International Institute of
A Markov Chain Approach for Modelling Normally Distributed Online Assessment Time in a University Setting
Lugoma, Masikini; Ilunga, Masengo; Dudu, Violet Patricia; Bukanga, Amuli (South Africa)
https://doi.org/10.54808/IMSCI2025.01.25
ABSTRACT:
The Markov chain (MC) technique is applied to an online invigilated assessment
situation to predict the writing time in a typical university setting.
Different students' writing times cannot be determined accurately in
advance and are associated with randomness. This preliminary study simulates
data related to the time to download the question paper and the writing
time, from a normal distribution. The time variable is simulated to
have a reasonably good approximation of the real settings where most
students’ writing times are spread around the expected value, namely
the mean. Simulations are conducted based on the experience and knowledge
of researchers in the online teaching and learning environment. Computer
simulations demonstrate that the writing time estimates depicted a stable
convergence, thus giving clear insights for optimising online assessment
implementation. The findings showed that the average writing time of
a selected trial reaches a stable value at 1.498 hours (89 minutes)
within the confidence interval [0.6, 2.5], at 95%. Therefore, these
results offered a more realistic range of feasible times to guide academic
practitioners on the planning and implementation of invigilated online
assessments.
A Transdisciplinary Approach to Enhancing Online Engineering Education Through Learning Analytics
Lugoma, Masikini; Yende, Lethuxolo; Dikgwatlhe, Pule; Mkonde, Akhona; Thage, Rorisang; Maseko, Lucky; Chimwani, Ngonidzashe (South Africa)
https://doi.org/10.54808/IMSCI2025.01.142
ABSTRACT:
In the context of expanding digital education and persistent global
disparities in access, this study explores how learning analytics (LA)
can enhance teaching effectiveness and student success in open and distance
learning (ODeL) environments. Focusing on Mineral Exploitation IA, a
first-year engineering module offered in a South African university’s
Diploma in Mining Engineering program, the study exemplifies the use
of data-driven methodologies to address systemic educational challenges
such as low pass rates, high dropout rates, and poor learner retention.
This case study employs an interdisciplinary and mixed-methods research
design, integrating educational data mining (EDM), behavioral analytics,
and comparative analysis to assess student engagement, performance,
and demographic context. Drawing on data extracted from the institution’s
Moodle learning management system, the study examines how students interact
with online materials (e.g., video content, discussion forums), complete
assessments, and vary in performance across geographic and socioeconomic
boundaries.
Findings reveal that students from remote or under-resourced regions—primarily
in developing countries—face significant challenges in accessing digital
platforms, often due to infrastructural and technological limitations.
These constraints negatively impact their participation and performance,
highlighting the interdependence of technological, pedagogical, and
socio-economic systems in ODeL contexts.
Methodologically, the study aligns with an applied research paradigm,
while demonstrating adaptive methodological flexibility. It incorporates
a comparative framework that crosses disciplinary boundaries—drawing
from education, data science, development studies, and digital communication.
In doing so, it situates learning analytics not merely as a technical
tool, but as a transdisciplinary research instrument capable of responding
to context-specific educational realities.
The study recommends targeted pedagogical interventions, including the
integration of low-bandwidth, high-accessibility tools such as WhatsApp-based
academic support and e-tutoring. These interventions reflect a culturally
and technologically responsive design logic, emphasizing methodological
pragmatism rooted in lived student experiences.
By connecting data-informed research, methodological innovation, and
context-sensitive teaching practices, this study contributes to the
growing field of transdisciplinary education research. It argues for
a shift from content-centred instructional design toward learner-responsive,
equity-oriented strategies. It demonstrates how the thoughtful use of
learning analytics can foster inclusive and effective online learning
environments.
Agent-Based Modeling of Conceptual–Experiential Learning Balance: A Cybernetic Approach to Educational Systems
Ueno, Aya; Kikuchi, Takamasa; Yoshikawa, Atsushi (Japan)
https://doi.org/10.54808/IMSCI2025.01.67
ABSTRACT:
Educational systems exhibit complex cybernetic properties because of
dynamic feedback loops between conceptual and experiential learning
processes. This study introduces a novel cybernetic modeling framework
transforming Axelrod’s cultural dissemination model into an educational
agent-based system, revealing emergent learning behaviors previously
unobservable in traditional educational research.
