Learning About Measurement Uncertainties in Secondary Education: A Model of the Subject Matter

Priemer, Burkhard; Hellwig, Julia

doi:10.1007/s10763-016-9768-0

Cited by 22 publications

(24 citation statements)

References 22 publications

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“…If the numbers differed, participants assumed that there is a main effect. This is in line with a study conducted by Priemer and Hellwig [16], in which students measured temperatures inside foam cubes of different sizes and used only the readings of the thermometer with all its digits to investigate if there are differences between the temperatures. One of the students' lines of argument was that if the numbers differ, there must be a main effect.…”

Section: Discussionsupporting

confidence: 84%

“…There are several examples in science contexts to be found, e.g., Refs. [16,23,24]. But teaching about measurement uncertainties and variance is not a task reserved just for science teachers.…”

Section: Implications For Teachersmentioning

confidence: 99%

“…Further, measurement uncertainties-that can be the source of variance in data-are rarely discussed in schools even though they are inherent to all measurements and cannot be neglected when analyzing data [16]. Consequently, research shows students' low competences in understanding measurement uncertainties [13,[16][17][18]. Lubben et al [19] have categorized students' reasoning with data into two categories: point paradigm and set paradigm.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Students’ conclusions from measurement data: The more decimal places, the better?

Kok

Priemer

Musold

et al. 2019

Phys. Rev. Phys. Educ. Res.

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Section: Discussionsupporting

confidence: 84%

Section: Implications For Teachersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Students’ conclusions from measurement data: The more decimal places, the better?

Kok

Priemer

Musold

et al. 2019

Phys. Rev. Phys. Educ. Res.

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“…The brief review shows that steps like data interpretation or conclusion are of general importance, for example, when judging the quality of measurement data (Priemer and Hellwig 2018), describing the conceptualization of evidence (Duncan, Chinn, and Barzilai 2017), or reasoning on the basis of evidence (Osborne, Erduran, and Simon 2004). Reasoning is especially not limited to empirical inquiry but is general to problemsolving and scientific work.…”

Section: Sciencementioning

confidence: 99%

A framework to foster problem-solving in STEM and computing education

Priemer

Eilerts

Filler

et al. 2019

Research in Science & Technological Education

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Background: Recent developments in STEM and computer science education put a strong emphasis on twenty-first-century skills, such as solving authentic problems. These skills typically transcend single disciplines. Thus, problem-solving must be seen as a multidisciplinary challenge, and the corresponding practices and processes need to be described using an integrated framework. Purpose: We present a fine-grained, integrated, and interdisciplinary framework of problem-solving for education in STEM and computer science by cumulatively including ways of problem-solving from all of these domains. Thus, the framework serves as a tool box with a variety of options that are described by steps and processes for students to choose from. The framework can be used to develop competences in problem-solving. Sources of evidence: The framework was developed on the basis of a literature review. We included all prominent ways of domain-specific problem-solving in STEM and computer science, consisting mainly of empirically orientated approaches, such as inquiry in science, and solely theory-orientated approaches, such as proofs in mathematics. Main argument: Since there is an increasing demand for integrated STEM and computer science education when working on natural phenomena and authentic problems, a problem-solving framework exclusively covering the natural sciences or other single domains falls short. Conclusions: Our framework can support both practice and research by providing a common background that relates the ways, steps, processes, and activities of problem-solving in the different domains to one single common reference. In doing so, it can support teachers in explaining the multiple ways in which science problems can be solved and in constructing problems that reflect these numerous ways. STEM and computer science educational research can use the framework to develop competences of problem-solving at a finegrained level, to construct corresponding assessment tools, and to investigate under what conditions learning progressions can be achieved.

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“…Deneysel çalışmalarda ölçüm belirsizliklerini tahmin etmek çok önemlidir. Bununla birlikte, bu durum okul müfredatlarında ve öğretmenlik uygulamasında çoğunlukla ihmal edilmektedir (Priemer ve Hellwig, 2018). Araştırma sonuçlarına göre, lisans fizik ve lise öğrencilerinin, ölçümleri tekrarlamanın neden gerekli olduğuyla ilgili doğru bir anlayışları bulunmamaktadır (Grant, 2011;Lubben ve Millar, 1996).…”

Section: öğRencilerin Deneysel Kanıtları Değerlendirirken Karşılaştıkunclassified

Pre-service Physics Teachers’ Difficulties in Evaluating Experimental Evidence

Gkioka

2019

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Bu çalışma, fizik öğretmen adaylarının deneysel sonuçların niteliğini değerlendirirken karşılaştıkları zorluklar hakkındadır. Çalışmaya, altı dönem boyunca (her dönemde altı katılımcı olmak üzere) toplam otuz altı fizik öğretmen adayı katılmıştır. Katılımcılar deneyleri tasarlamış, uygulamış, sonuçları analiz etmiş, deneysel kanıtların niteliğini değerlendirmiş ve son olarak tüm deneysel prosedürü değerlendirmiştir. Ayrıca, katılımcılardan kendi elde etmedikleri deneysel kanıtların ve yargıların (ikincil veri kaynağı) niteliklerini de değerlendirmeleri istenmiştir. Çalışmanın veri kaynaklarını, her bir deney için hazırlanan laboratuvar raporları, sınav kağıtları ve bireysel görüşmeler oluşturmaktadır. Nitel ve nicel veri analizleri sonucunda, katılımcılar arasında belirli trend bulgularına rastlanmıştır. Fizik öğretmen adaylarının, deneysel geçerlik, ölçüm güvenirliği, kesinlik ve hassasiyet kavramlarını anlama konusunda zorluk yaşadığı tespit edilmiştir. Öğretmen adayları, bu tip kavramları göz önünde bulundurarak kanıtları değerlendirmede ve yargıda bulunmada zorlanmıştır. Katılımcıların, deneysel hata kaynaklarıyla ilgili de zorluk yaşadığı tespit edilmiş, sistematik ve rastgele hataları birbirinden ayıramadıkları gözlenmiştir. Özellikle, sürekli ölçüm yapmanın neyi "daha iyi hale getirdiği" konusunda öğrencilerde kafa karışıklığı saptanmıştır. Öğretmen adaylarının laboratuvar becerilerini geliştirecek ve liselerde laboratuvar dersi verme konusunda öz güvenlerini arttıracak özel öğretmen eğitimi programlarına ihtiyaç vardır. Öğretmenlik uygulaması, müfredat geliştirme ve ileri araştırmayla ilgili öneriler tartışılmıştır.

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Learning About Measurement Uncertainties in Secondary Education: A Model of the Subject Matter

Cited by 22 publications

References 22 publications

Students’ conclusions from measurement data: The more decimal places, the better?

Students’ conclusions from measurement data: The more decimal places, the better?

A framework to foster problem-solving in STEM and computing education

Pre-service Physics Teachers’ Difficulties in Evaluating Experimental Evidence

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