Exploring the relationship between learning strategies and learning outcomes in inquiry-based online resources

Student learning strategies in online learning environments are known to be an important factor contributing to learning outcomes. Active learning strategies, a key element of constructivist learning theory, are considered to be particularly valuable, and this has been used as an argument for employing inquiry-based designs. On the other hand, researchers have highlighted empirical evidence showing that ‘pure’ discovery learning is of limited value and that strategies to reduce the complexity and provide guidance to learners are important if the potential learning benefits are to be achieved. This seminar reports on a study in which the learning outcomes from exploration and manipulation of a computer-based simulation were compared with the outcomes from observation of simulation output from a set of logically sequenced simulation parameters, the latter condition designed to limit the complexity of the task. The participants in the study were 158 university students who each used two computer-based simulations – one which allowed exploration through manipulation of simulation parameters and one which allowed only observation of simulation output from preset parameters, in two different scientific content areas. Student learning outcomes were assessed via pre-tests and post-tests of conceptual understanding. Students’ interactions using the discovery-based simulation were recorded and coded as either systematic or unsystematic. The results showed that when compared with observation, systematic exploration resulted in learning benefits, while unsystematic exploration did not. The implications of these results for the design of learning tasks using online learning resources will be discussed. The potential for more widespread application of the learning analytic methods used in the study will also be discussed. It is proposed that such methods could underpin the provision of dynamic support for students based on an automated characterisation of their learning strategies.         
1-2pm, Wednesday 22 May - Frank Tate Room (new), Lvl 9, Melbourne Graduate School of Education, 100 Leicester St, Associate Professor Barney Dalgarno, Sub Dean Learning and Teaching School of Education, Charles Sturt University.