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Related Experiment Video

Updated: Jan 14, 2026

Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning

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Published on: August 29, 2025

Validating and prioritizing key indicators for blended MOOC implementation in English language learning using the

Anh Tuan Pham^1,2, Muhammad Ridhuan Tony Lim Abdullah¹

¹Department of Management, Universiti Teknologi PETRONAS, Perak, Malaysia.

|October 27, 2025

Summary

This study validated 20 key indicators for blended Massive Open Online Courses (bMOOCs) in English language learning using the Fuzzy Delphi Method (FDM). This provides a structured framework for evaluating bMOOCs in English as a Foreign Language (EFL) contexts.

Keywords:

Blended learning EFL instruction Fuzzy Delphi analysis Indicators Massive Open Online Courses

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Area of Science:

Educational Technology
Applied Linguistics
Decision Science

Background:

Massive Open Online Courses (MOOCs) are increasingly adopted in higher education, particularly blended MOOCs (bMOOCs).
A lack of standardized evaluation criteria for bMOOCs in English as a Foreign Language (EFL) contexts hinders effective implementation.
The COVID-19 pandemic accelerated the need for robust frameworks for online and blended learning environments.

Purpose of the Study:

To develop and validate a structured method for identifying and prioritizing key indicators for bMOOC implementation in EFL.
To establish expert consensus on essential sub-indicators for effective bMOOC design and evaluation.
To address the existing gap in standardized evaluation criteria for blended learning in EFL.

Main Methods:

The Fuzzy Delphi Method (FDM), an 8-step process, was employed to achieve expert consensus.
A panel of 15 experts evaluated 21 proposed sub-indicators across six predefined domains.
Fuzzy logic was utilized to handle uncertainty and enhance decision-making among experts.

Main Results:

A validated set of 20 key sub-indicators for bMOOC implementation in English language learning was established.
The indicators were systematically categorized into six domains: learner analysis, objectives, materials and technology, teaching methodologies, learner participation, and assessment.
The FDM process demonstrated transparency and replicability in developing the evaluation framework.

Conclusions:

The validated indicator set offers a foundational framework for instructional design, policy development, and quality assurance in EFL bMOOCs.
This structured method enhances the reliability and validity of evaluation frameworks for blended online learning environments.
The findings support the systematic implementation and continuous improvement of bMOOCs in English language education.