Available via license: CC BY-SA 4.0
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Journal of Learning for Development 11(1), 2024, 1-14.
Published by Commonwealth of Learning, Canada
CC BY-SA 4.0
Microlearning and Learning Performance in Higher Education: A
Post-Test Control Group Study
Sathiyaseelan Balasundaram, Jain Mathew and Sridevi Nair
School of Business and Management, Christ University, Bengaluru, India
Keywords
Abstract
microlearning,
instructional
design,
instructional
methods,
cognitive load
theory, learning
effectiveness
This study aimed at evaluating the effectiveness of microlearning in higher
education. The sample consisted of first-year MBA students, and a post-test
control group design was used to assess the effectiveness of a microlearning
module. The results indicated that the use of microlearning was significantly
related to learning performance and participants' reactions to the module.
Moreover, the microlearning group scored significantly higher than the control
group. The findings suggest that microlearning has the potential to improve
learning outcomes and enhance participant engagement. However, the study has
certain limitations, and future research is needed to gain a comprehensive
understanding of the optimal design and delivery of microlearning modules. The
study supports the use of microlearning in higher education as an effective
instructional strategy.
Introduction
Microlearning is an instructional method that delivers concise learning content in easily
digestible formats, addressing the limitations of traditional training approaches (Hug, 2022). It
allows learners to acquire knowledge in short bursts, aligning with their fast-paced lifestyles (So
et al., 2020). Microlearning can take diverse forms, such as videos, quizzes and simulations,
accessible through various devices (Ghirardini, 2011).
While microlearning has gained popularity in industries like healthcare and finance, its
application in an academic setting, particularly business schools, remains unexplored. This study
aims to bridge this gap by examining the effectiveness of microlearning modules in enhancing
the learning performance of Masters in Business Administration (MBA) students. Figure 1
presents the growing research in the area.
Journal of Learning for Development 11(1), 2024 2
Figure 1: Growth trend of microlearning publications
Source: McKee & Ntokos (2022)
Empirical research on the effectiveness of microlearning in higher education is limited
and has yielded mixed results, necessitating a systematic investigation (McKee & Ntokos, 2022).
This study focuses on exploring the potential of microlearning modules to reduce cognitive load
and improve learning outcomes in business schools. By evaluating the effectiveness of
microlearning modules, this research contributes to evidence-based practices in higher education
and enhances instructional methods in business schools. Specifically targeting MBA students,
the study aims to fill a research gap by examining the effectiveness of microlearning in MBA
education, an area with limited prior research. The recommendations inform the design and
implementation of microlearning modules in business school programmes, with the goal of
optimising their effectiveness.
Objectives and Hypotheses
This research aimed at investigating the instructional effectiveness, learning performance, and
cognitive load associated with microlearning; and the following hypotheses were proposed:
H1: The use of microlearning modules will significantly impact the level of student learning.
H2: Microlearning modules will significantly impact the participants’ reaction to the learning
module.
In this post-test control group design study, researchers randomly assigned MBA students
to either the experimental group, which received microlearning modules, or the control group
which received traditional teaching methods. The study collected data on learning performance
and student reaction through quizzes and surveys. The researchers analysed the collected data to
test the hypotheses and determine the effectiveness of microlearning modules compared to
traditional teaching methods.
This research has important implications for various groups involved, such as academic
institutions, educators and students. It investigates the impact of microlearning modules on
learning performance using cognitive load theory (Sweller, 2010). Firstly, it adds valuable
insights to the existing microlearning literature by providing evidence-based findings, which can
guide educators and designers in developing more effective teaching methods. Secondly, it
applies cognitive load theory to microlearning, allowing the development of teaching approaches
Journal of Learning for Development 11(1), 2024 3
that minimise cognitive load. This is beneficial for MBA students as it provides them with tools
to improve their learning performance and reduce cognitive burden. Lastly, the results of the
study can inform business school programmes, leading to improved teaching strategies and
enhanced learning experiences.
