Bøker i Zeitschrift für Psychologie / Journal of Psychology-serien

A showcase of how the web can be used to advance psychological knowledgeWeb-based research methodology has evolved since the development of the world wide web in the 1990s and has proliferated and diversified with layers upon layers of new major developments in Internet technology and life generally (e.g., search engines, social media, smartphones, Open Science). This volume presents a selection of state-of-the-art contributions on web-based research in psychology. Expert authors explore research methodology, including new methods made possible through the web or research that cannot be done without the web. In addition, research ethics, which have special characteristics in the online research environment, are addressed to varying degrees, including deception and inclusivity. Further topics presented range from how web-based research can advance our knowledge on perception to the adoption of Open Science (including sharing data, materials, and preregistrations), as well as how behavior is observed in web-based research. This collection of contributions is a showcase of the creativity of researchers to find nifty new ways to harness the web to advance psychological research.

The joys and pains of using big data and research synthesis methods in the field of psychology This sixth collection of "Hotspots in Psychology" goes beyond presenting state-of-the-art systematic reviews and meta-analyses in research fields to also discuss the fruitfulness and challenges of using big data in psychological research. For instance, topics such as intensive longitudinal data (e.g., time series and experience sampling), nonobtrusive methods of data gathering (e.g., sensors and log data), and how big data can be handledand analyzed.Five contributions explore the application of individual participants meta-analyses as a way to replicate studies, the role of the degree of anthropomorphism ("humanlikeness") in human-robot interactions, the challenge of multiple dependent effect sizes when conducting a meta-analytical structural equation model, the value of using log data from online platforms as a way to predict learning outcomes, and the utility of a blockwise fit evaluation in structural equation models with many longitudinally measured variables. To promote open science, supplemental material is available in a repository.