Hiroaki Ogata

Kyoto University | Kyodai · Academic Center for Computing and Media Studies

To promote the development of students' reading literacy and learning skills in the k-12 setting, this study introduced an online extensive reading (ER) environment with self-directed learning (planning, monitoring, reflection) and social (discussion forum participation) support. This study aimed to examine whether planning behavior and discussion...

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),...

Blended learning (BL) combines traditional classroom activities with online learning resources, enabling students to obtain higher academic performance through well-defined interactive learning strategies. However, lacking the capacity to self-regulate their learning, many students might fail to comprehensively study the learning materials after fa...

Self-explanation is increasingly recognized as a key factor in learning. Identifying learning impasses, which are significant educational challenges, is also crucial as they can lead to deeper learning experiences. This paper argues that integrating self-explanation with relevant datasets is essential for detecting learning impasses in online mathe...

This paper explores co-design in Japanese education for deploying data-driven educational technology and practice. Although there is a growing emphasis on data to inform educational decision-making and personalize learning experiences, challenges such as data interoperability and inconsistency with teaching goals prevent practitioners from particip...

In online mathematics education, self-explanation is increasingly recognized as a key tool for improving learning outcomes. Identifying learning impasses, which present significant educational challenges, is crucial. Typically, detecting these impasses demands considerable effort from educators to manually review and identify issues in students' ma...

Self-direction skill (SDS) is an essential 21st-century skill that can help learners be independent and organized in their quest for knowledge acquisition. While some studies considered learners from higher education levels as the target audience, providing opportunities to start the SDS practice by K12 learners is still rare. Further, practicing s...

Expectations of big data across various fields, including education, are increasing. However, uncovering valuable insights from big data is like locating a needle in a haystack, and it is difficult for teachers to use educational big data on their own. This study aimed to understand changes in student participation rates during classes and teachers...

In the field of mathematics education, self-explanation is recognized as a critical facilitator for learners to articulate their understanding of complex mathematical concepts and problem-solving techniques. With the emergence of digital learning platforms, the potential to utilize such self-explanations for automated evaluation has expanded, yet s...

While building proper learning habits has been said to enhance academic performance, it is challenging to give long-term support for building habits in educational contexts due to the lack of continuous tracing of one’s habitual behaviors. With the accumulation of learning logs and the advancement of Learning Analytics (LA) techniques, this paper i...

Peer evaluation is a common practice in team-based learning (TBL) designs, which can cover the assessment of individual or group work. However, the integrity of peer evaluation can be compromised by unserious raters—individuals who do not earnestly engage in the evaluation process. These raters may exhibit behaviors like consistently assigning the...

This study examined whether self-direction skills (SDS) are generic and can be applied to a variety of situations using data, rather than being limited to a specific context. The concept of SDS, a crucial component in 21st-century learning, encompasses activities ranging from academic learning to daily physical tasks. The GOAL system was developed...

This research aims to explore how to effectively utilize the self-reflection data generated by students during their learning process to enhance self-directed learning (SDL). In this study we collected the last 2 years' data from an SDL support environment, GOAL, with 2304 logs related to reflections, key point summaries, learning strategies, and g...

This study proposes the Open Knowledge and Learner Model (OKLM), a universal learner model in which a knowledge map extracted from any domain's learning materials relates to everyday learning activities. OKLM offers various learning support, such as visualization in a dashboard, network analysis, and feedback/recommendation. To address the issue of...

Chatbots have been increasingly playing a greater role in English as a foreign language education, offering learners the opportunity to practise with a conversational agent at any time and in different contexts. To grasp how this field has developed and identify emerging trends and opportunities, we conducted a systematic bibliometric analysis of r...

Traditional textbooks are progressively being replaced by e-book systems, which are also being utilized more commonly in K-12 education. The study investigated learning behavioral patterns in a seven-week high school mathematics course using an e-book system. In this study, learning data from the BookRoll system was analyzed with lag sequential ana...

Explainable recommendation, which provides an explanation about why a quiz is recommended, helps to improve transparency, persuasiveness, and trustworthiness. However, little research examined the effectiveness of the explainable recommender, especially on academic performance. To survey its effectiveness, the authors evaluate the math academic per...

Iterative team-based learning (TBL) is a common educational strategy for collaborative learning that involves sequential phases of individual and group learning activities. The advent of digital learning platforms, with the accumulation of learning log data, presents an opportunity to leverage data-driven techniques to enhance TBL practices. Howeve...

Evidence-based practice stems from medicine. It involves the concept of Real-World Evidence (RWE), which involves the analysis of routinely collected patient data to extract evidence of practice. In this paper, we propose a learning-analytics (LA) based reflective teaching workflow that analyzes data from daily teaching and learning environments. T...

