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Massive Open Online Courses (MOOCs) have become an important extension of
formal education, spurred by the Open Educational Resources (OER) movement and
supported by leading higher education institutions (HEIs). MOOCs offer lifelong
learning opportunities to a wide and diverse audience with an aim at making education
more accessible and inclusive. The adoption of MOOCs have significantly increased
during the COVID-19 pandemic, as institutions and learners turned to online platforms
to continue the learning process. Compared to traditional classroom learning, MOOCs
offer notable advantages such as courses are free, flexible, widely accessible and have
no strict entry requirements. These benefits have contributed to their growing
popularity. However, the proliferation of MOOC platforms, coupled with the ease of
switching between providers, has created a highly competitive environment. As
learners frequently shift between platforms, providers face mounting pressure to
distinguish themselves through enhanced service quality and user experience. Yet, a
major concern persists that MOOCs have a consistently low completion rate i.e. below
10%. This high dropout rate not only undermines the value of MOOCs for learners but
also leads to lost opportunities and reduced profitability for platform providers.
Service quality has emerged as a key differentiator for MOOC platforms, offering a
significant competitive advantage in an increasingly saturated market. Despite its
importance, research on service quality in the context of MOOCs remains in its early
stages. Today’s learners are highly discerning and exhibit low tolerance for subpar
service experiences, often leading to high attrition rates. In contrast, delivering
high-quality services can play a critical role in enhancing participant retention.
Consequently, marketing and platform managers are increasingly focused on
improving the quality of services offered through MOOCs. In response to this need,
the present study seeks to identify and examine the dimensions that comprehensively
capture service quality within the MOOC context. Specifically, the study
conceptualizes MOOC service quality as a second-order construct, comprising
multiple first-order dimensions that collectively define the overall learner experience.
Service quality plays a pivotal role in shaping learner behavior, particularly by
influencing engagement, satisfaction, and retention among MOOC participants. This
underscores the importance of examining the relationship between service quality and
learner retention within the MOOC environment. In response, the present study
proposes a theoretical framework that explores the linkage between MOOC Service
Quality (MOOCSQ) and MOOC Learner Retention (MLR). Recognizing that this
relationship may be complex and not entirely direct, the study also considers the role
of intervening and moderating variables in fostering learner retention. Specifically, it
investigates MOOC Learner Engagement (MLE) and MOOC Learner Satisfaction
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(MLS) as mediating variables to gain deeper insight into the underlying mechanisms.
In addition, the study examines the moderating effect of technostress (stress arising
from the use of digital technologies in online learning) on the associations between
service quality and learner engagement, satisfaction, and retention. This
comprehensive approach aims to provide a nuanced understanding of how service
quality influences learner outcomes in the MOOC context.
The relationships between the first-order dimensions of MOOC Service Quality
(MOOCSQ) and MOOC Learner Retention (MLR) are complex and not easily
explained through linear analysis alone. When predictors are highly correlated, relying
solely on linear models may fail to capture the true nature of their interactions. To
address this limitation, the study employs Artificial Neural Networks (ANN) to
uncover non-linear patterns among the first-order independent variables. The primary
objective of this research is to identify and validate the key dimensions of MOOCSQ
and to conceptualize it as a second-order construct. In addition, the study develops an
integrated framework that captures both linear and non-linear relationships between
MOOCSQ dimensions and learner retention, offering a more comprehensive
understanding of the factors influencing retention in MOOCs.
The five key first-order dimensions: Native Language MOOC Content, MOOC
Learner Interface, Adaptive Learning Environment, Learner Support and Credit
Mobility, and Functional Suitability and Performance Efficiency along with their
respective measurement items relevant to the MOOC context, were identified through
an extensive review of high-impact, highly cited empirical studies in the domains of
both offline and online service quality. To collect primary data, a mixed-mode
approach was employed, utilizing both paper-based and online survey methods. A total
of 751 responses were gathered from Indian MOOC learners.
The dataset was analyzed using Partial Least Squares Structural Equation
Modeling (PLS-SEM) to examine the influence of MOOC Service Quality
(MOOCSQ) on MOOC Learner Retention (MLR). Following this, Artificial Neural
Network (ANN) analysis was conducted to detect non-linear patterns among the
first-order dimensions of MOOCSQ and MLR. The study yielded three key findings.
First, MOOCSQ demonstrated a direct and statistically significant positive effect on
MOOC Learner Engagement (MLE), MOOC Learner Satisfaction (MLS), and MOOC
Learner Retention (MLR). Second, complementary partial mediation was identified in
the relationship between MOOCSQ and MLR via MLE and MLS. Third, technostress
was found to negatively moderate the relationships between MOOCSQ and both MLE
and MLS. The predictive accuracy and robustness of the model were further validated
using the ANN technique.
To further enhance the analysis, the study employed the Fuzzy Best Worst Method
(FBWM) to rank the first order dimensions of MOOC Service Quality (MOOCSQ).
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This research represents a pioneering effort in systematically evaluating service quality
dimensions within the MOOC context. By integrating both quantitative and qualitative
methodologies, the study presents a comprehensive research framework for assessing
MOOCSQ.
From an academic perspective, the study contributes to the existing literature by
demonstrating how MOOC service quality influences learner retention, particularly
through the inclusion of intervening and moderating variables. From a practical
standpoint, the findings provide valuable insights for MOOC platform managers,
highlighting specific dimensions of service quality that require greater attention in the
design and delivery of services. The proposed framework enables providers to gain a
competitive edge by focusing on the most influential aspects of service quality.
Moreover, it supports the development of targeted strategies aimed at enhancing
learner retention, improving market positioning, and increasing overall platform
effectiveness. This study also offers a valuable diagnostic tool for assessing the current
quality of service offerings, thereby guiding continuous improvement efforts across
MOOC platforms. |
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