---
_id: '55667'
abstract:
- lang: eng
  text: <jats:p>This study investigates how 11- to 12-year-old students construct
    data-based decision trees using data cards for classification purposes. We examine
    the students' heuristics and reasoning during this process. The research is based
    on an eight-week teaching unit during which students labeled data, built decision
    trees, and assessed them using test data. They learned to manually construct decision
    trees to classify food items as recommendable or not. They utilized data cards
    with a heuristic that is a simplified form of a machine learning algorithm. We
    report on evidence that this topic is teachable to middle school students, along
    with insights for refining our teaching approach and broader implications for
    teaching machine learning at the school level.</jats:p>
article_number: '3'
author:
- first_name: Franz Yannik
  full_name: Fleischer, Franz Yannik
  id: '42660'
  last_name: Fleischer
  orcid: https://orcid.org/0000-0003-0318-0329
- first_name: Susanne
  full_name: Podworny, Susanne
  id: '30619'
  last_name: Podworny
  orcid: 0000-0002-6313-5987
- first_name: Rolf
  full_name: Biehler, Rolf
  id: '16274'
  last_name: Biehler
citation:
  ama: Fleischer FY, Podworny S, Biehler R. Teaching and Learning to Construct Data-Based
    Decision Trees Using Data Cards as the First Introduction to Machine Learning
    in Middle School. <i>Statistics Education Research Journal</i>. 2024;23(1). doi:<a
    href="https://doi.org/10.52041/serj.v23i1.450">10.52041/serj.v23i1.450</a>
  apa: Fleischer, F. Y., Podworny, S., &#38; Biehler, R. (2024). Teaching and Learning
    to Construct Data-Based Decision Trees Using Data Cards as the First Introduction
    to Machine Learning in Middle School. <i>Statistics Education Research Journal</i>,
    <i>23</i>(1), Article 3. <a href="https://doi.org/10.52041/serj.v23i1.450">https://doi.org/10.52041/serj.v23i1.450</a>
  bibtex: '@article{Fleischer_Podworny_Biehler_2024, title={Teaching and Learning
    to Construct Data-Based Decision Trees Using Data Cards as the First Introduction
    to Machine Learning in Middle School}, volume={23}, DOI={<a href="https://doi.org/10.52041/serj.v23i1.450">10.52041/serj.v23i1.450</a>},
    number={13}, journal={Statistics Education Research Journal}, publisher={International
    Association for Statistical Education}, author={Fleischer, Franz Yannik and Podworny,
    Susanne and Biehler, Rolf}, year={2024} }'
  chicago: Fleischer, Franz Yannik, Susanne Podworny, and Rolf Biehler. “Teaching
    and Learning to Construct Data-Based Decision Trees Using Data Cards as the First
    Introduction to Machine Learning in Middle School.” <i>Statistics Education Research
    Journal</i> 23, no. 1 (2024). <a href="https://doi.org/10.52041/serj.v23i1.450">https://doi.org/10.52041/serj.v23i1.450</a>.
  ieee: 'F. Y. Fleischer, S. Podworny, and R. Biehler, “Teaching and Learning to Construct
    Data-Based Decision Trees Using Data Cards as the First Introduction to Machine
    Learning in Middle School,” <i>Statistics Education Research Journal</i>, vol.
    23, no. 1, Art. no. 3, 2024, doi: <a href="https://doi.org/10.52041/serj.v23i1.450">10.52041/serj.v23i1.450</a>.'
  mla: Fleischer, Franz Yannik, et al. “Teaching and Learning to Construct Data-Based
    Decision Trees Using Data Cards as the First Introduction to Machine Learning
    in Middle School.” <i>Statistics Education Research Journal</i>, vol. 23, no.
