Artificial Intelligence (AI) in education and learning analytics (LA) tools are increasingly being developed and implemented to enhance teaching and learning within Singapore’s education landscape. This paper provides an overview of key AI in education and LA projects and initiatives in Singapore, organized by the types of technology. The identified projects and initiatives involve a range of techniques and systems to achieve personalized learning, improve student engagement, optimize resources, and also predict student success among a list of educational outcomes. We briefly describe each identified project before further discussing the collective impact and limitations, as well as the implications for Singapore and her education environments. Overall, this paper seeks to provide an overview of the state and use of AI and LA in education-related projects within Singapore and highlights the need for further research and development in this area to fully realize the potential of these technologies for improvement of teaching and learning.

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 main research streams to support education. In this paper, we collected data and defined student learning patterns by leveraging online courses on Python programming and we then verified if their learning performance was influenced by different learning patterns and interventions. We designed the intervention process, explored the impact of final learning outcomes, and analyze Self-Regulated Learning (SRL) abilities. From the experimental results, we share the learning outcomes and the difference in SRL with detailed explanation based on different groups.

This study aimed to provide a comprehensive analysis of the Information and Communication Technology (ICT) environment for customized learning in elementary and secondary schools in South Korea, focusing on the initiative of one personal computer (PC) per student. Despite the country’s advanced digital infrastructure, which includes resources such as the Edunet platform, with extensive customized teaching content and functionalities, both the device-to-student ratio (0.34 devices per student) and students’ ICT usage in class were relatively low. One key reason for this low ratio and usage is the teacher-centric approach to ICT in classrooms compared with other countries. Such an approach can diminish student autonomy in personalized learning and lead to superficial customization. Although artificial intelligence (AI) powered assessments from AI digital textbooks may facilitate customized learning through analyzing student learning records starting in 2025, these challenges are unlikely to be resolved automatically. Enhancing teachers’ skills in designing individualized learning plans, providing personalized guidance for teachers, and fostering collaborative learning among students is necessary to address these issues.

In this paper, we 1) review the trend of informatization in elementary and secondary education in Japan, 2) summarize the individualization of learning in today’s educational policy, and 3) attempt to map the outcomes of educational technology research to the present day. The trend of individualization of learning in elementary and secondary education in Japan is characterized by the following two points: (1) the appropriate treatment of learning content, represented by CAI (Computer Assisted Instruction), which has been studied in the field of educational technology for a long time, has been put to practical use; and (2) the results of recent research on self-regulated learning based on the achievements of the psychology of learning that are now being reflected in elementary and secondary education.

In order to assess the extent to which text-mining techniques can be used to gain insights into a particular topic area, we apply hierarchical word clustering and the Term Frequency-Inverse Document Frequency (TF-IDF) measure to articles on computer programming published since the 1970s, when research articles on teaching programming are now more readily available in PDF files. Study 1 compares two sets of papers published before and after the introduction of the concept of Computational Thinking in 2006 to highlight the changes seen in these research sets. Articles mentioned in frequently cited review papers were selected as the target articles to ensure the quality of the sample. Study 2 extends the sample pool to include a range of papers published after the 1970s, allowing us to examine the stability of the conceptual structures identified in Study 1. In both studies, the obtained word clusters or concepts align with known research trends in the programming-education literature. The significance and potential of text-mining techniques are also discussed.

This study proposes a new method for detecting and preventing proxy test-taking in online examinations using a tablet device that authenticates the identity of examinees based on multiple types of touch gestures. We proved that the support vector machine has the best performance among classifiers for authentication when various touch gestures are used and various positions on the screen are touched. The results also showed that if support vector machine is used as the classifier, a handshape image taken from above or from the side can be used for identity authentication. In the future, we will improve the experimental environment to make it more similar to an actual online examination and investigate the possibility of performing authentication using touch gestures at arbitrary points on the touch screen of a tablet device.

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. This reflective teaching workflow uses a Learning and Evidence Analytics Framework (LEAF), a specific learning platform that is currently used in multiple Japanese and international educational institutions. This workflow provides a bottom-up approach for producing evidence from routinely collected data on the LA platform. We illustrate a case study in a Japanese high school math class to demonstrate the practical use of this reflective teaching workflow. We draw implications from this reflective workflow towards producing rich and robust evidence in the LEAF system, which should lead to the democratization of evidence-based practice in the classroom.

This study examined whether students’ learning strategies and class engagement were improved by teachers providing open-ended questions in advance and facilitating class-preparation. The participants were 42 university students (Mean age= 19.3, SD = 0.6) from an educational psychology class. In the first baseline assessment class, students responded to a scale that measured their intellectual curiosity. During Intervention 1, a simple explanation and several open-ended questions about the content were provided before class. During Intervention 2, the students received specific assignments for class-preparation. Results showed that the scores for learning strategies and class engagement were higher after the first and second interventions than after the baseline assessment. Moreover, class-preparation assignments and the provision of advanced open-ended questions were effective for students with low intellectual curiosity.

