Bringing the<i>Real World</i>into the Experimental Lab: Technology‐Enabling Transformative Designs

Miller, Lynn C.; Wang, Liyuan; Jeong, David C.; Gillig, Traci K.

doi:10.1002/9781119485001.ch16

Cited by 10 publications

(7 citation statements)

References 63 publications

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“…The concepts can be demonstrated through product learning models through a VR. According to Alessi and Trollip [5], the development of ICT has made a new paradigm in learning. This paradigm can be seen from the results of interviews with students who state that the VR learning model is interesting and enhances learning innovations.…”

Section: Discussionmentioning

confidence: 99%

“…That's why they changed from day to day and from hour to hour. In this era of technologies such as VR environments allowed us to create and validate the representative environment [4]. Indonesia has an educational institution that focused on producing teachers.…”

Section: Introductionmentioning

confidence: 99%

“…The LPTK (Teacher Training Institution) also focused on the structuring terms of the group coherence of general subjects, primary education subject in knowledge revitalization and skill and then the other subject is considered to be able to strengthen superior and innovative soft skills and personality. According to Alessi and Trollip [5] learning by using Information and Communication Technology (ICT) has many advantages. The development of ICT has made a new paradigm in learning.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

VR Use in Online Learning for Higher Education in Indonesia

Kustandi

Fadhillah

Situmorang

et al. 2020

Int. J. Interact. Mob. Technol.

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<p>This research leads to the object of learning in network-based learning programs application of the use of VR in online learning for students in Higher EducationThis research is located in the Education Technology study program, Universitas Negeri Jakarta, Indonesia. This study focuses on learning theories, learning methods and learning models used in technology to improve learning outcomes in class. This method used explanatory sequential mixed methods research. Field trials were conducted for students, with a total of 12 students and field trials would be conducted for students with a total of 30 people in 2018. Data collection through interviews of 15 students and 3 lecturers for 40 minutes. The results showed that using VR can foster motivation to learn to develop student skills in simulating learning models and learning can be efficient and effective. VR can also enhance students for teaching practices and train students to innovate learning models used in technology.</p>

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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VR Use in Online Learning for Higher Education in Indonesia

Kustandi

Fadhillah

Situmorang

et al. 2020

Int. J. Interact. Mob. Technol.

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“…Bente et al ( 2001 ) demonstrate the overlap between real-world experiences and virtual representations of those experiences by finding only marginal differences in socio-emotional impressions between dyadic interactions and virtual animations of the same interactions. Beyond impressions, virtual environments afford opportunities to test for correlations between real-world decisions and virtual versions of those decisions, otherwise known as virtual validity (Godoy et al, 2008 ; Smith et al, 2018 ; Miller et al, 2019a , b , c ). In addition to behavioral decisions, avatars may further influence behavioral change, such as those sought by health interventions.…”

Section: Related Workmentioning

confidence: 99%

Protean Kinematics: A Blended Model of VR Physics

Jeong

Kim

et al. 2021

Front. Psychol.

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Avatar research largely focuses on the effects of the appearance and external characteristics of avatars, but may also warrant further consideration of the effects of avatar movement characteristics. With Protean kinematics, we offer an expansion the avatar-user appearances-based effects of the Proteus Effect to a systematic exploration into the role of movement in affecting social perceptions (about others) and idealized perceptions (about self). This work presents both a theoretical (typology) and methodological (physics-based measurement) approach to understanding the complex blend of physical inputs and virtual outputs that occur in the perceptual experience of VR, particularly in consideration of the collection of hippocampal (e.g., place cells, grid cells) and entorhinal neurons (e.g., speed cells) that fire topologically relative to physical movement in physical space. Offered is a novel method that distills the blend of physical and virtual kinematics to contribute to modern understandings of human-agent interaction and cognitive psychology.

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“…Others (e.g., virtual intelligent agents) subsequently respond to the participants' responses, and those responses are adjusted given the participant's behavior. Different agent responses can then affect the participant's subsequent options and choices, creating interactional sequences into which participants "self-select" that are narratively designed to be more generalizable to everyday life (see below; Appendix; Miller, Wang, Jeong, & Gillig, 2019). However, there are not between group differences in self-selection opportunities in SRD, unless systematically manipulated by design with all other variables held constant or controlled as a source of alternative explanations.…”

Section: Optimizing Representative Design Strengths In Srdmentioning

confidence: 99%

Causal Inference in Generalizable Environments: Systematic Representative Design

Miller

Shaikh

Jeong

et al. 2019

Psychological Inquiry

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Causal inference and generalizability both matter. Historically, systematic designs emphasize causal inference, while representative designs focus on generalizability. Here, we suggest a transformative synthesis -Systematic Representative Design (SRD)concurrently enhancing both causal inference and "built-in" generalizability by leveraging today's intelligent agent, virtual environments, and other technologies. In SRD, a "default control group" (DCG) can be created in a virtual environment by representatively sampling from real-world situations. Experimental groups can be built with systematic manipulations onto the DCG base. Applying systematic design features (e.g., random assignment to DCG versus experimental groups) in SRD affords valid causal inferences. After explicating the proposed SRD synthesis, we delineate how the approach concurrently advances generalizability and robustness, cause-effect inference and precision science, a computationally-enabled cumulative psychological science supporting both "bigger theory" and concrete implementations grappling with tough questions (e.g., what is context?) and affording rapidly-scalable interventions for real-world problems.

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Bringing theReal Worldinto the Experimental Lab: Technology‐Enabling Transformative Designs

Cited by 10 publications

References 63 publications

VR Use in Online Learning for Higher Education in Indonesia

VR Use in Online Learning for Higher Education in Indonesia

Protean Kinematics: A Blended Model of VR Physics

Causal Inference in Generalizable Environments: Systematic Representative Design

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