    1, 3, International Association for Statistical Education, 2024, doi:<a href="https://doi.org/10.52041/serj.v23i1.450">10.52041/serj.v23i1.450</a>.
  short: F.Y. Fleischer, S. Podworny, R. Biehler, Statistics Education Research Journal
    23 (2024).
date_created: 2024-08-21T09:59:33Z
date_updated: 2024-08-21T10:02:38Z
department:
- _id: '363'
doi: 10.52041/serj.v23i1.450
intvolume: '        23'
issue: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://doi.org/10.52041/serj.v23i1.450
oa: '1'
publication: Statistics Education Research Journal
publication_identifier:
  issn:
  - 1570-1824
publication_status: published
publisher: International Association for Statistical Education
status: public
title: Teaching and Learning to Construct Data-Based Decision Trees Using Data Cards
  as the First Introduction to Machine Learning in Middle School
type: journal_article
user_id: '37888'
volume: 23
year: '2024'
...
---
_id: '32335'
abstract:
- lang: eng
  text: Aspects of data science surround us in many contexts, for example regarding
    climate change, air pollution, and other environmental issues. To open the “data-science-black-box”
    for lower secondary school students we developed a data science project focussing
    on the analysis of self-collected environmental data. We embed this project in
    computer science education, which enables us to use a new knowledge-based programming
    approach for the data analysis within Jupyter Notebooks and the programming language
    Python. In this paper, we evaluate the second cycle of this project which took
    place in a ninth-grade computer science class. In particular, we present how the
    students coped with the professional tool of Jupyter Notebooks for doing statistical
    investigations and which insights they gained.
article_number: '6'
author:
- first_name: SUSANNE
  full_name: PODWORNY, SUSANNE
  last_name: PODWORNY
- first_name: Sven
  full_name: Hüsing, Sven
  id: '58465'
  last_name: Hüsing
- first_name: CARSTEN
  full_name: SCHULTE, CARSTEN
  last_name: SCHULTE
citation:
  ama: 'PODWORNY S, Hüsing S, SCHULTE C. A PLACE FOR A DATA SCIENCE PROJECT IN SCHOOL:
    BETWEEN STATISTICS AND EPISTEMIC PROGRAMMING. <i>STATISTICS EDUCATION RESEARCH
    JOURNAL</i>. 2022;21(2). doi:<a href="https://doi.org/10.52041/serj.v21i2.46">10.52041/serj.v21i2.46</a>'
  apa: 'PODWORNY, S., Hüsing, S., &#38; SCHULTE, C. (2022). A PLACE FOR A DATA SCIENCE
    PROJECT IN SCHOOL: BETWEEN STATISTICS AND EPISTEMIC PROGRAMMING. <i>STATISTICS
    EDUCATION RESEARCH JOURNAL</i>, <i>21</i>(2), Article 6. <a href="https://doi.org/10.52041/serj.v21i2.46">https://doi.org/10.52041/serj.v21i2.46</a>'
  bibtex: '@article{PODWORNY_Hüsing_SCHULTE_2022, title={A PLACE FOR A DATA SCIENCE
    PROJECT IN SCHOOL: BETWEEN STATISTICS AND EPISTEMIC PROGRAMMING}, volume={21},
    DOI={<a href="https://doi.org/10.52041/serj.v21i2.46">10.52041/serj.v21i2.46</a>},
    number={26}, journal={STATISTICS EDUCATION RESEARCH JOURNAL}, publisher={International
    Association for Statistical Education}, author={PODWORNY, SUSANNE and Hüsing,
    Sven and SCHULTE, CARSTEN}, year={2022} }'
  chicago: 'PODWORNY, SUSANNE, Sven Hüsing, and CARSTEN SCHULTE. “A PLACE FOR A DATA
    SCIENCE PROJECT IN SCHOOL: BETWEEN STATISTICS AND EPISTEMIC PROGRAMMING.” <i>STATISTICS
    EDUCATION RESEARCH JOURNAL</i> 21, no. 2 (2022). <a href="https://doi.org/10.52041/serj.v21i2.46">https://doi.org/10.52041/serj.v21i2.46</a>.'