Participating in peer-review activities can enhance students’ learning outcomes. However, past studies have not thoroughly explored how student performance in peer-review activities and their open-ended tasks relate to online classes. Using synchronous and asynchronous communication tools, we analyzed how students’ collaborative learning activities and participation in a peer-review activity are associated with their learning outcomes in an online undergraduate course. By developing open-ended tasks in small groups, students created Open Educational Resources through a series of peer-review activities. Students’ contributions to collaborative activities were assessed using self-reports and a questionnaire. The findings highlighted the importance of active participation in peer-review activities in online learning that combine synchronous and asynchronous communication tools, which can enhance the completion of open-ended tasks.

This study examines the influence of class orientation and academic engagement on students’ sense of fulfillment in learning and self-growth at the university level. A total of 212 university students were asked which idea of class orientation suited them better: “I like classes where it is easier to get units even if I am not interested in classes,” or “I like classes where I am interested even if it is difficult to get units.” They were also administered a scale that measured academic engagement, sense of fulfillment in learning, and self-growth at the university level. The findings revealed that holding a more autonomous idea of class orientation promotes academic engagement, specifically cognitive and social engagement (for friends), which then leads to a sense of fulfillment in learning and self-growth at the university level.

This study revealed the actual conditions of work-life balance (WLB) and the support required for improving the work environment of faculty members engaged in various types of work such as education, research, and university operations under the discretionary labor system. A survey was conducted among the faculty members of three universities. The results obtained indicate the following: Faculty members tend to be more satisfied with their WLB than general workers and experience occupational stress due to obstruction of their research activities; specifically, such obstruction includes suspension of independent research and less time for research due to life events, other tasks, and adverse effects caused by the lack of support for people around faculty members who receive support. In addition, worry over the amount of workload results in negative attitudes toward promotion to a senior position, and women, especially, are reluctant to get promoted due to gender bias.

Artificial intelligence (AI) has the potential to contribute to solving various problems spreading through society today. To that end, students should acquire knowledge of AI from an early age and be sensitized to careers in this field. Therefore, this study implemented an educational practice using AI for career development in an elementary school. Four items were used to verify the educational effectiveness of the practice: intrinsic value, attainment utility value, expectancies for success, and career development. The results of the analysis confirmed an increase in the observed items. Thus, the educational practice proposed in this study is considered valid in terms of educational effectiveness from the perspectives of motivation, career development, and so on.

A dialogue system that responds mechanically to given queries can be used for public relations for prospective university students. However, as a user-specific problem, collecting information from first-time entrances and passive examinations is difficult, and a conventional dialogue system may not collect sufficient information. Therefore, we developed a recommendation-type dialogue system that supports information gathering by evoking potential user requests. Based on the preference analysis results using previous and real-time query histories and recommended information from universities, information in the form of queries is recommended to users when considering their personal attributes. We evaluated the presence or absence of a recommendation function and implemented an introduction evaluation targeting public relations for those who wish to enroll in a university. The average number of queries increases by evoking potential requests, and the information gathering of the user is supported.

This study aimed to create Augmented Reality (AR) materials aimed at understanding the scientific conceptions of electric current, devise teaching methods using the created AR materials, and verify the effectiveness of the teaching methods through class-room practice. To achieve these objectives, this study created AR materials that superimpose electric current models on experimental apparatuses and worksheets using a tablet PC, and devised a teaching method that focuses on clarifying the students’ mis-conceptions. The results showed that the AR materials and teaching methods contributed to the understanding of the directional concept of electric current. They also contributed to understanding some of the concepts of continuity and conservation of current.

In education, the importance of inquiry learning, in which students pursue their own interests, is emphasized. In this study, a special two-hour class supported sixth-grade students in a public elementary school in determining the topic of an independent research project for their summer vacation. Students were asked to establish a question about the theme they wanted to research, develop a hypothesis about the question, and choose a method to verify it. After the summer vacation, students conducted self-evaluation using Likert-scale items. The intervention group had higher scores on both the comprehensive and perspective-based self-evaluations than students who did not take the class (the control group). Additionally, in free writing many students in the intervention group mentioned the main learning points in class when asked for tips to conduct independent research effectively, which reflected their consciousness of their own inquiry skills.

This study examined the achievements and issues in online case development and online practice in elderly care facilities, which were implemented as alternative measures during COVID-19, in addition to regular hospital care. When said achievements were assessed using the gerontological nursing core curriculum scale, hospital practice, which included patient interaction, scored higher than online practice in “risk assessment of health disorders” and “comprehensive assessment of elderly people.” However, the online case development practice, where nurses could work at their own pace, scored as high as hospital practice in the “exploration of nursing to allow an individual to live true to themselves.” Furthermore, when the advantages and disadvantages of each form of practice were examined using quantitative text analysis, online practice caused anxiety due to the inability to grasp the progress of others, as well as difficulties in discussions. These factors hinder active learning, such as group work, which is necessary for team medicine and multidisciplinary cooperation in integrated community care.

This study examined the effects of an integrated lesson conducted for six months in a fourth-grade social studies class. The examination was made with respect to two issues: how the lesson’s conceptualization and generalization may aid with thinking skills in social studies, and how the use of learning strategies matches the problem-solving process. The children answered questions covering two major study units in their notebooks. The results indicated that the children’s conceptualizations and generalizations were stimulated. This study also proposes a learning method that matches the problem-solving process in social studies and examines the effects of gradually delegating the use of learning strategies to students. The results indicated that the children began to use learning strategies and that the quality of their learning plans improved.