Literature Review
Microlearning is a technology-based instructional method that involves delivering learning
content in small, bite-sized modules. It has gained popularity in recent years due to its ability to
provide learners with short bursts of information that can be easily absorbed and retained (Siegle
et al., 2021). Microlearning modules are typically designed to be between three to five minutes in
length and can be delivered in a variety of formats, including videos, infographics, quizzes and
interactive simulations. The content of microlearning modules is typically focused on a specific
learning objective and can be accessed on-demand, making it a flexible and convenient learning
method (Simanjuntak & Haris, 2023).
Studies have shown that microlearning can be an effective instructional method in
various contexts, including corporate training and higher education (Kuzminska et al., 2022). In
corporate training, microlearning has been found to be an effective way to deliver job-specific
training and improve employee performance. In higher education, microlearning has been found
to be effective in enhancing student engagement and learning performance. A study by Pappas
(2017) found that microlearning modules increased student engagement and improved learning
outcomes in a university setting. The study also found that microlearning modules can help
students retain information better and apply it more effectively.
From a cognitive load theory (Sweller, 2010) perspective, microlearning is beneficial
because it reduces cognitive overload by breaking down complex information into smaller, more
manageable pieces (Zhu, 2022). This allows learners to process the information more effectively
and retain it better. In summary, the literature suggests that microlearning is an effective
instructional method that can enhance learning outcomes, improve retention and reduce cognitive
load (Rajaram, 2020). Its popularity is increasing due to its flexibility, convenience and ability to
provide learners with on-demand access to learning content.
Microlearning and Cognitive Load Theory
Cognitive Load Theory (CLT) is a well-established and widely recognised theory of learning that
centres around the crucial role of cognitive load in the learning process. CLT posits that
cognitive load pertains to the mental effort required for processing information in working
memory during learning endeavours (Zheng & Gardner, 2019). CLT identifies three distinct
types of cognitive load: intrinsic, extraneous and germane. Intrinsic cognitive load characterises
the inherent complexity of the learning material itself. Extraneous cognitive load is attributable
to instructional design or delivery factors that may impede learning. Conversely, germane
cognitive load directly pertains to the learning process and facilitates knowledge acquisition
(DeLeeuw & Mayer, 2008). The overarching aim of CLT is to optimise cognitive load to
enhance learning outcomes.
Instructional designers play a pivotal role in achieving this objective by minimising
extraneous cognitive load, effectively managing intrinsic cognitive load and promoting an
increase in germane cognitive load (Mayer & Moreno, 2010). Numerous studies have
demonstrated the effective application of CLT across diverse learning contexts. For instance,
Sweller et al., (2011) established that CLT principles can significantly improve learning
Journal of Learning for Development 11(1), 2024 4
outcomes in higher education and online learning environments. Moreover, CLT has exhibited
efficacy in corporate training settings. Sitzmann and Ely (2011) discovered that integrating CLT
principles into the design of training materials resulted in enhanced learning outcomes and
increased transfer of acquired knowledge to job-related tasks.
Regarding microlearning, CLT suggests that employing bite-sized learning modules can
effectively reduce extraneous cognitive load by breaking down complex information into
smaller, more manageable segments (Mayer & Moreno, 2010). This approach aids learners in
processing information more efficiently and retaining it more effectively. Existing literature
substantiates CLT as an effective theory of learning with broad applicability across various
contexts for optimising cognitive load and improving learning outcomes. Specifically, within the
microlearning domain, CLT advocates the use of compact learning modules as a viable strategy
for reducing cognitive load and enhancing learning performance (Olivier, 2021).
Microlearning and Learning Performance
The efficacy of microlearning in enhancing learning performance has been extensively
investigated, with multiple studies reporting positive outcomes. For instance, Max et al. (2018)
conducted a randomised controlled trial to examine the impact of microlearning on medical
students and found that those who received microlearning modules exhibited significantly
superior learning outcomes compared to those who received traditional lecture-based instruction.
Similarly, Eden et al. (2020) employed a quasi-experimental design to investigate the
effects of microlearning on computer science students. The study revealed that students exposed
to microlearning modules achieved significantly higher scores on the final exam than their
counterparts who underwent traditional lecture-based instruction.
Additional research has explored the effectiveness of microlearning in workplace
settings. Govender and Madden (2020) conducted a study within a retail organisation,
demonstrating that employees who received microlearning modules displayed significantly
enhanced job performance, when compared to those who underwent traditional training.
