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Technology integration refers to the process of innovation diffusion, from understanding technology knowledge to achieving a high level quality of technology usage. To address the gap in research regarding the critical factors that influence K-12 teachers' practice of technology integration at the initial stage of a massive government-led training programme in rural areas, this study sought to explore the comprehensive effects of teachers' technological pedagogical content knowledge (TPACK) and beliefs on their technology integration. Participants included 267 in-service K-12 teachers from four pilot schools in a remote rural area in north-western China. We found that: (a) T-related knowledge positively predicted the teachers' technology integration quality and quantity, while T-unrelated knowledge negatively influenced technology integration quality and quantity; (b) the positive valence of teachers' beliefs (PVTBs) was positively related to technology integration quality, the negative valence of teachers' beliefs was negatively related to technology integration quantity; (c) the PVTBs impacted the quality and quantity of technology integration through T-related knowledge; and (d) gender significantly moderated the impact of positive beliefs and T-related knowledge on technology integration. This study suggests that improving K-12 teachers' technology integration in rural areas requires prioritizing professional development programmes that improve teachers' beliefs in the initial stage of technology diffusion.

The microscopic composition of substances is a piece of essential but abstract knowledge in chemistry. Junior high school students may experience difficulty in mental representation when learning micro concepts, which leads to problems such as unsatisfactory academic performance and low learning motivation. Augmented reality (AR) is an optimal choice for presenting abstract concepts and invisible phenomena. Consequently, this study developed an AR application including three-layer experiential learning activities and integrating multiple external representations (text, pictures, 3D models, operations, etc.). To assess the effect of the AR application on students' knowledge gains, learning motivation, and technology perception, an experiment was conducted with 95 ninth-grade students aged 13-15 years who were randomly assigned to two groups (AR and non-AR). The results show that the AR application helped increase students' knowledge gains. Although there was no significant difference in the retention test between the two groups, scores on the transfer test were significantly higher for the AR group than for the non-AR group. Moreover, the AR application significantly improved students' motivation to learn. Finally, students had a positive perception of AR technology.

Providing coaching to participants in inquiry-based online discussions contributes to developing cognitive presence (CP) and higher-order thinking. However, a primary issue limiting quality and timely coaching is instructors' lack of tools to efficiently identify CP phases in massive discussion transcripts and effectively assess learners' cognitive development. This study examined a computational approach integrating text mining and co-occurrence analysis for assessing CP and cognitive development in online discussions based on the community of inquiry (CoI) framework. First, text classifiers trained on different language models were evaluated for identifying and coding the CP phases. Second, epistemic network analysis (ENA) was employed to model cognitive patterns reflected by co-occurrences between the coding elements. Results indicated that text classifiers trained on the state-of-the-art language model Bidirectional Encoder Representations from Transformers (BERT) can address the efficiency issue in coding CP phases in discussion transcripts and obtain substantial agreements (Cohen's "k" = 0.76) with humans, which outperformed other baseline classifiers. Furthermore, compared to traditional quantitative content analysis, ENA can effectively model the temporal characteristics of online discourse and detect fine-grained cognitive patterns. Overall, the findings suggest a feasible path for applying learning analytics to tracking learning progression and informing theory-based assessments.

Situational engagement plays a critical role in promoting students' academic performance. In a smart classroom environment, this study collected longitudinal real-time data for 105 college students at a university in central China to investigate the relationship among situational engagement, personal characteristics and learning environment perceptions. Hierarchical linear modelling showed that environmental perception and students' personal factors have different effects on situational engagement. Specifically, (1) social support perceptions, autonomous motivation and controlled motivation have a significant impact on behavioural engagement; (2) perceptions of social and media support, autonomous motivation and controlled motivation have a significant impact on shallow cognitive engagement; and (3) perceptions of teacher and social support, self-efficacy and autonomous motivation significantly predict deep cognitive and emotional engagement. This study suggests that the effect of the perception regarding advanced technology-supported learning environments on students' situational engagement is limited, and instructors should pay more attention to improving students' perceptions of teacher and social support, self-efficacy and autonomous motivation to promote students' situational deep cognitive engagement in smart classrooms.

