As generative artificial intelligence (AI) is increasingly incorporated into higher education, renewed attention is required to understand how human capabilities are conceptualized relative to AI. This study has two aims. First, it examines the psychometric properties of the second edition of the Eight Multiple Intelligences Questionnaire among Taiwanese university students. Second, the study explores students' perceptions of human-AI strengths across intelligence domains. Data were collected from 936 students at a private university in Taiwan. Exploratory factor analysis supported an eight-factor structure, explaining 80.34% of the total variance. Reliability was satisfactory, with Cronbach's α and composite reliability greater than .90. Students perceived AI as stronger in linguistic, logical-mathematical, and spatial domains, while humans were viewed as stronger in interpersonal, intrapersonal, bodily-kinesthetic, naturalistic, and existential domains. These findings support the instrument while clarifying human-AI capability boundaries. The results offer implications for designing AI-assisted, human-led courses and online pedagogy.
The COVID-19 pandemic transformed higher education globally, and even after in-person instruction resumed in Fall 2021, the number of online courses continued to grow. This shift, combined with ongoing socioeconomic and health challenges, impacted student learning. This study analyzed data from 212 students in an undergraduate online synchronous management science course at a public university in the western U.S. to examine how personality traits, cognitive factors like learning approaches, and meta-cognitive factors, such as self-regulation and goal orientations, influenced performance and satisfaction post-pandemic. Stepwise regression models showed that certain goal orientations affected learning, while others influenced satisfaction. Intrinsic value had a significant negative effect on both. Logistic regression revealed factors influencing future online course preferences, including goal orientations, agreeableness, controlled regulation, intrinsic value, GPA, and gender. Implications for online education and classroom teaching are discussed.
In this research, action-narrative inquiry was utilized to examine the integration of information technology within a primary educational setting. The study focused on the utilization of the Planets of Tomorrow educational platform by a teacher in her instructional practices. It examined the strategies employed to introduce students to the platform and the techniques used to enhance their reading and writing proficiencies. The study was conducted at an elementary school in northern Taiwan, with one teacher and 28 first-grade students. The educational environment was elucidated through four dialogue dimensions: internal dialogues, dialogues with the platform development team, dialogues with parents of students, and dialogues with the research team. Examination of the data revealed a three-phase process of technology integration and provided recommendations for future research efforts on integrating technology into Chinese language learning.
In this research, action-narrative inquiry was utilized to examine the integration of information technology within a primary educational setting. The study focused on the utilization of the Planets of Tomorrow educational platform by a teacher in her instructional practices. It examined the strategies employed to introduce students to the platform and the techniques used to enhance their reading and writing proficiencies. The study was conducted at an elementary school in northern Taiwan, with one teacher and 28 first-grade students. The educational environment was elucidated through four dialogue dimensions: internal dialogues, dialogues with the platform development team, dialogues with parents of students, and dialogues with the research team. Examination of the data revealed a three-phase process of technology integration and provided recommendations for future research efforts on integrating technology into Chinese language learning.
Systems thinking is a fundamental cognitive skill that is essential for problem-solving contexts. Notably, there is a lack of instruction in systems concepts from the elementary to the tertiary levels. This study aimed to develop and to implement a course to guide undergraduate students to enhance their understanding of systems thinking. The authors designed a virtual reality game as an instructional tool. The course integrated didactic instruction, discovery learning, and digital game-based learning approaches. The results indicated that most participants demonstrated improved comprehension of system concepts. Virtual reality games provide learners with an engaging and interactive learning experience for system concepts.
This quasi-experimental study examined the impact of embedding ChatGPT within the “bridge-in, objective, pre-assessment, participatory learning, post-assessment summary” (BOPPPS) framework to enhance the speaking proficiency of 89 Taiwanese university English-as-a-foreign-language (EFL) learners. Over 18 weeks, the experimental group (n = 44) received structured, theory-aligned instruction with stage-based ChatGPT and BOPPPS integration, while the comparison group (n = 45) engaged in unstructured artificial intelligence (AI)-supported practice. Post-test results show significantly greater gains across all five speaking sub-skills for the experimental group, particularly in interactive communication (p = .004, η2 = .105) and discourse management (p = .037). Thematic analysis indicates that BOPPPS reframed ChatGPT from a static tool into a meta-cognitive dialogue partner. These findings suggest structured AI integration may reduce speaking anxiety and foster more autonomous, confident language use. The study offers a replicable framework for AI-assisted pedagogy, especially in large-scale or online EFL instruction.
This study examines the potential of generative artificial intelligence (AI) to enhance Chinese poetry instruction by investigating its impact on students' learning interest, collaborative perception, and writing abilities. Through AI's text-to-image and image-to-poetry translation capabilities, the research explores how AI-generated visuals can deepen students' understanding of poetic imagery and foster creative expression in poetry writing. Using a mixed-methods approach, the study analyzes pre-test, mid-test, and post-test assessments, student surveys, and student-generated poetry to evaluate the effectiveness of this innovative pedagogical approach. The findings contribute to the growing field of educational technology in humanities education, offering insights into how AI can support multimodal learning, enhance students' linguistic creativity, and enrich their poetic sensibilities. By integrating AI technology with traditional literary instruction, this study provides a foundation for further research on the role of generative AI in language and arts education.
