We extended research on scaffolds for formulating scientific hypotheses, namely the Hypothesis Scratchpad (HS), in the domain of relative density. The sample comprised of secondary school students who used three different configurations of the HS: Fully structured, containing all words needed to formulate a hypothesis in the domain of the study; partially structured, containing some words; unstructured, containing no words. We used a design with two different measures of student ability to formulate hypotheses (targeted skill): A global, domain-independent measure, and a domain-specific measure. Students used the HS in an intervention context, and then, in a novel context, addressing a transfer task. The fully and partially structured versions of the HS improved the global measure of the targeted skill, while the unstructured version, and to a lesser extent, the partially structured version, favored student performance as assessed by the domain-specific measure. The partially structured solution revealed strengths for both measures of the targeted skill (global and domain-specific), which may be attributed to its resemblance to completion problems (partially worked examples). The unstructured version of the HS seems to have promoted schema construction for students who revealed an improvement of advanced cognitive processes (thinking critically and creatively). We suggest that a comprehensive assessment of scaffolding student work when formulating hypotheses should incorporate both global and domain-specific measures and it should also involve transfer tasks.
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To effectively manage a transfer task in a new learning setting, students need to identify both the surface features that may differ from the prior instructional context and the underlying core aspects shared by the two learning contexts (e.g., Schwartz et al., 2011; Shemwell et al., 2015). Learners would be expected to bypass surface features and apply the learned underlying core aspects that are shared between the previous learning setting and the novel setting (Barnett & Ceci, 2002; Belenky & Schalk, 2014; Kaminski et al., 2008).
Coding for the number of trials in the Splash-Lab versus “smart” trials in the lab (with the “vary-one-variable-at-a-time”, VOTAT heuristic) as well as for the number of observations noted in the observation tool vs. “smart” observations (with a comparison between density of object and density of fluid) was performed by means of the computer screen capture software (River Past Screen Recorder Pro) and did not necessitate any control for inter-rater reliability.
The global and domain-specific measures of the targeted skill (hypothesis formulation) should be related somehow, since we should have expected that a student scoring high in the global (domain-independent) measure should also be capable of addressing effectively the domain-specific task as assessed by means of the rubric. This is what we examined in “Preliminary analysis” through non-parametric analyses (global measure treated as scale variable; domain-specific measure treated as nominal variable). A possible relation between the two measures should not lead us to collapse the two measures into one, however, since the first, global measure (scale variable) would still denote the targeted skill in a context-independent manner, while the second, domain-specific measure (nominal variable) would be confined within the frame of relative density (domain of the present study). In this domain, formulating testable hypotheses is not enough, since students also need to identify and incorporate in their hypotheses the interaction effect between the density of object and fluid.
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The present study was undertaken within the frame of the research project “Go-Lab: Global Online Science Labs for Inquiry Learning at School”, funded by the European Community (Grant Agreement No. 317601; Information and Communication Technologies (ICT) theme; 7th Framework Programme for R&D). We are grateful to our colleagues Ellen T. Wassink-Kamp, Casper H. W. de Jong, Margus Pedaste, Mario Mäeots, Leo Siiman, Effie Law, Matthias Heintz, and Rob Edlin White for their help in developing the rubric to score hypotheses.
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Hovardas, T., Zacharia, Z., Xenofontos, N. et al. How many words are enough? Investigating the effect of different configurations of a software scaffold for formulating scientific hypotheses in inquiry-oriented contexts. Instr Sci 50, 361–390 (2022). https://doi.org/10.1007/s11251-022-09580-x