Track Progress Research Articles

Interpreting Student Performance through Predictive Learning Analytics

In today's information-rich world, accurately predicting student performance is crucial for institutions seeking to support at-risk students and ensure their success, but this task can be challenging. Learning analytics (LA) can help identify students who are struggling and provide them with the tools and opportunities they need to succeed, benefiting both students and institutions. However, data integration from various sources can be challenging in learning analytics, causing educators to struggle with managing and keeping track of students' progress and dropouts. The goal of this project is to generate insights into student performance through the application of machine learning methods, including Random Forest (RF), Artificial Neural Network (ANN), and Support Vector Machine (SVM). These methods were used to predict students' future results and the likelihood of students' dropout based on predictive learning analytics. RF, ANN, and SVM predictive models were constructed to predict students' future final results and dropout. The dataset from The Open University is used in this study, which consists of information from multiple aspects including data about courses, student registration, results, and their interactions with virtual learning environment. RF, ANN, and SVM models were constructed to predict students' future final results based on their learning behaviour. The performance of the models is evaluated based on accuracy, precision, recall, and time taken for training. In this study, the RF model demonstrated the best performance among the three predictive models for predicting final results and dropout with the shortest training time and achieved the highest accuracy. The RF model achieved an accuracy of 87.8% in predicting final results and 82.3% in predicting dropout while maintaining an average training time of 3.6 seconds. At the end of the study, the dashboards visually presented the results, offering valuable insights into students' learning outcomes. This enables educators to effectively support their students by utilizing predictive analytics, which includes identifying potential dropouts and tailoring assistance based on these predictions.

Qualitative Assessment of Attitudes Towards Telerehabilitation in Patients with Metastatic Prostate Cancer.

Prostate cancer (PC) is one of the leading causes of cancer-related mortality among men. Androgen Deprivation Therapy (ADT) has been shown to increase survival in men with metastatic PC. Despite its efficacy, ADT's long-term use adversely impacts quality of life (QoL) due to multiple side effects. Multimodal cancer rehabilitation (CR) programs improve QoL but face limited uptake. This study explores perspectives of patients with metastatic PC on a Home Automated Telemanagement (HAT) system using semi-structured interviews. Findings indicate that patients appreciated the ease of use, guided exercise content, and progress tracking features of the HAT system. Significant benefits in symptom management, cognitive support, and QoL improvements were reported, suggesting the program's potential for long-term health management. In summary, the HAT system is a promising tool for supporting CR in patients with metastatic PC. Future developments should address technical issues, incorporate motivational elements, and enhance user feedback to optimize patient engagement and satisfaction.

Parkinson's Disease: Biomarkers for Diagnosis and Disease Progression.

Parkinson's disease (PD) is a progressive neurological disease that causes both motor and nonmotor symptoms. While our understanding of putative mechanisms has advanced significantly, it remains challenging to verify biomarkers with sufficient evidence for regular clinical use. Clinical symptoms are the primary basis for diagnosing the disease, which can be mild in the early stages and overlap with other neurological disorders. As a result, clinical testing and medical records are mostly relied upon for diagnosis, posing substantial challenges during both the initial diagnosis and the continuous disease monitoring. Recent biochemical, neuroimaging, and genetic biomarkers have helped us understand the pathophysiology of Parkinson's disease. This comprehensive study focuses on these biomarkers, which were chosen based on their relevance, methodological excellence, and contribution to the field. Biochemical biomarkers, including α-synuclein and glial fibrillary acidic protein (GFAP), can predict disease severity and progression. The dopaminergic system is widely used as a neuroimaging biomarker to diagnose PD. Numerous genes and genome wide association study (GWAS) sites have been related to the development of PD. Recent research on the SNCA gene and leucine-rich repeat protein kinase 2 (LRRK2) has shown promising results. By evaluating current studies, this review intends to uncover gaps in biomarker validation and use, while also highlighting promising improvements. It emphasizes the need for dependable and reproducible indicators in improving PD diagnosis and prognosis. These biomarkers may open up new avenues for early diagnosis, disease progression tracking, and the development of personalized treatment programs.

