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Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes

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Innovating workplace learning: Training methodology analysis based on content, instructional design, programmed

Sehoon Kim^1,2,3

¹Seoul School of Integrated Sciences and Technologies, Seoul, South Korea.

Frontiers in Psychology

|August 9, 2022

Summary

This study introduces a new framework for evaluating automotive sales training effectiveness, emphasizing human elements like efficacy and self-determination for better learning transfer and performance in digital sales environments.

Keywords:

CIP-R framework CIPP model COVID-19 training digital training hybrid learning technology-enhanced training training effectiveness workforce upskilling

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Area of Science:

Sales Management
Human Resource Development
Educational Evaluation

Background:

Sales process quality is vital for competitive advantage in the automotive industry.
Sales training is a key intervention for enhancing quality and productivity.
Existing training evaluation models, like CIPP, have limitations.

Purpose of the Study:

To propose a novel framework, Content, Instructional design, Programmed learning, and Recommendation (CIP-R), for evaluating automotive sales training effectiveness.
To compare the effectiveness of traditional, digital, and hybrid training methodologies.

Main Methods:

Applied the novel CIP-R framework to analyze automotive sales training data.
Collected data from 583 training instances in South Korea (2019-2020).
Examined traditional, pure digital, and hybrid training approaches.

Main Results:

Human elements, self-efficacy, and self-determination are critical for learning transfer.
These factors significantly influence performance in the digital sales age.
The CIP-R framework provides a comprehensive approach to training evaluation.

Conclusions:

The proposed CIP-R framework advances training evaluation in automotive sales.
Emphasizing psychological factors enhances learning transfer and performance.
Hybrid training models may offer a balanced approach in the digital era.