André Bittermann

@abitter.bsky.social

Senior researcher @zpid.bsky.social Metascience, PhD, psychologist, interested in researcher behavior and science mapping, using bibliometrics, natural language processing, and computational methods

I’ve officially resigned as Associate Editor for Frontiers in Systems Neuroscience. It used to be a reputable journal, but became a case study in how forced automation destroys academic integrity. 👇

Join our Mini-Hackathon and help us draft community-driven best-practice guidelines for preregistration!✨ 🗓️ Friday, June 5, 4-6 PM CET 📍 Zoom Register by indicating your interest in participating in the #prereg community events here: forms.gle/yrmK8Wnd4oqw... @zpid.bsky.social @forrt.bsky.social

Best-Practice Guidelines for Psychology

Thank you for your interest in being part of our community project "Best Practices in Psychology"! For more information on the project, please refer back to our website: https://forrt.org/best-practic...

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Generative AI and LLMs are rapidly transforming research, and psychological scientists are figuring out how to use them responsibly. Here are nine articles from AMPPS that offer practical tutorials, frameworks, and cautionary insights for researchers. #AI #AcademicSky

How Should Psychologists Use AI and Big Data? Nine Guides Point the Way

Practical tutorials, frameworks, and cautionary insights for researchers navigating this new terrain.

psychologicalscience.org

🚨THREATENED BY SCIENCE🚨People often reject science at odds with their prior beliefs. In three studies, we now show that much of this can be explained by feelings of threat and we test how affirmations in #SciComm might help alleviate such threats. Now out in Public Understanding of Science! 🧵1/4

doi.org

A clear gap in "#GenAI for learning" applications is a failure to understand scaffolding and the role of digital prompts in promoting not just knowledge but also agency internalization. This article has a helpful framework for bridging this gap. #GenAI companies would learn much from this article.

Digital Prompting in Education: A Design Framework and Bibliometric Analysis - Educational Psychology Review

Digital prompts are brief instructional cues designed to guide student learning. The variety of ways in which prompts are designed and labelled across education result in conceptual and…

doi.org

Tomorrow at Online #SIPS2026, I'll be presenting a bibliometric case study of two top-tier psychology journals, indicating effects of reference limits on citation diversity. How to ensure both accuracy and inclusiveness in referencing? I'll pitch an idea. 🕗May 6 | 08:45 AM (EDT) | 14:45 (Berlin)

Removing Reference Limits and Introducing Reference Evaluation

Happy to share that our bibliometric collaboration work with the Individualized Interventions Lab @dipfaktuell.bsky.social @garvinbrod.bsky.social has been published in EdPsyRev! 🎉 We propose a guiding framework that conceptualizes digital prompts as dynamic scaffolds. 🔓 #OA doi.org/10.1007/s106...

Digital Prompting in Education: A Design Framework and Bibliometric Analysis - Educational Psychology Review

Digital prompts are brief instructional cues designed to guide student learning. The variety of ways in which prompts are designed and labelled across education result in conceptual and terminological inconsistencies that make it difficult to integrate research findings. Furthermore, artificial intelligence (AI) has introduced a new dominant meaning of the term “prompt” that complicates the discoverability of relevant literature. To address these challenges, we propose a guiding framework that conceptualizes digital prompts as dynamic scaffolds and characterizes their instructional design through a typology of content, function, presentation, and source. Using a bibliometric approach, we analyzed 1,238 publications to examine how well this framework captures the structure of the field. We identified 283 distinct prompt labels, most of which were used in only one publication. The mapping of these labels onto the proposed typology led to a refined understanding of prompt design characteristics. Furthermore, we examined co-occurrences between labels and identified research topics and citation practices. The resulting patterns revealed two major research clusters centered on metacognitive and self-explanation prompts, which structure much of the literature. However, these two clusters lack integration. We show how these separate research traditions can be integrated into our framework of dynamic scaffolding through prompts. Finally, we demonstrate how our typology of prompt types can foster greater terminological coherence and improve search strategies in the age of AI.

doi.org

Selecting an effect size for power analysis is hard. Many researchers fall back on Cohen's thresholds, but they have no empirical basis and vary wildly by field. Our new paper offers a better option: field-specific effect size distributions built from meta-analytic data doi.org/10.3758/s134...

Abstract
Effect sizes are useful for understanding the magnitude of study results and for planning new studies via power analysis.
However, despite their wide usage, effect sizes are often misinterpreted. This is mostly due to an over-reliance on general
effect size benchmarks that were not intended for broad application across diverse research fields. Inaccurate effect size
interpretations can lead to incorrect conclusions about the magnitude of study results and incorrect sample size estimates,
thereby increasing the likelihood of false-positive results. This article introduces the ESDist R package, which is designed
to calculate empirically derived effect-size benchmarks or a range of reliably detectable empirical effect sizes for a specific
research question or field of interest by computing effect size distributions (ESDs). This package can be used on data that
can be easily extracted from pre-existing meta-analyses to help researchers more accurately plan new studies or to better
understand how an individual study might relate to other studies in their field. ESDist includes a set of features that make it
easy to use in a priori power analysis. Moreover, the package includes a feature for estimating effect size benchmarks that
account for publication bias and are weighted by effect sizes' variances, which addresses existing limitations of using ESDs
for study planning or interpretation.

How strong is the threat to academic freedom? If you are a publishing psychologist, please help us get a better understanding of the threats due to external pressure and self-censorship in the publication process by taking our 5-10 min anonymous survey: t1p.de/t1qof Results will be shared here!

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Our lab has the capacity to test ~500 uni students each semester If you’re a researcher in cognitive psychology or metascience and need data collection support, we’d love to collaborate. We can help collect high-quality data from a large student sample. Get in touch to discuss potential projects!