Through 4,000 large-scale simulations encompassing 50-agent networks
across three performance tiers, we demonstrate that educational systems
function as adaptive cybernetic networks where learning propagation
follows information-theoretic principles. Our quantitative analysis
reveals striking non-linear dynamics: low-performing schools achieve
58.5% improvement under teacher-led conceptual learning (vs. 28.8% for
high-performing schools), whereas network topology affects the variability
in the speed of learning convergence.
The study establishes three cybernetic principles for educational systems:
(1) diversity-enhanced learning efficiency through heterogeneous agent
interactions, (2) feedback-driven convergence acceleration via teacher–student
coupling, and (3) emergent collective intelligence through strategic
network design. These findings provide quantitative evidence for adaptive
educational control systems and offer systematic design principles for
optimizing learning environments.
This interdisciplinary approach integrating systems science, cybernetics,
and educational theory could contribute to both theoretical understanding
of complex learning systems and practical educational policy frameworks
for the digital age. The methodology might lend broad applicability
to social informatics and organizational learning.
AI Disruptions in Higher Education: Evolutionary Change, Not Revolutionary Overthrow
Leon, Cristo; Lipuma, James; Rafla, Maximus (United States)
https://doi.org/10.54808/IMSCI2025.01.125
ABSTRACT:
This paper offered a systems-theoretical analysis of large language
models (LLMs) in the context of higher education. It began by first
clarifying the conceptual landscape, then introducing key definitions
to frame LLMs, not as revolutionary threats, but as evolutionary developments,
grounded in decades of natural language processing and machine learning.
Then, it examined how the integration of LLMs prompted institutions
to seek new forms of homeostasis, balancing innovation with stability
through adaptive regulatory feedback loops.
Next, the analysis explored intersections with broader concepts such
as agency, authorship, commodification, and cybernetic governance. It
argued that LLMs act as boundary objects whose meanings are negotiated
across educational, industrial, and policy domains. It then responded
to critiques framing LLMs as epistemically corrosive or ethically destabilizing
by emphasizing the role of institutional reflexivity in mitigating risks.
Finally, the study concluded that LLMs do not fundamentally disrupt
the mission of higher education; instead, they reveal its structural
inertia. Their integration highlights the need for recalibrated pedagogical
and assessment frameworks on learning processes. Instead of resisting
technological change, institutions should evolve into feedback-responsive
ecosystems that uphold human-centered values while embracing permissible
forms of automation to enhance, rather than displace, intellectual and
creative engagement.
AI-Driven Grading and Moderation for Collaborative Projects in Computer Science Education
Yu, Songmei; Zagula, Andrew (United States)
https://doi.org/10.54808/IMSCI2025.01.6
ABSTRACT:
Collaborative group projects are integral to computer science education,
fostering teamwork, problem-solving, and industry-relevant skills. However,
assessing individual contributions within group settings is a long-standing
challenge. Traditional assessment strategies, such as equal distribution
of grades or subjective peer assessments, fall short in terms of fairness,
objectivity, and scalability, especially in large classrooms. This paper
introduces a semi-automated, AI-assisted grading system that evaluates
both project quality and individual effort using repository mining,
communication analytics, and machine learning models. The system comprises
modules for project evaluation, contribution analysis, and grade computation,
integrating seamlessly with platforms like GitHub. A pilot deployment
in a senior-level course demonstrated high alignment with instructor
assessments, increased student satisfaction, and reduced instructor
grading effort. We conclude by discussing implementation considerations,
ethical implications, and proposed enhancements to broaden applicability.
Education, Research, and Methodology: A Transdisciplinary Cybernetic Whole
Callaos, Nagib; Leon, Cristo (United States)
https://doi.org/10.54808/IMSCI2025.01.87
ABSTRACT:
In this article, we explore the implicit yet foundational cybernetic
relationships among three of the most transdisciplinary conceptual constructs:
Education, Research, and Methodology.
