This study examines how AI-based teachable agents with distinct personality traits influence middle school students’ emotions and mathematics learning. Grounded in the Big Five personality framework, six agents were developed: five designed to emphasize one of the Big Five traits and one without a personality emphasis. Students engaged in teaching the agents to solve mathematical problems. Guided by the Control-Value Theory of Achievement Emotions, students’ emotions were coded by valence (positive vs. negative) and activation (activating vs. deactivating) based on their conversations with the agents, while mathematics learning was assessed through coded applications of knowledge during interaction and a posttest. Results showed that extraversion-, openness-, and agreeableness-emphasis agents promoted positive activating emotions (e.g., enjoyment), whereas conscientiousness-emphasis agents were particularly effective in reducing both negative activating emotions (e.g., anxiety) and negative deactivating emotions (e.g., boredom). Emotions were further linked to learning outcomes: positive activating emotions positively predicted knowledge application and posttest performance, whereas negative deactivating emotions negatively predicted students’ knowledge application. These findings highlight the nuanced role of teachable agent personality in shaping students’ emotional experiences and provide design implications for developing teachable agents that effectively support affective and academic dimensions of mathematics learning.

Building on growing evidence of the effectiveness of teachable agents for learning, this study investigated their use of instructional, cognitive, and pastoral conversational strategies, three dimensions of support that learning theories (e.g., the Community of Inquiry framework and Self-Determination Theory) identify as interconnected and critical for student learning, to inform the design of pedagogical conversational agents. By analyzing over 8,000 conversations between teachable agents and students, we found that agents’ cognitive and instructional strategies strongly promoted students’ cognitive elaboration, whereas pastoral strategies were associated with surface-level cognitive engagement and higher affective engagement. Moreover, two-strategy combinations (e.g., cognitive + instructional, instructional + pastoral) were generally more effective for fostering cognitive, affective, and metacognitive engagement than any single strategy, while combining all three strategies often weakened effects. Integration of cognitive and pastoral strategies further enhanced procedural knowledge application, whereas instructional strategies supported conceptual knowledge. Overall, these results clarify the complementary yet distinct roles of instructional, cognitive, and pastoral strategies and provide insights for pedagogical agents to dynamically pair functional strategies to support student learning.

Some online learning platforms frequently recommend educational materials to attract student engagement, with visual elements playing a critical role in capturing attention. To optimize the visual design of mathematical stories, this study examines the relationship between visual features and click frequency, based on log data from a U.S. platform featuring AI-generated mathematical stories for elementary students. Our methodology involves a multi-level visual feature extraction framework, categorizing features into low-, mid-, and high-level. Low-level features capture fundamental visual elements like color, texture, shape, and composition, commonly used for their simplicity. Mid-level features, inspired by psychological and artistic theories, more directly link to emotional impact, including attributes like brightness and contrast. High-level features focus on semantic content, using AI models to extract aesthetic scores and identify entities. Based on the correlation analysis between visual features and clicks, our findings indicate that images featuring characters and natural landscapes positively correlate with student interest, aligning with theories of situational interest. In contrast, images with pronounced brightness contrasts negatively impact engagement, likely due to increased cognitive load. The study highlights the limited influence of mid-level aesthetic features on elementary students' engagement, emphasizing the importance of visual clarity and educational relevance over purely aesthetic considerations.

Students' participation in online discussions often varies over time. Leveraging over three million discussion interactions from an online math learning platform, the current study aims to investigate the sustainability of student participation in an online mathematical discussion board by examining how students evolve from newcomers in the discussion board into old-timers over an academic year. Additionally, it seeks to explore how the timing of students' joining the discussion board and their early technology and social participation behaviors influence their continued participation, based on Communicative Ecology Theory (CET), which conceptualizes the sustainability of an online community as being influenced by factors related to communicating technology, social interactions, and exchanged information. The results revealed that students decreased their participation or even left the discussion board over time, underscoring the need to maintain students' participation in online mathematical discussions. Students' social interactions and their technology use in the online discussion board were found to influence their sustained participation. The timing of students joining and their role as newcomers or old-timers were also found to affect their participation behaviors and sustained participation. Future investigations have been planned to further use machine learning to examine students' discussion content and understand the role of discussion content on students' continued participation.

Participating in online mathematical discussions is considered a beneficial strategy to improve online math learning. However, achieving high levels of interaction in these discussions is uncommon, and maintaining them is often challenging. To shed light on the potential mechanisms to sustain online mathematical discussions, this study draws on Communicative Ecology Theory (CET), which conceptualizes the sustainability of online communities as influenced by technical, social, and discursive factors, to examine how students' technical, social, and content-related participation patterns on an online mathematical discussion board are correlated. The results indicated that students' engagement with the communication tool and the motivation system significantly facilitated their social interactions and enhanced their demonstration of mathematical knowledge, mathematical literacy, and affect control. These findings demonstrate the interplay among the three types of participation patterns and provide insights for educators and designers of educational applications to enhance student participation in online discussions thereby improving the effectiveness of these discussions in online learning. Future investigations are planned to focus on how such interplay varies over time.