive rate of cyclin D1 was 76.47% in MCL, which was significantly higher than that in other SBCLs. The positive rate of t(11;14) translocation was 25.81% and 35.48%, respectively, tested by general and semi-nested PCR, while 93.10% positive rate was shown with low background and strong signals pattern when tested by Nuclei micro-array FISH. Our research shows that t(11;14) translocation is a special and useful diagnostic marker for MCL, and detection of the marker by nuclei micro-array FISH is convenient and economic, especially more sensitive and specific than other methods for the diagnosis of MCL

Design of a Learning Dashboard to Enhance Reading Outcomes and Self-directed Learning Behaviors in Out-of-class Extensive Reading

Self-directed learning (SDL) requires students to take initiative to learn and control their own learning process. Literature highlights the importance of SDL for lifelong learning. Yet, little understanding is known regarding how to support SDL at the school level, specifically for out-of-class learning context. To fill up this gap, this research developed a learning dashboard and integrated SDL process management in GOAL system. It was implemented to provide support for out-of-class online self-directed extensive reading (SDER) at a high school level. A two-group study conducted during a three-week spring vacation found the experimental group (N = 35, with SDL support) achieved significantly more reading outcomes than the control group (N = 12, without SDL support). Detailed GOAL interaction behavior analysis of the experimental group showed that viewing learning dashboard was significantly correlated with reading outcomes as well as interactions related to SDL process management. These findings highlights positive effect of SDL support in GOAL on students' out-of-class SDER outcomes as well as their SDL behaviors. The study provided implications for research related to extensive reading and SDL support for out-of-class learning

Supporting “time awareness” in self-regulated learning: How do students allocate time during exam preparation?

The development of technology enables diverse learning experiences nowadays, which shows the importance of learners’ self-regulated skills at the same time. Particularly, the ability to allocate time properly becomes an issue for learners since time is a resource owned by all of them. However, they tend to struggle to manage their time well due to the lack of awareness of its existence. This study, hence, aims to reveal how learners allocate their time and evaluate the effectiveness of the time allocation by examining its effects on learners’ performance. We collect the learning logs of 116 seventh-graders from the online learning system implemented in a Japanese public junior high school. We look at the data in the time window of 34 days before the regular exam. Even though clustering techniques as a Learning Analytics method help identify different groups of learners, it is seldom applied to group students’ learning patterns with different levels of indicators extracted from their learning process data. In this study, we adopt the method to cluster students’ patterns of time allocation and find that better performance can result from the consistency of study time throughout the exam preparation period. Practical suggestions are then proposed for different roles involved in digital learning environments to facilitate students’ time management. Collectively, this study is expected to make contributions to smart learning environments supporting self-regulated learning in the digital era

Explainable eBook recommendation for extensive reading in K-12 EFL learning

An automatic recommendation system for learning materials in e-learning addresses the challenge of selecting appropriate materials amid information overload and varying self-directed learning (SDL) skills. Such systems can enhance learning by providing personalized recommendations. In Extensive Reading (ER) for English as a Foreign Language (EFL), recommending materials is crucial due to the paradox that learners with low SDL skills struggle to select suitable ER resources, despite ER’s potential to improve SDL. Additionally, determining the difficulty level of ER materials and assessing learners’ progress remains challenging. The system must also explain its recommendations to foster motivation and trust. This study proposes a mechanism to estimate the difficulty of ER materials, adapted to learner preferences, using information retrieval techniques, and an explainable recommendation system for English materials. An experiment was conducted with 240 Japanese junior high school students in an ER program to assess the accuracy of difficulty estimation and identify learner characteristics receptive to the recommendations. While the recommendations did not significantly impact learners’ English skills or motivation, they were positively received. A strong relationship was found between the use and acceptance of recommendations and learners’ motivation. The study suggests that although the system did not increase overall motivation, it has potential to further enhance the motivation of naturally motivated learners

A framework to foster analysis skill for self-directed activities in data-rich environment

Self-direction skill is considered a vital skill for twenty-first-century learners in both the learning context and physical activity context. Analysis skill for self-directed activities requires the students to analyze their own activity data for understanding their status in that activity. It is an important phase that determines whether an appropriate plan can be set or not. This research presents a framework designed to foster students’ analysis skill in self-directed activities, which aims (1) to build a technology-enabled learning system allowing students to practice analyzing data from their own daily contexts, (2) to propose an approach to model student’s analysis skill acquisition level and process, and (3) to provide automated support and feedback for analysis skill development tasks. The analysis module based on the proposed framework was implemented in the GOAL system which synchronized data from learners’ physical and reading activities. A study was conducted with 51 undergraduate students to find reliable indicators for the model to then measure students’ analysis skills. By further analyzing students’ actual usage of the GOAL system, we found the actual activity levels and their preferences regarding analysis varied for the chosen contexts (learning and physical activity). The different context preference groups were almost equal, highlighting the utility of a system that integrates data from multiple contexts. Such a system can potentially respond to students’ individual preferences to execute and acquire self-direction skill

Hydrocarbon Generation Potential Evaluation of Coal Shale Gas of Permo-Carboniferous in Jiyang Depression

This paper studied the residual strata distribution of Carboniferous-Permian in Jiyang Depression, the organic geochemical characteristics of shale and the correlation of hydrocarbon-generating potential of shale by applying geochemistry, petroleum geology and coal geology, for study hydrocarbon generation potential of Permo-Carboniferous coal shale in Jiyang Depression. The results show that the thickness of Carboniferous-Permian residual strata in Jiyang Depression is generally 200-800 m, the thickest can reach 900 m; coal shale has good organic matter abundance and is type III kerogen, which is conducive to gas generation, and organic matter maturity reaches maturity-higher maturity stage; Benxi Formation and Taiyuan Formation have better hydrocarbon generation potential; medium to good hydrocarbon source rocks can be found in every sag of Shanxi Formation hydrocarbon source rocks, but the scope is limited, and the overall evaluation is still medium. Compared with other areas in China, it is found that the hydrocarbon-generating capacity of coal-bearing shale of Carboniferous-Permian in Jiyang Depression is generally at a medium level, which has a certain shale gas exploration potential

Heterosis-related genes under different planting densities in maize

Heterosis and increasing planting density have contributed to improving maize grain yield (GY) for several decades. As planting densities increase, the GY per plot also increases whereas the contribution of heterosis to GY decreases. There are trade-offs between heterosis and planting density, and the transcriptional characterization of heterosis may explain the mechanism involved. In this study, 48 transcriptome libraries were sequenced from four inbred Chinese maize lines and their F1 hybrids. They were planted at densities of 45,000 plants/ha and 67,500 plants/ha. Maternal-effect differentially expressed genes (DEGs) played important roles in processes related to photosynthesis and carbohydrate biosynthesis and metabolism. Paternal-effect DEGs participated in abiotic/biotic stress response and plant hormone production under high planting density. Weighted gene co-expression network analysis revealed that high planting-density induced heterosis-related genes regulating abiotic/biotic stress response, plant hormone biosynthesis, and ubiquitin-mediated proteolysis but repressed other genes regulating energy formation. Under high planting density, maternal genes were mainly enriched in the photosynthesis reaction center, while paternal genes were mostly concentrated in the peripheral antenna system. Four important genes were identified in maize heterosis and high planting density, all with functions in photosynthesis, starch biosynthesis, auxin metabolism, gene silencing, and RNA interference