Brendan Flanagan

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Verified

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• Doctor (Information Science)
• Associate Professor at Kyoto University

In recent years, learning analytics has become a hot topic with many institutes deploying learning management systems and learning analytics tools. In this paper, we introduce learning analytics platforms that have been established in two top national Japanese universities. These initiatives are part of a broader research project into creating wide...

Abstract It is a common practice to issue a summary of a learner’s learning achievements in form of a transcript or certificate. However, detailed information on the depth of learning and how learning or teachings were conducted is not present in the transcript of scores. This work presents the first practical implementation of a new platform for k...

While data privacy is a key aspect of Learning Analytics, it often creates difficulty when promoting research into underexplored contexts as it limits data sharing. To overcome this problem, the generation of synthetic data has been proposed and discussed within the LA community. However, there has been little work that has explored the use of synt...

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...

With the increasing integration of technology in education, chatbots and e-readers have emerged as promising tools for enhancing language learning experiences. This study investigates how students engage with digital texts and a purpose-built chatbot designed to promote active reading for EFL students. We analysed student inter- actions and compare...

To make accurate predictions, complex artificial intelligence techniques are being adopted in intelligent systems. It leads to the need for explanations, helping users understand how the model works. Beyond this original purpose, explanations in educational intelligent systems have been found to increase students’ awareness, perceived usefulness, a...

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),...

Educational recommender systems have been supporting personalized learning in various ways. However, less discussion is conducted about whether and how to personalize the strategies to generate recommendations based on student differences. In this study, we aim at investigating how students judge recommendations based on different strategies, and h...

E-learning environments are increasingly harnessing large language models (LLMs) like GPT-3.5 and GPT-4 for tailored educational support. This study introduces an approach that integrates dynamic knowledge graphs with LLMs to offer nuanced student assistance. By evaluating past and ongoing student interactions, the system identifies and appends the...

The Educational Research Data Platform (EREDA) developed at Kyoto University addresses the challenges of managing and analyzing educational data while prioritizing privacy and security. EREDA seamlessly integrates with the existing Learning and Evidence Analytics Framework (LEAF) and offers advanced data management and analysis capabilities, includ...

Learning EFL through translation tasks is an effective language learning technique, but requires consistent practice and scaffolding. This study evaluates TAMMY, a prototype EFL chatbot designed for Japanese learners to practise English translation tasks. Using the extended Technology Acceptance Model, the study examines Tammy's usability, usefulne...

Extensive Reading (ER) is recognized for enhancing English proficiency in EFL learners. Although understanding speed is essential for analyzing reading behavior, limited research has focused specifically on reading speed during ER sessions. This study addresses this issue by analyzing log data from junior high school students engaged in ER activiti...

Post-exam reflection is critical in helping students consolidate knowledge acquired during a course, enabling them to apply this understanding in future professional contexts. This study investigates the effectiveness of Mirai, a large language model-based (LLM) chatbot, in supporting students' post-exam reflection needs in an Automation Engineerin...

The rapid development of Generative AI (GenAl) provides more opportunities and methods to deliver meaningful, engaging and gamified learning experiences to language learners. While there are various language learning applications, current methods often suffer from low completion rates and a painful learning process. In this paper, we propose a new...

This study will explore and experiment with various combinations of methods to handle data imbalance in order to address the common issue of insufficient minority samples in at-risk student prediction. Additionally, we will examine the purpose of applying computer tools to educational issues and emphasize the necessity of adhering to models with hi...

The Educational Research Data Platform (EREDA) developed at Kyoto University addresses the challenges of managing and analyzing educational data while prioritizing privacy and security. EREDA seamlessly integrates with the existing Learning and Evidence Analytics Framework (LEAF) and offers advanced data management and analysis capabilities, includ...

This study aims at modeling and visualizing students' behavior in a self- regulated and unguided learning environment with a focus on learning progression. Since the modeling approach is process-oriented and does not depend on specific mastery learning criteria, this paper provides a novel way to identify wheel-spinning in self-regulated learning s...

Learning EFL through translation tasks is an effective language learning technique, but requires consistent practice and scaffolding. This study evaluates TAMMY, a prototype EFL chatbot designed for Japanese learners to practise English translation tasks. Using the extended Technology Acceptance Model, the study examines Tammy's usability, usefulne...

