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Self-efficacy is the belief in one's capacity to organize and execute actions necessary to manage prospective situations. This belief significantly influences how individuals approach goals, tasks, and challenges across different domains of life.Psychological and Educational ImpactsIndividuals with strong self-efficacy are more resilient in the face of difficulties. They are more likely to adopt effective problem-solving strategies, persist through obstacles, and regulate emotions such as...
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The Self-Evaluation Maintenance (SEM) model offers a psychological framework to understand how individuals’ self-esteem is influenced by the achievements of others, particularly those with whom they share close personal bonds. The SEM model operates when personal rather than social identity guides individuals. Central to this model is the notion that individuals have an inherent desire to preserve a favorable self-image, which is continuously shaped by interpersonal comparisons and...
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Developing an Instrument for Assessing Self-Efficacy in Data Mining and Analysis.

Yu-Min Wang1, Chei-Chang Chiou2, Wen-Chang Wang1

  • 1Department of Information Management, National Chi Nan University, Puli, Taiwan.

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|February 15, 2021
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Summary
This summary is machine-generated.

This study developed a reliable instrument to measure self-efficacy in data mining and analysis. The new tool helps assess individual readiness for data mining tasks, addressing the growing need for these skills.

Keywords:
artificial intelligencebig datadata miningmeasurement instrumentself-efficacy

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Area of Science:

  • Information Science
  • Psychology
  • Business Analytics

Background:

  • Organizations face information overload due to automated data collection.
  • There is a rising demand for data mining and analysis expertise.
  • Self-efficacy significantly influences task performance and willingness.

Purpose of the Study:

  • To develop and validate a new instrument for assessing self-efficacy in data mining and analysis.
  • To provide a tool for evaluating individual capabilities in data-related tasks.

Main Methods:

  • Initial item list generated from data mining skills and expert input.
  • Exploratory Factor Analysis (EFA) used to extract a 19-item, four-factor model.
  • Partial Least Squares-Structural Equation Modeling (PLS-SEM) applied for model validation.

Main Results:

  • A 19-item, four-factor measurement model was identified.
  • The instrument demonstrated satisfactory reliability and validity.
  • The developed scale effectively measures self-efficacy in data mining and analysis.

Conclusions:

  • The new instrument is valuable for researchers and practitioners.
  • It aids in evaluating an individual's proficiency and preparedness for data mining and analysis.
  • Supports the growing need for skilled data professionals.