Lesson study (LS) is an effective means of improving teachers' facility with teaching design. This research designs a case study of online to offline (O2O) LS and explores the social interaction and behaviour patterns in the process of the LS. The participants included 29 chemistry teachers from 10 secondary schools and two educational technology experts from a university in western China, who participated in the O2O LS, with Chemistry Teaching Design based on Augmented Reality (AR): Molecules and Atoms as its topic. Through social network analysis (SNA) and lag sequence analysis (LSA), the findings of this case study indicate that: (1) in the LS process, the two co-hosts played their due roles well, while different teachers played strong guiding and controlling roles in different discussion phases, and (2) in different discussion phases, the behaviour sequence of teachers' knowledge construction presented different characteristics in that high-level knowledge construction took place among teachers in the later phases under the leadership of the host. This study will aid in the design and implementation of O2O LS and the description of interactive characteristics in teachers' collaborative learning so as to provide reference for using teacher training process data and improving teachers' professional abilities.

The potential of online collaborative learning has been recognized in teacher education, and the value student teachers' collective agency in predict their sustainable professional develop has been discussed. However, there is limited understanding of how student teachers' collaborative knowledge construction behaviors correlate with their collective agency. This study investigated one class of student teachers' collaborative knowledge construction behavioral pattern in a multi-layered interaction activity, and further explained their correlation with the participants' collective agency. A total of 50 third-year student teachers from a class of a university in central China participated in the study. The results suggested that in terms of the average density, both intragroup and intergroup interaction networks were high-density ones. However, the number of interactions within each group was uneven. The student teachers had different reciprocity in intragroup and intergroup discussions. Their social knowledge construction behavioral patterns showed different characteristics in different stages of the multi-layered interaction activity. The questionnaire survey and interview data further revealed that though the student teachers built up collaborative learning awareness to some extent, their collective agency still has space to be improved. The authors conclude with some insights into the online collaborative learning in sustainable teachers' professional development.

The measurement of knowledge contribution in collaborative knowledge building is an important research topic in computer-supported collaborative learning. The information measures of knowledge contribution based on information theory are proposed in this study, which includes two measures: amount of information and information gain. Discourse data collected from a collaborative knowledge building activity were analyzed to validate these measures. The results showed that our information measures can complement the traditional behavioral. With the help of the two measures, community-level variation tendency and individual-level knowledge contribution characteristics could be analyzed in collaborative knowledge building activities. A log function was used to fit the community knowledge variation tendency to measure the convergence of knowledge building. Students were clustered into five types according to their behaviors and contributions in collaborative knowledge building. Both teachers and researchers can benefit from these two information measures by using them in practice.

Despite the continuous emphasis on emotion in multimedia learning, it was still unclear how pedagogical agent emotional cues might affect learning. In the present study, a between-subjects experiment was performed to examine the effects of a pedagogical agent with dual-channel emotional cues on learners' emotions, cognitive load, and knowledge transfer performance. Participants from a central Chinese university (age mean = 21.26, N = 66) were randomly divided into three groups. These groups received instructions from an affective pedagogical agent, a neutral pedagogical agent, or a neutral voice narration without pedagogical agent embodiment. Results showed that learners assigned the affective pedagogical agent reported a significantly higher emotional level than learners assigned the neutral pedagogical agent. Learners' perceived task difficulty was not significantly different among groups while instructional efficiency was significantly higher for learners with the affective pedagogical agent. Moreover, learners assigned to the affective pedagogical agent performed significantly better on the knowledge transfer test than those assigned the neutral pedagogical agent or the neutral voice.

While the use of experiments is important for developing students' scientific knowledge and skills, challenges may arise when teachers and students are conducting experiments in class, such as non-reusable experimental resources, safety issues and difficulties simulating some specific effects. Augmented reality (AR) technology affords an alternative approach to conducting experiments by bringing students a virtual-real mixed learning environment. In this study, taking junior high school physics knowledge on the magnetic field as an example, we designed and developed an AR-based mobile simulated experiment tool. This study investigates the effect of the AR-based experiment on students' knowledge improvement and cognitive load compared with 3D and traditional experiments. A sample of 122 ninth-grade students was randomly chosen and assigned to three groups (AR, 3D and Traditional). The results demonstrate that students in the AR group performed better than those in the 3D and Traditional groups in terms of their knowledge improvement. The AR group students also experienced the lowest cognitive load among the three groups. Moreover, students had positive perceptions about AR and 3D tools. The implications of this study are discussed.

