Emotions, engagement and well‑being are fundamental to primary students’ learning. Existing work on craft-based interventions and social robots shows benefits for creativity, mood and engagement. However, they rarely target young disaster‑affected learners or integrate craft and AI companions to support socio‑emotional recovery, such as community‑level trauma. This study investigates Loving Baby, an AI‑supported robotic companion embedded in a craft workshop for 96 primary students. The robot provides self-determination theory (SDT)‑informed emotional and scenario support while students design tailored clothes and write heartfelt words. SDT is administered pre‑ and post‑ workshop and shows significant improvements (p <.01) in behavioural, emotional and cognitive engagement, and motivation (p <.05). Internal consistency is excellent (Cronbach’s α =.955), with strong inter‑correlations between subscales (r =.78–.88), indicating a coherent engagement construct. Students also reveal rich emotional labelling (joy, sadness, anger, fear), links between happiness and helping others, and perspective‑taking towards peers and Loving Baby. The findings provide initial evidence that an AI‑supported robotic companion with a craft workshop can enhance engagement and motivation while opening a safe space for emotional expression in a post‑disaster primary context.

Dyslexia is a common neurobiological learning disorder significantly impacting reading, writing, and spelling worldwide. Early identification and intervention are essential, but most pre-screening tools focus on Latin languages, leaving Chinese-speaking students underserved. To address this gap, we conduct semi-structured interviews with special education (special-ed) teachers to gather their needs for dyslexia pre-screening tailored to Chinese contexts. Using their insights, we have developed DysVis, a user-centered data visualization system that combines handwriting analysis, body movement keypoint conversion, and a comprehensive visualization interface. DysVis provides teachers with multi-level visualizations, such as performance overviews, task analyses, handwriting observations, and behavioural insights, enabling them to identify the root causes of learning difficulties. Our evaluations, including case studies, a user study, and expert interviews, demonstrate that DysVis is user-friendly and effective in quickly identifying at-risk students, ultimately enhancing learning outcomes for Chinese-speaking students with dyslexia.

The previous work developed a language learning system with human-like robots utilizing self-determination theory (SDT) to enhance student’ learning engagement and proficiency. Initial evaluations indicated that typical students encountered stimulated interest and efficacy with the robot. To test the consistency of these findings, we conducted a replication study using the same system, robot, and tasks but with students with dyslexia. Through questionnaires, observations, and proficiency tests, the results confirmed that the interactive robot also improved learning motivation and performance in those with dyslexia, with the same system, robot, and tasks.

Students with autism spectrum disorders (ASD) often feel insecure in new environments due to social challenges, unfamiliarity, and a lack of support or understanding. Despite considerable efforts dedicated to assisting students in adapting to new environments and understanding appropriate behaviours in public settings, there remains a lack of interactive and personalized learning systems. In this work, we developed a robot-assisted scenario training (RAST) system to facilitate inclusive learning and arouse students' learning interests. With the RAST system, we seek to identify effective interactions that can improve students' engagement. To this end, we invited 13 students with ASD to participate in an evaluation study. In the study, self- determination theory (SDT) measures students' learning engagement. Learning engagement and effectiveness are evaluated using variance analysis (ANOVA). Students also participated in interviews to report their user experience regarding the system. The results reveal that learning with the RAST system can significantly arouse students' intrinsic motivation and improve their behavioural, emotional, and cognitive engagement. Additionally, students with ASD increased their learning performance by 8.33%. Furthermore, students exhibited a high level of engagement in scenario training with certain types of interactions, including personalized functions, visual cues and sound quality. Overall, the RAST system demonstrates promising capabilities in enhancing students' learning engagement and proficiency with ASD.

