Explaining the segmentation effect in learning from animations: The role of pausing and temporal cueing

Segmentation of animations, that is presenting them in pieces rather than as a continuous stream of information, has been shown to have a beneficial effect on cognitive load and learning for novices. Two different explanations of this segmentation effect have been proposed. Firstly, pauses are usually inserted between the segments, which may give learners extra time to perform necessary cognitive processes. Secondly, because segmentation divides animations into meaningful pieces, it provides a form of temporal cueing which may support learners in perceiving the underlying structure of the process or procedure depicted in the animation. This study investigates which of these explanations is the most plausible. Secondary education students (N = 161) studied animations on probability calculation, after having been randomly assigned to one of four conditions: non-segmented animations, animations segmented by pauses only, animations segmented by temporarily darkening the screen only, and animations segmented by both pauses and temporarily darkening the screen. The results suggest that both pauses and cues play a role in the segmentation effect, but in a different way.

[1]  F. Paas,et al.  Memory load and the cognitive pupillary response in aging. , 2004, Psychophysiology.

[2]  F. Paas,et al.  Cognitive Architecture and Instructional Design , 1998 .

[3]  Tamara van Gog Effects of identical example-problem and problem-example pairs on learning , 2011, Comput. Educ..

[4]  F. Paas Training strategies for attaining transfer of problem-solving skill in statistics: A cognitive-load approach. , 1992 .

[5]  F. Hesse,et al.  Do film cuts facilitate the perceptual and cognitive organization of activitiy sequences? , 2000, Memory & cognition.

[6]  M Boltz,et al.  Temporal accent structure and the remembering of filmed narratives. , 1992, Journal of experimental psychology. Human perception and performance.

[7]  Mary Hegarty,et al.  When static media promote active learning: annotated illustrations versus narrated animations in multimedia instruction. , 2005, Journal of experimental psychology. Applied.

[8]  R. Catrambone The subgoal learning model: Creating better examples so that students can solve novel problems. , 1998 .

[9]  F. Paas,et al.  How to Optimize Learning From Animated Models: A Review of Guidelines Based on Cognitive Load , 2008 .

[10]  Eric Jamet,et al.  Using video and static pictures to improve learning of procedural contents , 2009, Comput. Hum. Behav..

[11]  R. Moreno Optimising learning from animations by minimising cognitive load: cognitive and affective consequences of signalling and segmentation methods , 2007 .

[12]  R. Mayer,et al.  Nine Ways to Reduce Cognitive Load in Multimedia Learning , 2003 .

[13]  F. Paas,et al.  Attention guidance in learning from a complex animation: Seeing is understanding? , 2010 .

[14]  Béatrice S. Hasler,et al.  Learner Control, Cognitive Load and Instructional Animation , 2007 .

[15]  T. Gog,et al.  A Theoretical Analysis of How Segmentation of Dynamic Visualizations Optimizes Students' Learning , 2010 .

[16]  T. Gog,et al.  In the eyes of the beholder: How experts and novices interpret dynamic stimuli , 2010 .

[17]  Pavlo D. Antonenko,et al.  Using Electroencephalography to Measure Cognitive Load , 2010 .

[18]  Robert K. Atkinson,et al.  Using animations and visual cueing to support learning of scientific concepts and processes , 2011, Comput. Educ..

[19]  F. Paas,et al.  Interactivity in Video-based Models , 2007 .

[20]  John Sweller,et al.  The Mirror Neuron System and Observational Learning: Implications for the Effectiveness of Dynamic Visualizations , 2009 .

[21]  Fred Paas,et al.  Observational learning from animated models: Effects of modality and reflection on transfer , 2009 .

[22]  Fred Paas,et al.  Making instructional animations more effective: a cognitive load approach , 2007 .

[23]  D. Leutner,et al.  Direct Measurement of Cognitive Load in Multimedia Learning , 2003 .

[24]  J. Sweller,et al.  Cognitive load theory, modality of presentation and the transient information effect. , 2011 .

[25]  D. Leutner,et al.  Instructional animation versus static pictures: A meta-analysis , 2007 .

[26]  K. A. Ericsson,et al.  Protocol Analysis: Verbal Reports as Data , 1984 .

[27]  P. Barrouillet,et al.  The Time-Based Resource-Sharing Model of Working Memory , 2020, Working Memory.

[28]  F. Paas,et al.  Uncovering the problem-solving process: cued retrospective reporting versus concurrent and retrospective reporting. , 2005, Journal of experimental psychology. Applied.

[29]  F. Paas,et al.  Cognitive Load Measurement as a Means to Advance Cognitive Load Theory , 2003 .

[30]  Jeffrey M. Zacks,et al.  Event perception: a mind-brain perspective. , 2007, Psychological bulletin.

[31]  Tamara van Gog,et al.  An expertise reversal effect of segmentation in learning from animated worked-out examples , 2011, Comput. Hum. Behav..

[32]  R. Mayer,et al.  When learning is just a click away: Does simple user interaction foster deeper understanding of multimedia messages? , 2001 .

[33]  Rolf Ploetzner,et al.  What contributes to the split-attention effect? The role of text segmentation, picture labelling, and spatial proximity , 2010 .

[34]  Richard K. Lowe Extracting information from an animation during complex visual learning , 1999 .

[35]  Paul Ayres Using subjective measures to detect variations of intrinsic cognitive load within problems , 2006 .

[36]  Barbara Tversky,et al.  Animation: can it facilitate? , 2002, Int. J. Hum. Comput. Stud..

[37]  A. Baddeley Working memory: looking back and looking forward , 2003, Nature Reviews Neuroscience.

[38]  Richard K. Lowe,et al.  An Eye Tracking Comparison of External Pointing Cues and Internal Continuous Cues in Learning with Complex Animations , 2010 .