This article originated from a working group on “Learning beyond formal schooling through human–computer–human interaction (HCHI)” convened at the UNESCO EDUSummIT 2023 in Kyoto (Japan). A polylogue approach was adopted by engaging eight co-authors whose diverse perspectives culminated in propositions that addressed the pivotal question: How should...

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...

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...

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...

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...

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...

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 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...

Providing explanations in educational recommender systems are supposed to increase students’ awareness of the recommendations, trust toward the system, motivation to adopt the recommendations. With the expectation to have a higher prediction accuracy, more and more complex recommendation models are developed, which are difficult to explain. It rema...

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...

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...

As artificial intelligence systems increasingly make high-stakes recommendations and decisions automatically in many facets of our lives, the use of explainable artificial intelligence to inform stakeholders about the reasons behind such systems has been gaining much attention in a wide range of fields, including education. Also, in the field of ed...

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...

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...

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...

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...

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...

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...

Assessments evaluate students’ understanding of taught concepts. While students may be assessed on various concepts and in different learning environments, learning institutions often fail to provide students with a way to connect their learning and assessment results beyond a single institution. This results in problems such as the inability to un...

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...

Little research has addressed how systems can use the learning process of self-explanation to provide scaffolding or feedback. Here, we propose a model automatically generating sample self-explanations with knowledge components required to solve a math quiz. The proposed model contains three steps: vectorization, clustering, and extraction. In an e...

The interactive demo highlights the various data-driven services that are linked to the Learning and Evidence Analytics Framework (LEAF). LEAF enables reading-based learning activities through BookRoll and uses the interaction logs and data from the reading content to generate services for teaching and learning. BookRoll and the learning dashboard...

In the context of K-12 math education, identifying the quizzes of the appropriate difficulty is essential to improve the students' understanding of math concepts. In this work, we propose a quiz recommender system which not only considers the difficulty of the quiz but also the expected learning outcome of solving that quiz. To increase the student...

Previous studies have shown that e-book interaction logs can predict students at-risk of academic failure-students whose academic performance is low. However, in the context of an individualized e-learning system, it is very important to predict personality traits to realize the well optimized and suited assist, intervention and feedback based on p...

Explainable recommendations, which provide explanations about why an item is recommended, help to improve the transparency, persuasiveness, and trustworthiness. However, few research in educational technology utilize explainable recommendations. We developed an explanation generator using the parameters from Bayesian knowledge tracing models. We us...

Previous studies have found that the frequency and the regularity of taking the self-assessment are positively correlated with learning performance. However, as artificial intelligence is widely used for self-assessment in various educational contexts, numerous behaviors have been identified, including nonstandard behaviors that can negatively impa...

The use of blockchain in education has become one of the trending topics in education technology research. However, only a handful of education blockchain solutions have provided a measure of the impact on students' learning outcomes, teaching, or administrative processes. This work reviews how academic data stored on the blockchain is being visual...

The advent of blockchain technology over the last decade has led to the development of multiple use-cases of decentralization in various fields including education. This paper presents a unique bibliometric and qualitative analysis of the blockchain in education with novel contributions on temporal development, emerging themes and practical case st...

Using digital systems to group students according to their indicators provides opportunities for better group work implementation. However, how these indicators can affect group work performance remains unclear. Teachers tend to feel confused about which indicators should be considered when creating groups using learning log data. Capitalized on th...

Collaborative learning in online context has been in educational practice and also gained attention during the emergency remote teaching due to the pandemic. This study follows the Group Learning Orchestration Based on Evidence (GLOBE) framework that considers four phases of technology-supported group work and proposes data-driven services for each...

Emerging science requires data collection to support the research and development of advanced methodologies. In the educational field, conceptual frameworks such as Learning Analytics (LA) or Intelligent Tutoring System (ITS) also require data. Prior studies demonstrated the efficiency of academic data, for example, risk student prediction and lear...

Learning material recommendation has been a common field in the recommendation in e-learning due to the difficulty the learners experience in choosing appropriate learning materials among many resources. However, few traditional recommendation methods can be applied to e-learning as they are because they do not consider the learners' characteristic...

Learning path recommendation systems assist learners in learning in an optimal sequence of knowledge items. Conventional systems do not take into account the knowledge that the learner has already acquired, and thus knowledge that has already been acquired may be included in the recommended learning path. Therefore, in this paper, we focus on Engli...

