Literature DB >> 29469579

Big data in psychology: A framework for research advancement.

Idris Adjerid1, Ken Kelley1.   

Abstract

The potential for big data to provide value for psychology is significant. However, the pursuit of big data remains an uncertain and risky undertaking for the average psychological researcher. In this article, we address some of this uncertainty by discussing the potential impact of big data on the type of data available for psychological research, addressing the benefits and most significant challenges that emerge from these data, and organizing a variety of research opportunities for psychology. Our article yields two central insights. First, we highlight that big data research efforts are more readily accessible than many researchers realize, particularly with the emergence of open-source research tools, digital platforms, and instrumentation. Second, we argue that opportunities for big data research are diverse and differ both in their fit for varying research goals, as well as in the challenges they bring about. Ultimately, our outlook for researchers in psychology using and benefiting from big data is cautiously optimistic. Although not all big data efforts are suited for all researchers or all areas within psychology, big data research prospects are diverse, expanding, and promising for psychology and related disciplines. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Mesh:

Year:  2018        PMID: 29469579     DOI: 10.1037/amp0000190

Source DB:  PubMed          Journal:  Am Psychol        ISSN: 0003-066X


  8 in total

1.  Dog and owner characteristics predict training success.

Authors:  Jeffrey R Stevens; London M Wolff; Megan Bosworth; Jill Morstad
Journal:  Anim Cogn       Date:  2021-01-10       Impact factor: 3.084

2.  Introducing the Fear Learning and Anxiety Response (FLARe) app and web portal for the remote delivery of fear conditioning experiments.

Authors:  T McGregor; K L Purves; K S Young; T C Eley; T Barry; E Constantinou; M G Craske; G Breen
Journal:  Behav Res Methods       Date:  2022-09-07

3.  A New Remote Guided Method for Supervised Web-Based Cognitive Testing to Ensure High-Quality Data: Development and Usability Study.

Authors:  Victoria Leong; Kausar Raheel; Jia Yi Sim; Kriti Kacker; Vasilis M Karlaftis; Chrysoula Vassiliu; Kastoori Kalaivanan; S H Annabel Chen; Trevor W Robbins; Barbara J Sahakian; Zoe Kourtzi
Journal:  J Med Internet Res       Date:  2022-01-06       Impact factor: 5.428

4.  Gorilla in our midst: An online behavioral experiment builder.

Authors:  Alexander L Anwyl-Irvine; Jessica Massonnié; Adam Flitton; Natasha Kirkham; Jo K Evershed
Journal:  Behav Res Methods       Date:  2020-02

5.  Tracking stress via the computer mouse? Promises and challenges of a potential behavioral stress marker.

Authors:  Paul Freihaut; Anja S Göritz; Christoph Rockstroh; Johannes Blum
Journal:  Behav Res Methods       Date:  2021-04-05

6.  PONT: A Protocol for Online Neuropsychological Testing.

Authors:  William Saban; Richard B Ivry
Journal:  J Cogn Neurosci       Date:  2021-10-01       Impact factor: 3.225

Review 7.  Challenges and Future Directions of Big Data and Artificial Intelligence in Education.

Authors:  Hui Luan; Peter Geczy; Hollis Lai; Janice Gobert; Stephen J H Yang; Hiroaki Ogata; Jacky Baltes; Rodrigo Guerra; Ping Li; Chin-Chung Tsai
Journal:  Front Psychol       Date:  2020-10-19

8.  Online Assessment of Motor, Cognitive, and Communicative Achievements in 4-Month-Old Infants.

Authors:  Corinna Gasparini; Barbara Caravale; Valentina Focaroli; Melania Paoletti; Giulia Pecora; Francesca Bellagamba; Flavia Chiarotti; Serena Gastaldi; Elsa Addessi
Journal:  Children (Basel)       Date:  2022-03-16
  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.