I assume it will be 17:00 UTC (and not 16:00).

The Journal of Open Psychology Data (JOPD) invites data papers that present datasets for psychological research on learning processes, educational environments, individual differences, motivation, achievement, or social factors in education.

This study was made possible through a fruitful collaboration with 👉 @jpstein.de, Sabine Zinn, Florian Griese, and @markusappel.bsky.social.

- Direct experience with AI was still rather limited — especially in healthcare and education.

📊 In sum, while AI is broadly accepted across domains in Germany, first-hand experience remains relatively scarce.

Key findings:
- Overall, respondents expressed favorable attitudes toward AI.
- Healthcare applications of AI were viewed more positively than those in the work context.
- Cognitive evaluations were more positive than emotional or behavioral responses.

To help researchers in this respect, @uschroeders.bsky.social and I wrote a tutorial on sample size planning for IRT analyses (open access). It includes practical recommendations and R code examples in the supplemental material.

@lifbi.bsky.social

Further reading:
- Assessing reading competence: doi.org/10.14786/flr...
- Assessing math competence: doi.org/10.5157/NEPS...
- Assessing figural reasoning: doi.org/10.3389/fpsy...
- Assessing perceptual speed: doi.org/10.1027/2698...
- Out-of-level testing: doi.org/10.1027/1015...

Key findings:
- Tests for complex cognitive domains such as reading or math often show substantial limitations
- Tests for basic cognitive abilities such as reasoning or perceptual speed can be measured reliably and comparably
- Out-of level testing may improve measurement quality

A great collaboration with Wolfgang Lenhard, Uta Landrock, and Sabine Zinn.

Overall, remote testing introduces some bias, but the effects are smaller than often feared—showing promise for future large-scale assessments.