How can we teach tomorrow's adults the knowledge, skills, and attitudes needed to tackle global issues and intercultural situations?

互联网和社交媒体提供了大量的信息和联系的可能性，无论人们在世界的什么地方。不幸的是，观众已经准备好并愿意接受越来越多的与气候变化、疫苗接种、大屠杀等有关的错误信息和阴谋论的传播(例如，Terry，2017；Harvey等人，2018)。因此，为了集体利益，未来的成年人必须具备与各种观点的人进行有效互动的能力(教科文组织，2015年)。尽管这一愿望具有全球重要性，但对于衡量这些技能如何以及为什么在学生、学校和国家之间存在差异的研究仍然很少。这个跨学科的AQM、教育、地理和心理学项目的总体目标是揭示在校青少年认知和态度能力背后复杂而多样的机制，以便在一个相互关联和多样化的世界中茁壮成长。它将通过三项相互关联的研究来实现这一目标，这些研究分析了2018年国际学生评估方案(PISA)关于全球能力(GC)评估的新数据。实施国际学生评估方案(PISA)。这些数据覆盖了66个国家的60多万15岁儿童及其学校，并衡量了学生的能力，即“研究具有地方、全球和文化意义的问题；理解和欣赏他人的观点和世界观；参与开放、适当和有效的跨文化互动；并采取行动促进集体福祉和可持续发展”(经合组织，2020年，第47页)。多层次模型(MLM)和结构方程模型(SEM)框架将被用来分析这些丰富但复杂的跨国调查数据，以研究不同学校和国家的GC水平和社会人口差距是如何变化的，以及学生的幸福感、机构和国家政策以及地理差异如何有助于解释和解决这些差异。这些分析还将提供机会，评估这些GC测量在不同国家背景下的有效性，这被批评为有问题和不足(Grotluschen等人，2018年；Engel等人，2019年；TARC，2021年)。

The internet and social media provide vast information and possibilities to connect no matter where people are in the world. Unfortunately, with this there has been ready and willing audiences to consume an increasing spread of misinformation and conspiracy theories related to climate change, vaccinations, the holocaust, amongst many others (e.g., Terry, 2017; Harvey et al., 2018). It is therefore critical that tomorrow's adults grow up with the aptitudes to interact effectively with people from all viewpoints in the interests of the collective good (UNESCO, 2015). Despite the global importance of this aspiration, there is still very little research into measuring how and why these skills vary across students, schools, and countries.The overarching aim of this interdisciplinary AQM, education, geography, and psychology project is to uncover the complex and diverse mechanisms behind the cognitive and attitudinal aptitudes of schooled teenagers to thrive in an interconnected and diverse world. It will achieve this aim through three interlinked studies analysing new Programme for International Student Assessment (PISA) 2018 data on Global Competence (GC) assessments. delivery of the Programme for International Student Assessment (PISA). These data cover over 600,000 15-year-olds and their schools across 66 countries and measure students' abilities to "examine issues of local, global and cultural significance; understand and appreciate the perspectives and worldviews of others; engage in open, appropriate and effective interactions across cultures; and take action for collective well-being and sustainable development" (OECD, 2020, p. 47). The Multilevel Modelling (MLM) and Structural Equation Modelling (SEM) frameworks will be used to analyse these rich but complex cross-national survey data to study how levels and sociodemographic gaps in GC vary across schools and countries and how student wellbeing, institutional and national policies, and geographical variations can help explain and address these variations. These analyses will then also provide the opportunity to assess the validity of these GC measurements across different national contexts, which has been criticised as questionable and insufficient (Grotluschen et al., 2018; Engel et al., 2019; Tarc, 2021).