G UIDANCE

Characteristic for Go-Lab ILSs is that they provide students with integrated guidance. In deliverable D1.1 we have listed the different types of guidance applied in Go-Lab and in internal deliverable G1.3 we have presented more specific descriptions of one type of guidance, the scaffolds. The scaffolds are described from a more technical perspective in D5.5. In D1.1. we have defined scaffolds as: “Scaffolds are tools that help students perform a learning process by supporting the dynamics of the activities involved. Scaffolds often provide students with the components of the process and thus structure the process” (de Jong, 2013, p. 16). The scaffolds (or tools as we also call them) that we have introduced in Go-Lab and that are evaluated in the studies presented in this deliverable are summarized in the following sections.

1.1.1 Orientation: Concept mapper

To help students revive their prior knowledge and give them a structured start of the inquiry process the orientation phase may offer them a concept map. Overall, concept maps (Novak, 1990) are found to be good facilitators of the learning process in supporting higher order cognitive skills (e.g., Bramwell-Lalor & Rainford, 2014), to guide students through a domain (Hagemans, van der Meij, & de Jong, 2013) or to support collaboration between students (Gijlers & de Jong, 2013). In Go-Lab the concept map can include predefined concepts and relations and students. In the particular study reported in this deliverable the concept maps was generated by students themselves (with predefined concepts and relations present). Go-Lab also has the facility, however, to provide students with readymade (partial) concept maps which may also be a way to help students in the learning process (Chang, Sung, & Chen, 2001, 2002). Figure 1.1 shows an example of a Go-Lab concept map.

Figure 1.1. Example of a Go-Lab concept map.

1.1.2 Conceptualisation: Hypothesis and question scratchpad

The hypothesis scratchpad offers students a structured way to create hypotheses. The scratchpad offers (by the teacher) pre-defined elements and relations and students can add their own elements and relations as well. This scaffold is based on older work by van Joolingen and de Jong (1993). Teachers may also decide to give students a set of predefined completed hypotheses to start from (see e.g., Njoo & de Jong, 1993). Figure 1.2 shows the hypothesis scratchpad.

Figure 1.2. Example of a Go-Lab hypothesis scratchpad.

An alternative to the hypothesis scratchpad is the “question scratchpad”. The question scratchpad offers a more open way of creating statements but still gives a structure by means of the predefined terms that are available for the students. This question scratchpad can be used when students have more open issues to explore. Figure 1.3 gives an example of the question scratchpad.

Figure 1.3. The Go-Lab question scratchpad.

1.1.3 Investigation: Experiment design tool

Creating an informative and unconfounded experiment is a challenge for many students (Arnold, Kremer, & Mayer, 2014; Klahr, Zimmerman, & Jirout, 2011; Morgan & Brooks, 2012). The experiment design tool (EDT) created for Go-Lab is a new type of tool that helps students by presenting them an overview of variables and a means to structure these in well-designed experiments. Figure 1.4 shows an example of the EDT as used in the

“Guppies’ domain.

Figure 1.4. Example of the Go-Lab Experiment Design Tool (EDT).

1.1.4 Investigation: Data viewer tool

Interpreting data and finding trends in data is a skill that is very central for inquiry learning but often not well valued. It appears though that students often have real trouble making sense of data and seeing them in the right way (see e.g., Eckhardt, Urhahne, Conrad, &

Harms, 2013). The data viewer tool allows students to plot variables from their experiments against each other and see the relations in different representations. Figure 1.5 shows an example of the data viewer tool, here the experiment had two variables that are plotted against each other and a bar chart has been selected to view the relation between the variables.

Figure 1.5. Example of the Go-Lab data viewer tool.

1.1.5 Investigation: Experimental error tool

Virtual experiments normally do produce neat data without any measurement errors but in real experiments (and thus also in remote experiments) measurement (random and systematic) errors play a crucial role. Research shows that students are not always aware of these issues (see e.g., Kanari & Millar, 2004). The Go-Lab experimental error tool helps students to get an idea of what plays a role in interpreting data that may be effected by measurement errors and helps them to make the appropriate calculations. The experimental error tool allows students to calculate experimental errors that stem from real experimental setups. Using this tool, students may learn about the different sources of error that occur when performing experiments and about the different types of errors that can be calculated so as to decide whether an experiment is precise and accurate.

Figure 1.6 shows an example of a part of the experimental error tool, the upper parts are more theoretical and explain the students the background of experimental errors.

Figure 1.6. Screenshot of the Go-Lab experimental error tool.

1.1.6 Conclusion: Conclusion tool

After having collected and interpreted data these data have to come in touch with the original questions and/or hypotheses a student had. This is the process of drawing conclusions (de Jong, 2006) that is again a focal process in inquiry (Scanlon, Anastopoulou, Kerawalla, & Mulholland, 2011). The Go-Lab conclusion tool facilitates this process by letting students select a question from the set of questions and/or a hypothesis from the set of hypotheses and connect this question and/or hypothesis with student observations (as noted down in the observation tool) and/or saved explorations from the data viewer. The idea behind the conclusion tool is that students can systematically evaluate their hypotheses and questions. For hypotheses they can adapt their original confidence in each hypothesis in the conclusion tool. In case, students do not find any

data or observations related to the question or hypothesis they can go back to experiment to generate more data.

Figure 1.7 shows the Go-Lab conclusion tool in action.

Figure 1.7. The Go-Lab conclusion tool.

1.1.7 Discussion: Reflection tool

Reflection is a key aspect of learning. By reflection learners try to think at a meta-level on the knowledge acquired or the process gone through (Land & Zembal-Saul, 2003). In Go-Lab we focus on a number of different aspects to reflect on both on the product and the process side. For example, a tool showing aggregated concept maps (a kind of average concept map of all students) that individual students can use to compare their own concept map to. A reflection tool that focuses on the process is a tool that shows students their own time spending in the different phases of an ILS and present a “norm” (indicated by the teacher). Students can then compare their own distribution of time against this norm.

Figure 1.8 presents a screendump of this reflection tool.

Figure 1.8. Example of the time spent reflection tool.

1.1.8 General: Quiz tool

Asking students for their knowledge and insights may have different functions in an inquiry process, it may help to revive prior knowledge or as a kind of formative testing of developing understanding. With the Go-Lab quiz tool a teacher can design a multiple choice test and define the feedback for each alternative. Figure 1.9 shows part of a Go-Lab quiz.

Figure 1.9. Part of a Go-Lab quiz.