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This study has two objectives: to explore the factors that influence student self-efficacy regarding engagement and learning outcomes in a business simulation game course and to compare the difference between hierarchical and general teaching methods.

From September 2021 to May 2022, a questionnaire was administered to 126 students in a business simulation game course at the Zhongshan Institute, University of Electronic Science and Technology of China. Data were analyzed using nonparametric paired samples tests and linear regression.

The results showed that student self-efficacy, engagement and learning outcomes were significantly higher with the hierarchical teaching method than with the general teaching method. There were also differences in the factors that influenced self-efficacy regarding learning outcomes between the two teaching methods. With the general teaching method, student self-efficacy did not directly affect learning outcomes, but did so indirectly by mediating the effect of engagement. However, with the hierarchical teaching method, self-efficacy directly and significantly affected learning outcomes, in addition to indirectly affecting learning outcomes through student engagement.

Compared with the control group experimental research method, the quasi-experimental research method can eliminate the influence of sample heterogeneity itself, but the state of the same sample may change at different times, which is not necessarily caused by the hierarchical teaching design.

Based on the results of this study, teachers can apply hierarchical teaching according to student ability levels when integrating business simulation games. The results of this study can inspire teachers to protect student self-confidence and make teaching objectives and specific requirements clear in the beginning of the course, and also provide an important practical suggestion for students on how to improve their course performance.

The research results can be extended to other courses. Teachers can improve students' self-efficacy through hierarchical teaching design, thus improving students' learning performance and also provide reference value for students to improve their learning performance.

This study built a model based on self-system model of motivational development (SSMMD) theory, comparing factors that affect student self-efficacy regarding learning outcomes under different teaching methods. The model enriches the literature on SSMMD theory as applied to business simulation game courses and adds to our understanding of hierarchical teaching methods in this field. The results provide a valuable reference for teachers that can improve teaching methods and learning outcomes.

This study aims to extend understanding of individual innovation by examining how learning strategies and relational dynamics influence the generation and promotion of innovative ideas. By investigating the extent to which the relationship between learning strategies and innovation varies as a function of a social factor (i.e. leader–member exchange), this research strengthens the conceptual model of individual innovation by integrating cognitive, behavioral and environmental factors.

Data collected from 667 working adults met satisfactory standards of construct reliability, and confirmatory factor analyses were used to verify sufficient convergent and discriminant construct validity. A first-stage moderated-mediation model was used to measure the direct and indirect effects of the independent variable on the dependent variable, as well as the effect of the moderating variable.

Leader–member exchange positively moderated the relationship between behavioral learning strategies and idea generation, but not the relationship between cognitive learning strategies and idea generation. Furthermore, idea generation mediated the relationship between the interaction (i.e. behavioral learning strategies × leader–member exchange) and idea promotion. Idea generation also mediated the relationship between cognitive learning strategies and idea promotion.

This research extends the generalizability of social cognitive theory within individual innovation processes and provides a greater understanding of how relational dynamics strengthen employee innovation through behavioral learning strategies. Support for the hypothesized moderated-mediation model empirically validates how organizational leaders can leverage relational dynamics and learning strategies to elicit the conceptualization and championing of innovative ideas in the workplace.

Despite the interest in leaders' identity work as a framework for leadership development, coaching psychology has yet to expose its active ingredients and outcomes.

To do so, the authors reconcile published systematic literature reviews (SLRs) in the field to arrive at a more thorough understanding of the role of identity work in coaching. A total of 60 eligible SLRs on identity work and coaching were identified between 2010 and 2022. Four were included in the data extraction after selecting and screening, and the full texts of 196 primary studies reported therein were analysed.

Amongst the coachee-related factors of effective coaching, the coachee’s motivation, general self-efficacy beliefs, personality traits and goal orientation were the most frequently reported active ingredients, and performance improvement, self-awareness and goal specificity were the most frequently supported outcomes. The analysis indicates that leaders' identity work, as an active ingredient, can be a moderator variable for transformative coaching interventions, while strengthening leadership role identity could be one of the lasting outcomes because coaching interventions facilitate, deconstruct and enhance leaders' identity work. Further research is needed to explore the characteristics of these individual, relational and collective processes.

This study adds value by synthesising SLRs that report coachee-related active ingredients and outcomes of executive coaching research. It demonstrates that the role of leaders' identity work is a neglected factor affecting coaching results and encourages coaching psychologists to apply identity framework in their executive coaching practice.

