It has been almost a decade since the increasing availability of new data and pervasive computing was heralded as ‘the new digital age’. Today, these developments continue to inspire the way psychologists conduct research with new and emerging forms of data (e.g., social media data, digital interactions, and sensors) further complementing psychology’s diverse measurement practices. Results are already challenging traditional theory with many designs allowing researchers to explore individual and situational factors simultaneously, which have often been studied separately. Collectively termed the Internet of Things, the potential for data linkage across many contemporary data sources, has instigated a new era in research that allows psychologists to leave the laboratory.
At the same time, transcending disciplinary norms remains essential when it comes to answering big questions that can deliver social, economic, and industrial impacts. However, progress will stall without some level of disciplinary cohesion in the first instance and psychology is only now starting to grapple with how recent technological advances impact the discipline more broadly. Methodological approaches remain scattered among groups with uneven skill sets and different interpretations of what constitutes psychological value. Variations in transparent research practices have also become magnified. This inequality can lead to costly mistakes. For example, while information systems can provide researchers with dynamic and multivariate data about the economy, the environment, education, health, child well-being, gender inequality, conflict and violence, many of these secondary data sets can also ‘lead to bad science if researchers fail to pay close attention to how the data were generated’.
Therefore, the time is right to start providing methodological cohesion in this exciting new space that psychological science finds itself. This will require a mixture of technical (e.g., technology, data and behavioural analysis) and non-technical training (e.g., critical thinking, measurement theory, ethics). Hence, realistic methodological progress must overcome challenges with limited resources and time available for students and tenured faculty to learn new skills. A book that is too long and exhaustive will be ignored and fail to capitalise on the dynamic pace of change. Something overly short, or high-level will fail to provide enough information for psychologists and others to put new skills into practice.
This volume will outline the foundations of what new technological developments mean for psychological science. Readers will gain both an understanding of relevant psychological theory, but also how this can be aligned with new methodologies and data that support current and future research endeavours within and beyond academia.