期刊档案 · EDUCATION, SCIENTIFIC DISCIPLINES
Journal of Statistics and Data Science Education
ISSN 2693-9169 · Taylor & Francis Group · United States
Journal of Statistics and Data Science Education 中科院 教育学 4区（2025 年升级版），影响因子 2.3（官网公布），JCR Q2（官网公布），钻石开放获取（无 APC），免版面费，出版商公布外审后首次决定约 79 天，官网公布录用率 15%，2025 年发文 56 篇，ESCI、Scopus 收录。
研究范围
研究范围与定位
Journal of Statistics and Data Science Education 由 Taylor & Francis Group 出版，属中科院教育学大类（2025 升级版4区）。按 OpenAlex 近年发文统计，该刊主要发表 Statistics Education and Methodologies、Data Analysis with R、Innovations in Educational Methods 等主题的论文，这 3 个主题约占 53.4%，主导子领域为 Education。（根据 OpenAlex 主题统计与中科院分区数据生成）
The Journal of Statistics and Data Science Education (JSDSE) is an open access peer-reviewed journal published by the American Statistical Association. It disseminates accessible knowledge for the improvement of data science and statistics education at all levels, including: elementary, secondary, post-secondary, post-graduate, continuing, and workplace education. Although JSDSE is a journal of the American Statistical Association, submissions are welcome from educators, practitioners, and researchers around the world. Article types include, but are not limited to: Original Research Articles: Curricular reform Innovative methods of instruction or assessment Research (including case studies) on students’ understanding of data science, statistics, and probability Research on the teaching of statistics and data science and on attitudes and beliefs about statistics and data science Creative and tested ideas (including experiments and demonstrations) for teaching statistics, data science, and probability Articles that describe how students can develop data fluency and data acumen Articles that describe how students learn computational techniques and workflows, undertake the entire data analysis cycle, and master a broader set of learning outcomes Articles that help bridge the gap between traditional statistics, computational science, and domain applications in data science Use of active learning and student centered pedagogies (e.g., cooperative learning and projects, growth mindset) Statistical and data literacy Data ethics Distance education and online learning Overviews and reflective essays: Scholarly overview of the literature on topics in statistics and data science education Reflective essays by scholars with extensive experience in data science and statistics education Reviews of software, books, and teaching materials: Reviews of teaching materials must describe actual experiences using the materials Datasets and Stories: Description of the pedagogical uses of multivariate dataset(s) (including discussions of achievable learning outcomes, potential pitfalls, helpful teaching tips), with the associated dataset(s) available for download with the manuscript for instructional use in classes and further analysis Research in K-12 Education: Research related to the teaching, learning, and assessment of statistics and data science in K-12 settings Statistics and Data Science Education in the Health Sciences: Teaching and learning of statistics and data science
摘自期刊官网 Aims & Scope
研究方向（LetPub）：EDUCATION, SCIENTIFIC DISCIPLINES
主编 Juana Sanchez出版商官网
主要研究主题 OpenAlex 近年发文统计，占比为近似值
- Statistics Education and MethodologiesMathematics37.8%
- Data Analysis with RComputer Science9.6%
- Innovations in Educational MethodsSocial Sciences6%
- Genetics, Bioinformatics, and Biomedical ResearchBiochemistry, Genetics and Molecular Biology5.1%
- Scientific Computing and Data ManagementDecision Sciences4.3%
- Online Learning and AnalyticsComputer Science4%
- Research Data Management PracticesComputer Science3.6%
- Online and Blended LearningSocial Sciences2.8%
分区与收录
学科分区与数据库收录
中科院期刊分区表
期刊分区表（ 2025年3月升级版）教育学 4 区
| 类别 | 学科 | 分区 |
|---|---|---|
| 大类 | 教育学 | 4 区 |
| 小类 | 学科教育EDUCATION, SCIENTIFIC DISCIPLINES | 4 区 |