This study examines the relationship between higher education improvement and tacit knowledge importance. In this context, the scarcity of empirical and theoretical studies on acquiring tacit knowledge to enhance academic performance in higher education suggests that this research area holds significant importance for experts and policymakers. Consequently, this study aims to explore the factors that influence academic research performance at Chinese universities by acquiring tacit knowledge.

To achieve the study aims, the current approach utilizes the research technique based on the socialization, externalization, internalization and combination (SECI) model and knowledge management (KM) theory. To analyze the study objective, the authors collected data from post-graduate students at Chinese universities and analyzed it using structural equation modeling (SEM) to test the model and hypotheses.

The results indicated that social interaction, internalization and self-motivation have a positive impact on academic research performance through the acquisition of tacit knowledge. Furthermore, the findings suggest that academic researchers can acquire more knowledge through social interaction than self-motivation, thereby advancing research progress.

This study addresses the critical issues surrounding the acquisition of tacit knowledge and presents a comprehensive framework and achievements that can contribute to achieving exceptional academic performance.

This program evaluation aimed to investigate the benefits and challenges of an international, intercultural, e-community-engagement experience involving youth and higher education students. The authors sought to understand the meaning that participants would make of an international, intercultural, e-community-engagement experience.

The program evaluation component of this project was qualitative, participatory and action-oriented. It was composed of online reflection sessions with small, international groups of higher education students from Iraq, India, Morocco, South Africa and the USA immediately following each of five interactive exchange sessions with youth from South Africa. It also included one culminating reflection session to which all of the higher education student participants were invited and a written questionnaire that was completed by the youth participants at the conclusion of the project. The reflection sessions were recorded and transcribed. Transcripts and survey data were reviewed for emergent themes.

Cultural exposure emerged as the primary theme with participants valuing the opportunity to learn about different cultures and to connect with individuals from across the globe.

This program evaluation was not designed as a generalizable study. This pilot initiative provides evidence of the potential value and importance of international, intercultural e-community-engagement experiences for youth and higher education students.

The potential value of technology to build exchange opportunities for young people is immense and largely untapped. International, intercultural e-community-engagement initiatives can be made available to students globally with relatively limited resources. A highly structured and focused plan provides clarity about expectations and requirements for students. A high level of commitment is required by all participants, including the faculty coordinators.

Although the project was brief, exposure to numerous countries and cultures allowed participants to challenge their assumptions about different peoples and places in the world. The potential benefits for greater compassion and understanding of communities and cultures in an international context are high.

This program evaluation contributes to and extends the literature on the possibilities and challenges of international e-community-engagement; it demonstrates the potential for e-community-engagement across multiple countries to broaden students' exposure to and interest in global perspectives.

This paper investigates how individuals' decision-making approach and perceptions of a game's cognitive realism affect the performance of virtual businesses in a web-based simulation game.

Survey data are collected from 274 business simulation game users and is analysed using the fsQCA technique.

The study identifies three alternative pathways to high and low performance in a business simulation game. Results indicate that a flexible decision-making approach exists in all high performance pathway solutions. Where a game is perceived to be realistic, a more focused decision-making approach is associated with high performance. However, where perceived cognitive realism is absent, a less focused experimental decision-making approach is employed, which increases the chances to achieve low performance. Finally, perceived cognitive realism and an experimental decision-making approach are found to be mutually exclusive for achieving high performance.

Whilst the learning benefits of web-based simulation games are widely acknowledged, the complex interplay amongst factors affecting performance in games is under-researched. Limited research exists on how perceptions of a game's cognitive realism interact with user decision-making approaches to affect performance.

This study uses a comprehensive theoretical framework that combines social cognitive theory and neighborhood effect to investigate the influence of neighborhood effects on farmers’ outcome expectations, observational learning and self-efficacy. This study aims is to analyze the mechanisms that underlie the adoption of social media by farmers for knowledge exchange in the agricultural context. Specifically, this research explores the role of neighborhood effects, outcome expectations, observational learning and self-efficacy in shaping farmers’ decision-making process regarding the use of social media platforms for exchanging agricultural knowledge.

The study data was collected through a sample survey conducted among 570 agricultural households residing in the provinces of Thai Nguyen, Cao Bang, Bac Kan and Phu Tho, located in the northern region of Vietnam. To analyze the data, structural equation modeling was used as the statistical technique of choice.

