Nonlinear capital market payoffs to science-led innovation

This study explores the extent to which cross-sectional differences in firms’ propensity to absorb and utilize scientific knowledge matter for their stock market and operating performance. Unlike previous empirical studies and given the coexistence of both benefits and potential costs to science-guided search, I conceptualize innovation as a recombinant search to hypothesize a non-monotonic relationship. Using patent data from the European Patent Office (EPO) relative to 3281 international firms over the 1999–2015 period, empirical tests yield evidence in support of the predictions. However, the effect varies with firm-level absorptive capacity, across industries and countries. As suggested by a limited attention model, I find a stronger payoff predictive power of science for firms with lower investor attention and higher valuation uncertainty. Besides, the association between science and future operating performance increases with time, indicating that firms’ scientific capabilities are a potent driver of long-term profitability. The conclusions are robust to controlling for the endogenous nature of firms’ use of scientific knowledge. By providing a useful basis upon which to judge the economic merit of firms’ innovation endeavors, this study contributes to reducing capital market imperfections that curtail access to external finance and ultimately spurring private-sector investment in R&D. It also provides evidence of diminishing marginal payoffs to science-led search. Finally, the evidence is likely to be relevant to policymakers, who might wish to influence the innovation ecosystem in a way to sustain long-term prosperity.     

Innovation and productivity among heterogeneous firms

This paper examines the links between firm innovation and productivity using the largest cross-country panel dataset assembled for this purpose to date. We use harmonized and comparable data on a total of 40,577 small, medium and large firms surveyed in the World Bank Enterprise Surveys (WBES) and provide some support for the reported patterns previously found in the innovation literature. Our results indicate that estimates from studies using cross-section data may be upward biased but nevertheless, innovative firms are significantly and economically more productive in both the manufacturing and services sectors.     

OSCE的持续改进:复旦大学上海医学院的经验

复旦大学上海医学院持续不断地对OSCE项目进行研究改进,包括OSCE项目的组织与运行、SP队伍的发展与管理、病例的新增与优化、考站的安排与设置、反馈方式与对象等,取得了良好的理论和实践效果。     

The mediating effects of needs satisfaction on the relationships between prior knowledge and self-regulated learning through artificial intelligence chatbot

The anthropomorphic characteristics of artificial intelligence (AI) can provide a positive environment for self-regulated learning (SRL). The factors affecting adolescents' SRL through AI technologies remain unclear. Limited AI and disciplinary knowledge may affect the students' motivations, as explained by self-determination theory (SDT). In this study, we examine the mediating effects of needs satisfaction in SDT on the relationship between students' previous technical (AI) and disciplinary (English) knowledge and SRL, using an AI conversational chatbot. Data were collected from 323 9th Grade students through a questionnaire and a test. The students completed an AI basic unit and then learned English with a conversational chatbot for 5 days. Confidence intervals were calculated to investigate the mediating effects. We found that students' previous knowledge of English but not their AI knowledge directly affected their SRL with the chatbot, and that satisfying the need for autonomy and competence mediated the relationships between both knowledge (AI and English) and SRL, but relatedness did not. The self-directed nature of SRL requires heavy cognitive learning and satisfying the need for autonomy and competence may more effectively engage young children in this type of learning. The findings also revealed that current chatbot technologies may not benefit students with relatively lower levels of English proficiency. We suggest that teachers can use conversational chatbots for knowledge consolidation purposes, but not in SRL explorations.

Practitioner notes

What is already known about this topic

• Artificial intelligence (AI) technologies can potentially support students' self-regulated learning (SRL) of disciplinary knowledge through chatbots.
• Needs satisfaction in Self-determination theory (SDT) can explain the directive process required for SRL.
• Technical and disciplinary knowledge would affect SRL with technologies.

What this paper adds

• This study examines the mediating effects of needs satisfaction in SDT on the relationship between students' previous AI (technical) and English (disciplinary) knowledge and SRL, using an AI conversational chatbot.
• Students' previous knowledge of English but not their AI knowledge directly affected their SRL with the chatbot.
• Autonomy and competence were mediators, but relatedness was not.

Implications for practice and/or policy

• Teachers should use chatbots for knowledge consolidation rather than exploration.
• Teachers should support students' competence and autonomy, as these were found to be the factors that directly predicted SRL.
• School leaders and teacher educators should include the mediating effects of needs satisfaction in professional development programmes for digital education.

     

Keep DRAGging ON: Is solving more problems in DragonBox 12+ associated with higher mathematical performance during the COVID-19 pandemic?