This study explored drone-based learning in educational contexts using a mixed-method design to identify key learning attributes. After completing researcher-developed drone tasks, 73 learners demonstrated a significantly improved understanding of drone concepts and proficiency in Blockly coding. However, learners perceived self-efficacy as significantly lower than other self-regulated strategies in drone activities. Task-based drone activities, facilitated by group settings, encouraged learners to develop metacognition through collective scaffolding methods, such as peer discussions and team testing. The identified learning attributes provide valuable insights for educators in designing assessments for collaborative drone problem-solving. Additionally, the interplay among effort regulation, problem-solving, and cooperativity observed in this study offers essential references for the future development of distributed expertise systems.
Writing in the digital age has transformed from a mere communicative practice into a computational interface for multimodal creation-establishing a new paradigm where natural language functions as executable code for artificial intelligence systems. This research examines the pedagogical implications of this "Writing is Coding" framework, focusing on how learners navigate cross-media AI co-creation processes. Through a comprehensive three-round experiment, 102 undergraduate students engaged in progressive AI collaboration across textual, visual, and video modalities, using natural language as their primary creative instrument. Employing grounded theory methodology, the researchers analyzed data from student reflection journals, teacher observation logs, and semi-structured interviews to identify emergent patterns in AI-human creative partnerships. Five interconnected themes emerged: (1) prompt engineering as algorithmic thinking, (2) multimodal literacy development, (3) collaborative negotiation of creative agency, (4) emotional engagement through iterative refinement, and (5) metacognitive awareness of human-AI boundaries. Findings suggest that the "Writing is Coding" framework facilitates a deeper understanding of computational processes while enhancing creative expression. The three-round progression demonstrated increasing student comfort with AI collaboration, though tensions around authorship and creative identity persisted. This research contributes to emerging pedagogical approaches that position writing as a form of programming in AI-enhanced learning environments, with implications for curriculum design and digital literacy development.
This study examines the potential of generative artificial intelligence (AI) to enhance Chinese poetry instruction by investigating its impact on students' learning interest, collaborative perception, and writing abilities. Through AI's text-to-image and image-to-poetry translation capabilities, the research explores how AI-generated visuals can deepen students' understanding of poetic imagery and foster creative expression in poetry writing. Using a mixed-methods approach, the study analyzes pre-test, mid-test, and post-test assessments, student surveys, and student-generated poetry to evaluate the effectiveness of this innovative pedagogical approach. The findings contribute to the growing field of educational technology in humanities education, offering insights into how AI can support multimodal learning, enhance students' linguistic creativity, and enrich their poetic sensibilities. By integrating AI technology with traditional literary instruction, this study provides a foundation for further research on the role of generative AI in language and arts education.
This study explored drone-based learning in educational contexts using a mixed-method design to identify key learning attributes. After completing researcher-developed drone tasks, 73 learners demonstrated a significantly improved understanding of drone concepts and proficiency in Blockly coding. However, learners perceived self-efficacy as significantly lower than other self-regulated strategies in drone activities. Task-based drone activities, facilitated by group settings, encouraged learners to develop metacognition through collective scaffolding methods, such as peer discussions and team testing. The identified learning attributes provide valuable insights for educators in designing assessments for collaborative drone problem-solving. Additionally, the interplay among effort regulation, problem-solving, and cooperativity observed in this study offers essential references for the future development of distributed expertise systems.
This study used action narrative inquiry to examine how a mathematics tutor (2014–2024) in a shadow education setting built professional learning communities (PLCs) and promoted technological, pedagogical, and content knowledge (TPACK) through technology. Data from meeting records, online notes, videos, and diaries reveal a four-phase process: formation (awareness of PLCs), construction (building TPACK via dialogue), implementation (applying TPACK with remote teaching and blended methods), and reflection (adjusting instruction based on feedback). The findings stress the importance of a TPACK community, in-person meetings for trust, and addressing student needs in tech integration.
This study examines the pedagogical competence of elementary school teachers in managing online classes during the Covid-19 pandemic in the Kota Timur Selatan sub-district, Gorontalo City. Employing a mixed-method approach, data were gathered from 59 teachers through observations, questionnaires, and documentation to assess their effectiveness in online teaching. Quantitative descriptive analysis shows that teachers' pedagogical competence in online learning remains relatively low, with an overall effectiveness value of just 6.4% and a frequency rate of 64.64%. The findings emphasize significant challenges faced by teachers in adapting to online teaching methods, such as difficulties in delivering materials, engaging students, and utilizing online platforms. The study underscores the need for improved teacher training programs focused on enhancing pedagogical skills in virtual environments, particularly during crisis situations like the pandemic. These improvements are crucial for ensuring quality education and better student outcomes in online learning settings.