The findings of the study indicate a significant influence of neighborhood effects on outcome expectations, observational learning and self-efficacy. These factors, derived from social cognitive theory, also exhibit a positive association with farmers’ adoption of social media for knowledge exchange. Additionally, the study highlights that neighborhood contribute to a favorable adoption of social media among farmers via outcome expectations, observational learning, and self-efficacy.

The study is limited in examining farmers’ social media adoption for agriculture knowledge exchange in Northern mountainous area of Vietnam. This study could be replicated across various regions or nations, providing comparative insights into the adoption of social media among farmers for knowledge exchange.

The study findings suggest practical and innovative means to promote farmers’ social media adoption for agriculture knowledge exchange.

This study presents a pioneering approach by integrating social cognitive theory and neighborhood effect to elucidate the factors influencing farmers’ adoption of social media for the purpose of agriculture knowledge exchange.

The study integrated understanding by design-Internet of Things (UbD-IoT) education with design thinking and computational thinking to plan and design an IoT course. Cross-domain application examples were employed to train students in problem-understanding, deep thinking and logical design for IoT applications.

In this study, the UbD model was integrated with design thinking and computational thinking in the planning and design of an IoT course. The examples of cross-domain applications were used to train students to understand a problem by engaging themselves in deep thinking and helping them think and design logically for an IoT application.

The UbD-IoT learning design greatly decreased students' overall cognitive load. UbD-IoT learning has a significant impact on the performance of computational thinking in problem-solving and problem-understanding. The impact of UbD-IoT learning on logical thinking and program learning cognition in students needs to be verified.

The results of this study have shown that the UbD model is effective in reducing the cognitive load of a learning course and also strengthens T-competencies in the lateral skills of computational thinking, critical problem-solving, logical thinking and creative thinking.

This study explored the relationship between employees' cognitive capabilities and firm performance by exploring the moderating role of decision-making style and the mediating effect of knowledge creation. Understanding the role of cognitive capabilities in value creation is crucial for human resource management to achieve the anticipated organizational performance.

Structural equation modeling, cognitive skills theory, cognitive skills acquisition theory and a knowledge creation framework were applied.

The first finding suggests that only A-shaped skills predict higher knowledge creation, while T-shaped skills do not. Second, knowledge creation predicts higher financial performance and a lower level of financial uncertainty. Third, T-shaped skills have no indirect effect on financial performance or financial uncertainty. Fourth, A-shaped skills exerted significant indirect effects on financial performance and uncertainty. Fifth, the rational decision-making style did not moderate the link between knowledge creation and financial performance, as opposed to the intuitive decision-making style.

A review of existing research indicates a lack of studies examining the effect of cognitive skills on organizational outcomes and contingencies under which cognitive skills lead to superior outcomes. This study advances research on T-shaped and A-shaped skills and knowledge creation by empirically exploring their interrelationships with financial performance. Managerial implications and suggestions for future research are also highlighted.

To support achieving sustainable development goals (SDGs), we integrated science, technology, engineering and math (STEM) and extended reality technologies into an artificial intelligence (AI) learning activity. We developed Feature City to facilitate students' learning of AI concepts. This study aimed to explore students' learning outcomes and behaviors when using Feature City.

Junior high school students were the subjects who used Feature City in an AI learning activity. The learning activity consisted of 90-min sessions once per week for five weeks. Before the learning activity, the teacher clarified the learning objectives and administered a pretest. The teacher then instructed the students on the features, supervised learning and unsupervised learning units. After the learning activity, the teacher conducted a posttest. We analyzed the students' prior knowledge and learning performance by evaluating their pretest and posttest results and observing their learning behaviors in the AI learning activity.

(1) Students used Feature City to learn AI concepts to improve their learning outcomes. (2) Female students learned more effectively with Feature City than male students. (3) Male students were more likely than female students to complete the learning tasks in Feature City the first time they used it.

Within SDGs, this study used STEM and extended reality technologies to develop Feature City to engage students in learning about AI. The study examined how much Feature City improved students' learning outcomes and explored the differences in their learning outcomes and behaviors. The results showed that students' use of Feature City helped to improve their learning outcomes. Female students achieved better learning outcomes than their male counterparts. Male students initially exhibited a behavioral pattern of seeking clarification and error analysis when learning AI education, more so than their female counterparts. The findings can help teachers adjust AI education appropriately to match the tutorial content with students' AI learning needs.