Learning by Designing Instruction in the Context of Simulation-based Inquiry

Learning by Designing Instruction in the Context of Simulation-based Inquiry
Learning by Designing Instruction in the Context of Simulation-based Inquiry

Currently there is a general consensus that inquiry-based approaches to learning science that incorporate students’ active investigation and experimentation are necessary to motivate students for science (Osborne & Dilon, 2008). 

Inquiry is the process in which students engage in the investigation of scientifically oriented questions, perform active experimentation, formulate explanations from evidence, evaluate their explanations in light of alternative explanations, and communicate and justify their proposed explanations (National Research Council, 2000). 

1- Beyond the motivational benefit, inquiry 
Learning and its associated processes also have value of their own; inquiry learning generates knowledge and, if well supported, can be more effective than direct forms of instruction (Furtak, Seidel, Iverson, & Briggs, 2012). For these reasons, it is held that inquiry should be part of the science curriculum (e.g., National Research Council, 2000).  

This study compares learning from designing instruction in the context of simulation-based inquiry learning with learning from expository teaching. The domain of instruction was the electricity domain of high-pass and low-pass filters. Participants were students from a technical vocational school. 

In the experimental condition (N = 21) students created assignments for an imaginary student to help this student to learn from a computer simulation. The LOOK-EXPERIMENT-DESIGN (LED) approach was developed to support students in designing these assignments. 

This support structure scaffolded students in orienting themselves in the simulation (LOOK), in performing experiments to gain more insight into the simulated domain (EXPERIMENT), and in designing assignments (DESIGN) about the simulated domain. 

3- Students in the control condition (N = 28) received traditional instruction. 
Students came from two different classes and were divided over the two conditions. After 3 two-hour lessons, all students completed a test measuring conceptual and procedural knowledge. 

Results showed that, in one class, students who learned by designing assignments performed significantly better on test items measuring conceptual knowledge than students who learned from traditional instruction. This was not replicated in the other class. No differences between the conditions were found for procedural knowledge.

words Inquiry learning, Simulations, Learning by teaching, Physics teaching

4- Contemporary technology-based approaches 
To science learning provide students with ample opportunities for inquiry. Technology-based environments offer simulations, games, data sets, and/or remote and virtual laboratories for students' inquiry-related use

. Inquiry calls for non-linear and interactive content that these technology-based environments are able to provide, so that their technological affordances are directly used for pedagogical purposes (de Jong, 2006). 

5- Evidence is accumulating that technology-enhanced 
Learning environments for inquiry provide students with genuinely effective learning opportunities, and large-scale studies show that these inquiry environments outperform more direct approaches to instruction on a variety of outcome measures (e.g.,Deslauriers & Wieman, 2011; 

Eysink et al., 2009; Marusić & Slisko, 2012). However, these promising results only materialize when the inquiry process is structured and scaffolded (Alfieri, Brooks, Aldrich, & Tenenbaum, 2011). Effective scaffolds come in many forms. 

6- Examples include tools for creating hypotheses, 
Data analysis tools, and tools for saving and monitoring experiments (see e.g., de Jong, 2005; Quintana et al., 2004; Zhang, Chen, Sun, & Reid, 2004). A growing number of computer-based inquiry environments have emerged that provide students with inquiry facilities together with an integrated supportive structure and scaffolds. 

Examples of such learning environments are: Inquiry Island (White et al., 2002); GenScope (Hickey, Kindfield, Horwitz, & Christie, 2003); SimQuest-based environments (de Jong et al., 1998); Co-Lab (van Joolingen, de Jong, 

7- Overall, we found no differences on the conceptual and 
Procedural knowledge test items between the two conditions. Looking at the two classes separately, we found that students in the experimental condition of Class 1 performed significantly better on the conceptual items than students in the control condition. 

However, this result was not repeated for Class 2. This might have been caused by the difference in prior computer simulation experience between the two classes. 

During their regular lessons, students in Class 1, who came from a different educational program (Electronic Engineering) than students from Class 2 (Automotive Engineering), had used the program Multisim to build and simulate circuits. Experience with the Multisim simulations might have helped the students from Class 1 in learning from a simulation. 

For students in Class 2 this was their first encounter with computer simulations and we know from research that it takes students a bit of time to have enough experience in inquiry learning (Hickey et al., 2003; Ketelhut, 2007).

To guide the students in the experimental condition we developed a support structure. 8-
Asking students to design assignments already structures students’ inquiry process. Additional scaffolds were added to support the design process so that students would be able to explore the domain, perform experiments, gather data for the design of their assignments and formulate assignments based on their newly acquired knowledge. 

During the whole process, students made notes on their LED-sheets. An informal qualitative analysis of these notes and the observations we made during the lessons showed that the effects of these scaffolds look promising. First, the scaffolds “observation starter” and “drawing representations” seemed to assist students in starting an investigation, as was reflected in students’ notes 

9- LED-sheets and observations made during the lessons. 
In addition, the representations assisted students in formulating explanations for their assignments. Drawing representations of the total impedance in the circuit helped students remember the Pythagorean formula used to calculate the total impedance. 

Second, the “partly-filled-in table” (developed to support students in planning and monitoring a series of experiments) assisted students in performing a series of measurements and drawing conclusions about the collected data. It seems that this relatively straightforward table helped students to keep an overview of their data and enabled them to focus on the relations being investigated. 

10- This is in line with studies that have emphasized 
the importance of monitoring support (Veermans, van Joolingen, & de Jong, 2006). Third, in complying with the scaffold telling them to “perform calculations”, students performed two calculations with a formula and used the outcomes to describe the relation between the variables. 

11- With hindsight, we could have exploited this 
scaffold more by linking the calculations and its resulting quantitative relation from the EXPERIMENT phase more explicitly with the (qualitative) observations of the same relation in the LOOK phase. In this way, students might have realized that careful observations in a simulation can be used to check their understanding of a formula. 

A point of concern, however, is that, as our qualitative analysis showed, many predictions as formulated in the “prediction starters” were not correct. Students were not inclined to reflect on the correctness of their predictions - a process which might have given rise to interesting learning moments. Students might need extra support in reflecting on their work. 

This is important because reflection on one's own knowledge is a pivotal aspect of learning with computer simulations (Smetana & Bell, 2012). The current study had limitations in the small number of participants involved and the unfamiliarity of working with simulation software for a number of the participants. 

This study therefore is only a first step towards designing effective “learning by design” instruction (see also de Jong et al., 2012) . The current work indicates that designing assignments for a simulation with the LOOK-EXPERIMENT-DESIGN approach opens opportunities for students to gain insight into the simulated domain. Prior experience in working with simulations seems to be a potential facilitating condition in this learning process. 

With respect to the scaffolds, we found that these straightforward types of support were relatively easy to use and seemed to assist our students in focusing on important relations in de domain, learning from the simulation and in using the knowledge they had acquired in designing their assignments.


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