It argues that these three domains are not merely interconnected but
form a Cybernetic Triad whose interactions generate
emergent properties, such as deeper understanding, creativity, and systemic
synergy, when made explicit. By using a top-down approach, the article
models these relationships through feedback loops and mutual influence,
highlighting how each domain serves as both input and output to the
others. The discussion incorporates examples from various disciplines,
distinguishing between systematic (closed) and systemic
(open) methodologies, and proposing a knowledge framework that
includes not just "know-what" and "know-how" but also "know-why", "know-when",
and "know-where". It concludes that engaging with this triadic system
reflexively enhances individual and collective effectiveness, particularly
in transdisciplinary contexts. In this context, a gap is identified
in regard to making transdisciplinary communication a practical skill
within academia. Consequently, a structured model is proposed to embed
it systematically into education, research, and methodology, recommending
curricular, project, and institutional integration for greater impact.
Enhancing Educational Effectiveness Through Transdisciplinary Practice: The ETCOP Model
Oberer, Birgit; Erkollar, Alptekin; Kropfberger, Andreas (Austria)
https://doi.org/10.54808/IMSCI2025.01.152
ABSTRACT:
This paper presents the ETCOP Model, a transdisciplinary framework designed
to enhance educational effectiveness through stakeholder co-design,
critical reflexivity, and impact-oriented curriculum development. Developed
by the ETCOP Institute, the model integrates educational science, digital
innovation, and ethics, and has been applied across diverse domains
including digital transformation training for SMEs, AI literacy in teacher
education, and entrepreneurship education in secondary schools. Anchored
in design-based research and structured around five core principles,
the model promotes the use of open educational resources, modular learning
architectures, and continuous, mixed-methods evaluation.
Empirical findings from internal and external assessments indicate increased
learner engagement, competence acquisition, and evidence of institutional
transformation. By operationalizing transdisciplinarity at the levels
of pedagogy, governance, and evaluation, the ETCOP Model contributes
a scalable, ethically grounded approach to educational design. The paper
advances the field of transdisciplinary educational research by offering
a practice-based model that supports systemic innovation and alignment
with evolving societal and policy demands.
From Instruction to Interaction: Reflexive Learning Design for Cross-Generational Engagement at the Workplace
Nurani, Gita Aulia; Lee, Ya-Hui (Taiwan)
https://doi.org/10.54808/IMSCI2025.01.148
ABSTRACT:
As workforces grow increasingly age-diverse, designing learning environments
that foster meaningful engagement across generations has become a practical
necessity and a conceptual challenge. This paper argues for a shift
from traditional, hierarchical models of instruction toward reflexive,
interaction-driven approaches to learning design. The study repositions
intergenerational learning as a relational and communicative process,
where learners are not passive recipients of knowledge but active participants
in co-constructing meaning. Reflexivity, understood as a continuous,
critical awareness of one's position, assumptions, and influence within
the learning system. It is presented as a core methodological and pedagogical
tool for designing inclusive, adaptive, and reciprocal learning experiences.
Rather than viewing generational differences as barriers, this perspective
embraces them as sources of diversity that enrich collaborative inquiry
and innovation. The paper explores key design principles such as dialogic
learning, emotional safety, shared agency, and mutual respect, emphasizing
the importance of feedback loops and non-linear knowledge exchange.
By moving beyond age-based stereotypes and fixed instructional models,
reflexive learning design opens possibilities for sustaining lifelong
learning and fostering more human-centered organizational cultures.
Ultimately, this work advocates for intergenerational learning environments
that are educational and transformative.
Future-Ready Through Service-Learning: Building Twenty-First Century Skills in an Undergraduate Setting
Adarlo, Genejane; Petalio, Syra Marie Norin (Philippines)
https://doi.org/10.54808/IMSCI2025.01.47
ABSTRACT:
This mixed-methods study investigated whether service-learning facilitates
twenty-first century skills among undergraduate students. It examined
how service-learning specifically aids in developing knowledge application,
creative problem-solving, critical thinking, collaboration, and self-reflection.
