Massive open online courses (MOOCs) can disseminate academic knowledge, such as complete courses, to students and lifelong learners from all backgrounds and anywhere. Using a quantitative approach, this study examines the relationship between engagement, acceptance, and use of blended MOOCs among 1875 STEM students at the University of Cape Coast (UCC), Ghana. The theoretical basis is the proposed revised Community of Inquiry (RCoI) framework and the Unified Theory of Acceptance and Use of Technology (UTAUT). A structured questionnaire was designed and distributed via Google Forms to a randomly selected sample of 3,506 students using a two-stage cluster sampling technique. The survey achieved an 82% response rate, with 2,875 participants completing it. Out of these 2,875 participants, 1,875 were STEM students, and they were explicitly used for this paper. Structural equation modelling was employed to analyse how the RCoI model—encompassing cognitive, social, teaching, and learning presences—affects students’ acceptance and use of blended MOOCs. According to the study, STEM students’ engagement significantly impacts their ability to utilise blended MOOCs. The findings showed that within blended MOOCs, the presence of RCoI had a significant positive relationship with STEM students’ engagement. Again, the findings reveal significant influences of STEM students’ engagement on performance expectancy, effort expectancy, social influence, and facilitating conditions, highlighting the need for administrative and technical support to enhance the effective adoption of blended MOOCs. This study contributes robust insights into the dynamics of student interaction and learning outcomes in blended learning environments such as blended MOOCs within developing countries.
Digitalization of textbooks constitutes a pivotal aspect of the digital transformation of education, playing an indispensable role in the development of a modern education system. Currently, the construction of digital textbooks in higher education lacks a shareable and reusable model. Crowdsourcing is an innovative concept that leverages collective wisdom to improve the quality of resources, transcending organizational boundaries and facilitating the flow of knowledge. This study adopts the design-based research paradigm and comprehensively applies a variety of research methods to construct and implement a crowdsourcing-based construction model for digital textbooks in higher education. The model includes a knowledge subsystem, a process subsystem, and an organizational subsystem, covering crowdsourcing participants such as professionals, ordinary participants and artificial intelligence. The digital textbook developed based on this framework has demonstrated significant user satisfaction in terms of content, teaching, technical design, evaluation, opportunities for deep learning, accessibility, and security. It is expected that the construction model of the digital textbooks in high education built in this study can further enrich the research outcomes of digital textbooks, and provide a model reference for digital textbook construction in higher education.
Robot programming has become an effective means to promote primary school students’ computational thinking (CT). Direct instruction (DI), characterized by teacher instruction followed by student problem-solving, is a commonly adopted teaching approach for robot programming and CT. However, by emphasizing task completion and minimizing failures, DI limits students’ ability to understand the essence of problem-solving and learn from mistakes. In contrast, productive failure (PF) involves students’ problem-solving followed by teacher instruction, treating failure as a valuable experience that fosters deeper learning and problem-solving skills. Hence, this research compared the effects of the productive failure-based robot programming (PF-RP) and direct instruction-based robot programming (DI-RP) approaches on primary school students’ CT, self-efficacy, growth mindset, and learning perceptions. A quasi-experimental study involving both quantitative and qualitative data was designed. The sample comprised 87 third-grade students from China, with 43 students in the PF-RP group and 44 students in the DI-RP group. Results revealed that (1) both approaches enhanced students’ CT, with the PF-RP approach demonstrating greater improvements than the DI-RP approach over time; (2) both approaches improved students’ self-efficacy, but no significant differences were detected between the two approaches over time; (3) only the PF-RP approach significantly promoted students’ growth mindset and showed greater improvements than the DI-RP approach over time; and (4) students perceived that the PF-RP approach is an effective teaching approach that helped them think of more solutions and strengthen their understanding.
In the age of artificial intelligence, empathy is crucial for preschoolers’ social adaptation and personal development. The development of Humanoid Intelligent Robots (HIRs) offers an opportunity to provide preschoolers with personalized interactive experiences. This study recruited 77 rural preschoolers aged 5 to 6 years as participants, who were randomly assigned to an R-tutor group, an R-peer group, and a conventional teaching group. An 8-week empathy course was conducted to explore the impact of different roles of HIRs on their empathy. The results of the questionnaire analysis showed that the R-tutor method improved preschoolers’ empathy more than the R-peer method and the conventional teaching method; the R-peer method did not enhance preschoolers’ empathy compared to the conventional teaching method. In addition, perceptions of robot anthropomorphism in the R-tutor group were significantly higher than those in the conventional teaching group. Behavior analysis results showed that the R-tutor group significantly outperformed the R-peer group and the conventional teaching group in terms of emotional empathy and behavioral empathy, while the interactions in the R-peer group and the conventional teaching group remained mainly at the level of cognitive empathy. The teacher’s teaching reflections indicated that robot tutors can stimulate preschoolers’ interest in learning, optimize their emotional experiences, and develop their empathy. The Situation-Cognition-Emotion-Behavior (SCEB) empathy learning model proposed in this study provides a theoretical framework for cultivating preschoolers’ empathy. Furthermore, the exploration of using HIRs with different roles to foster preschoolers’ empathy also offers valuable practical experience for preschool teachers in conducting empathy education.
In the process of collaborative learning, effective grouping is the key to improving learning efficiency. A well-structured collaborative learning group can markedly improve the learning efficiency of both individuals and the group as a whole. Nonetheless, current grouping methods for collaborative learning frequently fall short of a comprehensive assessment of students’ knowledge proficiency, thereby failing to guarantee that group members’ knowledge structures are mutually complementary. Therefore, a grouping model combining knowledge complementarity and dynamic diagnosis is proposed. The grouping model is divided into five layers. Firstly, the learning objective analysis layer deconstructs the teaching content into several core knowledge points. On this basis, the dynamic knowledge diagnosis layer uses the improved deep knowledge tracking model DKVMN-KT to dynamically diagnose students’ mastery of core knowledge points. Then, in the personalized grouping layer, K-means algorithm is used to cluster the personalized grouping results. Furthermore, teachers were involved in the manual fine-tuning of the grouping results. Finally, the model forms a closed-loop feedback link through a deep interactive optimization layer to promote the iterative optimization of the collaborative learning grouping model. The experimental results indicate that the collaborative learning grouping model is helpful to effectively group students at the level of knowledge structure, and can improve the efficiency of collaborative learning, In order to guarantee more equitable and diverse grouping outcomes, this methodology promotes positive interplay among students, enabling them to mutually learn from one another and thereby enhance their comprehension of diverse knowledge points effectively.