Top 期刊：否综述期刊：否
《新锐期刊分区表》（ 2026年3月发布）教育学 3 区
| 类别 | 学科 | 分区 |
|---|---|---|
| 大类 | 教育学 | 3 区 |
| 小类 | 学科教育EDUCATION, SCIENTIFIC DISCIPLINES | 3 区 |
Top 期刊：否综述期刊：未标注
期刊分区表（ 2023年12月旧的升级版）未收录
该期刊未被此版本分区表收录。
期刊官网公布的 JCR / CiteScore 分区
- JCR Q2 · 最佳分区 · 2025 年度
- CiteScore Q1 · 2025 年度
出版商自述数据，JCR 以 Clarivate、CiteScore 以 Scopus 公布为准；与中科院分区是不同体系。出版商官网
数据库收录
ESCIScopusDOAJLetPub
国际期刊预警名单：各版本均未列入LetPub
期刊官网自述收录
PubMedERIC出版商官网
其他：American Statistical Association、Current Index to Statistics (Online)、Elsevier BV、ERIC (Education Resources Information Center)、National Library of Medicine
期刊官网列出的收录清单，未与各数据库逐一核对；Web of Science 各子库以上方记录为准。
不同版本、大类与小类分别展示，不将不同评价口径合并为一个分区值；投稿与考核前请确认所在机构采用的版本。
指标
影响力指标与发文规模
影响力指标
- 影响因子（出版商公布） 2025
- 2.3出版商官网 ·
- 五年影响因子（出版商公布） 2025
- 2.6出版商官网 ·
- CiteScore 2026-06
- 4.3LetPub ·
- CiteScore（出版商公布） 2025
- 4.3出版商官网 ·
- SJR 2026-06
- 1.01LetPub ·
- SJR（出版商公布） 2025
- 1.01出版商官网 ·
- SNIP 2026-06
- 1.74LetPub ·
- SNIP（出版商公布） 2025
- 1.74出版商官网 ·
- h-index
- 23OpenAlex ·
- i10-index
- 66OpenAlex ·
- 两年平均被引
- 2.01OpenAlex ·
- 自引率
- 26.1%LetPub ·
- Gold OA 文章占比
- 100%LetPub ·
发文规模
- 年文章数
- 51LetPub ·
- 年下载量（出版商公布）
- 453,000出版商官网 ·
逐年发文量 OpenAlex 统计 · 累计 285 篇 · 当年数据不完整
| 年份 | 发文量 | 其中 OA | 被引 |
|---|---|---|---|
| 2026 | 35 | 35 | 8 |
| 2025 | 56 | 56 | 78 |
| 2024 | 51 | 51 | 199 |
| 2023 | 35 | 35 | 390 |
| 2022 | 55 | 55 | 522 |
| 2021 | 29 | 29 | 378 |
不同来源的统计口径与观测时间不同，页面保留各来源原值；“出版商公布”为期刊官网自述数据。
审稿与录用
审稿周期与录用情况
出版商公布的审稿周期 期刊官网自述数据
79 天外审后首次决定 · 投稿社区反馈约 12 周
出版商统计口径以官网为准；本刊近 24 个月的文章日期尚未获得，因此以官方数据为准。
各来源数据
- 平均审稿速度（社区反馈）
- 12 WeeksLetPub ·
- 录用率（出版商公布）
- 15%出版商官网 ·
- 投稿到首次决定
- 8 天出版商官网 ·
- 外审后首次决定
- 79 天出版商官网 ·
- 接收到发表
- 74 天出版商官网 ·
- 投稿到发表（期刊自报）
- 约 12 周DOAJ ·
- 评审方式
- 双盲同行评审DOAJ
社区反馈来自投稿者样本，置信度 0.5，不代表期刊承诺；“出版商公布”的时间节点定义以官网为准。
费用与开放获取
版面费与开放获取政策
钻石开放获取（无 APC）DOAJ
所有文章开放获取，且不向作者收取文章处理费。
| 来源 | 文章处理费 | 费用减免 | 许可证 | 观测时间 |
|---|---|---|---|---|
| DOAJ | 无文章处理费 | 无 | CC BY、CC BY-NC | |
| LetPub | 无文章处理费 | 无 | — | |
| 出版商官网 | 有，金额未公布 | — | — |
- APC 费用说明 ↗DOAJ
- 开放获取声明 ↗DOAJ
- 许可与版权 ↗DOAJ
费用以期刊官网为准；不同来源的观测时间可能不同，页面保留各来源原值，不做平均。
投稿要求
文章类型与投稿政策（官网）
接收的文章类型7 种
- brief communicationsBrief Communications: Short articles (generally no more than six pages) that are particularly timely or relevant Short articles with potential for immediate pos…未说明篇幅
- datasets and storiesDatasets and Stories: Description of the pedagogical uses of multivariate dataset(s) (including discussions of achievable learning outcomes, potential pitfalls,…未说明篇幅
- overviews and reflective essaysOverviews and reflective essays: Scholarly overview of the literature on topics in statistics and data science education Reflective essays by scholars with exte…未说明篇幅
- research in k-12 educationResearch in K-12 Education: Research related to the teaching, learning, and assessment of statistics and data science in K-12 settings未说明篇幅
- reviews of software, books, and teaching materialsReviews of software, books, and teaching materials: Reviews of teaching materials must describe actual experiences using the materials未说明篇幅
- special issues and review articlesSpecial Issues and Review Articles Review articles in all of the above areas are welcome, as are proposals for special issues, which should be discussed with th…未说明篇幅
- statistics and data science education in the health sciencesStatistics and Data Science Education in the Health Sciences: Teaching and learning of statistics and data science in the health sciences Biostatistics and data…未说明篇幅
官网政策摘录出版伦理、开放获取、同行评审
- 出版伦理
Adheres to publishing ethics; Taylor & Francis is a member of COPE and uses Similarity Check via CrossRef. 模型摘要
The Journal adheres to the highest standards of publishing ethics, with rigorous processes in place to ensure this is achieved. Taylor & Francis is a member of Committee of Publications Ethics (COPE) and utilizes Similarity Check via CrossRef for all Journals.
