The present study employed two different Go-Lab scaffolds/tools. These tools were used by primary school students to carry out successive learning tasks during experimentation. The first tool assisted learners in formulating hypotheses, while the second tool guided students in designing experiments (EDT). Both tools were designed to take into account the trade-offs between structuring and problematizing student inquiry. Our aim was to investigate the effect of each tool separately, as well as the combined effect of the tools in supporting student work. Participants were 41 fifth graders from two classes of a public primary school in Cyprus. They were randomly assigned to four conditions: Condition 1 involved use of both tools, Condition 2 included the hypothesis tool only, Condition 3 included the EDT only, and Condition 4 had no tools provided. Conditions including one of the two tools outperformed the condition with no tools in the corresponding skill scaffolded by the tool. The cumulative effect of both tools seems to have been greater than the effect of each tool separately.
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The optimal degree of guidance for supporting student inquiry in science education has long been debated (Arnold, Kremer, & Mayer, 2014). Previous research has highlighted the possibility that guided inquiry could be beneficial for learners, for instance, in improving science process skills (e.g., Kirschner, Sweller, & Clark, 2006; Koksal & Berberoglou, 2014). However, there is always the need to engage students as active learners in inquiry-based science instruction, capable of taking over responsibility for a range of tasks (Minner, Jurist Levy, & Century, 2010). This unresolved controversy over emphasis on guidance, at the one extreme, and openness, at the other, has been also reflected in the design of computer-supported learning environments. In this case, guidance is taken over by software scaffolds, which aim to structure student tasks in order to decrease complexity and offload certain aspects of a variety of tasks (de Jong, 2006; Pea, 2004; Reiser, 2004; Reiser, Tabak, Sandoval, Smith, Steinmuller, & Leone, 2001; Simons & Klein, 2007; van Joolingen, 1999). If technology can narrow down the multiplicity of potential routes students might follow, then student effort can be devoted to following these more tractable trajectories. However, a rigidly structured learning activity sequence would reduce student ownership and responsibility of their inquiry (e.g., Chang, Chen, Lin, & Sung, 2008).
The challenge of configuring the optimal balance between guidance and openness in inquiry learning in computer-supported learning environments translates into tension between structuring student work, on the one hand, and “problematizing” student inquiry, on the other (Reiser, 2004). Eliminating task complexity, overall, might reduce student active engagement and lock them into unproductive pathways. After any learning gain has been accomplished, the tasks that follow should challenge students to move on at a higher level, beyond their current expertise (Kalyuga, 2007). In contrast to structuring, which reduces complexity, problematizing student inquiry introduces complexity (Reiser, 2004), at least up to a point, so that the difficulty students are confronted with always surpasses the knowledge and skills they have already acquired. By adding such challenge, learner focus is usually re-directed towards parts of the task that otherwise might not be addressed (Reiser, 2004). Despite the unsettled theoretical and methodological interplay between structuring and problematizing student work, to the best of our knowledge, the question of how to problematize inquiry has not yet received the attention it deserves in the relevant literature (see the work of Wieman on PhET simulations for a notable exception, e.g., Wieman, Adams, & Perkins, 2008).