Improving learning outcomes is always one of the key objectives of learning analytics (LA) and educational data mining (EDM). In recent years, many Massive Open Online Courses (MOOC) have been deployed and making it easier to collect learners’ data for further analysis. Naturally, leveraging AI to process such kind of big data becomes one of the ma...

In inclusive education, students with different needs learn in the same context. With the advancement of artificial intelligence (AI) technologies, it is expected that they will contribute further to an inclusive learning environment that meets the individual needs of diverse learners. However, in Japan, we did not find any studies exploring curren...

In the age of artificial intelligence (AI), trust in AI systems is becoming more important. Explainable recommenders, which explain why an item is recommended, have recently been proposed in the field of learning technology to improve transparency, persuasiveness, and trustworthiness. However, the methods for generating explanations are limited and...

Many systems to assist in learning English grammar have been developed in the field of learning material recommendation systems (LMRSs). Compared with those based on knowledge models, recommendations based on data tend to cause the cold-start problem, and it is said that explainable LMRSs may be able to enhance learners' motivation. In our research...

Educational recommender systems are increasingly becoming a core feature of modern educational systems. Often the recommender component of a system is tightly integrated, or might be remotely located without accessing data from other local systems. This paper proposes a framework called ECLAIR in which local educational systems can work and share d...

Learners may have a unique chronotype of learning habits that they have the preferred time of day to work. Even though learner activity extracted from trace data can provide useful and insightful information about their learning habits, there is a lack of tracing habits in daily learning at a school level from learning logs. Therefore, we propose t...

The Blockchain of Learning Logs (BOLL) system is a blockchain-based platform for connecting learners' educational records from multiple schools. The BOLL system creates a permanent record of learners' lifelong learning as immutable hashes on the blockchain, which can be analyzed to inform teaching and learning. This paper presents a usability analy...

Many modern learning systems rely on a data representation of the knowledge that is to be learned to estimate a learner’s mastery state and recommend appropriate learning tasks to further improve their acquisition of knowledge and skills. In particular, the rapid development of intelligent tutoring systems (ITS) and standardized curricula has incre...

This research introduces the self-explanation-based automated feedback (SEAF) system, aimed at alleviating the teaching burden through real-time, automated feedback while aligning with SDG 4’s sustainability goals for quality education. The system specifically targets the enhancement of self-explanation, a proven but challenging cognitive strategy...

In the realm of mathematics education, self-explanation stands as a crucial learning mechanism, allowing learners to articulate their comprehension of intricate mathematical concepts and strategies. As digital learning platforms grow in prominence, there are mounting opportunities to collect and utilize mathematical self-explanations. However, thes...

In recent years, smart learning environments have become central to modern education and support students and instructors through tools based on prediction and recommendation models. These methods often use learning material metadata, such as the knowledge contained in an exercise which is usually labeled by domain experts and is costly and difficu...

Recommender systems can provide personalized advice on learning for individual students. Providing explanations of those recommendations are expected to increase the transparency and persuasiveness of the system, thus improve students’ adoption of the recommendation. Little research has explored the explanations’ practical effects on learning perfo...

Self-explanation is a widely recognized and effective pedagogical method. Previous research has indicated that self-explanation can be used to evaluate students’ comprehension and identify their areas of difficulty on mathematical quizzes. However, most analytical techniques necessitate pre-labeled materials, which limits the potential for large-sc...

Reading is fundamental in language learning, and active reading strategies using annotations prove beneficial. In parallel, collaborative learning is also an instructive practice for active reading in flipped classrooms. The advance of information infrastructures with increasing learning log data facilitates technical innovations to scaffold readin...

Self-directed learning requires students to take the initiative to learn and control their learning process. Scholars have provided evidence for the positive effect of self-directed learning on academic achievement, and they emphasize the importance of self-direction for lifelong learning. Yet, a limited study has been conducted in K-12 education....

Various efforts to scaffold improving reading performance and skills have been investigated, yet there have been no efforts to visualize the active reading (AR) process using logs, verify the effects on learning behavior and performance, and further deepen reading comprehension in a data-driven manner. To this end, an Active Reading Dashboard (AR-D...

Explainable recommendation, which provides an explanation about why a quiz is recommended, help to improve the transparency, persuasiveness and trustworthiness. Recently, some explainable recommenders were proposed in the educational field. However little research focused on the tailored intervention. We proposed personality based tailored explanat...

The GOAL project aimed to collect and synchronize learners’ data from physical activity sensors as well as online learning tools to design data-driven services. We extend the potential of learning tools interoperability (LTI) protocol to link physical activity and sensor data from smartwatch platforms. Our primary purpose is to provide this synchro...

