Elsevier

Computers & Education

Volume 80, January 2015, Pages 108-121
Computers & Education

Effects of different video lecture types on sustained attention, emotion, cognitive load, and learning performance

https://doi.org/10.1016/j.compedu.2014.08.015Get rights and content

Highlights

  • Learning performance with lecture capture and picture-in-picture is superior to voice-over type.

  • Verbalizers and visualizers have the same learning performance with three video types.

  • Voice-over type generates the higher sustained attention than picture-in-picture type.

  • Voice-over type generates the highest cognitive load in three video lecture types.

  • Emotions induced by three video lectures do not appear significantly differences.

Abstract

Although online courseware often includes multimedia materials, exactly how different video lecture types impact student performance has seldom been studied. Therefore, this study explores how three commonly used video lectures styles affect the sustained attention, emotion, cognitive load, and learning performance of verbalizers and visualizers in an autonomous online learning scenario by using a two-factor experimental design, brainwave detection, emotion-sensing equipment, cognitive load scale, and learning performance test sheet. Analysis results indicate that, while the three video lecture types enhance learning performance, learning performance with lecture capture and picture-in-picture types is superior to that associated with the voice-over type. Verbalizers and visualizers achieve the same learning performance with the three video types. Additionally, sustained attention induced by the voice-over type is markedly higher than that with the picture-in-picture type. Sustained attention of verbalizers is also significantly higher than that of visualizers when learning with the three video lectures. Moreover, the positive and negative emotions induced by the three video lectures do not appear to significantly differ from each other. Also, cognitive load related to the voice-over type is significantly higher than that with by the lecture capture and picture-in-picture types. Furthermore, the cognitive load for visualizers markedly exceeds that of verbalizers who are presented with the voice-over type. Results of this study significantly contribute to efforts to design of video lectures and also provide a valuable reference when selecting video lecture types for online learning.

Introduction

Although most university classes use traditional face-to-face instruction, many online courses are available in which video lectures are used in digital form. Created by simply uploading a video recording of a lecturer, a video lecture may be more complex, paired with slide presentations, interactive quizzes and demonstrations (Osborn, 2010). Online video lectures have become increasingly common in recent years, as evidenced by their use in many organizations, educational institutions, and open learning systems, such as Coursera, Khan Academy, and TED. Video lectures often provide students with additional time to fully understand classroom course materials by allowing them to review lectures repeatedly (Brecht & Ogilby, 2008). Additionally, online video lectures with audio and video instruction can enrich a learning experience, allowing students to see and listen as they would be in an actual classroom.

Common online learning media include lecture capture (or called the talking-head lecture) (Danielson et al., 2013, Ilioudi et al., 2013, Wiese and Newton, 2013), voice-over presentation (Griffin, Mitchell, & Thompson, 2009), picture-in-picture (Chorianopoulos & Giannakos, 2013), and Khan-style video lecture (Chorianopoulos & Giannakos, 2013), all of which present multimedia information in different styles. A video lecture must harness learning motivation, increase learning performance, satisfy individual learning needs with different learning styles, and select the most appropriate format to facilitate learning (Hornbæk, Engberg, & Gomme, 2002). Moreover, cognitive psychology commonly views attention as facilitating the selection of incoming perceptual information and limiting the number of external stimuli processed by the bounded cognitive system to avoid overloading (Driver, 2001). Importantly, a learning process without sustained attention lacks effective identification, learning, and memory (Broadbent, 1958). Restated, sustained attention to learning content is of priority concern for effective learning, explaining the need to determine whether different styles of video lectures affect sustained attention in online learning scenarios. Moreover, many studies have asserted that design of multimedia materials or video lectures should consider the affective state (i.e. a learner's emotional state) (Chen and Sun, 2012, Chen and Wang, 2011). However, exactly how video lecture types affect learning performance, learner emotions, and sustained attention has seldom been studied empirically, results of which would provide a valuable reference for video lecture design.

According to Sweller, van Merriënboer, and Paas (1998), limited working memory is a defining aspect of the human cognitive architecture and, accordingly, all instructional designs should be analyzed from a cognitive load perspective. Educational research has also confirmed that considering individual learning styles is more important than instructing all learners with one style (Dunn & Griggs, 2000). Individual differences in learning styles must be identified when learners process video lectures since they add to existing knowledge of processing preferences and predict personality variables accurately. Of the cognitive styles related to multimedia learning, the visualizer–verbalizer hypothesis is especially relevant to individual differences when using video lectures for online learning because they typically present information to learners using audio and video (containing slides, texts, and pictures simultaneously) (Mayer & Massa, 2003).

Although many educational organizations create and share video lectures, no conventional standard is available to create a video lecture. No guidelines are also available for the presentation style of video lectures (Ilioudi et al., 2013). Importantly, the merits and limitations of each video lecture type for online learning have not yet been thoroughly investigated. In sum, despite a growing number and variety of online educational video lectures, their effectiveness in terms of learning and usability is poorly understood (Chorianopoulos & Giannakos, 2013). Therefore, this study aims to explore how the three considered video lecture types including lecture capture, voice-over presentation, and picture-in-picture affect the sustained attention, emotion, cognitive load, and learning performance of verbalizers and visualizers in an autonomous online learning scenario by using a two-factor experimental design. Results of this study significantly contribute to efforts to select the most appropriate video lecture type for online learning that maximizes learning performance in an autonomous learning context.

Section snippets

Video lecture design based on cognitive load, multimedia learning, and media richness theories

Learners generally process and remember images much more efficiently than what they read or hear (Shorter & Dean, 1994). Recent years have witnessed tremendous growth of available online educational video lectures, spanning K-12 tutorials to university lectures. Different video lectures (e.g., lecture capture, voice-over presentation, picture-in-picture, and Khan-style video lecture) present multimedia information differently (Chorianopoulos and Giannakos, 2013, Griffin et al., 2009, Ilioudi

Lecture capture format

Despite the popularity of e-learning in recent years, most learning activities occur in traditional classrooms. Lecture capture records classroom lectures using a digital video camera, allowing students to watch the video online or via a computer or a mobile device. Lecture capture technology records a lecturer's voice and image simultaneously, as well as instructional aids, such as writing on a whiteboard and PowerPoint slides. Moreover, lecture capture is characterized by its ability to

Effects of students' sustained attention

This section aims to examine whether the three considered video lectures leaded to that sustained attention of students differed significantly as well as whether sustained attention of visualizers and verbalizers who were presented with the three considered video lectures differed significantly. Table 2 summarizes statistical results for the sustained attention of verbalizers and verbalizers when students were viewing the three video lectures. Analysis by two-way analysis of variance (ANOVA)

Discussion

This study examines the effects of verbalizers and visualizers presented with three considered different video lectures on sustained attention, emotion, cognitive load, and learning performance in an autonomous online learning scenario. Analytical results confirm that although the three video lecture methods significantly promote learning performance, learning performance with the lecture capture and picture-in-picture types is superior to that of the voice-over type. This observation is

Conclusions and future work

This two-factor based study investigates whether the three considered video lecture styles, which present information differently, verbalizers and visualizers significantly differ in sustained attention, emotions, cognitive load, and learning performance. Analytical results confirm that although the three considered video lectures markedly promote learning performance, learning performance with the lecture capture and picture-in-picture types is significantly better than that with the

Acknowledgements

The authors would like to thank the Ministry of Science and Technology of the Republic of China, Taiwan for financially supporting this research under Contract No. NSC 100-2511-S-004-001-MY3.

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