Twelve students from Ateneo de Manila University were closely followed
up as they participated in service-learning projects in poor urban communities
in the Philippines. Responses from the Service-Learning Outcomes Measurement
Scale provided quantitative data, whereas the students’ reflective essays
offered qualitative insights. The Wilcoxon Signed-Rank Test showed significant
improvements in knowledge application (p = .029, rrb = 0.69),
creative problem-solving (p = .012, rrb = 0.79), and self-reflection
(p = .003, rrb = 1.00). No significant changes were observed
in critical thinking (p = .051, rrb = 0.60) or collaborative
skills (p = .624, rrb = -0.09). Thematic analysis guided
by Kolb's Experiential Learning Theory revealed that navigating the
unknown, making sense of reality, conceptualizing solutions, experimenting
with ideas, and internalizing experiences contributed to the development
of twenty-first century skills. This study recommends incorporating
explicit prompts to promote critical thinking, and structured group
activities to enhance collaboration. The findings indicate that service-learning
promotes twenty-first century skills through concrete experience, reflective
observation, abstract conceptualization, and active experimentation.
GIS in Aquatic Animal Health Surveillance: A Transdisciplinary eLearning Initiative Integrating Education, Research, and Methodology (The Aquae Strength Project)
Franzago, Eleonora; Macario, Rodrigo; Mazzucato, Matteo; Sbettega, Federica; Cassani, Manuela; Ricaldi, Guido; Bissoli, Francesco; Nadin, Anna; Personeni, Fabrizio; Dalla Pozza, Manuela; Manca, Grazia; Ferré, Nicola (Italy)
https://doi.org/10.54808/IMSCI2025.01.108
ABSTRACT:
The Aquae Strength initiative is an international cooperation project
between countries, whose activities include the realization of an e-learning
course on Geographic Information Systems (GIS) and veterinary epidemiological
surveillance in aquaculture. The course is an example of a synergetic
relationship between training, research and methodological innovation
that makes the knowledge, acquired by experts during the project, available
to international learners through user-friendly technology. The advanced
training proposal is not based on pure theory, but integrates practical
applications that learners are likely to encounter in their daily work.
The initiative contributes to a future-ready veterinary workforce equipped
with the tools to navigate both digital and ecological complexity.
Impact of Artificial Intelligence in Higher Education
Ilyas, Mohammad (United States)
https://doi.org/10.54808/IMSCI2025.01.1
ABSTRACT:
Artificial Intelligence (AI) is a rapidly growing field and deals with
simulating human behaviors and decision making with the use of computer.
AI is rapidly becoming a transformative force in almost all aspects
of our society. Higher education is no exception, and AI is reshaping
the landscape of teaching, learning, research, and management in higher
education institutions around the world. As the demands of the digital
environment around us continue to evolve, higher education institutions
are adapting to use AI as a tool for higher efficiency and increased
productivity. In this paper, we discuss the scope of AI’s impact on
higher education. The impact of AI is divided into three sections; aspects
of AI that are perceived to be positive, aspects of AI that are perceived
to be negative, and aspects of AI that are perceived to be neutral.
Integrating English Debate and Public Speaking Tournaments in Universities' Curricula: Critical Comparison Between the Greek and the Emirati Cases
Kyriakidis, Kleanthis; Al Khatib, Soulafa; Adourian, Sevan; Koikas, Evgenia (United Arab Emirates)
https://doi.org/10.54808/IMSCI2025.01.59
ABSTRACT:
This comparative study explores the integration of English debate and
public speaking tournaments, particularly those involving original oratory
and impromptu formats into the fabric of university education in Greece
and the United Arab Emirates (UAE). In recent years, with the rise of
artificial intelligence (AI) in academic and workplace settings, there
has been a noticeable resurgence of interest in inherently human skills
such as persuasive communication, sound reasoning, quick thinking, and
language mastery. These are the sorts of abilities that, arguably, no
algorithm can truly replicate.
Using a comparative approach, the paper aims to shed light on how such
activities can refine argumentation techniques, foster civil discourse,
and enhance intercultural understanding. To set the stage, it first
outlines the broader educational and developmental benefits of debating
and public speaking, drawing on literature from fields such as communication
studies and educational psychology. After that, it shifts toward reviewing
international examples of best practices, before zooming in on how things
are playing out specifically in Greece and the United Arab Emirates
(UAE).