Redefining the impact of professional development in education with ProDES (Professional Development Evaluation Scale)

This study introduces the Professional Development Evaluation Scale (ProDES), a tool that has been developed to evaluate the impact of professional development as it relates to participants' Learning and Use of New Knowledge and Skills, Organisational Support, Student Learning Outcomes, and reactions. Grounded in Guskey’s (2000) framework for evaluating Professional Development, ProDES was developed with data from five study groups in Turkey and underwent refinement across four factors. Exploratory and Confirmatory Factor Analyses confirmed the scale's structure, accounting for 62.72% of the total variance, with robust fit indices. Within this, ProDES demonstrated high internal consistency and test-retest reliability, with significant correlations validating its effectiveness. The scale's high internal consistency and test-retest reliability ensure that it can be used to make evidence-informed decisions that can foster more effective and supportive professional development activities. As a result, by identifying which professional development initiatives lead to improvements, those associated with professional development can use resources more efficiently, leading to enhanced school and system-wide improvements. Moreover, the use of ProDES can also help schools and education systems track progress over time, making ProDES an invaluable tool for continuous improvement and strategic planning.

Deep Learning and IoT-Based Ankle-Foot Orthosis for Enhanced Gait Optimization.

This paper proposes a method for managing gait imbalances by integrating the Internet of Things (IoT) and machine learning technologies. Ankle-foot orthosis (AFO) devices are crucial medical braces that align the lower leg, ankle, and foot, offering essential support for individuals with gait imbalances by assisting weak or paralyzed muscles. This research aims to revolutionize medical orthotics through IoT and machine learning, providing a sophisticated solution for managing gait issues and enhancing patient care with personalized, data-driven insights. The smart ankle-foot orthosis (AFO) is equipped with a surface electromyography (sEMG) sensor to measure muscle activity and an Inertial Measurement Unit (IMU) sensor to monitor gait movements. Data from these sensors are transmitted to the cloud via fog computing for analysis, aiming to identify distinct walking phases, whether normal or aberrant. This involves preprocessing the data and analyzing it using various machine learning methods, such as Random Forest, Decision Tree, Support Vector Machine (SVM), Artificial Neural Network (ANN), Long Short-Term Memory (LSTM), and Transformer models. The Transformer model demonstrates exceptional performance in classifying walking phases based on sensor data, achieving an accuracy of 98.97%. With this preprocessed data, the model can accurately predict and measure improvements in patients' walking patterns, highlighting its effectiveness in distinguishing between normal and aberrant phases during gait analysis. These predictive capabilities enable tailored recommendations regarding the duration and intensity of ankle-foot orthosis (AFO) usage based on individual recovery needs. The analysis results are sent to the physician's device for validation and regular monitoring. Upon approval, the comprehensive report is made accessible to the patient, ensuring continuous progress tracking and timely adjustments to the treatment plan.

Elevating Vocational Training: The Power of Learning Management Systems in Shaping Digital Skills

This article examines the impact of Learning Management Systems (LMS) on the development of learners' technological skills within the context of vocational training. Drawing on an analysis of pedagogical practices and recent studies, it explores how the use of LMS facilitates the acquisition of digital skills essential for the employability of future professionals. The article highlights the advantages of LMS in terms of personalized learning paths, flexible access to content, and tracking of learners' progress. It also discusses the challenges associated with the adoption of LMS, particularly in terms of faculty training and technological integration. The findings of this study emphasize that LMS are not just content management tools, but they play a central role in preparing learners to meet the technological requirements of the current job market. The customization features of LMS allow learners to engage with content in a way that suits their individual learning styles and pace. This personalized approach can lead to more effective skill development and a deeper understanding of technological concepts. Furthermore, the flexibility offered by LMS in accessing learning materials enables learners to engage with the content at their convenience, which is particularly beneficial for individuals balancing work and study commitments. Additionally, the ability to track learners' progress through LMS provides valuable insights for educators to tailor their teaching methods and interventions to address specific areas of need. However, the adoption of LMS also presents challenges, particularly in ensuring that educators are proficient in utilizing the technology to its full potential. Effective training and support for faculty members are crucial in maximizing the benefits of LMS for skill development. Furthermore, integrating LMS into existing educational systems requires careful planning and consideration to ensure seamless implementation and usability. In conclusion, this article underscores the significant role of LMS in fostering the technological skills of learners in vocational training. By leveraging the capabilities of LMS, educational institutions can better prepare their students for the demands of the contemporary workforce, ultimately enhancing their employability and competitiveness in the job market.

