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BackgroundThis study focuses on probing preservice technology teachers’ cognitive structures and how they construct engineering design in technology-learning activities and explores the effects of infusing an engineering design process into science, technology, engineering, and mathematics (STEM) project-based learning to develop preservice technology teachers’ cognitive structures for engineering design thinking.ResultsThe study employed a quasi-experimental design, and twenty-eight preservice technology teachers participated in the teaching experiment. The flow-map method and metalistening technique were utilized to enable preservice technology teachers to create flow maps of engineering design, and a chi-square test was employed to analyze the data. The results suggest that (1) applying the engineering design process to STEM project-based learning is beneficial for developing preservice technology teachers’ schema of design thinking, especially with respect to clarifying the problem, generating ideas, modeling, and feasibility analysis, and (2) it is important to encourage teachers to further explore the systematic concepts of engineering design thinking and expand their abilities by merging the engineering design process into STEM project-based learning.ConclusionsThe findings of this study provide initial evidence on the effects of infusing the engineering design process into STEM project-based learning to develop preservice technology teachers’ engineering design thinking. However, further work should focus on exploring how to overcome the weaknesses of preservice technology teachers’ engineering design thinking by adding a few elements of engineering design thinking pedagogy, e.g., designing learning activities that are relevant to real life.

The current study investigates whether there are statistically independent age-related influences on the canine cognitive structure and how individual factors moderate cognitive aging on both cross-sectional and longitudinal samples. A battery of seven tasks was administered to 129 pet dogs, on which exploratory and confirmatory factor analyses were employed to unveil the correlational structure underlying individual differences in cognitive performance. The best-fitting model featured a hierarchical structure with two first-order cognitive domains (individual problem solving, learning) and a second-order common factor. These higher order factors exhibited consistency over a period of at least 2.5 years. External validation linked the common factor positively to discrimination and reversal learning performance, exploration, neophilia, activity/excitability, and training level while negatively to cognitive dysfunction symptoms, suggesting that it is a good candidate for a general cognitive factor ( canine g ). Structural equation models identified three distinct age-related influences, operating on associative learning, on memory, and on canine g . Health status moderated the negative age- canine g relationship, with a stronger association observed in dogs with poorer health status, and no relationship for dogs in good health. On a longitudinal sample ( N  = 99), we showed that the direction and magnitude of change in canine g over up to 3 years is affected by various interactions between the dogs’ age, communication score, baseline performance, and time elapsed since the baseline measurement. These findings underscore the presence of a general cognitive factor in dogs and reveal intriguing parallels between human and canine aging, affirming the translational value of dogs in cognition and aging research.

Many research studies have clearly demonstrated the importance of cognitive structures as the building blocks of meaningful learning and retention of instructional materials. Identifying the learners' cognitive structures will help instructors to organize materials, identify knowledge gaps, and relate new materials to existing slots or anchors within the learners' cognitive structures. The purpose of our empirical investigation is to track the development of cognitive structures over time. Accordingly, we demonstrate how various indicators derived from graph theory can be used for a precise description and analysis of cognitive structures. Our results revealed several patterns that helped us to better understand the construction and development of cognitive structures over time. We conclude by identifying applications of our approach for learning and instruction and proposing possibilities for the further development of our approach.

PurposeThe success of a young entrepreneur depends on how institutional support can facilitate venture performance. Drawing on the institutional theory, this study posited the role of self-efficacy in supporting the effect of institutional support. Self-efficacy is a driving factor for entrepreneurs in managing and implementing business action confidently and successfully. With macro- and micro-oriented research, this study aims to examine how the micro-level factor that is self-efficacy could mediate the influence of macro-level factors (i.e. institutional governance, cultural and social norms and cognitive structure) toward iGen's new venture performance.Design/methodology/approachA total of 462 respondents representing the population of Malaysian iGen entrepreneurs participated in this study. The samples were selected using a multistage sampling technique (i.e. probability cluster sampling technique and non-probability purposive sampling). Survey items were adapted from the previous studies. Structural equation modelling was used, and the first stage involved testing confirmatory factor analysis (CFA) to test the measurement items' unidimensionality, validity and reliability. The second stage of analysis is to test the mediation model.FindingsThe mediation analysis results confirm that the relationship between institutional governance, cultural and social norms, cognitive structure and new venture performance is mediated by self-efficacy. The results confirm that the relationship between institutional governance and cultural and social norms toward new venture performance is fully mediated by self-efficacy. On the other hand, the relationship between cognitive structure and new venture performance is partially mediated by self-efficacy.Research limitations/implicationsFor future research, it is necessary to consider a wide-ranging sample size in improving research generalisation. Moreover, the cross-sectional study only observes the phenomenon at a certain point and cannot explain the process in the correlational relationship. Future researchers are encouraged to adopt a longitudinal study, which allows the researchers to study a sample throughout a period to draw firm conclusions. Survey data also raise the concern of common method variance (CMV), and future studies may use different data types to solve the problem. In addition, future studies are encouraged to examine other factors that could influence new venture performance.Originality/valueThis study extends the current literature on public policy and entrepreneurship. It comprehensively explains the relationship between institutional governance, cultural and social norms, cognitive structure and self-efficacy toward new venture performance. This study was also conducted in a developing country and iGen context, which can offer new insights into the current literature. Many empirical studies have applied institutional theory in examining entrepreneurship action and behaviour, yet the scholarly consecration on micro-level factors is limited. With macro- and micro-oriented research, this study has examined the influence of self-efficacy as a potential mediating variable.