Likewise, Emerson and Berge (2018) conducted a randomised controlled trial to assess the
impact of microlearning on information retention in the workplace. The results indicated that
employees exposed to microlearning modules exhibited significantly superior retention of
information in comparison to those who received traditional training.
Collectively, the literature supports the effectiveness of microlearning as an instructional
approach for improving learning outcomes across various domains, encompassing educational
and workplace contexts alike. By deconstructing complex information into smaller, manageable
units, microlearning enables learners to process and retain information more effectively,
consequently leading to enhanced learning performance (Kuzminska et al., 2022).
Microlearning and Learning Context
Microlearning has been widely researched in various contexts, including educational and
workplace settings, and has been found to be effective in improving learning outcomes. Here are
a few examples of previous research on microlearning:
Educational context: A study by Aleassa et al. (2020) investigated the effectiveness of
microlearning in improving the knowledge and skills of nursing students. The study used a
randomised controlled trial design and found that students who received microlearning modules
performed significantly better on a post-test than those who received traditional instruction.
Journal of Learning for Development 11(1), 2024 5
Workplace context: A study by Lockee (2021) examined the effectiveness of
microlearning in improving the performance of salespeople in a pharmaceutical company. The
study used a quasi-experimental design and found that salespeople who received microlearning
modules had significantly higher sales performance than those who received traditional training.
Language learning context: A study by Wang et al. (2020) investigated the
effectiveness of microlearning in improving the vocabulary acquisition of English language
learners. The study used a quasi-experimental design and found that learners who received
microlearning modules had significantly better vocabulary acquisition than those who received
traditional instruction.
Professional development context: A study by Hsu et al. (2021) explored the
effectiveness of microlearning in improving the professional development of medical
professionals. The study used a quasi-experimental design and found that professionals who
received microlearning modules had significantly higher self-efficacy and motivation than those
who received traditional training.
Microlearning has gained significant attention as a technology-driven method of
instruction that has the potential to improve learning outcomes. Studies suggest that
microlearning consistently produces positive effects on student and employee performance and
satisfaction. This effectiveness can be explained by the cognitive load theory, which
acknowledges the limited cognitive resources available to learners and the negative impact of
excessive cognitive load on the learning process (Sweller, 2010). By providing information in
small, manageable chunks, microlearning effectively reduces cognitive load, thereby facilitating
optimal learning (Ghafar et al., 2023). However, the specific application of microlearning in
business school programmes has not been extensively explored. Further research is needed to
uncover the potential benefits and implications of microlearning in this context, allowing for the
development of tailored microlearning approaches that meet the unique needs of business school
students. Such research has the potential to enhance learning experiences and improve
educational outcomes in business school programmes.
Methods
The research design employed in this study utilised a post-test control group design comprising
two groups: an experimental group and a control group. This design is commonly employed in
experimental research to establish the causal relationship between an intervention and an
outcome variable. It enables researchers to control for extraneous variables that may impact the
outcome variable, ensuring the study's internal validity. The experimental group in this study
received a microlearning module, while the control group received a document-based version of
the same module. Upon completing the module, participants from both groups took a quiz
designed to evaluate their learning performance. The quiz consisted of questions covering the
content presented in the microlearning module.
Participants
In order to recruit the participants for this study, the researchers approached colleges in
Bangalore, India. The final set of participants belonged to a b-school and were in the first year of
their two-year MBA programme. Participation was not made mandatory and consent was sought
prior to the study. One-hundred and four students agreed to be a part of the study. To ensure that
the students were at the same level with regards to their knowledge, the participation was limited
Journal of Learning for Development 11(1), 2024 6
to students of a particular course. Approximately 18% of the students were male and the students
belonged to the age group of 21 to 26 years.
Materials and Instruments
The module selected for this study focused on the topic of the Global Mobility Framework,
which was unfamiliar to the participants. Both the regular and microlearning modules used in the
study were prepared by the same lecturer and administered to both groups simultaneously. The
control group received a research article on the topic and were instructed to read it and respond
to the quiz and reaction survey. In contrast, the experimental group received a microlearning
module created using the 7taps application. The 7taps microlearning app is a platform designed
to deliver bite-sized learning content to users, making learning more accessible and engaging.