While both nations have shown a fair degree of enthusiasm and have taken
steps, albeit scattered, to promote rhetorical engagement at the university
level, there is still a noticeable lack of coordination at the national
scale. Without clear policies or collaboration among universities, the
implementation remains somewhat patchy.
In response to this, the study puts forward a more structured proposal:
one that encourages the adoption of unified frameworks in higher education.
This includes offering policy-driven incentives, hosting nationwide
tournaments, establishing standard evaluation criteria, and leveraging
AI tools to aid in training and feedback. The final takeaway? There
is a real opportunity here—not just to meet educational goals at home,
but to equip students with the kinds of skills that make them effective
communicators and global citizens. At its core, the research advocates
for a renewed focus on rhetorical education, especially in contexts
where English is not the native tongue and where linguistic diversity
presents both challenges and opportunities.
Key Aspects for a Secure Migration of Databases to the Cloud: Challenges and Solutions
Pérez-Castillo, Yadira-Jazmín; Orantes-Jiménez, Sandra-Dinora; Aguirre-Anaya, Eleazar; Aguilar-Jáuregui, María-Elena (Mexico)
https://doi.org/10.54808/IMSCI2025.01.12
ABSTRACT:
In the digital age, migrating databases to the cloud has become an essential
strategy for organizations seeking greater flexibility, scalability,
and operational efficiency. However, this process poses significant
challenges related to information security, including cyberattacks,
regulatory compliance, data loss, and access control. This article explores
the main challenges associated with migrating and managing databases
in the cloud, providing an analysis of the most common risks and their
impact on protecting critical data. In addition, practical solutions
such as encryption, multi-factor authentication, and disaster recovery
strategies are presented to enable organizations to mitigate risks and
ensure information confidentiality, integrity, and availability. Finally,
the article highlights the benefits of adopting good security practices
during migration, promoting a smooth transition to the cloud while safeguarding
sensitive data. Organizations can achieve a more secure and efficient
cloud environment by addressing these challenges proactively.
Machine Learning for Analysing Student Performance in Selected Engineering Mining-Based Modules: The Use of Hierarchical Agglomerative Clustering
Ilunga, Masengo; Mkonde, Akhona; Dube, Zakithi (South Africa)
https://doi.org/10.54808/IMSCI2025.01.16
ABSTRACT:
The hierarchical clustering, as an unsupervised machine learning algorithm,
is employed to capture the different groups that emerge from students’
grades compiled of different assessments for a given course. No prior
classification is given to machine learning. In the clustering analysis
carried out, the algorithm groups without prior knowledge of classification
of students, in two courses or modules of level 1 and level 2 respectively,
taught in the Department of Mining Minerals and Geomatics Engineering
at the University of South Africa. For both modules, the findings showed
three distinct main categories of students, however the sub-clusters
increased as the number of students increased. This preliminary research
demonstrated methodologically a baseline for comparing and complementing
the university instructional practice for student performance, based
on the different classes, mainly fail or pass. This algorithm could
be suggested as a guiding tool for academic decision-making team in
categorising students’ performance based solely on assessment outcomes.
It is suggested that a set of differentiated strategies should be established
to respond to the characteristics of each cluster for the attainment
of student’s success, especially for future students.
Motivated to Serve, Driven to Learn: Exploring the Relationship Between Student Motivation and Meaning-Making in Service-Learning
Abenir, Mark Anthony; Adarlo, Genejane (Philippines)
https://doi.org/10.54808/IMSCI2025.01.39
ABSTRACT:
Service-learning integrates classroom instruction with community engagement
and fosters meaning-making through real-world applications. The outcomes
vary among students due to differences in motivation, which can influence
their engagement and perceived benefits. Despite substantial research
on service-learning outcomes, the impact of student motivation remains
understudied. Based on Self-Determination and Transformative Learning
Theories, this study examined how student motivation affects the quality
of service-learning experiences. This study involved 34 undergraduate
students from Ateneo de Manila University, who completed a survey containing
items from the Academic Motivation Scale and Service-Learning Experience
Questionnaire. Multiple linear regression analysis revealed that amotivation
had a negative effect (β = −0.36, p = .026), and intrinsic
motivation had a positive effect (β = 0.57, p = .004) on the quality
of the service-learning experience, explaining 36% of the variance (p
= .003). Amotivated students struggled to find meaning, whereas intrinsically
motivated students reported deeper engagement. These findings provide
insight into the role of motivation in fostering meaningful community
engagement through service-learning.
