Yvonne G. Mulder

Finding Out How They Find It Out: An Empirical Analysis of Inquiry Learners' Need for Support.

Inquiry learning environments increasingly incorporate modelling facilities for students to articulate their research hypotheses and (acquired) domain knowledge. This study compared performance success and scientific reasoning of university students with high prior knowledge (n = 11), students from senior high‐school (n = 10), and junior high‐school (n = 10) with intermediate and low prior knowledge, respectively, in order to reveal domain novices’ need for support in such environments. Results indicated that the scientific reasoning of both groups of high‐school students was comparable to that of the experts. As high‐school students achieved significantly lower performance success scores, their expert‐like behaviour was rather ineffective; qualitative analyses substantiated this conclusion. Based on these findings, implications for supporting domain novices in inquiry learning environments are advanced.

Simulation-Based Inquiry Learning and Computer Modeling

Background. Inquiry learning environments increasingly incorporate simulation and modeling facilities. Students acquire knowledge through systematic experimentation with the simulations and express that knowledge in runnable computer models. Aim. As inquiry and modeling activities are new and demanding for students, support for learning is needed. This article reports three experimental studies that examine how students’ inquiry and modeling activities can be supported. Need for support. Study 1 was an empirical assessment of students’ support needs. It compared a group of domain novices to two more knowledgeable reference groups in order to determine the novices’ support needs. Model progression and worked examples. In Studies 2 and 3, the need for support was addressed by model progression (gradually increasing task complexity) and worked-out examples, examining the effect of those interventions on students’ performance and learning. Results suggest positive effects due to both increasing model complexity and providing worked examples that show what the activities in each model progression phase entail and how they should be performed. Implications. The pattern of results across the three studies are discussed with regard to students’ use of available resources, influence of prior knowledge, and the relationship between performance and learning.