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Advancing Statistical Inference: A Comprehensive Exploration of Curriculum Development, Teacher Seminars, and Teacher Perceptions in Hungarian Secondary Schools

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Title: Advancing Statistical Inference: A Comprehensive Exploration of Curriculum Development, Teacher Seminars, and Teacher Perceptions in Hungarian Secondary Schools
Language: English
Authors: Péter Fejes-Tóth (ORCID 0009-0002-8465-8266), Manfred Borovcnik (ORCID 0000-0001-9044-5326), Ödön Vancsó (ORCID 0000-0002-2831-6328)
Source: Canadian Journal of Science, Mathematics and Technology Education. 2026 26(3).
Availability: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
Peer Reviewed: Y
Page Count: 23
Publication Date: 2026
Document Type: Journal Articles
Reports - Research
Education Level: Secondary Education
Descriptors: Statistical Inference, Curriculum Development, Teacher Workshops, Seminars, Teacher Attitudes, Secondary School Teachers, Foreign Countries, Experimental Curriculum, Curriculum Evaluation, Alignment (Education), Educational Change, Technical Support, Statistics Education, National Curriculum
Geographic Terms: Hungary
DOI: 10.1007/s42330-026-00477-2
ISSN: 1492-6156
1942-4051
Abstract: Our research project aims to integrate inferential statistics into the Hungarian secondary school curriculum. Between 2019 and 2023, we developed and tested an experimental curriculum incorporating simulations and Excel-based calculations. This approach addresses broader challenges in understanding statistical inference and presents our strategies for designing an experimental seminar for in-service teachers. The underlying principles of the curriculum are inspired by Complex Mathematics Education, a long-term initiative rooted in the ideas of Tamás Varga. Using a pre-post-test design and semi-structured teacher interviews, we evaluated the curriculum's feasibility. Feedback indicates that our revised approach and materials align well with the current Hungarian curriculum reform. Findings across the project's phases suggest that, with adequate technical support and sufficient practice tasks, even complex statistical concepts can be successfully taught to beginners. This approach supports diverse learner profiles and accommodates varying levels of prior knowledge and ability across schools. The article presents key insights from our teacher-training efforts over three phases, involving a total of 32 educators.
Abstractor: As Provided
Entry Date: 20260101
Accession Number: EJ1513809
Database: ERIC
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  Data: Advancing Statistical Inference: A Comprehensive Exploration of Curriculum Development, Teacher Seminars, and Teacher Perceptions in Hungarian Secondary Schools
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  Data: <searchLink fieldCode="AR" term="%22Péter+Fejes-Tóth%22">Péter Fejes-Tóth</searchLink> (ORCID <externalLink term="http://orcid.org/0009-0002-8465-8266">0009-0002-8465-8266</externalLink>)<br /><searchLink fieldCode="AR" term="%22Manfred+Borovcnik%22">Manfred Borovcnik</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0001-9044-5326">0000-0001-9044-5326</externalLink>)<br /><searchLink fieldCode="AR" term="%22Ödön+Vancsó%22">Ödön Vancsó</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0002-2831-6328">0000-0002-2831-6328</externalLink>)
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  Data: <searchLink fieldCode="SO" term="%22Canadian+Journal+of+Science%2C+Mathematics+and+Technology+Education%22"><i>Canadian Journal of Science, Mathematics and Technology Education</i></searchLink>. 2026 26(3).
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  Data: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
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  Data: <searchLink fieldCode="DE" term="%22Statistical+Inference%22">Statistical Inference</searchLink><br /><searchLink fieldCode="DE" term="%22Curriculum+Development%22">Curriculum Development</searchLink><br /><searchLink fieldCode="DE" term="%22Teacher+Workshops%22">Teacher Workshops</searchLink><br /><searchLink fieldCode="DE" term="%22Seminars%22">Seminars</searchLink><br /><searchLink fieldCode="DE" term="%22Teacher+Attitudes%22">Teacher Attitudes</searchLink><br /><searchLink fieldCode="DE" term="%22Secondary+School+Teachers%22">Secondary School Teachers</searchLink><br /><searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink><br /><searchLink fieldCode="DE" term="%22Experimental+Curriculum%22">Experimental Curriculum</searchLink><br /><searchLink fieldCode="DE" term="%22Curriculum+Evaluation%22">Curriculum Evaluation</searchLink><br /><searchLink fieldCode="DE" term="%22Alignment+%28Education%29%22">Alignment (Education)</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Change%22">Educational Change</searchLink><br /><searchLink fieldCode="DE" term="%22Technical+Support%22">Technical Support</searchLink><br /><searchLink fieldCode="DE" term="%22Statistics+Education%22">Statistics Education</searchLink><br /><searchLink fieldCode="DE" term="%22National+Curriculum%22">National Curriculum</searchLink>
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  Data: Our research project aims to integrate inferential statistics into the Hungarian secondary school curriculum. Between 2019 and 2023, we developed and tested an experimental curriculum incorporating simulations and Excel-based calculations. This approach addresses broader challenges in understanding statistical inference and presents our strategies for designing an experimental seminar for in-service teachers. The underlying principles of the curriculum are inspired by Complex Mathematics Education, a long-term initiative rooted in the ideas of Tamás Varga. Using a pre-post-test design and semi-structured teacher interviews, we evaluated the curriculum's feasibility. Feedback indicates that our revised approach and materials align well with the current Hungarian curriculum reform. Findings across the project's phases suggest that, with adequate technical support and sufficient practice tasks, even complex statistical concepts can be successfully taught to beginners. This approach supports diverse learner profiles and accommodates varying levels of prior knowledge and ability across schools. The article presents key insights from our teacher-training efforts over three phases, involving a total of 32 educators.
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      – SubjectFull: Statistical Inference
        Type: general
      – SubjectFull: Curriculum Development
        Type: general
      – SubjectFull: Teacher Workshops
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      – SubjectFull: Seminars
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      – SubjectFull: Teacher Attitudes
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      – SubjectFull: Secondary School Teachers
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      – SubjectFull: Statistics Education
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      – SubjectFull: National Curriculum
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      – SubjectFull: Hungary
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