Trends and Foundations in Research on Students’ Conceptual Understanding in Science Education: A Method Based on the Structural Topic Model

Mi, Shuaishuai; Lu, Shanshan; Bi, Hualin

doi:10.33225/jbse/20.19.551

Cited by 7 publications

(5 citation statements)

References 74 publications

(147 reference statements)

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“…Concepts and principles are the basic building blocks of scientific knowledge and understanding of a concept is a precondition for making complex inferences or accomplishing any scientific work with it (Mi et al, 2020). Therefore, it is decisive for students to attain CU about the core ideas of science subjects and build this understanding coherently.…”

Section: Teaching That Promotes Student Conceptual Understandingmentioning

confidence: 99%

Identification of Science Teacher Profiles Based on Lesson Observation Data

Greitans,

Namsone

2024

SEI

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It is characteristic that besides other duties teacher competence management and development is becoming a part of school responsibilities. Still, school leaders lack the experience and instruments to accomplish these duties. From a teacher’s perspective competence management and development can be seen as the process of identification and implementation of professional development (PD). An effective competence management approach that is widely used in business environments is the identification of required and actual competence profiles to judge which development is needed. Such a competence management approach isn’t characteristic of school environments, still a promising perspective on how to solve challenges regarding teacher PD (TPD). TPD interventions are often criticized as being too general (“one size fits all” dominates); therefore, the search for practices on how to “tailor” PD initiatives to individual teacher needs is topical for TPD research. An effective way to personalize TPD could be the determination of TPD profiles and the design of the PD around these profiles. Person-centered approaches dominate in the identification of science teacher profiles, as surveys and tests are commonly used. Examples, of how the identification of science teacher profiles can be done using lesson observation data are missing. Science teaching is a complex process; to limit the complexity of this study, the authors focus on teaching that promotes student conceptual understanding (CU). A mixed method study was designed and conducted in a sample of 26 science teachers, who represented urban municipalities’ science teacher population. The study included science teacher lesson observation and analysis, and determination of science teacher performance regarded teaching that promotes student CU. Science teacher performance data were used to identify teachers with similar performance across the selected criteria and to create science teacher profiles. A methodology for how lesson observation data can be used to identify teacher profiles in small teacher samples is described. Six various science teacher profiles in teaching that promote student understanding were identified, characterizing the variety of science TPD needs.

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Section: Teaching That Promotes Student Conceptual Understandingmentioning

confidence: 99%

Identification of Science Teacher Profiles Based on Lesson Observation Data

Greitans,

Namsone

2024

SEI

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“…TM is often used to identify which underlying concepts are discussed within a collection of documents and can help determine which topics each document is addressing. For example, Mi et al (2020) used TM to uncover the trends and foundations in research on students' conceptual understanding in science education. They categorized articles into 10 topics that considered information about the semantic cohesion and exclusivity of words to topics.…”

Section: Background About Topic Modelingmentioning

confidence: 99%

Emergent Coding and Topic Modeling: A Comparison of Two Qualitative Analysis Methods on Teacher Focus Group Data

Miyaoka

Decker-Woodrow

Hartman

et al. 2023

International Journal of Qualitative Methods

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More than ever in the past, researchers have access to broad, educationally relevant text data from sources such as literature databases (e.g., ERIC), an open-ended response from online courses/surveys, online discussion forums, digital essays, and social media. These advances in data availability can dramatically increase the possibilities for discovering new patterns in the data and testing new theories through processing texts with emerging analytic techniques. In our study, we extended the application of Topic Modeling (TM) to data collected from focus groups within the context of a larger study. Specifically, we compared the results of emergent qualitative coding and TM. We found a high level of agreement between TM and emergent qualitative coding, suggesting TM is a viable method for coding focus group data when augmenting and validating manual qualitative coding. We also found that TM was ineffective in capturing more nuanced information than the qualitative coding was able to identify. This can be explained by two factors: (1) the word level tokenization we used in the study, and (2) variations in the terminology teachers used to identify the different technologies. Recommendations include additional data cleaning steps researchers should take and specifications within the topic modeling code when using topic modeling to analyze focus group data.

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“…Understanding a concept is a prerequisite for creating complex interferences and conceptual knowledge (Hurrell, 2021). There has been a great amount of interest from science educators on students' conceptual understanding and the process of conceptual change, as seen by the number of studies published (Mi et al, 2020). Pintrich et al (1993) presented an overview of classroom contextual, motivational and cognitive factors related to the process of conceptual change, in which personal interest is one of the motivational factors.…”

Section: Students' Conceptual Understanding Of Food Technologymentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Interest, identity and perceptions: What makes a food technologist?

Staberg

Jakobsen²,

Persson³

et al. 2022

BFJ

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PurposePrevious research shows that identity formation is a crucial bridge between higher education and future employment. The objective of this study was to improve our understanding and knowledge of food technology students' prior interests, their perceived identity formation, perceptions of food technology and the profession of food technologist.Design/methodology/approachA qualitative study was conducted and the data consisted of audio recordings of 10 semi structured group interviews of first-, second- and third-year students, as well as alumni, at work. The interviews were transcribed and analysed by conventional content analysis, here following an inductive approach.FindingsMost students had previous general culinary interest, an interest in the science behind or an interest in contemporary food-related issues. Regardless of the year group and prior interest, most felt that graduation was the stage at which they could identify themselves as food technologists. They evolved from having a rather diffuse understanding of food technology and what is a food technologist before they started to have an increased awareness in their second and third years.Originality/valueThe research findings inform higher education food technology programmes aiming to promote the development of food technology students' professional identity. The study suggests that a holistic approach to teaching, as well as context-based and professional activities at an early stage might help students in their identity formation.

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Trends and Foundations in Research on Students’ Conceptual Understanding in Science Education: A Method Based on the Structural Topic Model

Cited by 7 publications

References 74 publications

Identification of Science Teacher Profiles Based on Lesson Observation Data

Identification of Science Teacher Profiles Based on Lesson Observation Data

Emergent Coding and Topic Modeling: A Comparison of Two Qualitative Analysis Methods on Teacher Focus Group Data

Interest, identity and perceptions: What makes a food technologist?

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