  ieee: 'S. PODWORNY, S. Hüsing, and C. SCHULTE, “A PLACE FOR A DATA SCIENCE PROJECT
    IN SCHOOL: BETWEEN STATISTICS AND EPISTEMIC PROGRAMMING,” <i>STATISTICS EDUCATION
    RESEARCH JOURNAL</i>, vol. 21, no. 2, Art. no. 6, 2022, doi: <a href="https://doi.org/10.52041/serj.v21i2.46">10.52041/serj.v21i2.46</a>.'
  mla: 'PODWORNY, SUSANNE, et al. “A PLACE FOR A DATA SCIENCE PROJECT IN SCHOOL: BETWEEN
    STATISTICS AND EPISTEMIC PROGRAMMING.” <i>STATISTICS EDUCATION RESEARCH JOURNAL</i>,
    vol. 21, no. 2, 6, International Association for Statistical Education, 2022,
    doi:<a href="https://doi.org/10.52041/serj.v21i2.46">10.52041/serj.v21i2.46</a>.'
  short: S. PODWORNY, S. Hüsing, C. SCHULTE, STATISTICS EDUCATION RESEARCH JOURNAL
    21 (2022).
date_created: 2022-07-08T12:06:48Z
date_updated: 2022-07-08T12:07:46Z
department:
- _id: '67'
doi: 10.52041/serj.v21i2.46
intvolume: '        21'
issue: '2'
keyword:
- Education
- Statistics and Probability
language:
- iso: eng
publication: STATISTICS EDUCATION RESEARCH JOURNAL
publication_identifier:
  issn:
  - 1570-1824
publication_status: published
publisher: International Association for Statistical Education
status: public
title: 'A PLACE FOR A DATA SCIENCE PROJECT IN SCHOOL: BETWEEN STATISTICS AND EPISTEMIC
  PROGRAMMING'
type: journal_article
user_id: '58465'
volume: 21
year: '2022'
...
---
_id: '48108'
abstract:
- lang: eng
  text: <jats:p>Aspects of data science surround us in many contexts, for example
    regarding climate change, air pollution, and other environmental issues. To open
    the “data-science-black-box” for lower secondary school students we developed
    a data science project focussing on the analysis of self-collected environmental
    data. We embed this project in computer science education, which enables us to
    use a new knowledge-based programming approach for the data analysis within Jupyter
    Notebooks and the programming language Python. In this paper, we evaluate the
    second cycle of this project which took place in a ninth-grade computer science
    class. In particular, we present how the students coped with the professional
    tool of Jupyter Notebooks for doing statistical investigations and which insights
    they gained.</jats:p>
article_number: '6'
author:
- first_name: SUSANNE
  full_name: PODWORNY, SUSANNE
  last_name: PODWORNY
- first_name: SVEN
  full_name: HÜSING, SVEN
  last_name: HÜSING
- first_name: CARSTEN
  full_name: SCHULTE, CARSTEN
  last_name: SCHULTE
citation:
  ama: 'PODWORNY S, HÜSING S, SCHULTE C. A PLACE FOR A DATA SCIENCE PROJECT IN SCHOOL:
    BETWEEN STATISTICS AND EPISTEMIC PROGRAMMING. <i>STATISTICS EDUCATION RESEARCH
    JOURNAL</i>. 2022;21(2). doi:<a href="https://doi.org/10.52041/serj.v21i2.46">10.52041/serj.v21i2.46</a>'
  apa: 'PODWORNY, S., HÜSING, S., &#38; SCHULTE, C. (2022). A PLACE FOR A DATA SCIENCE
    PROJECT IN SCHOOL: BETWEEN STATISTICS AND EPISTEMIC PROGRAMMING. <i>STATISTICS
    EDUCATION RESEARCH JOURNAL</i>, <i>21</i>(2), Article 6. <a href="https://doi.org/10.52041/serj.v21i2.46">https://doi.org/10.52041/serj.v21i2.46</a>'
  bibtex: '@article{PODWORNY_HÜSING_SCHULTE_2022, title={A PLACE FOR A DATA SCIENCE
    PROJECT IN SCHOOL: BETWEEN STATISTICS AND EPISTEMIC PROGRAMMING}, volume={21},
    DOI={<a href="https://doi.org/10.52041/serj.v21i2.46">10.52041/serj.v21i2.46</a>},
    number={26}, journal={STATISTICS EDUCATION RESEARCH JOURNAL}, publisher={International
    Association for Statistical Education}, author={PODWORNY, SUSANNE and HÜSING,
    SVEN and SCHULTE, CARSTEN}, year={2022} }'
  chicago: 'PODWORNY, SUSANNE, SVEN HÜSING, and CARSTEN SCHULTE. “A PLACE FOR A DATA
    SCIENCE PROJECT IN SCHOOL: BETWEEN STATISTICS AND EPISTEMIC PROGRAMMING.” <i>STATISTICS
    EDUCATION RESEARCH JOURNAL</i> 21, no. 2 (2022). <a href="https://doi.org/10.52041/serj.v21i2.46">https://doi.org/10.52041/serj.v21i2.46</a>.'