This paper proposes a conceptual framework on knowledge accumulation and depletion in industrial districts (IDs). The framework introduces three types of endogenous cognitive processes, namely learning, forgetting and unlearning, affected by internal and external dynamics. Such processes determine the reconfiguration of the ID cognitive structure based on the expansion and contraction of local knowledge. We apply the framework to three empirical cases: the Stokeon-Trent ceramic ID, the Prato textile ID and the Macerata–Fermo footwear IDs. The empirical analysis describes the reconfiguration of the ID cognitive structure in relation to different cross-boundary relations, such as the introduction of a new policy, technological change and internationalisation. The results inform us that the contraction of some productive specialisations through forgetting may not be just the prelude of decline, but rather a condition fostering the exploration of new learning opportunities within paths of manufacturing recovery.

Personalized education has been a widely shared goal pursued by Chinese and foreign educators. As the primary method of teacher–student interaction, the importance of personalized questioning is self-evident. Due to a lack of technical support, teachers rely on their teaching experience to ask questions without considering the learning situation of learners. This results in teaching questioning being unable to support learners’ learning. These questions are relatively shallow and cannot promote the construction and transfer of learners’ knowledge. Cognitive diagnostic technology could diagnose learners’ cognitive states and provide services for personalized teaching. Therefore, a personalized teaching questioning strategy based on learners’ cognitive structure diagnosis was proposed in this study. Firstly, we diagnosed learners’ cognitive structure through usability, distinguishability, and stability. Secondly, we discussed the types of questions that teachers should raise when facing learners in different situations. We also discussed the application of personalized teaching questioning strategies. The experiment took place at M Primary School in Ningxia, China, with the participation of one teacher and ninety-seven fourth-grade students. Seven lessons were observed and videotaped across a range of topics. The study revealed that personalized teaching questioning strategies could improve learners’ academic performance and subject literacy. They can also increase the number of teacher questioning, change the depth of teacher questioning content, and expand the scope of questioning subjects.

Modelling the structure of cognitive systems is a central goal of the cognitive sciences—a goal that has greatly benefitted from the application of network science approaches. This paper provides an overview of how network science has been applied to the cognitive sciences, with a specific focus on the two research ‘spirals’ of cognitive sciences related to the representation and processes of the human mind. For each spiral, we first review classic papers in the psychological sciences that have drawn on graph-theoretic ideas or frameworks before the advent of modern network science approaches. We then discuss how current research in these areas has been shaped by modern network science, which provides the mathematical framework and methodological tools for psychologists to (i) represent cognitive network structure and (ii) investigate and model the psychological processes that occur in these cognitive networks. Finally, we briefly comment on the future of, and the challenges facing, cognitive network science.

Employing social network sites (SNSs) for academic purposes has been investigated in the literature; however, there is not enough scientific knowledge about university instructors’ behavioral perceptions and values that drive their academic use of SNSs. Therefore, a systematic cognitive framework, regarding SNSs academic usage, is beneficial to understand these behavioral perceptions. This research utilizes the means–end chain (MEC) analysis approach to investigate university instructors’ cognitive structure toward the academic use of SNSs. It identifies important requirements for the effective academic use of SNSs by recognizing the relationship between the critical features of SNSs and instructors’ perceived values derived from these features. The findings show that seven significant features of SNSs form 45 MECs that appear to be the most useful features used by university instructors for academic purposes. These seven features were found to be cognitively associated with 10 positive benefits, which are crucial to the fulfillment of nine of the instructors’ personal values. Of the seven features, following others and being a group member were used most frequently by instructors in their academic practices. These two features were of significant value for the instructors to achieve a sense of accomplishment. The findings have practical implications for instructors and educational institution policy makers to enhance the effectiveness of SNSs use in academic settings.

Systemic racism is a scientifically tractable phenomenon, urgent for cognitive scientists to address. This tutorial reviews the built-in systems that undermine life opportunities and outcomes by racial category, with a focus on challenges to Black Americans. From American colonial history, explicit practices and policies reinforced disadvantage across all domains of life, beginning with slavery, and continuing with vastly subordinated status. Racially segregated housing creates racial isolation, with disproportionate costs to Black Americans’ opportunities, networks, education, wealth, health, and legal treatment. These institutional and societal systems build-in individual bias and racialized interactions, resulting in systemic racism. Unconscious inferences, empirically established from perceptions onward, demonstrate non-Black Americans’ inbuilt associations: pairing Black Americans with negative valences, criminal stereotypes, and low status, including animal rather than human . Implicit racial biases (improving only slightly over time) imbed within non-Black individuals’ systems of racialized beliefs, judgments, and affect that predict racialized behavior. Interracial interactions likewise convey disrespect and distrust. These systematic individual and interpersonal patterns continue partly due to non-Black people’s inexperience with Black Americans and reliance on societal caricatures. Despite systemic challenges, Black Americans are more diverse now than ever, due to resilience (many succeeding against the odds), immigration (producing varied backgrounds), and intermarriage (increasing the multiracial proportion of the population). Intergroup contact can foreground Black diversity, resisting systemic racism, but White advantages persist in all economic, political, and social domains. Cognitive science has an opportunity: to include in its study of the mind the distortions of reality about individual humans and their social groups.

The ideological and political (I&P) education in colleges must keep abreast with the times. This paper mainly studies the role of cognitive psychology in the reform of the I&P education in colleges. First, the theoretical basis of cognitive psychology was introduced. Then, the author analysed how cognitive psychology affects teaching effectiveness, and how to reform the I&P education based on cognitive psychology. Finally, empirical experiments were carried out on classroom teaching of the I&P education based on cognitive psychology. The results show that the teaching quality and learning effect hinges on the cognition level and cognitive structure of individuals; the application of cognitive psychology enables the I&P teachers to update their cognitive structure and professional knowledge, and to promote the teaching and case analysis abilities; the I&P teaching mode based on cognitive psychology has an ideal teaching effect. The research findings lay a solid basis for the reform of the I&P education in colleges.