The Interplay of Scientific Reasoning and Self-Regulation in Inquiry Learning: A Temporal Process-Oriented Analysis

Abstract

This dissertation investigated the prerequisites, the processes and the promotion of scientific reasoning and argumentation during inquiry learning. Three conceptual aimed at investigating 1) the combined influence of students’ cognitive and motivational characteristics on their experimentation skills and conceptual understanding, 2) the interplay of self-regulation and scientific reasoning processes and argumentation quality, and 3) the effectiveness of integrated instruction of self-regulation and scientific reasoning for students’ learning processes and learning outcomes in the context of inquiry learning. Three studies were conducted to investigate these conceptual aims. Each study used a novel statistical method going beyond the traditional variable-oriented approach and instead considers the conjoint influence of different factors (person-oriented analysis, epistemic network analysis, process mining). Study 1 (N = 110) focused on cognitive and motivational learning prerequisites for experimental skills and conceptual understanding. The study identified three clusters of learners which differed regarding experimentation skills and conceptual understanding. These findings indicate that motivational variables need to be considered alongside prior knowledge when assessing the effectiveness of inquiry learning. Study 2 (N = 30) investigated the interplay of self-regulation and scientific reasoning processes in relation to argumentation quality. Results from epistemic network analysis show that self-regulation rarely occurs spontaneously and when it does occur, it is mostly in learners who also formulate higher-quality arguments. Findings from Study 2 were used to design instruction that supports the interplay of self-regulation and scientific reasoning. The effectiveness of the instruction on students’ learning processes and outcomes was tested in Study 3. In Study 3 (N = 127), an intervention targeted at supporting the self-regulation of scientific reasoning processes using video modeling examples and metacognitive prompts was developed and tested in a training and a transfer task. Video modeling examples had positive effects on hypothesis and argumentation quality – two important aspects of scientific reasoning. Process analyses using epistemic network analysis and process mining provide further evidence for the interplay of self-regulatory processes and scientific reasoning processes in participants who watched the video modeling examples. The findings from the three studies are integrated into the Self-Regulated Learning during Scientific Reasoning (SRLSR) model, which provides important theoretical implications for self-regulation and scientific reasoning research. The findings from this dissertation provide important educational implications for teaching science using inquiry learning.