The Math and Science Engagement Scales: Scale development, validation, and psychometric properties

Wang, Ming-Te; Fredricks, Jennifer A.; Ye, Feifei; Hofkens, Tara L.; Linn, Jacqueline Schall

doi:10.1016/j.learninstruc.2016.01.008

Cited by 592Education, Achievement, and GiftednessPsychometric Methodologies and TestingEarly Childhood Education and Development

The Math and Science Engagement Scales: Scale development, validation, and psychometric properties

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Wang, Ming-Te, Fredricks, Jennifer A., Ye, Feifei, Hofkens, Tara L., Linn, Jacqueline Schall·2016·Learning and Instruction

DOI 10.1016/j.learninstruc.2016.01.008

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The dimensions of student engagement are related yet distinct constructs.
“Exploring these dimensions, Wang et al (2016) confirmed that these are related yet distinct constructs.”
From Unpacking student engagement in higher education learning analytics: a systematic review (2024) · cites this paper as Wang et al (2016)
Social engagement is characterised by behaviours like building on others' ideas and working cooperatively in academic settings, particularly in science or maths.
“Wang et al. (2016) characterised social engagement with behaviours like building on others' ideas and working cooperatively in academic settings, particularly in subjects like science or maths.”
From Unpacking student engagement in higher education learning analytics: a systematic review (2024) · cites this paper as Wang et al. (2016)
The Math and Science Engagement Scales proposed by Wang et al. (2016) were adapted to measure engagement.
“For engagement, the Math and Science Engagement Scales proposed by Wang et al. (2016) was adapted, dividing engagement into cognitive, behavioral, and emotional aspects.”
From Empowering ChatGPT with Guidance Mechanism in Blended Learning: Effect of Self-Regulated Learning, Higher-Order Thinking Skills, and Knowledge Construction (2024) · cites this paper as Wang et al. (2016)
The SRL scale's reliability and validity were confirmed in prior studies (Chen et al., 2001; Guay et al., 2000; Wang et al., 2016).
“Its reliability and validity were confirmed in prior studies (Chen et al., 2001;Guay et al., 2000;Wang et al., 2016).”
From Empowering ChatGPT with Guidance Mechanism in Blended Learning: Effect of Self-Regulated Learning, Higher-Order Thinking Skills, and Knowledge Construction (2024) · cites this paper as Wang et al., 2016

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Authors: Wang, M.-T., Fredricks, J. A., Ye, F., Hofkens, T. L., & Linn, J. S.
Affiliations: University of Pittsburgh (US)
Connecticut College (US)
Corresponding author: Wang, Ming-Te
ORCID: Wang, Ming-Te
Fredricks, Jennifer A.
Ye, Feifei
Hofkens, Tara L.
Venue: Learning and Instruction
Publisher: Elsevier BV
Published: 2016-06
Volume: 43
Pages: 16-26
ISSN: 0959-4752 (ISSN-L)
DOI: 10.1016/j.learninstruc.2016.01.008
OpenAlex: W2256824667
Cited by: 592
References: 48
Citations by year: 2026: 73 · 2025: 100 · 2024: 96 · 2023: 87 · 2022: 64 · 2021: 56 · 2020: 46 · 2019: 38 · 2018: 16 · 2017: 10 · 2016: 4
FWCI: 32.26
Type: journal article
Language: en
Open access: bronze
doi.org
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
www.elsevier.com/legal/tdmrep-license (tdm)
www.elsevier.com/open-access/userlicense/1.0/ (am, 344 d)
doi.org/10.15223/policy-017 (stm-asf)
doi.org/10.15223/policy-037 (stm-asf)
doi.org/10.15223/policy-012 (stm-asf)
doi.org/10.15223/policy-029 (stm-asf)
doi.org/10.15223/policy-004 (stm-asf)
Locations: Learning and Instruction (acceptedVersion)
Funders: National Science Foundation (1503181)
Topics: Social Sciences › Psychology › Experimental and Cognitive Psychology › Education, Achievement, and Giftedness
Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
Social Sciences › Education › Early Childhood Education and Development
Keywords: student engagement, student engagement in mathematics learning, public engagement with science, scale development, bifactor model, measurement invariance, predictive validity, middle and high school students

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The Math and Science Engagement Scales: Scale development, validation, and psychometric properties

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