The impact of frequency and stakes of formative assessment on student achievement in higher education: A learning analytics study

AbstractBackgroundResearch shows that how formative assessments are operationalized plays a crucial role in shaping their engagement with formative assessments, thereby impacting their effectiveness in predicting academic achievement. Mandatory assessments can ensure consistent student participation, leading to better tracking of learning progress. Optional assessments may encourage voluntary engagement, potentially leading to a more genuine reflection of student understanding. Also, frequent assessments provide continuous opportunities for feedback and adjustment, which can keep students actively engaged in the learning process.ObjectivesThis study aims to investigate two crucial facets of formative assessments: frequency and the level of stakes involved (mandatory vs. optional). We examine how modifying the frequency of formative assessments affects students' course performance. Additionally, we evaluate the impact of mandatory versus optional formative assessments on students' course performance in higher education.MethodsThe sample of this study consisted of undergraduate students (n = 336) enrolled in three sections of a large asynchronous course at a Canadian university. We extracted features associated with online formative assessments (e.g., the number of attempts and average scores) from the learning management system. Next, we used these features to predict students' performance in summative assessments (two midterms and a final exam).Results and ConclusionsOur findings indicated that increasing the frequency of online formative assessments did not consistently improve student performance. Also, participation frequency in online formative assessments seemed to vary depending on assessment stakes (i.e., optional vs. mandatory). We recommend that instructors examine what conditions can maximize the contribution of formative assessments to students' academic achievement before building predictive models.

Theories of change: navigating diverse expert perceptions and preferences for global food system transformation

IntroductionEfforts are underway to transform food systems in light of their contributions to global challenges like climate change. However, food systems are highly complex, involve noteworthy place-based challenges, and there is often debate and disagreement among experts over appropriate technologies or interventions to prioritize. Tracking progress, and understanding these differences, is thus a critical need.MethodsWe surveyed food systems experts in eight countries about their preferences for 20 different food system transformation strategies and their sentiment regarding whether current initiatives are sufficient to meet 2030 goals for climate and biodiversity.ResultsExpert sentiment is overwhelmingly negative, and experts are concerned about multiple “transformation gaps,” including gaps in ambition, strategy, and implementation. Expert rankings for 20 strategies vary notably among countries and in ways that do not match those same experts’ rankings for the strength of the science behind each lever. Factor analysis reveals four distinct theories of change informing experts’ subjective biases: transformation via technical optimization, via smallholder support, via nature-positive solutions, and via supply chain enabling conditions.DiscussionThese findings provide insights for navigating the complexities of food system transformation and illustrate the influence on our strategies of preconceptions and biases in how we have come to understand the nature of the challenge.

Perkembangan Pendidikan Islam di Indonesia pada Masa Klasik dan Modern

Understanding the history and dynamics of Islamic education and making effective policies in the future are necessary for the advancement of Islamic education in Indonesia, from classical to modern times. Pesantren became the centre of religious learning and knowledge in the past, shaping Indonesia's religious and cultural identity. The transformation of Islamic education experiences challenges such as limited access and quality of education issues and is influenced by modernisation, globalisation and technological advances today. This research uses the literature method and a qualitative approach by collecting data from various sources, such as books, journals and digital sources. This allows for a more in-depth understanding of the historical development and tracking of progress. Islamic education is constantly evolving to meet the needs of the times while maintaining the core values of Islam. To improve Islamic education, it requires strengthening educational institutions, improving teachers' capacity, developing relevant curricula, co-operation between institutions, government, and society, and greater public participation.

Bureaucracy and Surveillance-Care: The Partograph in Tanzanian Maternity Care

ABSTRACT Based on fieldwork in maternity wards in Tanzania, I argue that the partograph – a graphical representation of a pregnant woman’s labor – far exceeds its intended role as tracking and surveillance of labor progress. Through surveillance and its concomitant documentation, nurses, especially, also utilize this document to co-create care for themselves and their colleagues. These forms of care proliferate largely unseen by global health systems but are vital for understanding the meeting point of bureaucracy, surveillance, and care and the dynamics of maternity care in this and other lower resource settings. Nurses use the partograph to generate novel forms of surveillance-care.

