ETR&D

Although there seemed to be an optimistic consensus about the use of Information and Communication Technologies to support teaching and learning, the negative effects of introducing technology into the classroom have become apparent in recent years. Evidence suggests that instead of using technological devices for the purpose for which they were introduced into the classroom, students are distracted by simultaneous multimedia activities. This is known as the multimedia multitasking tendency. This is not the only negative consequence of digital media in education. In line with this phenomenon, some authors have found that reading comprehension is lower when reading digitally (on screen) than when reading analogue (on paper). The aim of the present study is to investigate whether Multimedia Multitasking Tendency in the educational context plays a relevant role in the effect of the reading medium (analogue or digital) on reading comprehension. To this end, the responses of 97 participants in whom Multimedia Multitasking Tendency was measured, as well as their reading comprehension, were analyzed. Half of them took the reading comprehension test in an analogue medium (i.e. on paper; n = 50), while the other half took it in a digital medium (i.e. on a computer or mobile phone; n = 47). The results suggest that reading comprehension accuracy is lower in a digital medium than in an analogue medium. The results of this study also suggest that Multimedia Multitasking Tendency may play a substantial role in the effect of the reading medium on reading comprehension.

With the rapid development of artificial intelligence, digital technology-based error correction significantly improves the efficiency of error correction by automatically identifying and clustering students’ errors and then analyzing the types of errors. However, in China’s whole class teaching, teachers still rely on experience to randomly select students with representative errors for error correction, making it difficult to ensure that all students’ errors are corrected in a timely and effective manner. In addition, in Chinese primary classrooms, high-achieving students and low-achieving students learn together in the same class, making it difficult to ensure that each student achieves the learning goals. Therefore, this study proposes a peer teaching-based digital error correction approach, focusing on its effects on primary school students’ learning performance, learning engagement, and perceptions of error correction. A total of 63 primary school students were recruited for the study, with 31 in the experimental group using the PT-DEC approach and 32 in the control group using the E-DEC approach. The results showed that students using the PT-DEC approach performed better than the control group in terms of learning performance and learning engagement. The results of this study validate the effectiveness of peer teaching in digital error correction and provide valuable insights and guidance for exploring more efficient error correction in the future.

Increasingly ubiquitous access to Generative Artificial Intelligence (GenAI) presents many challenges, but also opportunities. The fundamental capacity of GenAI to mimic and augment human cognitive functioning, sets it aside from the myriad of previous technological ‘cognitive tool’ innovations that have been promoted as supporting human thinking, problem solving and knowledge construction. Indeed, GenAI has the potential to play a far more substantive and interactive role in knowledge building, founded on real-time dialogic discourse between humans and GenAI working in symbiotic knowledge building partnerships. This article draws on Scardamalia and Bereiter’s early work on human knowledge building communities and Krathwohl’s revision of Bloom’s Cognitive Domain, reconceptualising these to theorise how humans and GenAI might partner in processes of collaborative, joint knowledge construction. It presents a unique model identifying three flexible ‘Zones’, representing different but overlapping components of knowledge building, aligned with Bloom’s cognitive dimensions. It identifies a possible ‘division of labour’ within and across Zones, but argues the primacy of innately human capabilities operating in the Judgement Zone, as crucial to reasoned decision making and accurate knowledge building. The model and its discussion provide new insights into how human-GenAI knowledge building partnerships might be established and sustained.

Promoting students’ collaborative discussions has consistently been a focal topic in the field of computer-supported collaborative learning. Productive collaborative discussions rarely happen spontaneously without external support, and student groups usually encounter challenges in developing a high-quality collaborative knowledge construction. To address this gap, this research designed a group knowledge awareness (GKA) tool by using knowledge graph approach to promote collaborative discussions in China’s higher education. A within-subject design research was conducted to investigate the effects of the GKA tool on groups’ collaborative knowledge construction. The findings revealed that the GKA tool had positive effects on collaborative knowledge construction, students’ domain understanding, and collaborative cognitive load. In addition, students reported positive collaborative learning experiences with the support of the GKA tool. Based on the results, this research provided technological implications for developing and applying the GKA tools in education and pedagogical implications to promote collaborative learning supported by GKA tools.

Computer vision is the automated analysis of visual imagery by computer algorithms that includes, but not limited to object detection and identification, three-dimensional shape estimation, material recognition, and segmentation. The intervention consisted of two to three weeks of professional development that emphasized computer vision technologies with middle school teachers from Title I schools/districts in the states of Arizona and Georgia. Each location trained six in-service teachers. The questions answered through this research were: After in-service teachers engage in professional development emphasizing computer vision: (a) how do their perceptions of computer vision change? (b) how do their perceptions of human vision change? And (c) what are the differences between their perceptions of computer vision and human vision? Personal Construct Theory (Kelly, 1955) was used to explore our research questions. Elements (n = 2; computer vision and human vision) were defined and pairwise comparisons yielded constructs (n = 18) administered in the form of repertory grids. Hierarchical cluster analysis was performed, and clusters were identified. Results showed that in-service teachers’ perspectives of computer vision changed with construct shifts within all four dendrograms that contained between one to eight constructs; all clusters yielded mean increases. Perspectives of human vision stayed relatively consistent across two clusters. The element human vision had a 6% (n = 1) shift in cluster membership, and the element computer vision generated a 72% (n = 13) change in the number of constructs that shifted clusters. Comparisons of computer vision and human vision indicated that in-service teachers had richer perspectives of computer vision after professional development. The significance of this study rests in its contribution to the limited research on computer vision in teacher education. The results show that a relatively short (two to three weeks) professional development experience can have an impact on in-service teachers’ perspectives of computer vision classroom use.