Patterns of Scientific Reasoning Skills among Pre-Service Science Teachers: A Latent Class Analysis

Abstract

We investigated the scientific reasoning competencies of pre-service science teachers (PSTs) using a multiple-choice assessment. This assessment targeted seven reasoning skills commonly associated with scientific investigation and scientific modeling. The sample consisted of 112 PSTs enrolled in a secondary teacher education program. A latent class (LC) analysis was conducted to evaluate if there are subgroups with distinct patterns of reasoning skills. The analysis revealed two subgroups, where LC1 (73% of the PSTs) had a statistically higher probability of solving reasoning tasks than LC2. Specific patterns of reasoning emerged within each subgroup. Within LC1, tasks involving analyzing data and drawing conclusions were answered correctly more often than tasks involving formulating research questions and generating hypotheses. Related to modeling, tasks on testing models were solved more often than those requiring judgment on the purpose of models. This study illustrates the benefits of applying person-centered statistical analyses, such as LC analysis, to identify subgroups with distinct patterns of scientific reasoning skills in a larger sample. The findings also suggest that highlighting specific skills in teacher education, such as: formulating research questions, generating hypotheses, and judging the purposes of models, would better enhance the full complement of PSTs’ scientific reasoning competencies.

Do they have inquiry skill profiles? Exploring high school students' scientific inquiry in an animation‐based activity

“…SR skills in the sophisticated group and DA skills in the experimental group are the features of those students, respectively. This finding is in line with Khan and Krell's (2021) study that groups revealed a superior skill among inquiry competencies regarding SR and associated skills. Nevertheless, an issue that emerges from these findings is that the inferiority of DA skills was conceded in the basic students.…”

“Let’s transform!”: A systematic literature review of science learning in COVID-19 pandemic era

“…The global world is filled with anger, fear, misinformation, distrust and discouragement (Reis, 2021), especially during a pandemic. Global society should be modern science-and technology-based societies (Krell et al, 2022) and has strong scientific reasoning (Bicak et al, 2021;Hilfert-Rüppell et al, 2021;Khan & Krell, 2021;Mahler et al, 2021;Meister & Upmeier Zu Belzen, 2021;Rost & Knuuttila, 2022;Schellinger et al, 2021). COVID-19 pandemic has provided on disclosing the fact that most of the public science education and learning.…”

Scientific Reasoning in Science Education: From Global Measures to Fine-Grained Descriptions of Students’ Competencies

“…Others have broadened their scope and discuss aspects that are somewhat "on the sidelines" of what is typically considered scientific reasoning, such as the relevance of conceptual knowledge for reasoning in a specific context [40] and through reasoning on controversial science issues [41]. Most of the contributions address the abilities related to experimentation and modeling (e.g., [39,42,43]); this mirrors the focus of science education on these two styles of reasoning. However, this focus has been criticized as "an impoverished account" of scientific reasoning [9] (p. 17).…”

“…The approach of coding outlined in [39] indicates that scientific correctness is at the center of this conceptualization and not measurement repetition or error analysis, as it might have been in a physics approach. Another example is provided by Khan and Krell [42], who describe a two-dimensional competency-based approach to scientific reasoning (conducting scientific investigations and using scientific models) and also define sub-competencies of scientific reasoning and the associated abilities, including the necessary procedural and epistemic knowledge (based on [11]). They argue that the ability of generating hypotheses requires the knowledge that hypotheses are empirically testable, intersubjectively comprehensible, clear, logically consistent, and compatible with an underlying theory [42] (p. 3).…”

“…Another example is provided by Khan and Krell [42], who describe a two-dimensional competency-based approach to scientific reasoning (conducting scientific investigations and using scientific models) and also define sub-competencies of scientific reasoning and the associated abilities, including the necessary procedural and epistemic knowledge (based on [11]). They argue that the ability of generating hypotheses requires the knowledge that hypotheses are empirically testable, intersubjectively comprehensible, clear, logically consistent, and compatible with an underlying theory [42] (p. 3). This also presents the opportunity to link global and fine-grained perspectives on scientific reasoning competencies.…”