Alexander Renkl

Bio: Alexander Renkl is an academic researcher from University of Freiburg. The author has contributed to research in topics: Educational psychology & Experiential learning. The author has an hindex of 60, co-authored 280 publications receiving 15140 citations. Previous affiliations of Alexander Renkl include Ludwig Maximilian University of Munich & Max Planck Society.

Cognitive Load Theory and Instructional Design: Recent Developments

Abstract: (2003). Cognitive Load Theory and Instructional Design: Recent Developments. Educational Psychologist: Vol. 38, No. 1, pp. 1-4.

Learning from Examples: Instructional Principles from the Worked Examples Research:

Abstract: Worked examples are instructional devices that provide an expert's problem solution for a learner to study. Worked-examples research is a cognitive-experimental program that has relevance to classroom instruction and the broader educational research community. A frame- work for organizing the findings of this research is proposed, leading to instructional design principles. For instance, one instructional design principle suggests that effective examples have highly integrated components. They employ multiple modalities in presentation and emphasize conceptual structure by labeling or segmenting. At the lesson level, effective instruction employs multiple examples for each conceptual problem type, varies example formats within problem type, and employs surface features to signal deep structure. Also, examples should be presented in close proximity to matched practice problems. More- over, learners can be encouraged through direct training or by the structure of the worked example to actively self:explain ...

Cognitive Load Theory: Instructional Implications of the Interaction between Information Structures and Cognitive Architecture

Abstract: Within the cognitive load theory research community it has become customary to report theoretical and empirical progress at international conference symposia and in special issues of journals (e.g., Educational Psychologist 2003; Learning and Instruction 2002). The continuation of this custom at the 10th European Conference for Research on Learning and Instruction, 2003, in Padova, Italy, has materialized in this special issue of Instructional Science on the instructional implications of the interaction between information structures and cognitive architecture. Since the 1990s this interaction has begun to emerge as an explicit field of study for instructional designers and researchers. In this introduction, we describe the basics of cognitive load theory, sketch the origins of the instructional implications, introduce the articles accepted for this special issue as a representative sample of current research in this area, and discuss the overall results in the context of the theory. It is generally accepted that performance degrades at the cognitive load extremes of either excessively low load (underload) or excessively high load (overload) – see e.g., Teigen (1994). Under conditions of both underload and overload, learners may cease to learn. So, whereas learning situations with low processing demands will benefit from practice conditions that increase the load and challenge the learner, learning situations with an extremely high load will benefit from practice conditions that reduce the load to more manageable levels (Wulf and Shea 2002). Cognitive load theory (CLT; Paas, Renkl and Sweller 2003; Sweller 1988, 1999) is mainly concerned with the learning of complex cognitive tasks, where learners are often overwhelmed by the number of information elements and their interactions that need to be processed simultaneously before meaningful learning can commence. Instructional control of this (too) high load, in order to attain meaningful learning in complex cognitive domains, has

Structuring the Transition From Example Study to Problem Solving in Cognitive Skill Acquisition: A Cognitive Load Perspective

Abstract: Cognitive load research has shown that learning from worked-out examples, in comparison to problem solving, is very effective during the initial stages of cognitive skill acquisition In later stages, however, solving problems is superior In this contribution, theoretical analyses of different types of cognitive load and their changes over the stages of skill acquisition are presented Two basic arguments are put forth: (a) Intrinsic cognitive load gradually decreases so that a gradual increase of problem-solving demands is possible without inducing cognitive overload (b) In contrast to the earlier stages, different learner activities during the later stages constitute either germane or extraneous load, because different instructional goals are to be achieved Based on these analyses, we propose a fading procedure in which problem-solving elements are successively integrated into example study until the learners are expected to solve problems on their own Empirical evidence supporting this fading proce

Why Minimal Guidance During Instruction Does Not Work: An Analysis of the Failure of Constructivist, Discovery, Problem-Based, Experiential, and Inquiry-Based Teaching

Abstract: Evidence for the superiority of guided instruction is explained in the context of our knowledge of human cognitive architecture, expert–novice differences, and cognitive load. Although unguided or minimally guided instructional approaches are very popular and intuitively appealing, the point is made that these approaches ignore both the structures that constitute human cognitive architecture and evidence from empirical studies over the past half-century that consistently indicate that minimally guided instruction is less effective and less efficient than instructional approaches that place a strong emphasis on guidance of the student learning process. The advantage of guidance begins to recede only when learners have sufficiently high prior knowledge to provide "internal" guidance. Recent developments in instructional research and instructional design models that support guidance during instruction are briefly described.

Multimedia in Learning

Abstract: A wide variety of media can be used in learning, including distance learning, such as print, lectures, conference sections, tutors, pictures, video, sound, and computers. Any one instance of distance learning will make choices among these media, perhaps using several.

Focus on Formative Feedback

Abstract: This article reviews the corpus of research on feedback, with a focus on formative feedback—defined as information communicated to the learner that is intended to modify his or her thinking or behavior to improve learning According to researchers, formative feedback should be nonevaluative, supportive, timely, and specific Formative feedback is usually presented as information to a learner in response to some action on the learner’s part It comes in a variety of types (eg, verification of response accuracy, explanation of the correct answer, hints, worked examples) and can be administered at various times during the learning process (eg, immediately following an answer, after some time has elapsed) Finally, several variables have been shown to interact with formative feedback’s success at promoting learning (eg, individual characteristics of the learner and aspects of the task) All of these issues are discussed This review concludes with guidelines for generating formative feedback