我是胡传鹏，2017年博士毕业于清华大学心理学系(现心理与认知科学系)，自2020年12月起在南京师范大学心理学院任教。I am Dr. Hu Chuan-Peng, a faculty member of the School of Psychology, Nanjing Normal University.
I am interested in how humans make speeded decisions, especially when these decisions involves self-related information. I followed recommended practices to counter the "credibility crisis" in psychology, and adopted a non-conventional approach in my team: we re-examine effects via meta-science, curate datasets for cumulating knowledge and (cognitive) modeling, and (re)assess (psychological) measurements to improve ontological commitment of constructs.
I co-found the Chinese Open Science Network (see our position paper in AMPPS or book chapter). I have contributed to a series of Big-Team Science (BTS) and collected data in China. In the past five years, I also reflected on how researchers embrace open science practices in resource-constrained context (see our guide for researchers in developing countries). Below are the resources we shared so far.
Dataset 1: Data from the Human Penguin Project (data, data descriptor, original study). This dataset includes 1755 participants' (from 12 countries) data measured by multiple psychological scales.
Dataset 2: Questionnaire Data From the Revision of a Chinese Version of Free Will and Determinism Plus Scale (data, data descriptor, original study). An updated study on the measurement invariance of FAD+ scale across four languages was published in Royal Society Open Science in 2024. Both datasets contain questionnaire data focus on belief in free will.
Dataset 3: A dataset of cognitive ontology for neuroimaging studies of self-referential process of human, with meta data extracted from 136 published neuroimaging studies that employed self-referential encoding task (dataset, data descriptor). These data can be used for coordinate-based meta-analyses of fMRI (e.g., Hu et al., 2016, Neuroscience & Biobehavioral Reviews paper ALE maps) or other purposes. This dataset is continuous evolving.
Dataset 4: An Extended Chinese Social Evaluative Words List (data, article, code), which include Chinese words that describe people's appearance,socioeconomic status, sociability, competence, and morality.
Dataset 5: A dataset of trial-level data that employed self-matching task (Sui et al., 2012). We curated all trial-levels data available and standardized them for future use(dataset. This dataset now include trial-level data from 44 papers, covering 70 datasets and 3603 participants in total, and is continuing evolving.
Please see the website of my lab for more about my research, please see our github account for data and code our projects.
dockerHDDM: We created a docker image for HDDM, a python package for hierarchical drift-diffusion models, please see our tutorial paper on AMPPS.
本人在南师大心理学院教授统计相关的课程，所有的课件、录屏和录屏所转的电子书均在线公开，欢迎大家批评建议，如果您觉得本人公开的资料有用，也可以给本人写邮件反馈，让本人了解开放这些教学资源帮助到了谁。I am teaching two courses related to statistics and all slides and recording of lectures are open (with CC-BY license).
2022 ~ currently, 本科生的《高级心理统计学(贝叶斯统计)》。该课程以《Bayes Rules!》为教材，2023/2024的课件均使用Jupyter Notebook完成，2025年以后转向使用R语言实现，以CC-BY方式开放，见这里，2025年/2024年的录屏上传至B站，录屏转录的在线电子书也公开获取。 | Advanced Psychological Statistics (Bayesian statistics with Python) for undergrads. This course focuses Bayesian statistics, I used Bayes Rules! as the textbook with both R and PyMC as the programming language. All slide are prepared using Jupyter Notebook or qmd and are avialable here. This course is in the autumn-winter semester.
2022 ~ currently, 《R语言在心理学研究中的应用》。给心理学及相关背景学生的R语言入门课程。所有课件、录屏和录屏所转的电子书均已经开放。| R for Psychological Research for graduate students. The goal of this course is introducing R language to students with psychology background. All slide are prepared using RMarkdown and are avialable here. This course is in the spring-summer semester.
2021 ~ 2023: (本科生的《心理统计学》). 所有的课件均使用RMarkdown做成，以CC-BY的方式开放，见这里。Psychological Statistics for undergrads. All slide are prepared using RMarkdown and are avialable here. This course lasts for two semesters.