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，无论人们在世界的哪个地方。不幸的是，在这种情况下，已经有准备好并且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 et al., 2018）。因此，至关重要的是，未来的成年人在成长过程中要具备与所有观点的人有效互动的能力，以实现集体利益（UNESCO, 2015）。尽管这一愿望在全球具有重要意义，但关于衡量这些技能在学生、学校和国家之间如何以及为何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受教育青少年在相互联系和多样化的世界中茁壮成长的认知和态度倾向背后的复杂和多样的机制。它将通过三个相互关联的研究来分析新的国际学生评估项目（PISA） 2018年全球能力（GC）评估数据，以实现这一目标。国际学生评估项目（PISA）的实施。这些数据涵盖了66个国家的60多万名15岁学生及其学校，并衡量了学生“审视当地、全球和文化意义问题；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；并为集体福祉和可持续发展采取行动”（经合组织，2020年，第47页）。多层模型（MLM）和结构方程模型（SEM）框架将用于分析这些丰富但复杂的跨国调查数据，以研究GC水平和社会人口差距在学校和国家之间的差异，以及学生福利、制度和国家政策以及地理差异如何帮助解释和解决这些差异。然后，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，这些测量被批评为有问题和不充分（Grotluschen等人，2018；Engel等人，2019;Tarc, 2021）。

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).