Prior research has shown that game-based learning tools, such as DragonBox 12+, support algebraic understanding and that students' in-game progress positively predicts their later performance. Using data from 253 seventh-graders (12–13 years old) who played DragonBox as a part of technology intervention, we examined (a) the relations between students' progress within DragonBox and their algebraic knowledge and general mathematics achievement, (b) the moderating effects of students' prior performance on these relations and (c) the potential factors associated with students' in-game progress. Among students with higher prior algebraic knowledge, higher in-game progress was related to higher algebraic knowledge after the intervention. Higher in-game progress was also associated with higher end-of-year mathematics achievement, and this association was stronger among students with lower prior mathematics achievement. Students' demographic characteristics, prior knowledge and prior achievement did not significantly predict in-game progress beyond the number of intervention sessions students completed. These findings advance research on how, for whom and in what contexts game-based interventions, such as DragonBox, support mathematical learning and have implications for practice using game-based technologies to supplement instruction.

Practitioner notes

What is already known about this topic

• DragonBox 12+ may support students' understanding of algebra but the findings are mixed.
• Students who solve more problems within math games tend to show higher performance after gameplay.
• Students' engagement with mathematics is often related to their prior math performance.

What this paper adds

• For students with higher prior algebraic knowledge, solving more problems in DragonBox 12+ is related to higher algebraic performance after gameplay.
• Students who make more in-game progress also have higher mathematics achievement, especially for students with lower prior achievement.
• Students who spend more time playing DragonBox 12+ make more in-game progress; their demographic, prior knowledge and prior achievement are not related to in-game progress.

Implications for practice and/or policy

• DragonBox 12+ can be beneficial as a supplement to algebra instruction for students with some understanding of algebra.
• DragonBox 12+ can engage students with mathematics across achievement levels.
• Dedicating time and encouraging students to play DragonBox 12+ may help them make more in-game progress, and in turn, support math learning.

     

Taking the maker movement to school: A systematic review of preK-12 school-based makerspace research

In this systematic review, we examined research on school-based makerspaces, emergent but increasingly popular sites for instruction and learning in preK through 12 settings. Through electronic database, hand, and ancestral searches, we identified 22 empirical studies published in peer-reviewed journals and dissertations that reported preK-12 students’ learning outcomes after participating in school-based makerspace interventions. We found that school-based makerspace research is increasing and published internationally, with a majority of studies (n = 13) conducted with middle and high school participants. Outcomes and interventions varied considerably across studies, demonstrating the disparate nature of school-based makerspace research. In the studies we reviewed, the goals, objectives, and scope of makerspace interventions did not conflict with those of schools, but best practices for makerspace teachers were lacking and equity-oriented approaches to designing makerspace activities and materials were still emerging. Implications of our findings for planning makerspace instruction and future research on makerspace interventions are discussed.     

A systematic literature review of K-12 environmental Citizen Science (CS) initiatives: Unveiling the CS pedagogical and participatory aspects contributing to students’ environmental citizenship

Environmental Citizen Science (CS) initiatives have been largely embraced in K-12 education, as they are often hypothesized to improve students' knowledge, skills, attitudes, and behaviours to act as “environmental citizens” according to the notion of Environmental Citizenship (EC). However, the potential of environmental CS initiatives to promote Education for Environmental Citizenship (EEC) has not been systematically explored. At the same time, environmental CS initiatives for educational purposes are highly heterogenous and learning is enacted in diverse ways, according to the participatory and the pedagogical components underpinning each initiative. To address the complexity of the field, this review study adopts the PRISMA methodology to synthesize thirty-four empirical studies (n = 34) retrieved from a systematic review of the literature covering the last two decades (2000–2020). The reviewed environmental CS initiatives were subjected to a content analysis to identify their impact on students' EC (e.g., EC competences, actions, outcomes), as well as to unveil the CS initiatives' constitutional components in terms of (a) Participation (e.g., types of students' contributions, level of data collection, frequency of students' participation, modes of student engagement, forms of students’ involvement), and (b) Pedagogy (e.g., learning goals, educational contexts, learning mechanisms, EEC pedagogy). Our analysis shed light to the three territories (Participation, Pedagogy, Environmental Citizenship) underpinning the reviewed CS initiatives as well as to their interrelations. We reflect on these findings, and we provide directions for future research to guide the development of more successful environmental CS initiatives in K-12 education, serving as a vehicle for EC.