Some Factors to Consider when Designing Semi-Autonomous Learning Environments ARTICLE
Electronic Journal of e-Learning Volume 7, Number 2, ISSN 1479-4403
This research aims to answer the question, “in what ways do mediated learning environments support or hinder learner autonomy?” Learner autonomy has been identified as one important factor in the success of mediated learning environments. The central aspect of learner autonomy is the control that the learner exercises over the various aspects of learning, beginning with the decision to learn or not to learn. But as Candy (1995) points out, there are several areas where learner-control can be exercised. The first are the motivational-intentional forces that drive the learner to apply some determination (or “vigour”) to the act of learning. They are the conative functions of learning and include learner intiative, motivation and personal involvement. They are often associated with life goals that are independent of the actual learning goals pursued within the strict confines of the learning environment (Long, 1994). The second area of learner-control is the one comprising the “nuts-and-bolts” of the act of learning, such as defining learning goals, deciding on a learning sequence, choosing a workable pacing of learning activities, and selecting learning resources (Hrimech & Bouchard, 1998). These are the algorithmic aspects of learning, and in traditional schooling, they are the sole responsibility of the teacher. In mediated learning environments, it can be shared between the platform and the actual learner. Just a few years ago, learner control was necessarily limited to these two sets of features, conative and algorithmic. Today however, with the proliferation of educational offerings in both the private and public sector, as well as the developments in educational technology, two other aspects of the learning environment emerge as important areas where learner-control can be exercised. The semiotic dimension of learner-control includes the symbolic platforms used to convey information and meaning, for example web “pages”, hypertext, video/audio multimedia, animation, each of these bringing with them their own specific set of possibilities and limitations for autonomy in learning. And then again, all learning environments exist in their own distinct economic sphere where decisions about whether, what and how to learn are made on the basis of cost-benefit, opportunity cost, and extrinsic market value. We will examine the implications of each of these areas of learner-control, and share our analysis of a series of interviews with cyber-learners, based on this framework of conative, algorithmic, semiotic and economic factors. (Contains 1 figure.)
Bouchard, P. (2009). Some Factors to Consider when Designing Semi-Autonomous Learning Environments. Electronic Journal of e-Learning, 7(2), 93-100. Retrieved November 16, 2018 from https://www.learntechlib.org/p/55157/.