Reflexivity as a Compass: The European AI Act and Its Implications for U.S. Higher Education Institutions
Cowin, Jasmin (United States)
https://doi.org/10.54808/IMSCI2025.01.102
ABSTRACT:
This narrative analysis explores how the European Union’s Artificial
Intelligence Act (EU AI Act) holds the potential to shape institutional
discourse of U.S. higher education. As artificial intelligence becomes
deeply embedded in university operations, from admissions and instruction
to monitoring and assessment, it raises urgent questions about institutional
purpose, power, and accountability. Drawing on Kantian ethics, the analysis
highlights the tension between external regulatory structures and internal
moral reasoning. The EU AI Act (Regulation 2024/1689), with its risk-based
classification of AI systems and its extraterritorial provisions, introduces
binding obligations for transparency, oversight, and ethical alignment
in educational applications. These obligations challenge existing norms
of voluntary governance in U.S. academia and signal a shift toward anticipatory
and structured forms of technological oversight. Within this landscape,
reflexivity is positioned not as a rhetorical gesture but as a necessary
institutional capacity. It refers to the ongoing process of self-examination
that engages with embedded assumptions, power dynamics, and the normative
dimensions of algorithmic systems. This analysis argues that reflexivity
must guide institutional responses to AI governance if universities
are to align technological adoption with their academic values and global
responsibilities.
Required General Education Program Evaluation: Bridging the Gap Between Educators and Administrators
Lipuma, James; Leon, Cristo; Reich, Jeremy (United States)
https://doi.org/10.54808/IMSCI2025.01.137
ABSTRACT:
This paper reported on the development of an online data-gathering system
for the programmatic assessment of General Education Programs (GEP)
at a US public polytechnic university. The article began with a brief
introduction to the study area and population. It then presents the
findings of a literature review that underpinned the study, including
research on faculty buy-in for programmatic evaluation. The primary
findings highlighted a significant disconnect between those managing
the data-reporting process for accreditation agencies and those charged
with teaching and assessing students who are required to provide the
data. Next, the study methods and procedures utilized for developing
the online data-gathering system were described. A group of educators
was engaged in a collaborative co-design process to develop the necessary
data-gathering instrument and to test various tools during feedback
sessions. For this pilot test, the GEP outcome being examined was 'Oral
Communication,' which utilized a four-point Likert-style scale for indicators.
The results of the pilot test are presented, along with user observations
and comments. The article concludes with a series of findings and implications
for how these methods can be applied to other GEPs and, more broadly,
to any program evaluation needs.
Researching Ourselves
Horne, Jeremy (Mexico)
https://doi.org/10.54808/IMSCI2025.01.114
ABSTRACT:
Education, research, and methodologies form an organic unit that is
the essence of human identity. Education is the object (which also is
a process); research is the domain of process in which knowledge is
to be found; methodology is the manner in which a person is to bring
information into the mind that is to be transformed into knowledge.
Education etymologically stems from conducting or leading, that is knowing
oneself. It is transdisciplinary, recursive, and second-order cybernetic,
all aspects of organicity, or life, itself. It is not enough to realize
these things; we need to apprehend the context in which these are set,
i.e., our universe, itself, conscious and organic, as we are. Did not
God make us in his image, as the Biblical saying goes? Along the way,
we need to be cognizant of innate processes in the universe, such as
the most fundamental law known since ancient times and expressed by
GWF Hegel, the unity of opposites, as well as organicity, itself (as
opposed to static entities). These factors implicitly describe transdisciplinary
access to knowledge. Anatomically, the Universe is both deductive and
inductive, the former as descending from the outer limits of our knowledge
to the center (ourselves), the latter inductively, reaching outward
to find what is there to be known. These "ends", from the infinitesimal
to the infinite, describe the domain of research. Our method of investigation
is contradiction, employing the unity of opposites, the most extreme
form of critical thinking. Permeating the Universe is Plato’s realm
of the ideal, consciousness, the transcendental, represented by the
words of Buddha, Christ, Mahoma, Aristotle, and Plato, among others.