A big challenge in educational resources construction is the intelligent and personalized resource recommendation for learners. This paper proposes a semantic recommendation framework of educational resources based on semantic web and pedagogics. In this framework, a domain ontology is constructed to describe the knowledge structure of the domain. All the resources and user portfolio are described with ontology technology and resource description framework to support semantic inference. Based on the semantic resource organization, we made a set of reasoning rules based on pedagogics. These rules are made from the synthesis of the type of the knowledge, the internal structure of knowledge and learner's learning performance. A case study was implemented on the course "theory and practice of database". In this case, learners are recommended different learning materials according to the different knowledge structure and different learning performance. Three typical learning modes are proposed to describe the personalized learning experience. This framework can be used as a guide for teachers and resource designers.

Accurate assessment and effective feedback are crucial for cultivating learners' abilities of collaborative problem‐solving and critical thinking in online inquiry‐based discussions. Based on quantitative content analysis (QCA), there has been a methodological evolvement from descriptive statistics to sequential mining and to network analysis for mining coded discourse data. Epistemic network analysis (ENA) has recently gained increasing recognition for modelling and visualizing the temporal characteristics of online discussions. However, due to methodological restraints, some valuable information regarding online discussion dynamics remains unexplained, including the directionality of connections between theoretical indicators and the trajectory of thinking development. Guided by the community of inquiry (CoI) model, this study extended generic ENA by incorporating directional connections and stanza‐based trajectory tracking. By examining the proposed extensions with discussion data of an online learning course, this study first verified that the extensions are comparable with QCA, indicating acceptable assessment validity. Then, the directional ENA revealed that two‐way connections between CoI indicators could vary over time and across groups, reflecting different discussion strategies. Furthermore, trajectory tracking effectively detected and visualized the fine‐grained progression of thinking. At the end, we summarize several research and practical implications of the ENA extensions for assessing the learning process.Practitioner notesWhat is already known about this topicAssessment and feedback are crucial for cultivating collaborative problem‐solving and critical thinking in online inquiry‐based discussions.Cognitive presence is an important construct describing the progression of thinking in online inquiry‐based discussions.Epistemic network analysis is gaining increasing recognition for modelling the temporal characteristics of online inquiries.What this paper addsDirectional connections between discourses can reflect different online discussion strategies of groups and individuals.A pair of connected discourses coded with the community of inquiry model can have different meanings depending on their temporal order.A trajectory tracking approach can uncover the fine‐grained progression of thinking in online inquiry‐based discussions.Implications for practice and/or policyBesides the occurrences of individual discourses, examining the meanings of directional co‐occurrences of discourses in online discussions is worthwhile.Groups and individuals can employ different discussion strategies and follow diverse paths to thought development.Developmental assessment is crucial for understanding how participants achieve specific outcomes and providing adaptive feedback. [ABSTRACT FROM AUTHOR]

Teacher workshops attract teachers with common goals; they wish to improve their teaching practices and subject and information technology knowledge. The asynchronous online discussion is the main activity in teacher workshops. An analytical model was developed in this study to examine the temporal characteristics of collaborative knowledge construction in teacher workshops. Specifically, 664 posts were analyzed from an asynchronous online discussion--involving 91 teachers--on the topic, "How to Make a Language Course Interesting?" The aim of this paper is to present the changes in knowledge construction levels and teachers' social interactive characteristics resulting from participation in teacher workshops. From the findings of this study, advances in theory, methodology and pedagogical practice are indicated. The findings also indicate that knowledge construction levels and teachers' social interactive characteristics change at different stages of discussions. Suggestions for improving the effects of online teacher workshops are provided.

This study analysed the instructors' teaching presence of three courses conducted by an instructor to explore the effects of the instructors' online teaching presence on students' interactions and collaborative knowledge constructions. Content analysis, social network analysis, and lag sequential analysis were used to explore the mechanism of teaching presence on students' interactions and collaborative knowledge construction. Results demonstrate that the design and organization, as well as facilitating discourse, can facilitate students' interaction, reduce the number of peripheral students, and facilitate students' collaborative knowledge construction, especially in the knowledge sharing, discovery, discussion, and application, whereas direct instruction has positive effects on teachers' centrality and negative effects on knowledge negotiation and testing. The result can give the instructors some guidance on online teaching practices.