The app allows the creation of short, focused lessons or modules that are easy to digest and can
be consumed on-the-go.
Upon completing the module, participants were asked to answer quiz questions and
provide responses to the reaction survey, both of which were designed using the Google Forms
platform. The microlearning module presented the contents of the research article in the form of
points and included quizzes and challenges at periodic intervals to test the participant’s level of
understanding
The learning outcomes were measured as per the Kirkpatrick (1959) model. The first
level of the Kirpatrick model suggests measuring the reaction of the participants. To measure
participants' reaction to the programme, Brown's (2005) instrument was employed. This
instrument assessed overall reaction, enjoyment and perceived relevance, consisting of seven
items rated on a five-point scale. The instrument demonstrated high reliability, with a Cronbach's
alpha score of 0.92. This was established through a pilot study. Sample items included
statements such as "The lecture was relevant to my education" and "The lecture provided useful
examples and illustrations."
The second level of the Kirkpatrick model refers to the knowledge gained or the level of
learning. Learning outcomes were evaluated through a post-test comprised of ten multiple-choice
questions. Each correct answer carried a value of one point, and no penalty was imposed for
incorrect responses. Participants were allowed to attempt the test only once. The test was
administered to both groups in person.
Procedure
The participants were invited to voluntarily participate in the study and were assured that their
test results would not be used in evaluations. After obtaining informed consent, 104 students
were finally chosen for the study. The students were then randomly assigned to two groups. The
control group was comprised of 52 students and the experimental group contained 52 students.
Both groups received the same module on the Global Mobility Framework but in
different formats. The control group received a research article, while the experimental group
received a microlearning module designed on the 7taps application.
Both the groups were asked to complete a quiz and a reaction survey questionnaire. The
quiz measured learning performance and consisted of multiple-choice questions. The reaction
survey questionnaire, developed by Brown (2005), measured the overall reaction to the module,
level of enjoyment and perception of its relevance. The survey used a five-point Likert scale and
consisted of seven items. Both the quiz and survey were administered on the Google Forms
platform.
Journal of Learning for Development 11(1), 2024 7
Data obtained from the quiz and survey were analysed using statistical software to
compare the performance of the two groups. The analysis included descriptive statistics such as
mean and standard deviation, and inferential statistics such as t-test and effect size calculations.
The significance level was set at p < 0.05.
Results
The objective of the study was to evaluate the effectiveness of a microlearning module in the
context of higher education. The participants were MBA students in their first year of the
programme. The researchers chose a post-test control group design to assess the effectiveness of
the module. This section presents the analysis of the collected data. Initially, the researchers
analysed the distribution of the data using descriptive statistics, and the results are shown in
Table 1.
Table 1: Descriptive Statistics of the Variables
Variable
Mean
Std. Deviation
Skewness
Kurtosis
Reac_tech
4.028
.8604
-1.096
1.191
Reac_enj
4.038
.8086
-.857
1.119
Reac_rel
4.072
.7772
-.704
.299
Reac
4.044
.7314
-1.096
1.986
Learn
6.14
1.037
-1.412
2.341
The mean score for the reaction (Reac) was 4.04, and the mean scores for the sub-
dimensions of (Reac_rel) relevance, (Reac_enj) enjoyment and (Reac_tech) technology were
also greater than 4. The average score on the test taken after the module was 6.14. This suggests
that the accuracy rate for the test was approximately 61%. This score represents the level of
learning. The skewness and kurtosis values were within the limits of +3 and -3, indicating that
the data could be treated as normally distributed and that parametric tests could be used for the
analysis (Kline, 2005). A correlation analysis was used to examine the relationship between the
variables of reaction, learning and microlearning. The correlation matrix is presented in Table 2.
