We are planning an online workshop on how machine learning contributes to theory building in social sciences/neuroscience. We really want to be interdisciplinary. Someone has suggestions for speakers? No guarantee we invite your suggestions, but we'll seriously consider!

SubgroupSEM is R-based software to exploratively cluster people based on SEM parameters. E.g: People with which covariate-combinations show the biggest growth rate? We distinguished it from SEM trees and compare its result to LCA in this applied example: econtent.hogrefe.com/doi/full/10.10…

Please RT!! We will hold a free online interdisciplinary workshop on #MachineLearning and theory development on July 10-12 (three half days), with excellent speakers from psychology, neuroscience, sociology, cognitive science etc. Please register here. ml-theory.com

I'll be speaking in this workshop about the synergy between AI research and neuroscience. Looking forward to the discussion.

Do you want to know how machine learning can help develop new theoretical ideas? Come and join us for this free online workshop. For more information, speakers and registration go here: ml-theory.com Kou Murayama @CatherineALebel Baobao Zhang @[email protected] Blake Richards Ryota Kanai

a student shared that they create a study guide, show it to chatGPT, and ask it to generate practice exam questions. It can generate tons of questions for them to quiz themselves. Seems like a pretty good use of chatGPT to support student learning!

Our workshop on ML & Theory Development is coming close (10-12 Jul). Ryota Kanai (Ryota Kanai) will give a talk on NeuroAI & consciousness. "The Synergy of AI Research and Neuroscience: Clarifying Concepts in Consciousness Studies" For (free) registration: ml-theory.com/registration

Just one month before our free online workshop on machine learning and theory development (July 10-12)!! Caspar van Lissa @cjvanlissa will talk "Machine Learning can Advance Theory Formation in the Social Sciences". Program and registration are here: ml-theory.com/home

Another speaker in our exciting lineup is Rebecca Johnson. See her important talk on "Machine Learning and the Targeting of Help in U.S. Government Bureaucracies: Promises and Perils". Free reg at ml-theory.com/home Kou Murayama Julia Moeller Adeel Razi @CatherineALebel Alexander Jung

Another reminder of our free, online workshop on #MachineLearning and theory development!! One speaker, Mayank Agrawal, will show how we can combine computational modeling and ML, titled: "Integrating Theory-Based and Data-Driven Approaches to Human Decision-Making".

Thrilled to share the 1st pre-print from MERF, the Meta-Analysis of Educational RCTs w/ Follow-up w/Tyler Drew Bailey. Our new dataset includes approx 2500 effect sizes across 89 RCTs compiled to investigate critical questions about fadeout. tinyurl.com/merf2 1/

Register now for our workshop series on theory development & machine learning! ml-theory.com On 7/10, 3.45 pm CEST, Anna Ivanova discusses whether machines can think or just use language properly. Drew Bailey Kou Murayama Adeel Razi @CatherineALebel Alexander Jung

Finally out: Our (w/ Carolin Hahnel, Frank Goldhammer) example on using theoretical hypotheses on mental processes to select indicators and draw inferences from #ProcessData. Example on decisionmaking in #websearch-tasks. DIPF @LEAD_GradSchool doi.org/10.1027/1015-5…

Need a quick data summary? gt_plt_summary() from {gtExtras} is your friend 🥳 #rstats

Wunderbare Umfrage für alle #Lehrerinnen und #Lehrer: Wie äußert sich der Einfluss von Schulklassen auf das Unterrichtsgeschehen? #Twitterlehrerzimmer, #EduPnx, #EduChat

This new Review from Drew Bailey et al. looks at key challenges for causal inference in studies of human behaviour and offers an overview of methodological solutions for these challenges. nature.com/articles/s4156…

I have been very inactive on social media recently but will try to recover... Here is our new publication on #causalinference and cross-lagged panel models in Psych Metods. People use RI-CLPM as a default nowadays but we should think more deeply about it. psycnet.apa.org/fulltext/2025-…

Happy to share our (@SKoivuhovi et al.) article on students' academic development based on teachers' perceptions and tracking! In Finland (our data source) tracking is accompanied by only small differences in curriculum which has interesting implications! authors.elsevier.com/c/1k3au,Gtqw3e…