Learners in a Changing Learning Landscape: Reflections from an Instructional Design Perspective

Van Merriënboer, J. J. G., & Stoyanov, S. (2008). Learners in a changing learning landscape: Reflections from an instructional design perspective. In J. Visser & M. Visser-Valfrey (Eds.), Learners in a changing learning landscape: Reflections from a dialogue on new roles and expectations (pp. 69-90). Dordrecht, The Netherlands: Springer.Both learners and teachers find themselves in a learning landscape that is rapidly changing, along with fast societal and technological developments. This paper discusses the new learning landscape from an instructional design perspective. First, with regard to what is learned, people more than ever need flexible problem-solving and reasoning skills allowing them to deal with new, unfamiliar problem situations in their professional and everyday life. Second, with regard to the context in which learning takes place, learning in technology-rich, informal and professional 24/7 settings is becoming general practice. And third, with regard to the learners themselves, they can more often be characterized as lifelong learners who are mature, bring relevant prior knowledge, and have very heterogeneous expectations and perceptions of learning. High-quality instructional design research should focus on the question which instructional methods and media-method combinations are effective, efficient and appealing in this new learning landscape. Some innovative instructional methods that meet this requirement are discussed

Development of an instrument for measuring different types of cognitive load

Item does not contain fulltextAccording to cognitive load theory, instructions can impose three types of cognitive load on the learner: intrinsic load, extraneous load, and germane load. Proper measurement of the different types of cognitive load can help us understand why the effectiveness and efficiency of learning environments may differ as a function of instructional formats and learner characteristics. In this article, we present a ten-item instrument for the measurement of the three types of cognitive load. Principal component analysis on data from a lecture in statistics for PhD students (n = 56) in psychology and health sciences revealed a three-component solution, consistent with the types of load that the different items were intended to measure. This solution was confirmed by a confirmatory factor analysis of data from three lectures in statistics for different cohorts of bachelor students in the social and health sciences (ns = 171, 136, and 148), and received further support from a randomized experiment with university freshmen in the health sciences (n = 58)