Role of subjective and objective measures of cognitive processing during learning in explaining the spatial contiguity effect

Makransky, Guido; Terkildsen, Thomas; Mayer, Richard E.

doi:10.1016/j.learninstruc.2018.12.001

Cited by 63 publications

(55 citation statements)

References 48 publications

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“…However, the current study suggests that VR experience may not completely support student learning. In line with the current study, Makransky et al (2019) reported that instruction by VR using HMDs harmed students’ learning because of the features of immersive virtual reality compared to conventional media. To use HMDs more effectively, based on the results of the current study, specific content and instructions for VR should be offered to help students memorize more correctly and effectively.…”

Section: Discussionsupporting

confidence: 88%

“…Regarding spatial learning in virtual environments, Péruch and Wilson (2004) noted that passive viewing requires fewer cognitive resources, which might improve spatial learning. Recently, Makransky et al (2019) reported an EEG study and suggested that high immersion in VR inhibited learning because of higher cognitive load. Although the use of cognitive resources alone could not fully explain the results of the current study because there was no difference in the memory test immediately after viewing, this possibility should be assessed in further studies.…”

Section: Discussionmentioning

confidence: 99%

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Active View and Passive View in Virtual Reality Have Different Impacts on Memory and Impression

Hine

Tasaki

2019

Front. Psychol.

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Virtual reality (VR) through a head-mounted display (HMD) can provide new experiences. However, it remains unclear how the characteristics of HMDs affect users’ memory. To use HMDs more effectively and appropriately in several applied fields, including education, it is necessary to clarify what characteristics of HMDs affect users’ memory. A head-tracking function mounted on an HMD helps to detect the user’s head direction to enable a simulation experience akin to the real world. When we experience a simulation on an HMD, we actively perceive the visual world. In this study, we assessed how active/passive viewing affects users’ memory of VR content. We conducted a psychological experiment in which participants watched a movie on an HMD. In the active viewing condition, the presented view changed depending on the participant’s head direction. In the passive viewing condition, the presented view was a recorded movie that was shown to the participants in the active viewing condition. All participants took a memory test about the content presented in the movie on the day of viewing and 2 weeks later. The results showed that performance on the memory test in the active viewing condition was significantly lower than that in the passive viewing condition after 2 weeks. This result indicated that active viewing in VR inhibited users’ memory compared to passive viewing. The current study contributes to the development of new VR techniques, such as educational learning.

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Section: Discussionsupporting

confidence: 88%

Section: Discussionmentioning

confidence: 99%

Active View and Passive View in Virtual Reality Have Different Impacts on Memory and Impression

Hine

Tasaki

2019

Front. Psychol.

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“…Thus, the student's overall perception of high CL could also influence the EL interaction subscale, which theoretically should remain the same. While this is a limitation with the current scale it is a general limitation when using self‐report measures (Makransky, Terkildsen, & Mayer, 2019c). Future studies should therefore investigate the use of objective measures of CL and combine these with subjective questionnaires.…”

Section: Discussionmentioning

confidence: 99%

“…Accurately measuring cognitive load in relation to learning situations is essential for understanding when cognitive overload occurs, and for developing instructional design guidelines that can limit unnecessary cognitive load and facilitate learning. Although the current measures are useful for obtaining a general measure of students perceptions of CL, previous research has highlighted several limitations (e.g., Antonenko & Niederhauser, 2010;Kirschner et al, 2011;Makransky, Terkildsen, & Mayer, 2019c), and specifically called for the need to measure different components of CL that are relevant when learning through, and designing virtual learning environments (e.g., Makransky, Terkildsen, & Mayer, 2019b).…”

Section: Discussionmentioning

confidence: 99%

The validation and further development of a multidimensional cognitive load scale for virtual environments

Andersen

Makransky

2020

Computer Assisted Learning

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Measuring cognitive load is important in virtual learning environments (VLE). Thus, valid and reliable measures of cognitive load are important to support instructional design in VLE. Through three studies, we investigated the validity and reliability of Leppink's Cognitive Load Scale (CLS) and developed the extraneous cognitive load (EL) dimension into three sub-scales relevant for VLE: EL instructions, EL interaction, and EL environment. We investigated the validity of the measures using the Partial Credit Model (PCM), Confirmatory Factor Analysis (CFA), and correlations with retention tests. Study 1 (n = 73) investigated the adapted version of the CLS. Study 2 describes the development and validation of the Multidimensional Cognitive Load Scale for Virtual Environments (MCLSVE), with 140 students in higher education. Study 3 tested the generalizability of the results with 121 higher education students in a more complicated VLE. The results provide initial evidence for the validity and reliability of the MCLSVE.

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“…The benefits of an integrated format over a split-attention format cover a range of topics, such as mathematics (e.g., Tarmizi & Sweller, 1988 ), biology (e.g., Chandler & Sweller, 1991 ; Cierniak et al, 2009 ), electrical engineering (e.g., de Koning et al, 2020a ), meteorology (e.g., Makransky et al, 2019 ; Mayer et al, 1995 ; Moreno & Mayer, 1999 ), and technology of mechanical devices (e.g., Bodemer et al, 2004 ; Johnson & Mayer, 2012 ).…”

Section: Problem: Materials Presents Texts and Visualizations Separatementioning

confidence: 99%

Five Strategies for Optimizing Instructional Materials: Instructor- and Learner-Managed Cognitive Load

et al. 2021

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Researchers of cognitive load theory and the cognitive theory of multimedia learning have identified several strategies to optimize instructional materials. In this review article we focus on five of these strategies or solutions to problematic instructional designs in multimedia learning: (a) the multimedia principle (use visualizations and drawings to complement texts); (b) the split-attention effect or spatial contiguity principle (show texts contiguously or integrated with visualizations); (c) the redundancy effect, alike the coherence principle (remove nonessential learning information); (d) the signaling principle (cue or signal essential learning information); and (e) the transient information effect or segmenting principle (segment or control the pace of animations and videos). Usually, both cognitive theories have investigated solutions that instructors, teachers, and designers should pursue to optimize students’ learning. Here, in a novel approach, we show that these strategies can also be used by learners who want to self-manage their cognitive load and learning process. We provide several examples of both instructor- and learner-managed solutions aligned with these strategies. When assessing which agent, either the instructor or the learner, was most effective, we observed mixed results in the literature. However, the expertise reversal effect may help predict the direction of these effects: novice students may learn better under instructor-managed conditions, whereas more expert students may learn more under learner-managed conditions.

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Role of subjective and objective measures of cognitive processing during learning in explaining the spatial contiguity effect

Cited by 63 publications

References 48 publications

Active View and Passive View in Virtual Reality Have Different Impacts on Memory and Impression

Active View and Passive View in Virtual Reality Have Different Impacts on Memory and Impression

The validation and further development of a multidimensional cognitive load scale for virtual environments

Five Strategies for Optimizing Instructional Materials: Instructor- and Learner-Managed Cognitive Load

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