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Design thinking is regarded as an essential way to cultivate 21st century competency and there has been a concomitant rise of needs and interest in introducing K-12 students to design thinking. This study aimed to review high-qualified empirical studies on design thinking integrated learning (DTIL) in K-12 education and explore its future research perspectives. After a systematic search in online database via a keyword search and snowballing approach, 43 SSCI journal papers with 44 studies were included in this review. The results indicate that: (1) There has been a growing popularity of integrating design thinking into K-12 education over the past decade, and most empirical studies target middle school students with small group size and a short period; (2) Studies tend to pay more attention to STEM related curriculum domains by incorporating non-unified design thinking models or processes, and the core concepts of design thinking in K-12 education have been frequently valued and pursued including prototype, ideate, define, test, explore, empathize, evaluate, and optimize; (3) The mostly evaluated learning performances are design thinking, followed by emotional/social aspect, subject learning performance and skill. For evaluation, qualitative assessments are used more frequently with instruments like survey/questionnaire, portfolio, interview, observation, protocol analysis, etc. (4) interventions with non-experimental study, formal classroom setting, collaborative learning, and traditional tools or materials have been mainly applied to the open-ended and challenging activities in real situated DTIL. Overall, the 43 papers suggest that design thinking shows great educational potential in K-12 education, however, the empirical evidence that supports the effectiveness of DTIL is still rather limited. Research gaps and future directions derived from reviewed papers are also discussed.

Over the past two decades, the field of STEM education has produced a wealth of research findings. This study systematically reviewed the published literature from the perspective of subject integration and theme evolution, considering both K-12 and higher education. It was found that STEM education originated from higher education, but the main emphasis is gradually shifting to the K-12 stage. There were mainly sixteen subjects involved in STEM education, showing the gradual in-depth integration of science, engineering, technology, math, humanities, and social sciences, in which humanism is increasingly emphasized. Culture is a new perspective for understanding the diversity of participants, which also gives STEM education a distinctive regional character. In addition, in the K-12 stage, research related to computer science and art stands out alongside the four main subjects, demonstrating relatively even distribution across research themes. Conversely, in higher education, engineering, and chemistry garner considerable attention, with research themes predominantly concentrated on learning outcomes and social relevance. On a holistic scale, researchers exhibit a pronounced interest in learning outcomes, yet relatively less emphasis is placed on pedagogical aspects. Regarding prospective trends, there should be a heightened focus on the cultivation of students’ thinking competencies, students’ career development, and pedagogy.

(1) Deficits in adaptive behavior significantly hinder individuals with intellectual disabilities from performing essential daily tasks and participating in community life. Although virtual reality shows promise for supporting adaptive behavior in this population, systematic reviews on this topic remain scarce. (2) Methods: Twenty-five experimental studies from the databases Web of Science, PubMed, Scopus, and ERIC, published between 2005 and 2024, were analyzed in the context of a systematic review. (3) Results: The studies revealed a significant surge in research on VR interventions for adaptive behavior in individuals with intellectual disabilities, particularly after 2021. The most frequently applied domain was practical skills, while social and conceptual skills received relatively less attention. Most studies employed high-immersion head-mounted displays as the primary technology type and adopted controller-based unimodal interaction as the dominant interaction mode. Pedagogical strategies such as ABA, structured teaching, and contextual learning are favored in interventions. (4) Conclusions: VR interventions have been increasingly applied to support adaptive behavior development in this population. However, further exploration is needed to tailor VR designs to better accommodate the individual differences and specific needs. This review synthesizes current evidence, identifies key trends and limitations, and offers guidance for future research.