The article explored the effects of game-based teaching on primary student dance teaching and learning. Two semesters of dance teaching and learning conducted by the same teacher were analyzed. In the first semester, the teacher taught dance in a traditional way. In the second semester, the teacher taught dance with a serious game in the teaching design and implementation. Results indicated that the use of the serious game improved teacher and students co-engagement in the teaching activities. It enhanced classroom interactions and student learning satisfaction, as well as the teacher's serious game acceptance. Results supported that the serious game was helpful to primary student dance teaching and learning.

The contextual influences on technological pedagogical content knowledge (TPACK) enactment and the method of TPACK assessment remain to be important research topics. Discourse data of 81 teachers in an online professional learning community were collected and analyzed based on the framework of TPACK. Frequency distribution and time series characteristics of teachers' knowledge domains were analyzed. In addition, epistemic network analysis was used to compare the epistemic network characteristics of teachers in the higher-score and the lower-score groups, different age groups, and post and reply groups. Results showed that teachers' knowledge domains enacted in the context of online discourse were mainly pedagogical content knowledge and general pedagogical knowledge. The teachers in the higher-score group had a rich, organized and flexible knowledge structure of TPACK. Younger teachers had more connections between pedagogical knowledge and pedagogical content knowledge, while senior teachers had more connections between technological knowledge and pedagogical knowledge. The teachers in the reply group had more connections among the different categories of knowledge as compared to the post group. Finally, implications, limitations and future research were discussed.

This study investigated whether video lectures instructed by a heightened level of expressiveness instructor were better than those instructed by a conventional level of expressiveness instructor or audio-only in promoting students' online learning, and what kind of effects do instructor's facial expressions have on students' learning. Three different types of video lectures (one with a heightened level of expressiveness instructor, one with a conventional level of expressiveness instructor and one with the instructor' audio only) were used to study the effects of instructor's facial expressions. Sixty-nine participants from Chinese Normal University were selected to learn with these video lectures. Results of this study indicated that video lectures with a heightened level of expressiveness instructor were better than those with a conventional level of expressiveness instructor and audio-only ones with regard to improving students' arousal level and learning satisfaction. Instructor's facial expressions had no significant influence on participants' short-term recall (p = 0.90), while instructor's facial expressions did influence students' medium-term recall (p = 0.03). Instructor's facial expressions played a key role in students' online learning.

This research employs the fuzzy‐set qualitative comparative analysis (fsQCA) method to investigate the configurations of multiple factors influencing scientific concept learning, including augmented reality (AR) technology, the concept map (CM) strategy and individual differences (eg, prior knowledge, experience and attitudes). A quasi‐experiment was conducted with 194 seventh‐grade students divided into four groups: AR and CM (N = 52), AR and non‐CM (N = 51), non‐AR and CM (N = 40), non‐AR and non‐CM (N = 51). These students participated in a science lesson on ‘The structure of peach blossom’. This study represents students' science learning outcomes by measuring their academic performance and cognitive load. The fsQCA results reveal that: (1) factors influencing students' academic performance and cognitive load are interdependent, and a single factor cannot constitute a necessary condition for learning outcomes; (2) multiple pathways can lead to the same learning outcome, challenging the notion of a singular best path derived from traditional analysis methods; (3) the configurations of good and poor learning outcomes exhibit asymmetry. For example, high prior knowledge exists in both configurations leading to good and poor learning outcomes, depending on how other conditions are combined. Practitioner notes What is already known about this topic Augmented reality proves to be a useful technological tool for improving science learning. The concept map can guide students to describe the relationships between concepts and make a connection between new knowledge and existing knowledge structures. Individual differences have been emphasized as essential external factors in controlling the effectiveness of learning. What this paper adds This study innovatively employed the fsQCA analysis method to reveal the complex phenomenon of the scientific concept learning process at a fine‐grained level. This study discussed how individual differences interact with AR and concept map strategy to influence scientific concept learning. Implications for practice and/or policy No single factor present or absent is necessary for learning outcomes, but the combinations of AR and concept map strategy always obtain satisfactory learning outcomes. There are multiple pathways to achieving good learning outcomes rather than a single optimal solution. The implementation of educational interventions should fully consider students' individual differences, such as prior knowledge, experience and attitudes. What is already known about this topic Augmented reality proves to be a useful technological tool for improving science learning. The concept map can guide students to describe the relationships between concepts and make a connection between new knowledge and existing knowledge structures. Individual differences have been emphasized as essential external factors in controlling the effectiveness of learning. What this paper adds This study innovatively employed the fsQCA analysis method to reveal the complex phenomenon of the scientific concept learning process at a fine‐grained level. This study discussed how individual differences interact with AR and concept map strategy to influence scientific concept learning. Implications for practice and/or policy No single factor present or absent is necessary for learning outcomes, but the combinations of AR and concept map strategy always obtain satisfactory learning outcomes. There are multiple pathways to achieving good learning outcomes rather than a single optimal solution. The implementation of educational interventions should fully consider students' individual differences, such as prior knowledge, experience and attitudes. [ABSTRACT FROM AUTHOR]

