The integration of computer simulation and learning support: An example from the physics domain of collisions

Abstract

Discovery learning is generally seen as a promising but demanding mode of learning that, in most cases, can only be successful if students are guided in the discovery process. The present article discusses a study on discovery learning with a computer simulation environment in the physics domain of collisions. In the learning environment, which is called Collision, students learned about collisions where two particles move in the same direction and interact via a conservative force in such a way that the total mechanical energy is conserved. In the experiment we conducted with Collision, we evaluated the effects of adding two different ways to guide students: model progression, in which the model is presented in separate parts; and assignments, small exercises that the student can choose to do. The effect of providing assignments and model progression was evaluated by comparing the learning behavior and learning results over three experimental conditions in which different versions of the simulation environment were presented: pure simulation, simulation plus assignments, and simulation plus model progression and assignments. Students' use of the environment was logged, their subjectively experienced workload was measured on-line, and their learning was assessed using a number of assessment procedures. Providing assignments with the simulation improved students' performance on one aspect of a so-called intuitive knowledge test. Providing the students with model progression did not have an effect. A subjective workload measure indicated that expanding the simulation with assignments and model progression did not raise the workload experienced by the students.Discovery learning with computer simulations is generally seen as a promising area for learning and instruction. There are a number of studies in the literature that compare the effects of simulation-based learning to some kind of expository teaching. These studies cover a variety of domains such as biology (

Validating and Optimizing the Effects of Model Progression in Simulation-Based Inquiry Learning

“…A comparison of the 'standard' model progression condition with the control condition assessed the effectiveness of model order progression per se. This analysis was a replication of the Mulder et al (2011) study, and was deemed necessary because research on other forms of model progression failed to produce consistent crossstudy findings, even when conducted by the same researchers or research groups (Swaak et al 1998;De Jong et al 1999;Quinn and Alessi 1994;Alessi 1995). Model order progression in the remaining two conditions was supplemented with one of the improvement options.…”

“…This outcome corroborates the conclusion of Mulder et al (2011) that students benefit from model order progressions that gradually increase the specificity of the students' reasoning about the relations between variables. The success of the present replication is particularly noteworthy because previous attempts to replicate the effectiveness of model progression have generally been unsuccessful (e.g., De Jong et al 1999;Quinn and Alessi 1994). A possible explanation is that the latter studies progressed task complexity along different dimensions (i.e., the degree of realism in the simulation interface and the number of variables that could be manipulated).…”

“…Research on this form of model progression has produced mixed findings. Some studies report that learning with increasingly more elaborate simulations is more effective than learning with a full simulation (Rieber and Parmley 1995;Swaak et al 1998), whereas other studies found no such effects (De Jong et al 1999;Quinn and Alessi 1994). These inconsistent findings suggest that assigning students to a gradually expanding set of simulation variables is probably not the best way to arrange inquiry learning tasks in a simple-to-complex sequence.…”

Cognitive load theory, educational research, and instructional design: some food for thought

“…Still others use a 5-point scale (Camp et al 2001;Huk 2006;Salden et al 2004), a 10-point scale (Moreno 2004), a 100-point scale (Gerjets et al 2006), or a continuous (electronic) scale with or without numerical values (de Jong et al 1999;Swaak and de Jong 2001;van Gerven et al 2002).…”

Students’ Understanding of Statistical Inference: Implications for Teaching

“…Computer simulations have been used in a variety of contexts such as economics, decision theory, Newtonian mechanics, physics, and mathematics (de Jong et al, 1999). In statistics, computer simulations allow students to do what they cannot do in reality, that is, repeat a study many times (Burrill, 2002).…”