Table 2: Correlation Matrix
Microlearn
Rt
Re
Rr
R
Test
Microlearn
1
Reac_tech
.251*
1
Reac_enj
.239*
.694**
1
Reac_rel
.155
.636**
.722**
1
Reac
.249*
.916**
.885**
.852**
1
Learn
.456**
.195*
.161
.089
.176
1
The study found a significant and positive correlation (r = 0.456) between the use of the
microlearning module and learning performance. Furthermore, the participants' reaction to the
Journal of Learning for Development 11(1), 2024 8
module was also significantly and positively related to the use of the microlearning module (r =
0.25). The dimensions of reaction related to technology used (r = 0.25) and enjoyment (r = 0.24)
were also significantly and positively related to the use of the microlearning module. However,
there was no significant relationship found between microlearning and the relevance dimension.
To determine if the participants who received the microlearning module scored
significantly higher than those who received the regular module, an independent sample t-test
was conducted. Additionally, an independent sample t-test was used to compare the difference in
the reaction to the module. The results of these tests are presented in Table 3.
Table 3: Comparison of the Mean Scores
Microlearn
N
Mean
t
df
Sig.
Mean diff
Reac_tech
C
52
3.814
-2.617
102
0.01
-0.429
E
52
4.244
Reac_enj
C
52
3.846
-2.486
102
0.015
-0.385
E
52
4.231
Reac_rel
C
52
3.952
-1.589
102
0.115
-0.240
E
52
4.192
Reac
C
52
3.863
-2.598
102
0.011
-0.363
E
52
4.225
Learn
C
52
5.673
-5.180
102
0.000
-0.942
The findings support our research hypotheses.
H1: The use of microlearning modules can significantly impact the level of learning.
To test this hypothesis, an independent sample t-test was conducted. The results showed
that the experimental group (participants of the microlearning module) had a significantly higher
mean score (M = 6.6) than the control group (participants of the regular module) with a mean
score of 5.6 (p < 0.05). Therefore, the hypothesis was accepted.
H2: The use of microlearning modules significantly impacts the participants’ reaction
to the learning module.
The participants who used the microlearning module (mean = 4.22) reacted more
positively to the new learning strategy than those who used the regular module (mean = 3.8, p <
0.05). While a comparison of the mean scores for the dimensions of reaction suggests that the
microlearning module rated higher on the dimensions of enjoyment, relevance and technology,
the difference in the mean scores was only found to be significant for the dimensions of
enjoyment and technology.
Hence, there is statistical evidence to conclude that the use of a microlearning module
significantly improves the level of learning and the reaction of the participants to the module.
Discussion
The objective of the study was to evaluate the effectiveness of a microlearning module in the
learning performance of MBA students. To do so, the researchers used a post-test control group
design, where one group underwent the microlearning module and the other participated in a
regular self-learning module. The control group was provided with a document that they were
expected to read and then answer the questions in the test.
Journal of Learning for Development 11(1), 2024 9
The effectiveness of the tool was evaluated through reaction and learning, the first two
levels of the Kirkpatrick (1959) model. Reaction was measured through an instrument that was
made available to the students immediately after the programme and the students were asked to
rate the programme in terms of the level of enjoyment, reaction to the technology used and the
perception of relevance. On the dimensions of enjoyment and reaction to technology, the
students of the microlearning module rated the programme significantly higher than the students
of the regular module. On the dimension of relevance, although the students of the microlearning
module rated the programme higher, the difference was not found to be statistically significant.
Overall, the students of the experimental group reacted more positively to the microlearning
module. Thus, there is statistical evidence to conclude that participants are likely to react more
positively to a microlearning module.
The findings of the study indicate that microlearning can be a powerful teaching tool and
can significantly improve learning performance and satisfaction. The findings are in line with
many other studies on microlearning. In a study by Pascual et al. (2018), the researchers used
microlearning to train stroke patients and their caregivers through microlearning components of
flashcards and cheat sheets. The response from the patients and caregivers was overwhelmingly
positive. Similarly, Gross et al. (2019) studied the reaction of participants of a crew resource
management training programme and found that the experimental group rated the intervention
more than 50% higher on relevance and usefulness. However, Sichani et al. (2018) evaluated the
use of microlearning in lessons for medical students and found that the participants in the
microlearning module were extremely dissatisfied. This may be attributed to the fact that the
microlearning module was used as a standalone instructional technique and the absence of
additional supporting learning resources, like a lecture or online module, may have reduced the
effectiveness of the module. Furthermore, Sichani et al. (2018) also propose that since the
students were accustomed to traditional lecture-style classroom learning, the abrupt change to a
text- driven learning method may have been unsettling.