Storytelling is vital to children’s development by nurturing creative thinking, effective communication, and self-expression. Many tools have been created to support children’s creativity. Unfortunately, the existing tools do not adequately integrate visual elements with storytelling, limiting children’s imaginative potential. This study addresses the gap by introducing a proxy visual storytelling tool (PVST) that employs a character-based approach (i.e., proxy character assembling) to enhance children’s creativity and storytelling skills. Through a comparative study using Kurt Vonnegut’s “The Shape of Stories" theory, the PVST was evaluated. The results from a pilot test show that the PVST can increase children’s sense of agency and engagement in the storytelling learning process. Additionally, it can stimulate children’s creative imagination, improve their storytelling abilities, and enable them to construct more fluent and articulate narratives. The findings highlight the importance of incorporating visual storytelling elements in enhancing children’s creativity and storytelling skills, ultimately fostering a more engaging and enriching learning experience.

Most students with specific learning disabilities (SLDs) have difficulties in reading and writing. The SLDs pre-screening is crucial because the golden period for therapy is before six years old. However, many students in Hong Kong receive SLDs assessments after the golden period. Also, the SLDs pre-screening is challenging, especially in a language with the logographic script but without prominent sound-script correspondence (e.g., Chinese, Japanese). To make pre-screening SLDs in Chinese more effective and efficient, we designed a new comprehensive pre-screening game for SLDs in Chinese (i.e., dyslexia, dysgraphia, and dyspraxia). Notably, we designed a Chinese morphological awareness puzzle that challenges students to recognize different words made up with the first character that is identical and the second character that is different, such as樹枝 (literally means tree branch),樹幹 (literally means tree truck),樹葉 (literally means tree leaves), and樹根 (literally means tree root). We experimented with students, which showed that our game can effectively pre-screen students with SLDs in Chinese. Our work contributes an approach to quick SLDs in Chinese pre-screening, potentially useful for other logographic languages (e.g., Japanese).

Students with specific learning disabilities (SLDs) often experience reading, writing, attention, and physical movement coordination difficulties. However, in Hong Kong, it takes years for special education needs coordinators (SENCOs) and special-ed teachers to pre-screen and diagnose students with SLDs. Therefore, many students with SLDs missed the golden time for special interventions (i.e., before six years old). In addition, although there are screening tools for students with SLDs in Chinese and Indo-European languages (e.g., English and Spanish), they did not provide a student data visualization dashboard that could help teachers speed up the pre-screening process. Therefore, we designed a new visualization dashboard for Hong Kong SENCOs and special-ed teachers to assist them in pre-screening students with SLDs. Our formative study showed that our current design met teachers’ need to quickly identify a student’s specific under-performing tasks and effectively collect evidence about how the student was affected by SLDs. Future work will further test the efficacy of our design in real life.

The learning of Chinese is an abstract learning mode for primary school students. Correct writing stroke is an elementary but difficult task for most of students. This study tried to create a more efficient and interesting learning environment through human-computer interaction technology with mastery learning approach, and a self-pace learning mode to construct a learning system, where rich, efficient and effective interactions in learning were considered. The prototype was designed for tablets with human-computer interaction technology with the purpose to facilitate learning of a fundamental set of Chinese characters. This paper shown an interesting way to enhance self-learning Chinese character writing via human-computer interaction technology. The final outcomes of the project included the improvement of Chinese characters learning tool and feedback from parents, teachers and students.

Unlike other phonetic alphabet languages, the pronunciation and writing of Chinese are different learning modes. This study intends to motivate primary students to learn Chinese characters and improve learning performance by integrating Augmented Reality (AR) technology with 3D models. The paper first describes the exertion of AR and 3D models to construct a Chinese character recognition application and then presents the findings of the pilot test in assessing the effectiveness of AR and 3D models in learning Chinese characters. Data collection methods are pre-test, post-test, teacher focus group, and student focus group. The study reveals that the prototype of this AR learning application enables students to have a better understanding of the recognition of Chinese characters. This enhances the learning motivation, concentration, and interest of school children. In summary, the study shows an interactive and interesting way to promote Chinese character learning via the AR environment and 3D models. Implications for future development in using AR and 3D models in supporting Chinese language learning discusses at the end of the paper.