Writing in the digital age has transformed from a mere communicative practice into a computational interface for multimodal creation—establishing a new paradigm where natural language functions as executable code for artificial intelligence systems. This research examines the pedagogical implications of this “Writing is Coding” framework, focusing on how learners navigate cross-media AI co-creation processes. Through a comprehensive three-round experiment, 102 undergraduate students engaged in progressive AI collaboration across textual, visual, and video modalities, using natural language as their primary creative instrument. Employing grounded theory methodology, the researchers analyzed data from student reflection journals, teacher observation logs, and semi-structured interviews to identify emergent patterns in AI-human creative partnerships. Five interconnected themes emerged: (1) prompt engineering as algorithmic thinking, (2) multimodal literacy development, (3) collaborative negotiation of creative agency, (4) emotional engagement through iterative refinement, and (5) metacognitive awareness of human-AI boundaries. Findings suggest that the “Writing is Coding” framework facilitates a deeper understanding of computational processes while enhancing creative expression. The three-round progression demonstrated increasing student comfort with AI collaboration, though tensions around authorship and creative identity persisted. This research contributes to emerging pedagogical approaches that position writing as a form of programming in AI-enhanced learning environments, with implications for curriculum design and digital literacy development.
This study examines the pedagogical competence of elementary school teachers in managing online classes during the Covid-19 pandemic in the Kota Timur Selatan sub-district, Gorontalo City. Employing a mixed-method approach, data were gathered from 59 teachers through observations, questionnaires, and documentation to assess their effectiveness in online teaching. Quantitative descriptive analysis shows that teachers' pedagogical competence in online learning remains relatively low, with an overall effectiveness value of just 6.4% and a frequency rate of 64.64%. The findings emphasize significant challenges faced by teachers in adapting to online teaching methods, such as difficulties in delivering materials, engaging students, and utilizing online platforms. The study underscores the need for improved teacher training programs focused on enhancing pedagogical skills in virtual environments, particularly during crisis situations like the pandemic. These improvements are crucial for ensuring quality education and better student outcomes in online learning settings.
This study aimed to develop and validate a Board Games Attitude Scale for primary school teachers (hereinafter, BGAS-PT) to assess their perspectives on using board games in educational settings. Board games had already been integrated into Taiwan's senior high school disaster prevention curriculum. However, their adoption in primary classrooms remained limited, largely due to varying teacher perceptions concerning curriculum alignment and pedagogical value. The methodology involved validating items from previous scales to fit the context of primary education. Findings indicated that teachers generally recognized significant cognitive benefits from using board games, particularly in enhancing teaching strategies and classroom dynamics. Teachers who actively incorporated board games in their teaching reported higher levels of positive engagement and perceived cognitive benefits. Moreover, early-career teachers showed a greater openness to integrating games, suggesting that newer educators were more inclined to adopt innovative tools.
Artificial intelligence (AI) models struggle to reach performance levels due to the complex nature of Arabic grammar and diverse regional dialects. This study investigated how generative AI (GenAI) functions as a teaching assistant in Arabic language classrooms. Using qualitative methods, semi-structured interviews were conducted with 15 instructors; the data was then analyzed using thematic analysis. Results revealed that instructors used GenAI to create material, assess students' work, and create personalized learning plans. Instructors struggled, however, with AI accuracy in dialect processing, cultural authenticity, and ensuring accurate assessment methods. The analysis raised significant gaps in teacher training, assessment strategies, and institutional guidelines. Instructors found it challenging to evaluate AI-generated Arabic content across different dialects and maintain academic integrity in student assignments. This study recommends developing instructor training, specifically on using GenAI tools for Arabic dialect variations and creating culturally appropriate Arabic language learning materials.
Learner-centered education through appropriate methodologies will facilitate effective learning in higher educational institutions. Learners in any educational institute come from varied backgrounds, abilities, and various personal attributes that will affect the pace of learning. To achieve learner-centric education, instructors have to use appropriate methodologies to engage students actively in learning. Methodologies include individual and collaborative learning types. This paper focuses on active learning strategies and their impact on achieving learner-centric education. Strategies are used based on session outcomes and assessment plans to achieve the outcomes planned. The paper also discusses the strategies available for instructors to develop independent learning, interactive learning, and collaborative learning among students.
Engagement is an essential aspect of students' success in learning. Even though students' engagement with learning has been widely investigated, the level of learners' online engagement and the relationship between learners' online engagement and their achievement, especially in the English as a foreign language (EFL) context, using a learning management system (i.e. Blackboard), remains unexplored. To fill that gap, this study examines the effects of learner engagement, using its three dimensions (behavioural, emotional, and cognitive), on students' achievement in learning EFL in online courses. In total, 189 college students participated in the study. Data was analysed using the second-generation analysis technique structural equation modelling (SEM) to examine the relationships among constructs and test the hypothesis. Results revealed that students' engagement significantly affected their achievement in learning EFL in an online environment.
This study explores how problem-based learning (PBL) in a hybrid-flexible (HyFlex) environment has affected critical thinking skills among Chinese university students. Recognizing the importance of critical thinking in producing quality design solutions, the authors involved a mixed-methods approach including quantitative research using analysis of covariance (ANCOVA) and qualitative analyses. Pretests and posttests with 30 students revealed significant improvements in critical thinking. The findings led to seven proposed teaching strategies, offering insights into the effectiveness of PBL and its implications for future educational practices.