As an emerging learning support technology, large language model-powered pedagogical agents demonstrate significant potential in enhancing video learning effectiveness, yet the underlying cognitive mechanisms remain inadequately elucidated. This study employed a multimodal approach combining EEG and eye-tracking to investigate the effects of AI-generated mind maps and text summaries on learning performance and cognitive processing. Following data screening, 80 valid datasets from education majors were randomly assigned to three groups: mind map summary (PA-MMS, n = 27), text summary (PA-TS, n = 28), and control (NPA, n = 25). Results showed both experimental groups achieved significantly higher post-test scores than controls, with PA-MMS demonstrating the strongest performance (d = 3.78). EEG evidence indicated pedagogical agents reduced Theta activity (decreased working memory load) while PA-MMS enhanced Alpha activity (superior attention control). Eye-tracking revealed differentiated strategies: PA-MMS exhibited networked fixation patterns facilitating integration; PA-TS demonstrated linear scanning. Delayed testing showed PA-MMS achieved the highest retention (96.8%). Correlations confirmed posttest scores negatively correlated with Theta (r = −0.46) and extraneous load (r = −0.61), positively with germane load (r = 0.54). Mind maps simultaneously reduced extraneous load (d = 1.26) while enhancing germane processing (d = 1.15), representing a shift from static scaffolds to AI-mediated generative support.

General large language models (LLMs) often suffer from semantic misinterpretation, information redundancy, and hallucinated content when applied to educational question-answering tasks. These issues hinder their effectiveness in supporting students’ specialized course learning and self-directed study. To address these challenges, this study proposes an intelligent tutoring model that integrates a knowledge graph with a large language model (KG-CQ). Focusing on the Data Structures (C Language) course, the model constructs a course-specific knowledge graph stored in a Neo4j graph database. It incorporates modules for knowledge retrieval, domain-specific question answering, and knowledge extraction, forming a closed-loop system designed to enhance semantic comprehension and domain adaptability. A total of 30 students majoring in Educational Technology at H University were randomly assigned to either an experimental group or a control group, with 15 students in each. The experimental group utilized the KG-CQ model during the answering process, while the control group relied on traditional learning methods. A total of 1515 data points were collected. Experimental results show that the KG-CQ model performs well in both answer accuracy and domain relevance, accompanied by high levels of student satisfaction. The model effectively promotes self-directed learning and provides a valuable reference for the development of knowledge-enhanced question-answering systems in educational settings.

This study examined the effects of two performance assessment approaches on students' learning achievement, attitude, computational thinking, and 4C key competencies in an introductory robotics course. An experimental study was conducted with 72 students in a middle school for 16 weeks. A performance assessment given at the end of the course was used as a reflection tool in one group (RPA), while given during the learning process as a guidance tool in another group (GPA). Results indicated that GPA showed a significantly better effect than RPA on students' learning attitude and computational thinking, although the improvement in learning performance and 4C key competencies was not evident. Within the 4C sub-dimensions, GPA outperformed RPA in promoting students' creativity and collaboration. However, the RPA group performed significantly better in improving critical thinking. The results confirmed that both GPA and RPA played an important role in robotics education. GPA provides a structured learning experience with clear goals and expectations, allowing students to effectively adjust their learning strategies through immediate feedback and a greater sense of control over their learning process with a positive attitude. In contrast, RPA encourages students to critically reflect on their learning journey from a holistic perspective, which increases student autonomy and deep learning during the process, while requiring a level of self-awareness and introspection that may be challenging for some students. The advantages and disadvantages of both approaches were discussed. The findings highlight the importance of adopting an appropriate approach to performance assessment and avoiding over-guidance in robotics education.

PurposeThis study aims to provide a comprehensive review and bibliometric analysis of the literature in the field of science, technology, engineering and mathematics (STEM) education over the past 15 years, with a specific focus on global distribution and research trends.Design/methodology/approachThis study collected 1,718 documents from the Web of Science (WOS) database and analyzed their timeline distribution, geographical distribution, research topics, subject areas, learning stages and citation burst using a bibliometric approach with VOSviewer and Citespace.FindingsResults indicated that: overall, STEM education has increasingly gained scholarly attention and is developing diversely by emphasizing interdisciplinary, cross-domain and regional collaboration. In terms of global collaboration, a collaborative network with the USA in the center is gradually expanding to a global scope. In terms of research themes, four key topics can be outlined including educational equity, pedagogy, empirical effects and career development. Social, cultural and economic factors influence the way STEM education is implemented across different countries. The developed Western countries highlighted educational equity and disciplinary integration, while the developing countries tend to focus more on pedagogical practices. As for research trends, eastern countries are emphasizing humanistic leadership and cultural integration in STEM education; in terms of teachers’ professional development, teachers’ abilities of interdisciplinary integration, technology adoption and pedagogy application are of the greatest importance. With regards to pedagogy, the main focus is for developing students’ higher-order abilities. In terms of education equity, issues of gender and ethnicity were still the hottest topics, while the unbalanced development of STEM education across regions needs further research.Originality/valueThis study provides a global landscape of STEM education along the timeline, which illustrates the yearly progressive development of STEM education and indicates the future trends.