To evaluate the increase in knowledge or knowledge retention, the researchers of this
study conducted a test after the module. The students of the microlearning module scored
significantly higher than their counterparts in the regular module. Similarly, Mohammed et al.
(2018) revealed the effectiveness of microlearning modules, particularly for complex and
technical subjects, in improving learning outcomes. Schumacher and Ifenthaler (2018) also
contributed to this body of evidence by showing that microlearning modules were effective in
reducing cognitive load and enhancing learning outcomes when compared to traditional
classroom training. However, the authors acknowledged that the design and delivery of
microlearning modules played a significant role in their effectiveness.
Thus, the findings of the current study add to the empirical evidence of the effectiveness
of microlearning modules. While the findings of the study propose that microlearning is an
effective learning tool, the intervention planned for the study was meant to supplement
classroom teaching and the tool was found to be effective. However, in studies where the
microlearning module was the only teaching tool, statistical evidence for its effectiveness was
not found (Taylor & Hung, 2022).
The findings of the current study corroborate previous research, underscoring the
potential benefits of microlearning modules in improving learning outcomes and participant
reactions. Nonetheless, further research is warranted to investigate the optimal design and
delivery of microlearning modules in diverse educational contexts and for different topics.
Journal of Learning for Development 11(1), 2024 10
Implications of the Study
This section discusses the implications of the study, both theoretical and practical.
Theoretical Implications
The findings of the study demonstrate that employing microlearning modules effectively
enhances learning in higher education. Participants who received the microlearning module
outperformed the control group, which received a regular module, in the post-test. Moreover, the
participants who received the microlearning module displayed significantly higher levels of
enjoyment and positive responses to the training programme’s technology compared to those
who received the regular module.
Microlearning involves providing students with information in manageable, bite-sized
portions. The study confirms that microlearning is an effective learning tool, and students
generally have a positive reaction to microlearning modules. As a result of this experimental
study, the researchers propose a microlearning paradigm consisting of three stages:
Consumption, Conceptualisation, and Confirmation, each playing a vital role in the learning
process. The model is shown in Figure 2.
Figure 2: Three stage model of microlearning paradigm
Source: Own work
In the Consumption stage, learners assimilate the provided information. This stage
introduces students to new knowledge or ideas that they may not have encountered previously.
The information is presented in a condensed and understandable format, such as text, graphics,
audio or video. This stage is crucial as it establishes the foundation for learning and provides the
necessary information to proceed to the subsequent stage.
In the Conceptualisation stage, the microlearning module complements the main teaching
pedagogy. After acquiring the material, learners attempt to relate it to prior knowledge or apply it
to familiar situations. This stage is essential for learners to make meaningful connections with
the content and integrate new knowledge with existing knowledge. Activities like problem-
solving, introspection and practical application of knowledge contribute to the conceptualisation
stage.
The third stage, Confirmation, involves testing or evaluating the acquired knowledge to
identify any gaps and provide learners with an opportunity to review the subject matter. This
Journal of Learning for Development 11(1), 2024 11
phase assists students in solidifying their understanding and identifying areas that require further
study. Quizzes, questionnaires, and reflection exercises are examples of assessment methods
employed in the Confirmation stage. Confirmation is critical as it enables students to assess their
progress and identify areas where they may need additional assistance. Designing the
microlearning module with these three stages in mind can significantly enhance learning
effectiveness. This model has been proposed specifically for microlearning and differs from
other learning theories in this regard.
Implications for Practice
The findings of this study carry significant implications for the design of educational and training
programmes in higher education. The utilisation of microlearning modules yielded notable
improvements in both learning outcomes and participant reactions to the training programme.
Consequently, microlearning can be recommended as an effective instructional strategy in higher
education.
Furthermore, the results emphasise the importance of incorporating cognitive load theory
into instructional material design. By implementing microlearning modules, the cognitive load
experienced by learners is reduced, leading to enhanced learning and knowledge retention. These
findings provide educators and instructional designers with valuable insights to create more
effective and efficient learning materials tailored to learners' specific needs.