  ieee: 'S. PODWORNY, S. HÜSING, and C. SCHULTE, “A PLACE FOR A DATA SCIENCE PROJECT
    IN SCHOOL: BETWEEN STATISTICS AND EPISTEMIC PROGRAMMING,” <i>STATISTICS EDUCATION
    RESEARCH JOURNAL</i>, vol. 21, no. 2, Art. no. 6, 2022, doi: <a href="https://doi.org/10.52041/serj.v21i2.46">10.52041/serj.v21i2.46</a>.'
  mla: 'PODWORNY, SUSANNE, et al. “A PLACE FOR A DATA SCIENCE PROJECT IN SCHOOL: BETWEEN
    STATISTICS AND EPISTEMIC PROGRAMMING.” <i>STATISTICS EDUCATION RESEARCH JOURNAL</i>,
    vol. 21, no. 2, 6, International Association for Statistical Education, 2022,
    doi:<a href="https://doi.org/10.52041/serj.v21i2.46">10.52041/serj.v21i2.46</a>.'
  short: S. PODWORNY, S. HÜSING, C. SCHULTE, STATISTICS EDUCATION RESEARCH JOURNAL
    21 (2022).
date_created: 2023-10-17T05:59:38Z
date_updated: 2023-10-17T06:01:58Z
doi: 10.52041/serj.v21i2.46
intvolume: '        21'
issue: '2'
keyword:
- Education
- Statistics and Probability
publication: STATISTICS EDUCATION RESEARCH JOURNAL
publication_identifier:
  issn:
  - 1570-1824
publication_status: published
publisher: International Association for Statistical Education
status: public
title: 'A PLACE FOR A DATA SCIENCE PROJECT IN SCHOOL: BETWEEN STATISTICS AND EPISTEMIC
  PROGRAMMING'
type: journal_article
user_id: '30619'
volume: 21
year: '2022'
...
---
_id: '34920'
abstract:
- lang: eng
  text: <jats:p>A very warm welcome to this Special Issue of the Statistics Education
    Research Journal (SERJ) on data science education. Our hope is to give an overview
    of selected theoretical thoughts and empirical studies on data science education
    from a statistics education research perspective. Data science education is rapidly
    developing but research into data science education is still in its infancy. The
    current issue presents a snapshot of this developing field.</jats:p>
article_number: '1'
author:
- first_name: Rolf
  full_name: Biehler, Rolf
  id: '16274'
  last_name: Biehler
- first_name: Richard
  full_name: De Veaux, Richard
  last_name: De Veaux
- first_name: Joachim
  full_name: Engel, Joachim
  last_name: Engel
- first_name: Sibel
  full_name: Kazak, Sibel
  last_name: Kazak
- first_name: Daniel
  full_name: Frischemeier, Daniel
  last_name: Frischemeier
citation:
  ama: 'Biehler R, De Veaux R, Engel J, Kazak S, Frischemeier D. Editorial: Research
    on Data Science Education. <i>Statistics Education Research Journal</i>. 2022;21(2).
    doi:<a href="https://doi.org/10.52041/serj.v21i2.606">10.52041/serj.v21i2.606</a>'
  apa: 'Biehler, R., De Veaux, R., Engel, J., Kazak, S., &#38; Frischemeier, D. (2022).
