Consumer Behavior in the Online  Classroom: Using Video Analytics  and Machine Learning to Understand the Consumption of Video Courseware

Zhou, Mi; Chen, George H.; Ferreira, Pedro; Smith, Michael D.

doi:10.1177/00222437211042013

Cited by 51 publications

(28 citation statements)

References 55 publications

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“…In addition to the content of the images, the feature variables of the images themselves are also added to the model in this paper. The feature variables of the images themselves include image texture ( Pieters et al, 2010 ), image color, and lightness and darkness ( Zhou et al, 2021 ). The texture part is extracted using the Sobel operator in OpenCV, and then the top five feature values are averaged by applying the PCA model ( Li and Xie, 2020 ).…”

Section: Methodsmentioning

confidence: 99%

Is something out of reach more attractive? The effectiveness of visual distance in computational advertising

Liu

2022

Front. Psychol.

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With the development of mobile Internet technology, firms need to complete the entire process of consumer targeting, ad content generation, and ad display in a very short time window. Therefore, computational advertising, such as native ads on social media platforms, has become the mainstream of online advertising with its automation and personalization features. However, computational advertising faces some problems when using artificial intelligence technology to generate content. First, the images should have a significant enough impact on consumers and be easy to adjust to save computational power at the same time; second, the iteration of the computational advertising system relies on consumer behaviors or advertising effectiveness, and firms need to learn the relationship between ad design and consumer behaviors. Under the above two problems, this paper selects visual distance as the main variable, and images can be adjusted by cropping to save computational power. This paper incorporates image design and ad effectiveness metrics into the construal level theory framework, under which the effectiveness metrics can be quickly determined. Following previous studies, we use click-through rate (CTR) to represent the early stage of the sales funnel and a higher construal level and CVR (conversion rate) to represent the later stage of the sales funnel and a lower construal level. Therefore, visually distant images bring distant psychological distance or higher construal level, which can get higher CTR; visually proximate images bring near psychological distance or lower construal level, which can bring higher CVR. These findings suggest that firms can improve the efficiency of their advertising systems and gain more revenue by understanding consumer psychological states.

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Section: Methodsmentioning

confidence: 99%

Is something out of reach more attractive? The effectiveness of visual distance in computational advertising

Liu

2022

Front. Psychol.

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“…Although we recognized their engagement was independent of the teacher, we were not able to determine how they interacted with the 360° videos, the duration of time on specific content, or the return to a particular timestamp for further exploration. Gathering these information requires the integration of an appropriate framework for video viewing behaviors (Kleftodimos & Evangelidis, 2014), educational data mining (El Aouifi et al, 2021) and video analytics (Zhou et al, 2021). Another concern was pupils' actual perceptions of the experience.…”

Section: Implications Limitations and Future Researchmentioning

confidence: 99%

“We're going on a virtual trip!”: a switching-replications experiment of 360-degree videos as a physical field trip alternative in primary education

Garcia

Nadelson

Yeh

2023

ICEP

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Field trips are steadily declining due to limited funding, time constraints, safety concerns, and other logistical issues. Many schools are resorting to a virtual field trip (VFT), especially when education is disrupted due to public health concerns, natural disasters, or other unforeseen significant events. Virtual reality as a common form of VFT is likely not an option for many schools due to cost and other barriers. The purpose of our study was to explore the potential of going in a VFT using 360-degree (360°) videos as an alternative to a physical field trip in primary education. We recruited third-grade pupils (aged 8–9) from two private elementary schools to experience VFTs using 360° videos (360V) and regular videos (REGV). Using a switching-replications experimental design, we compared their content recall (assessment tests) and VFT experience (attitude, perceived usefulness, involvement, inquiry, video engagement, and virtual guide) across four-time points. Our results show that the increase in content recall scores of 360V groups after VFTs was consistently higher compared to REGV groups at all time points, although it was only significant in one quarter. We also found pupils’ video engagement, involvement, and attitude as significant factors in their VFT experience. These results call attention to a possible implementation of VFTs and continue the long-standing tradition that has been acknowledged as a student-centered, interactive instructional method.

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“…Moreover, this makes it mainly used in the general technological development and decision-making in terms of facts rather than imaginations that cannot be ascertained, among other critical factors in general. Besides, based on technological advancement, the future of big data is ascertained, making it the most effective and efficient among other critical factors in general [11].…”

Section: Limitations and Prospectsmentioning

confidence: 99%

Consumer Behavior Prediction in the Big Data Era: a Comparison Analysis

Liu¹

2023

BCPBM

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Consumer behavior prediction is one of the critical factors that every business organization needs to understand to aware the market structure as well as purchase and sales pattern in a market kind of structure. To address this issue, the only measure can be undertaken is using the big data analytics. In this case, it makes the most preferred and suitable based on analysis of such complex data and can arrive at specific key findings in general. In this paper, different analysis approaches and scenarios will be compared. Based on the analysis, various variables can be used to undertake consumer behavior, i.e., psychological, social, cultural, personal, and economic factors. On this basis, the organizations can undertake. However, one limitation of big data is data manipulation, which makes some of the findings lack the needed objectivity in general. In this case, the analysis has a higher level of applicability and significance in current and future development in market analysis. These results shed light on guiding further exploration focusing on consumer behavior prediction.

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Consumer Behavior in the Online Classroom: Using Video Analytics and Machine Learning to Understand the Consumption of Video Courseware

Cited by 51 publications

References 55 publications

Is something out of reach more attractive? The effectiveness of visual distance in computational advertising

Is something out of reach more attractive? The effectiveness of visual distance in computational advertising

“We're going on a virtual trip!”: a switching-replications experiment of 360-degree videos as a physical field trip alternative in primary education

Consumer Behavior Prediction in the Big Data Era: a Comparison Analysis

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