Moreover, the study demonstrates a positive correlation between the integration of
technology in educational settings and learner outcomes. Thus, educators should consider the
integration of technology into their teaching and learning activities to foster improved learning
and engagement.
Overall, this study highlights the paramount significance of evidence-based instructional
design practices in higher education. Educators and instructional designers are encouraged to
embrace microlearning and technology as a means to optimise the learning experience for their
students.
Microlearning possesses transformative potential in revolutionising educational
approaches by offering flexible and personalised learning experiences that enhance knowledge
retention and student engagement (McKee & Ntokos, 2022). As technology becomes
increasingly accessible, the utilisation of microlearning in education is anticipated to witness
rapid growth in the forthcoming years (Kuzminska et al., 2022). Educational institutions and
instructors ought to contemplate the incorporation of microlearning into their instructional
strategies, while maintaining a balance with other pedagogical methods. This holistic approach
will facilitate the provision of a comprehensive and effective learning experience that caters to
the diverse needs of students.
Study Limitations and Recommendations for Future Research
The present study acknowledges several limitations that warrant careful consideration. Firstly,
the relatively small sample size may restrict the generalisability of the findings. To enhance
external validity, future investigations could employ larger and more diverse samples.
Additionally, expanding the study duration would enable examination of the long-term impact of
microlearning on learning outcomes.
Secondly, the study focused exclusively on the Global Mobility Framework as the subject
matter and targeted first-year MBA students as participants. Caution should be exercised when
extending the findings to other contexts or topics. Future research endeavours could explore the
Journal of Learning for Development 11(1), 2024 12
efficacy of microlearning modules across various academic disciplines and among diverse
learner populations to ascertain the breadth of its impact.
Furthermore, the study solely examined the short-term effects of the microlearning
module, leaving the long-term sustainability of the benefits uncertain. Future investigations
could delve into the enduring effects of microlearning modules, providing a more comprehensive
understanding of their impact over time. This would involve assessing participant learning
outcomes beyond immediate post-module assessments.
Lastly, the study did not account for individual differences such as prior knowledge,
cognitive abilities, and learning styles, all of which potentially influence the effectiveness of
microlearning modules. Future studies should examine the intricate interplay between these
individual differences and the outcomes of microlearning modules, shedding light on the
nuanced factors at play. Considering these factors would allow for a more nuanced interpretation
of the findings and the development of tailored instructional approaches.
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Author Notes
https://orcid.org/ 0000-0001-9593-871X
https://orcid.org/0000-0003-4019-5132
https://orcid.org/0000-0002-1529-4297
Dr. Sathiyaseelan Balasundaram is an Associate Professor and Area Chair of Human
Resources. He holds an MBA from IIM Calcutta and a PhD in Management. He has over 30
years of HR experience, 24+ years in leadership roles and 5+ years in teaching and research. His
areas of interest are leadership, spirituality, and employee engagement. Email:
sathiyaseelan.b@christuniversity.in
Dr. Jain Mathew is the Dean of the School of Business and Management. He has more than 30
years of experience in Finance and Human Resources. Dr. Mathew has rich academic and
research expertise. He has supervised several MPhil and PhD scholars over the years. He has
delivered leadership sessions for academicians and management executives. His current area of
research and practice interest is the gamification of learning. Email:
jainmathew@christuniversity.in
Dr. Sridevi Nair is an Assistant Professor of Human Resources with a bachelor's degree from
IHM, Mumbai, a master's degree from Welingkar, Mumbai, and a doctorate from CHRIST
University. Before joining CHRIST University, Dr. Sridevi worked briefly with TISS before
starting her own company. She has also worked in the hospitality sector, with experience at the
Taj Mahal Palace and Tower, Mumbai; The Oberoi New Delhi and The Park Navi Mumbai. Dr.
Sridevi's research focuses on gamification, learning, mental health and well-being. Email:
sridevi.nair@res.christuniversity.in
Cite as: Balasundaram, S., & Mathew, J., & Nair, S. (2024). Microlearning and learning performance in
higher education: A post-test control group study. Journal of Learning for Development, 11(1), 1-
14.