    Editorial: Research on Data Science Education. <i>Statistics Education Research
    Journal</i>, <i>21</i>(2), Article 1. <a href="https://doi.org/10.52041/serj.v21i2.606">https://doi.org/10.52041/serj.v21i2.606</a>'
  bibtex: '@article{Biehler_De Veaux_Engel_Kazak_Frischemeier_2022, title={Editorial:
    Research on Data Science Education}, volume={21}, DOI={<a href="https://doi.org/10.52041/serj.v21i2.606">10.52041/serj.v21i2.606</a>},
    number={21}, journal={Statistics Education Research Journal}, publisher={International
    Association for Statistical Education}, author={Biehler, Rolf and De Veaux, Richard
    and Engel, Joachim and Kazak, Sibel and Frischemeier, Daniel}, year={2022} }'
  chicago: 'Biehler, Rolf, Richard De Veaux, Joachim Engel, Sibel Kazak, and Daniel
    Frischemeier. “Editorial: Research on Data Science Education.” <i>Statistics Education
    Research Journal</i> 21, no. 2 (2022). <a href="https://doi.org/10.52041/serj.v21i2.606">https://doi.org/10.52041/serj.v21i2.606</a>.'
  ieee: 'R. Biehler, R. De Veaux, J. Engel, S. Kazak, and D. Frischemeier, “Editorial:
    Research on Data Science Education,” <i>Statistics Education Research Journal</i>,
    vol. 21, no. 2, Art. no. 1, 2022, doi: <a href="https://doi.org/10.52041/serj.v21i2.606">10.52041/serj.v21i2.606</a>.'
  mla: 'Biehler, Rolf, et al. “Editorial: Research on Data Science Education.” <i>Statistics
    Education Research Journal</i>, vol. 21, no. 2, 1, International Association for
    Statistical Education, 2022, doi:<a href="https://doi.org/10.52041/serj.v21i2.606">10.52041/serj.v21i2.606</a>.'
  short: R. Biehler, R. De Veaux, J. Engel, S. Kazak, D. Frischemeier, Statistics
    Education Research Journal 21 (2022).
date_created: 2022-12-23T11:20:39Z
date_updated: 2024-04-18T09:45:53Z
department:
- _id: '363'
doi: 10.52041/serj.v21i2.606
intvolume: '        21'
issue: '2'
keyword:
- Education
- Statistics and Probability
language:
- iso: eng
publication: Statistics Education Research Journal
publication_identifier:
  issn:
  - 1570-1824
publication_status: published
publisher: International Association for Statistical Education
status: public
title: 'Editorial: Research on Data Science Education'
type: journal_article
user_id: '37888'
volume: 21
year: '2022'
...
---
_id: '35672'
abstract:
- lang: eng
  text: <jats:p>This study examines modelling with machine learning. In the context
    of a yearlong data science course, the study explores how upper secondary students
    apply machine learning with Jupyter Notebooks and document the modelling process
    as a computational essay incorporating the different steps of the CRISP-DM cycle.