Truth characterizes the Creator, and so is the object of search in education,
and so it is, we must realize authenticity, both in ourselves and the
world around us. Training as deduction, validates it through virtue
(internalizing behavior exhibiting our values, or meaning). Truth, itself
is a function of order. A disordered identity compromises a person’s
being, and conversely. Two methods of identity location are neurocorrelation
and deep personal questioning (as with an authentic method of self-discovery).
I will merely reference the former and describe in more detail the latter,
a representative being Authentic Systems, showing specifically why it
is educative.
The Self-Aware, Reflective Learner: Fostering Metacognitive Awareness and Reflexivity in Undergraduates Through Service-Learning
Adarlo, Genejane (Philippines)
https://doi.org/10.54808/IMSCI2025.01.78
ABSTRACT:
This article explores how service-learning in higher education fosters
metacognitive awareness and reflexivity among students by positioning
education, methodology, and research as a mutually reinforcing triad.
It defines metacognitive awareness as students’ ability to regulate
their own thinking, and reflexivity as critical self-examination shaped
by social contexts, both seen as essential twenty-first century skills.
Service-learning is presented as a high-impact educational practice
that challenges students to apply academic knowledge in real-world settings,
confront ill-structured problems, and reflect deeply on their experiences
of community engagement. This discussion emphasizes the central role
of reflection in cultivating metacognitive awareness and reflexivity
by using various strategies. This article also highlights how artificial
intelligence can support reflection by offering personalized feedback
while underscoring irreplaceable aspects of learning. Finally, it examines
how service-learning must be culturally contextualized through transdisciplinary
communication, especially in Asian settings, to resonate with local
values and facilitate collective sense-making. Together, these aspects
illustrate how thoughtfully designed service-learning can nurture self-aware,
reflective learners.
Use of Support Vector Machines for Modelling Student Performance: Case of a Graduate Attribute Based-Assessed Mining Design Engineering Module
Maseko, Lucky; Ilunga, Masengo; Maduna, Lusiwe; Thage, Rorisang (South Africa)
https://doi.org/10.54808/IMSCI2025.01.30
ABSTRACT:
The modelling capability of 2 variants of the support vector machines
(SVM), namely the linear kernel SVM and radial basis function (RBF)
SVM, is compared preliminarily for classification of assessment scores,
in an online setting for teaching and learning. The 2-categorical class
is used for the label, whereas assessment scores constitute the features.
The models have been tested on the Mine Design module, which includes
all engineering graduate attributes and forms part of the Advanced Diploma
in Mining Engineering qualification. This qualification is taught in
universities of technology and the University of South Africa. The findings
revealed that the RBF kernel SVM outperformed the linear kernel SVM
in terms of model accuracy, precision, recall, F1-score, and Receiver
Operating Characteristic curve-Area Under Curve (ROC-AUC). Additionally,
the RBF SVM performed better than the linear SVM. The former could be
preferred over the latter for classifying student results. This research
contributes to the growing arena of learning analytics in engineering
education.
Using Workbook Templates to Improve Teaching
Hendel, Russell Jay (United States)
https://doi.org/10.54808/IMSCI2025.01.54
ABSTRACT:
The paper advocates the use of templates to significantly improve pedagogy.
By templates, also sometimes referred to as a workbook approach, the
intent is on providing model solutions with key words or phrases omitted;
the student, after training in the use of the template, fills in these
omitted phrases or words when attacking a new problem. However, to accomplish
pedagogic improvement, templates must be accompanied by higher-order
instructional strategies including contrasts, decisions, evaluations,
and componential analysis. The theory presented is fully consistent
with a variety of educational hierarchies such as those of Bloom, Anderson,
Van Hiele, and Marzano. The theory is also consistent with the four
educational pillars of Hendel. The theory is supported by literature;
illustrations are provided from statistics and literary analysis.
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