Inputs and Outputs
The Impact of Group Cooperative Learning on the Participation Attitude, Learning Outcomes, and Interaction Method of Blended Teaching View Digital Media
Paper Presentation in a Themed Session Joni Tzuchen Tang, DeJun Mo
The nationwide implementation of distance learning in response to the COVID-19 pandemic has catalyzed significant transformations in the educational landscape. Educational practitioners, students, and campus infrastructures have undergone notable changes to accommodate digital learning modalities, reducing the challenges associated with blended teaching in the post-pandemic era. Additionally, the disparities in digital resource accessibility between urban and rural areas have been mitigated to some extent. Consequently, the issue of blended teaching has garnered increasing importance. Grounded in spatial production theory and the IBIS discussion model, this study employs questionnaire surveys, observational records, and semi-structured interviews to preliminary explore group cooperative learning among elementary school teachers and students in the context of blended teaching. The findings indicate that group cooperative learning continues to yield positive learning outcomes and influences subgroup differences within the framework of blended teaching. Moreover, the study reveals the diverse possibilities of integrating other instructional designs and methods into blended teaching, leveraging the pandemic-induced educational disruptions as opportunities for transformation. Educators can enhance the learning motivation and effectiveness of students with diverse needs by developing diverse instructional activities.
Featured AI in Shadow Education: An Experimental Study in Hong Kong Tutorial Centres
Paper Presentation in a Themed Session Ching Ho Cheng
Shadow education is very demanding in Hong Kong, since most of the parents and students do not want to be eliminated in the public exam. However, there are different forms of shadow education in Hong Kong. The quality of those lessons has often been questioned by educators, parents and students. The ways of increasing the quality of shadow education have become a topic that widely discussed by scholars and educators. In this study, 10 local tutorial centres participated in using Artificial Intelligence (AI) in their English lessons, and 24 participants were invited to express their thoughts about AI in shadow education. Interviews were used and participants were centre owners, tutorial centre tutors and students. The results indicated that AI could help to provide a second opinion to students but there were a lot of ambiguity in AI responds. As this is an experimental study, there still a lot of research needs to be conducted in this topic, especially the practical methods to use AI in shadow education settings.
Enhancing Teachers’ Attitudes and Competence in AI-Integrated Instruction: The Interplay of Multiple Workshops and Teaching Experience
Paper Presentation in a Themed Session Yiju Lin
The rapid growth of artificial intelligence (AI) in education has made teachers’ attitudes and competence in AI integration a critical area of innovation. This study examines the effects of four professional development workshops and school-based practices on teachers’ attitudes and abilities in AI-integrated instruction, focusing on the interplay between teaching experience and workshop participation. Data from 162 teachers across four workshops were analyzed, incorporating questionnaire responses and qualitative feedback. Key variables included "teaching quality," "teaching efficiency," "quick learning ability," and "instructional helpfulness." Statistical methods included descriptive analysis, repeated-measures ANOVA, interaction analysis, and structural path modeling. Workshops significantly improved "teaching quality" (mean = 4.23) and "instructional helpfulness" (mean = 4.56). Repeated-measures ANOVA confirmed significant effects on "quick learning ability" and "instructional helpfulness" (p < 0.05). Interaction analysis revealed that senior teachers exhibited greater improvements despite lower initial scores. The structural model demonstrated that "workshop participation" influenced outcomes via "teaching quality" and "efficiency." Workshops and school-based practices effectively enhance teachers’ attitudes and competencies in AI integration, with differentiated impacts based on teaching experience. Personalized training approaches are essential to optimize adoption and innovation in AI-driven education.