As intelligent tutoring systems (ITS) fast develop, they have been implemented in many classrooms combing with various tutorial tools. Especially, matching exercises with knowledge components is the fundamental task of many applications, such as automatic recommendation, student knowledge tracing etc. However, manually labelling educational data is...

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 appro...

Open book exams (OBE) have been a mandated part of each course structure at some universities. Also during the COVID19 emergency remote teaching situation, OBE would be an option for many instructors over a proctored examination. In this study we investigate a Critical Analysis of Literature and Cinema course which had offered open book exam compon...

Explainable artificial intelligence has been gaining much attention as systems increasingly make high-stakes recommendation and decisions automatically in a wide range of fields, including education. Meanwhile, research into self-explanation by students as a beneficial intervention to promote metacognitive skills has a long history of research. In...

Learners often change their learning environment over the course of their education. This makes it difficult to measure their engagement across different contexts due to a lack of seamless connection and shared analytics across heterogenous learning systems. Previous research has shown that access to prior engagement information of learners can be...

Knowledge tracing is the task of modelling each student's mastery of knowledge components by analysing a student's learning activities trajectories. Each student's knowledge state is modelled based on his or her past learning performance and is an important research area in improving personalized education. In recent years, many researches have foc...

During the process of learning, students face challenging quizzes that require various knowledge and skills, which results in stuck points. Identifying concepts that cause these stuck points can help identify potential areas of remedial study to overcome the students' difficulties. To achieve the goal of generating a model to identify students' stu...

Explainable recommendations, which provides explanations about why an item is recommended, helps to improve the transparency, persuasiveness, and trustworthiness. However, there are few research in educational technology that utilize explainable recommendation. Previous research has identified that learner motivation can deteriorate while using edu...

When students change school, they are unable to take their learning records with them to the new school except for certificates and/or transcripts. One of the main barriers to connecting and transferring learning records across different institutions is the presence of different learning systems and the inability to ensure privacy and trust among d...

UNESCO reported that 90% of students are affected in some way by COVID-19 pandemic. Like many countries, Japan too imposed emergency remote teaching and learning at both school and university level. In this study, we focus on a national university in Japan, and investigate how teaching and learning were facilitated during this pandemic period using...

This study investigates learner’s reading behaviors in a critical reading task in humanities course using learning analytics techniques. A Critical Analysis of Literature and Cinema course was selected as a context. The course activities evolved over 10 years, and for this instance, some face-to-face classroom critical reading activities were migra...

In recent years, machine learning of increasing complexity is being applied to problems in education. However, there is an increasing call for transparency and understanding into how the results of complex models are derived, leading to explainable AI gaining attention. The application of machine learning to automated group formation for collaborat...

In this paper, we propose an interactive drawing based activity in BookRoll, an e-book-based teaching-learning platform. Participants who were researchers drew an overview of their research as a handwritten memo. We demonstrate the affordances of the learning analytics (LA) enhanced platform to facilitate practice and research of such a drawing act...

Learning vocabulary is a crucial but challenging activity for English as a foreign language learners, and computer-assisted language learning can facilitate this process. Moreover, e-learning is attracting a great deal of attention as a new technology to bring educational support which traditional learning systems cannot provide. Recommender system...

Reviewing learned knowledge is critical in the learning process. Testing the learning content instead of restudying, which is known as the testing effect, has been demonstrated to be an effective review strategy. However, education research recommends that instructors generate practice tests, but this burdens teachers and may also hinder teaching q...

The vocabulary taught in language classes or through digital language learning tools is disconnected from the real-life needs of many language learners. Immigrants, refugees, students abroad learn a language to navigate through their daily lives and often need words that are missing from their curricula they study. Today’s language learners rely he...

Learning a new language is a major challenge faced by many forced migrants. Current vocabulary learning curricula are not adapted to the migrants’ needs, which makes the learning process even more challenging. Today, the widespread use of smartphones among forced migrants provides us with new opportunities to collect and recommend the vocabulary th...

The effectiveness of extensive reading on various linguistic skills is well understood in learning English as a foreign language. However, although the importance of personalized e-learning systems has been emphasized, few ideal recommender systems have been developed. This study proposes a recommender system of picture-books for extensive reading...

Multi-modal analytics has the potential for understanding learning activities and possibly supporting the process based on the interpretation of the signals captured. However, the integration of multiple data sources remains an issue. While some commercial packages assist researchers to organize the data for their specific study, infrastructure is...