As the adoption of digital learning materials in modern education systems is increasing, the analysis of reading behavior and their effect on student performance gains attention. The main motivation of this workshop is to foster research into the analysis of students' interaction with digital textbooks, and find new ways in which it can be used to...

This work aims to propose a learner model-based feedback model for self-direction skills (SDS) acquisition to address the challenge of providing learning services with multimodal data in K-12 settings. The feedback model leverages students' daily life activity data from learning systems and wearable devices, creates a learner model of SDS, and prov...

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...

Language teaching has a rich research history. A research discipline of Computer-Assisted Language Learning (CALL) has focused on technology integration in that practice. However, integrating the learning logs to create a data-driven workflow for the teachers and students is still limited. We design a technology framework called LEAF (Learning and...

During the COVID-19 pandemic there was a rapid shift to emergency remote teaching practices and online tools for education have already gained further attention. While eLearning initiatives are developed and its implementation at scale are widely discussed, this research focuses on the utilization of data which can be logged in such eLearning syste...

With COVID-19 pandemic forcing academic institutions to shift to emergency remote teaching (ERT), teachers worldwide are attempting several strategies to engage their learners. Even though existing research in online learning suggests that effectiveness of the online session is more dependent on pedagogical design rather than technology feature, te...

Providing explanations in educational recommender systems is expected to improve students' motivation and learning outcomes. In this study, we aim at exploring the practical effects of the explanation in a K-12 math recommender system. We implemented a concept-explicit quiz recommender system and generated explanations of the estimated quiz difficu...

Extensive Reading (ER) activity is useful in language learning where learners pick any reading materials in target language by themselves and continue reading. In this study, we aim to understand students' self-regulation behaviors and strategies in ER so that facilitators can give learning strategy-based instruction. For this purpose, we first exp...

Learning analytics (LA) is maturing as a research discipline in its own terms, focusing on multiple perspectives of data-informed understanding and supporting teaching and learning activities in different educational contexts. With the development of learning technology platforms, it is now possible to gather users’ interaction traces in a standard...

Creating a set of quizzes for the students' test is almost an irreplaceable task to teachers. In practice, a teacher could use a learning analytics dashboard while creating a test to control the quiz difficulty and the amount of time it takes to solve. This paper draws inspiration from this practical example, and we propose an automated test set qu...

The educational use of nudges has received much attention. However, individually optimized nudge interventions have not been well studied. In order to determine which nudge messages are effective for learners with what profiles based on personality inventories, we examined two nudge message interventions that promote the use of learning systems dur...

Evaluation plays a substantial role in group work implementation and peer evaluation gets prevalent with increasing flipped learning scenarios and online evaluation platforms. The accuracy of peer evaluation remains contingent in group work practice thus eliciting relevant studies on grader reliability. In this study, we present a data-driven appro...

Computerized adaptive testing (CAT) can effectively facilitate student assessment by dynamically selecting questions on the basis of learner knowledge and item difficulty. However, most CAT models are designed for one-time evaluation rather than improving learning through formative assessment. Since students cannot remember everything, encouraging...

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 fo...

The application of student interaction data is a promising field for blended learning (BL), which combines conventional face-to-face and online learning activities. However, the application of online learning technologies in BL settings is particularly challenging for students with lower self-regulatory abilities. In this study, a personalized lear...

Digitized learning materials are a core part of modern education, and analysis of the use can offer insight into the learning behavior of high and low performing students. The topic of predicting student characteristics has gained a lot of attention in recent years, with applications ranging from affect to performance and at-risk student prediction...

Language learners’ engagement with a specific task is crucial to improving their academic achievement. To enhance student engagement and academic achievement in language learning, personalized language learning (PLL) can be employed to consider individual learning needs. Personalized review learning has emerged to facilitate PLL as a promising mean...

Mobile learning (M-learning) refers to the use of mobile and wireless communication technologies to enable students to access learning materials in an interactive manner, regardless of location and time constraints. However, without a proper learning design or the provision of learning guidance, most students might fail to plan their learning sched...

Habit is an important concept attracting researchers’ attention in many fields. In the past, habit was commonly measured by tools such as questionnaires and diaries which involve subjects’ self-reported behaviors. However, attempts to extract and support good learning habits with actual learners’ data are still limited. Therefore, in this study, we...

In-classroom observations often rely on developed protocols and human observers. However, it requires a lot of human effort. This study investigates how accurately the pre-trained action recognition model can label teacher’s behaviors in the classroom. We adopt SlowFast, a state of the art action recognition model, to a real classroom at a junior-h...