    The students’ work is based on a teaching module about decision trees in machine
    learning and a worked example of such a modelling process. The study outlines
    the students’ performance in carrying out the machine learning technically and
    reasoning about bias in the data, different data preparation steps, the application
    context, and the resulting decision model. Furthermore, the context of the study
    and the theoretical backgrounds are presented.</jats:p>
article_number: '7'
author:
- first_name: Franz Yannik
  full_name: Fleischer, Franz Yannik
  id: '42660'
  last_name: Fleischer
  orcid: https://orcid.org/0000-0003-0318-0329
- first_name: Rolf
  full_name: Biehler, Rolf
  id: '16274'
  last_name: Biehler
- first_name: Carsten
  full_name: Schulte, Carsten
  id: '60311'
  last_name: Schulte
citation:
  ama: Fleischer FY, Biehler R, Schulte C. Teaching and Learning Data-Driven Machine
    Learning with Educationally Designed Jupyter Notebooks. <i>Statistics Education
    Research Journal</i>. 2022;21(2). doi:<a href="https://doi.org/10.52041/serj.v21i2.61">10.52041/serj.v21i2.61</a>
  apa: Fleischer, F. Y., Biehler, R., &#38; Schulte, C. (2022). Teaching and Learning
    Data-Driven Machine Learning with Educationally Designed Jupyter Notebooks. <i>Statistics
    Education Research Journal</i>, <i>21</i>(2), Article 7. <a href="https://doi.org/10.52041/serj.v21i2.61">https://doi.org/10.52041/serj.v21i2.61</a>
  bibtex: '@article{Fleischer_Biehler_Schulte_2022, title={Teaching and Learning Data-Driven
    Machine Learning with Educationally Designed Jupyter Notebooks}, volume={21},
    DOI={<a href="https://doi.org/10.52041/serj.v21i2.61">10.52041/serj.v21i2.61</a>},
    number={27}, journal={Statistics Education Research Journal}, publisher={International
    Association for Statistical Education}, author={Fleischer, Franz Yannik and Biehler,
    Rolf and Schulte, Carsten}, year={2022} }'
  chicago: Fleischer, Franz Yannik, Rolf Biehler, and Carsten Schulte. “Teaching and
    Learning Data-Driven Machine Learning with Educationally Designed Jupyter Notebooks.”
    <i>Statistics Education Research Journal</i> 21, no. 2 (2022). <a href="https://doi.org/10.52041/serj.v21i2.61">https://doi.org/10.52041/serj.v21i2.61</a>.
  ieee: 'F. Y. Fleischer, R. Biehler, and C. Schulte, “Teaching and Learning Data-Driven
    Machine Learning with Educationally Designed Jupyter Notebooks,” <i>Statistics
    Education Research Journal</i>, vol. 21, no. 2, Art. no. 7, 2022, doi: <a href="https://doi.org/10.52041/serj.v21i2.61">10.52041/serj.v21i2.61</a>.'
  mla: Fleischer, Franz Yannik, et al. “Teaching and Learning Data-Driven Machine
    Learning with Educationally Designed Jupyter Notebooks.” <i>Statistics Education
    Research Journal</i>, vol. 21, no. 2, 7, International Association for Statistical
    Education, 2022, doi:<a href="https://doi.org/10.52041/serj.v21i2.61">10.52041/serj.v21i2.61</a>.
  short: F.Y. Fleischer, R. Biehler, C. Schulte, Statistics Education Research Journal
    21 (2022).
date_created: 2023-01-10T08:48:23Z
date_updated: 2024-08-21T10:04:41Z
department:
- _id: '363'
- _id: '67'
doi: 10.52041/serj.v21i2.61
intvolume: '        21'
issue: '2'
keyword:
- Education
- Statistics and Probability
language:
- iso: eng
publication: Statistics Education Research Journal
publication_identifier:
  issn:
  - 1570-1824
publication_status: published
publisher: International Association for Statistical Education
status: public
title: Teaching and Learning Data-Driven Machine Learning with Educationally Designed
  Jupyter Notebooks
type: journal_article
user_id: '37888'
volume: 21
year: '2022'
...
