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.
Research
I am interested in how human beings process self-related information, with a “3M” approach: meta-science, (cognitive) modeling, and (psychological) measurement. We are also trying to apply the “3M” approach to the mental health issues in the real world.
I support Open Science and co-found the Chinese Open Science Network, please see our position paper in AMPPS or book chapter. Also, I have contributed to a series of Big-Team Science (BTS) and collected data in China. Below are the resources we shared so far.
Open Data (开放数据)
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.
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.
Open Educational Resources (开放教学资源)
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(贝叶斯统计及其在Python中的实现)》。该课程以《Bayes Rules!》为教材，所有的课件均使用Jupyter Notebook完成，以CC-BY方式开放，见这里，同时在B站上传录屏，并有将课程转成在线电子书。 | Advanced Psychological Statistics (Bayesian statistics with Python) for undergrads. This course focuses Bayesian statistics, I used Bayes Rules! as the textbook but PyMC as the programming language. All slide are prepared using Jupyter Notebook and are avialable here. This course is in the autumn-winter semester.
- 2024年R课的B站录屏; Recordings of the 2024 fall semester are available here
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.
- 2024年R课的B站录屏; Recordings of the 2024 Spring semester are available here
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.