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Permanent record · RIR–2071

Video-Based Learning Impacts on Undergraduate Business Numeracy Achievement: A Longitudinal Longitudinal Analysis

A longitudinal study evaluating the efficacy of video-based learning (VBL) in improving business statistics performance among first-year undergraduate students.

Open to researchMBA suitableQualified 78/100P4 provenance
Primary research question

To what extent does video-based learning improve academic achievement in undergraduate business numeracy courses?

Knowledge gap

What remains worth asking

Evidence regarding the long-term efficacy of specific digital pedagogical interventions in business numeracy remains limited.

Potential contribution

Why it may matter

Informs evidence-based curriculum design for business schools integrating digital learning tools.

Academic placement

OECD fields and topic tags

EducationBusiness Management

Scope: UK undergraduate business numeracy education. · Method signals: Longitudinal Study, Quantitative Analysis

Possible study pathways

One question, different levels

Postgraduate diploma

Evaluating digital pedagogical tools in professional training environments.

Professional master’s / MBA

Optimizing organizational training and knowledge transfer through digital media.

originalityAccessible
methodologyModerate
Data accessAccessible
ethicsAccessible

Qualification signal

78/100

  • Longitudinal data provides strong evidence.
  • Applicable to corporate training contexts.
  • Open-access scholarly source and DOI metadata verified

Provenance

Research Idea Registry curation

  • DOI and bibliographic metadata independently resolved
  • Open-access status verified
  • The research direction is transparently marked as AI-inferred
The public contributor code contains no name or account email.

APA 7 source

Lewis, N., Lewis, R., & Luca, C. (2023). Impact of video-based learning in business statistics: a longitudinal study. Humanities and Social Sciences Communications, 10(1), Article 146. https://doi.org/10.1057/s41599-023-01634-w

Paper abstract and discussion context; AI-inferred direction

Open source ↗