PurposePreservice teachers (PSTs) often face challenges in STEM teaching, including cognitive conservatism, limited collaboration experience and weak innovation capacity. To address this, based on cognitive conflict and collaborative innovation theories, this study aims to propose the Cognitive Conflict in Community of Practice (CCCP), following an “Activation-Reinforcement-Diversification” pathway. Anchored in a university–school–enterprise collaboration, the model aims to explore effective support mechanisms and assess its impact on STEM PSTs’ Interdisciplinary Teaching Competence (ITC) and innovative design ability.Design/methodology/approachA mixed-methods approach was used, combining quasi-experimental design and qualitative analysis. Centered on the CCCP, interdisciplinary teaching practices were implemented to assess its impact. Questionnaires measured ITC improvement between experimental and control groups, while interviews and textual analysis explored the development of instructional design innovation.FindingsThe model significantly improved PSTs’ ITC and fostered innovative awareness in a STEM course, facilitating a shift from idealized to practical design. It also promoted cognitive interaction and professional growth among in-service teachers, supporting a mutually empowering development pathway.Originality/valueThis study presents an innovative integration of cognitive conflict theory and multidimensional collaboration, offering a practical and scalable framework for interdisciplinary teacher education. It contributes to the theoretical understanding of cognitive conflict transformation in pedagogical contexts and provides actionable guidance for PSTs course reform.

Parents’ expectations affect children’s key competencies acquired from STEM education, and influence their future career development. This study aimed to determine the influence of parents’ expectations on children’s key competencies gained through STEM education, with a particular focus on gender difference. A total of 736 parents (44% fathers and 56% mothers) of children aged 3–12 (50.4% boys and 49.6% girls) participated in a two-section survey and rated the degree of importance of each key competency. Subsequently, exploratory factor analysis was used to identify the potential structure of the STEM-related competencies, and ANOVA was used to gain further insights into the gender difference tendency. Results targeted 10 most emphasized competencies which were clustered into four categories, namely the Innovation factor (Inquiring competency, Creativity competency), the Social factor (Cooperative competency, Expressing competency), the Making factor (Hands-on competency, Problem-solving competency, Anti-frustration competency), and the Learning factor (Thinking competency, Knowledge acquisition competency, Concentration competency). Results also indicated that the parents had significantly different expectations for boys and girls regarding the expressing, thinking, knowledge acquisition, concentration, and hands-on competencies. Fathers’ and mothers’ expectations only differed for children’s anti-frustration competency. These findings provide deeper insights into STEM-related competencies from parents’ viewpoints, and contribute a greater understanding of gender difference in STEM education.

The main reason students drop out of online courses is often that they lose interest during learning. Moreover, it is not easy for students to choose an appropriate course before actually learning it. Course recommendation is necessary to address this problem. Most existing course recommendation methods depend on the interaction result (e.g., completion rate, grades, etc.). However, the long period required to complete a course, especially large-scale online courses in higher education, can lead to serious sparsity of interaction results. In view of this, we propose a novel course recommendation method named HGE-CRec, which utilizes context formation for heterogeneous graphs to model students and courses. HGE-CRec develops meta-path embedding simulation and meta-path weight fusion to enhance the meta-path embedding set, which can expand the learning space of the prediction model and improve the representation ability of meta-path embedding, thereby avoiding tedious manual setting of the meta-path and improving the effectiveness of the resulting recommendations. Extensive experiments show that the proposed approach has advantages over a number of existing baseline methods.