---
_id: '56706'
abstract:
- lang: eng
  text: "<jats:p>Group comparisons offer students opportunities to reason about many
    fundamental statistical concepts like center, variation, or distribution. When
    doing such activities using large, real datasets, technology becomes and essential
    tool for exploring the data. With its large variety of features and its user-friendly
    handling, TinkerPlotsTM --as a software for learners and teachers--can facilitate
    the process of comparing distributions. In this article we focus on eight preservice
    teachers´  reasoning when comparing groups with TinkerPlots. We present ideas
    on the design of a course to develop statistical reasoning with TinkerPlots, present
    a framework to rate learners´  performance when comparing groups with TinkerPlots,
    and present results of a laboratory study about preservice teachers´  reasoning
    when comparing groups with TinkerPlots. Findings suggest that the TinkerPlots
    tool and design of the course supported these preservice teachers´  reasoning
    and that more learning opportunities are needed to increase their group comparison
    elements´  repertoire and interpretation in context.\r\nFirst published May 2018
    at Statistics Education Research Journal Archives</jats:p>"
author:
- first_name: Daniel
  full_name: Frischemeier, Daniel
  last_name: Frischemeier
- first_name: Rolf
  full_name: Biehler, Rolf
  id: '16274'
  last_name: Biehler
citation:
  ama: Frischemeier D, Biehler R. Preservice teachers´ comparing groups with TinkerPlots
    - An exploratory video study. <i>Statistics Education Research Journal</i>. 2018;17(1):35-60.
    doi:<a href="https://doi.org/10.52041/serj.v17i1.175">10.52041/serj.v17i1.175</a>
  apa: Frischemeier, D., &#38; Biehler, R. (2018). Preservice teachers´ comparing
    groups with TinkerPlots - An exploratory video study. <i>Statistics Education
    Research Journal</i>, <i>17</i>(1), 35–60. <a href="https://doi.org/10.52041/serj.v17i1.175">https://doi.org/10.52041/serj.v17i1.175</a>
  bibtex: '@article{Frischemeier_Biehler_2018, title={Preservice teachers´ comparing
    groups with TinkerPlots - An exploratory video study}, volume={17}, DOI={<a href="https://doi.org/10.52041/serj.v17i1.175">10.52041/serj.v17i1.175</a>},
    number={1}, journal={Statistics Education Research Journal}, publisher={International
    Association for Statistical Education}, author={Frischemeier, Daniel and Biehler,
    Rolf}, year={2018}, pages={35–60} }'
  chicago: 'Frischemeier, Daniel, and Rolf Biehler. “Preservice Teachers´ Comparing
    Groups with TinkerPlots - An Exploratory Video Study.” <i>Statistics Education
    Research Journal</i> 17, no. 1 (2018): 35–60. <a href="https://doi.org/10.52041/serj.v17i1.175">https://doi.org/10.52041/serj.v17i1.175</a>.'
  ieee: 'D. Frischemeier and R. Biehler, “Preservice teachers´ comparing groups with
    TinkerPlots - An exploratory video study,” <i>Statistics Education Research Journal</i>,
    vol. 17, no. 1, pp. 35–60, 2018, doi: <a href="https://doi.org/10.52041/serj.v17i1.175">10.52041/serj.v17i1.175</a>.'
  mla: Frischemeier, Daniel, and Rolf Biehler. “Preservice Teachers´ Comparing Groups
    with TinkerPlots - An Exploratory Video Study.” <i>Statistics Education Research
    Journal</i>, vol. 17, no. 1, International Association for Statistical Education,
    2018, pp. 35–60, doi:<a href="https://doi.org/10.52041/serj.v17i1.175">10.52041/serj.v17i1.175</a>.
  short: D. Frischemeier, R. Biehler, Statistics Education Research Journal 17 (2018)
    35–60.
date_created: 2024-10-22T08:31:51Z
date_updated: 2024-10-22T08:33:25Z
department:
- _id: '363'
doi: 10.52041/serj.v17i1.175
intvolume: '        17'
issue: '1'
language:
- iso: eng
main_file_link:
- url: https://iase-pub.org/ojs/SERJ/article/view/175
page: 35-60
publication: Statistics Education Research Journal
publication_identifier:
  issn:
  - 1570-1824
publication_status: published
publisher: International Association for Statistical Education
status: public
title: Preservice teachers´ comparing groups with TinkerPlots - An exploratory video
  study
type: journal_article
user_id: '37888'
volume: 17
year: '2018'
...