Cognitive engagement involves mental and physical involvement, with observable behaviors as indicators. Automatically measuring cognitive engagement can offer valuable insights for instructors. However, object occlusion, inter-class similarity, and intra-class variance make designing an effective detection method challenging. To deal with these problems, we propose the Object-Enhanced–You Only Look Once version 8 nano (OE-YOLOv8n) model. This model employs the YOLOv8n framework with an improved Inner Minimum Point Distance Intersection over Union (IMPDIoU) Loss to detect cognitive engagement. To evaluate the proposed methodology, we construct a real-world Students' Cognitive Engagement (SCE) dataset. Extensive experiments on the self-built dataset show the superior performance of the proposed model, which improves the detection performance of the five distinct classes with a precision of 92.5%. [ABSTRACT FROM AUTHOR]

Teachers' online discussion text data shed light on their reflective thinking. With the growing scale of text data, the traditional way of manual coding, however, has been challenged. In order to process the large-scale unstructured text data, it is necessary to integrate the inductive content analysis method and educational data mining techniques. An inductive content analysis on samples taken from 17,624 posts was implemented and the categories of teachers' reflective thinking were obtained. Based on the results of inductive content analysis, we implemented a single-label text classification algorithm to classify the sample data. Then, we applied the trained classification model on a large-scale and unexplored online discussion text data set and two types of visualizations of the results were provided. By using the categories gained from inductive content analysis to create a radar map, teachers' reflection level was represented. In addition, a cumulative adjacency matrix was created to characterize the evolution of teachers' reflective thinking. This study could partly explain how teachers reflected in online professional learning environments and brought awareness to educational policy makers, teacher training managers, and education researchers.

This study investigates the role of a collaboration script, the Funnel Model, in supporting students' computer-supported collaborative scientific argumentation, and how the students appropriated the collaboration script in scientific argumentation. In this exploratory case study, a class of 33 Secondary grade four students went through four phases of computer-supported collaborative argumentation activity scripted by the Funnel Model: individual ideation, intra-group synergy, inter-group critique and intra-group refinement. Multiple sources of data were collected including student-generated artefacts online at different phases of collaboration, and the post-intervention interviews with the students. The results show that the Funnel Model facilitated students' computer-supported collaborative argumentation. The students' levels of content mastery, motivation, classroom culture and time allocated for classroom participation affect students' appropriation of the script for effective collaborative argumentation. [ABSTRACT FROM AUTHOR]

Problem‐oriented teaching (POT) activities are important in classroom instruction. The level of student response can be influenced by different teacher behaviours in POT. However, the characteristics of teachers' multimodal behaviours at different levels of response are unclear. This study applied epistemic network analysis to explore the characteristics of teachers' multimodal behaviours in POT with different response levels. Using 256 POT segments from 12 classroom teaching videos in primary and secondary schools, this study found that authentic questions and iconic gestures occupied a central position in multimodal behaviours. The concomitant use of multimodal behaviours and the flexibility in eye contact could improve the response levels of students. These findings help understand how teachers' multimodal behaviours can promote students' responses. Practitioner notesWhat is already known about this topic Various behaviours have been shown to impact learners' response, such as teachers' responses to students and teachers' non‐verbal behaviours.Epistemic network analysis can be used to analyse the structure of the connections between cognitive, social and interaction data.What this paper adds This study analyses the characteristics of teachers' multimodal behaviours during problem‐oriented activities.It also compares the salient properties of non‐verbal, verbal and multimodal behavioural networks generated by interactive fragments of students' responses of different cognitive levels.Implications for practice and policy Teachers should ask more authentic questions in the classroom to promote in‐depth thinking processes in students.The appropriate coordination of multimodal behaviours by teachers is crucial to promote the cognitive level of students' responses.Upon making eye contact with students, teachers should also use iconic gestures and be flexible regarding the use of eye contact. [ABSTRACT FROM AUTHOR]