About the Journal

Quanta Research (QR) is an open-access and free-of-charge journal aimed at catalysing transformative research endeavours in the diverse landscape of social sciences, with a specific focus on psychology, evaluation, and education. QR provides a platform for scholars and researchers to explore pioneering methodologies and computational AI approaches that redefine traditional boundaries and drive meaningful advancements in the field.


  • Innovative Methodologies in Psychology: QR welcomes research contributions that introduce novel methodologies and analytical approaches in psychology, aiming to deepen our understanding of human behavior, cognition, and emotion. Topics may include but are not limited to cognitive neuroscience, behavioral analysis, psychometrics, and computational modeling in psychology.
  • Evaluation and Assessment Strategies: QR invites scholarly works that propose innovative evaluation and assessment strategies in various domains, including education, healthcare, organizational management, and social policy. Contributions may explore new frameworks, methodologies, and tools for assessing program effectiveness, learning outcomes, and organizational performance.
  • AI Applications in Social Sciences: QR provides a platform for research that harnesses the power of artificial intelligence (AI) to address complex social issues and challenges. Submissions may focus on AI-driven data analytics, machine learning algorithms, natural language processing (NLP), and predictive modeling applied to social science domains such as sentiment analysis, social network analysis, and decision support systems.
  • Interdisciplinary Research and Collaborations: QR encourages interdisciplinary collaborations that integrate insights from multiple fields, including computer science, cognitive science, sociology, and economics, to tackle pressing societal issues and advance knowledge in social sciences. Interdisciplinary research topics may explore emerging trends, cross-disciplinary methodologies, and interdisciplinary frameworks for addressing complex social phenomena.
  • Innovative Approaches to Education: QR seeks contributions that propose innovative approaches to teaching, learning, and educational practice. Topics may include instructional design, educational technology, adaptive learning systems, gamification, and personalized learning environments, with a focus on leveraging computational AI methods to enhance educational outcomes and promote lifelong learning.


Abstracting and Indexing