原文 ↗出版商官网 ·- 开放获取 Open access
Journal of Statistics and Data Science Education is an open access journal and only publishes open access articles. Publishing open access means that your article will be free to access online immediately on publication, increasing the visibility, readership, and impact of your research. Why choose open access? Increase the discoverability and readership of your article Make an impact and reach ne…
原文 ↗出版商官网 ·- 同行评审 Peer-Review Policy
Peer review is doubly anonymous; initial editor appraisal followed by review by independent, anonymous expert referees. 模型摘要
All submitted manuscripts are subject to initial appraisal by the Editor, and, if found suitable for further consideration, to rigorous and rapid peer review by independent, anonymous expert referees.
原文 ↗出版商官网 ·
摘录来自期刊官网页面，仅保留原文片段；“模型摘要”由 Workers AI 生成并经原文校验，以官网为准。
基本信息
出版信息与官方入口
- 出版商
- Taylor & Francis Group
- 出版国家或地区
- United States
- 出版语言
- English
- ISSN
- 2693-9169
- 学会 / 主办单位
- American Statistical Association
- 官网最新一期
- Volume 34, Issue 4（2026 年）
- 官方链接
- 期刊主页 ↗DOAJ
- 投稿系统 ↗出版商官网
- 作者指南 ↗LetPub
- Aims & Scope ↗LetPub
- 专刊 / 特刊征稿 ↗出版商官网
- APC 费用说明 ↗DOAJ
- 开放获取声明 ↗DOAJ
- 许可与版权 ↗DOAJ
- 评审流程 ↗LetPub
- 编委会 ↗LetPub
- 查重政策 ↗DOAJ
常见问题
关于 Journal of Statistics and Data Science Education 的常见问题
Journal of Statistics and Data Science Education 是中科院几区期刊？
2025 年升级版分区表中，Journal of Statistics and Data Science Education 为教育学 4区，小类 学科教育 4 区。2026 年新锐版分区表中为教育学 3区。不同版本与大小类分区不能混用。
Journal of Statistics and Data Science Education 的影响因子是多少？
期刊官网公布的影响因子为 2.3（2025 年度），属期刊自述数据，LetPub 暂无该刊的影响因子记录，CiteScore 为 4.3，h-index 为 23。
Journal of Statistics and Data Science Education 的审稿周期多长？
出版商公布的外审后首次决定时间约为 79 天；投稿社区反馈的平均审稿速度为约 12 周；期刊官网公布的录用率为 15%。文章统计只含被录用的稿件，出版商数据口径以官网为准，社区反馈来自投稿者样本，均不代表期刊承诺。
Journal of Statistics and Data Science Education 是 JCR 几区？
期刊官网公布的 JCR 分区为 Q2（最佳分区）。JCR 分区以 Clarivate 公布为准，与中科院分区是不同体系；该刊中科院分区为教育学 4区。
Journal of Statistics and Data Science Education 被哪些数据库收录？
据 LetPub 与 DOAJ 记录，Journal of Statistics and Data Science Education 被 ESCI、Scopus、DOAJ 收录。期刊官网自述还被 PubMed、ERIC 收录，该清单未与各数据库逐一核对。
Journal of Statistics and Data Science Education 是开放获取期刊吗？版面费多少？
Journal of Statistics and Data Science Education 为钻石开放获取（无 APC）。不收取文章处理费。
来源与更新
本页事实来自 LetPub、出版商官网、OpenAlex、DOAJ；每个数字旁标注来源与观测日期，冲突数据保留各来源原值。LetPub 原始详情页：查看 ↗（2026-08-26 归档）。最近更新：。