Web-Based Task Organizer for Enhanced Productivity

The Web-Based Task Organizer for Enhanced Productivity (WBTO) mainly aims to improve task management and overall increase in productivity. In our system we offer features such as task prioritization, categorization, due dates and recurrence options which is integrated into a user friendly interface. We use a full stack approach using java for the back end logic, JavaScript for a dynamic user interface and a SQL database for preserving data storage. It provides key features like task creation, categorization, prioritization, scheduling and progress tracking and interactive functionalities and ensuring data integrity and privacy. As this not only improves individual productivity but also further provides group work collaboration allowing for much faster task tracking, reminders and analytics which improves overall user experience.

MANAGING CORPORATE CLEANING OPERATIONS WITH A FLUTTER-DEVELOPED MOBILE APP: MAXIMIZING EFFICIENCY WITH THE CLEANER APP

This study introduces a mobile application designed to streamline and supervise institutional operations. The application facilitates seamless coordination for cleaning staff and supervisors. At our university, cleaners used to mark their tasks on paper to prove completion, but this method did not allow for tracking cleaning durations and details. To address these issues, we developed an application that offers a new approach to institutional digital transformation for monitoring cleaning tasks. The application is programmed in Flutter, with a Firebase database, and allows for the recording of task start and completion times, providing managers with a transparent overview. Cleaners access and complete tasks via the user interface, while managers monitor activities, track progress, and generate daily reports through the management interface. A key feature of the application is its ability to archive historical data, allowing managers to access past records and gain insights into operational trends. Additionally, the capability to export reports in PDF format offers accessibility and ease of sharing. The evaluation of the application was conducted by examining data from the Cleaning Services Monitoring Unit under the University's Administrative and Financial Affairs Department. The examined data comprises 280 days and includes 33,587 records. By meticulously recording task start and completion times, the application provides managers with a transparent overview for analysis and evaluation. According to the data from the Cleaning Services Monitoring Unit, the application has increased efficiency by 23% and reduced task completion times by 28%. As a result, cleaners have been able to complete an additional task each day. This demonstrates that the application enhances functionality and makes operations more efficient.

Impact of Smartphone-Induced Mental Fatigue on Resistance Training Performance and Efficiency - The Role of Smartphone Use During Workout

Introduction Resistance training volume is a key determinant of muscle hypertrophy and strength development. However, mental fatigue can significantly impact this volume, ultimately affecting performance. One prominent source of mental fatigue in modern gym environments is smartphone use, which has become pervasive and may reduce workout efficiency and overall training volume. Purpose This review examines the dual effects of smartphone use on resistance training outcomes and offers strategies to balance these impacts effectively. Conclusions Smartphone-induced mental fatigue increases perceived exertion, leading to reduced performance during resistance training by lowering volume-load and endurance, particularly in low- and moderate-intensity exercises. Despite this, maximal strength appears to remain unaffected. Additionally, smartphone use diverts cognitive resources, resulting in mental fatigue and impairing both physical and technical performance due to distractions during workouts. It can also unintentionally prolong rest periods, which disrupts the balance between muscle recovery and mental readiness, further decreasing training efficiency. However, smartphones also offer valuable benefits, such as access to fitness apps, progress tracking, and motivational music, which can help maintain or even enhance performance by improving focus and motivation. To minimize distractions and optimize training outcomes, strategies such as using airplane mode or scheduling specific times for phone use are recommended. While excessive smartphone use can impair training efficiency, careful management and strategic use can enable athletes to capitalize on its benefits and improve resistance training results. Future research should focus on developing best practices for incorporating smartphone use in fitness settings to balance its advantages while minimizing its downsides.

Dietary diversity and nutrient adequacy among women in Bosomtwe District, Ghana.

The sustainable development goals seek to end all forms of malnutrition of women of reproductive age (WRA) by 2030. As such, recent data on nutrient adequacy are needed to aid in tracking progress. However, data on specific dietary nutrient intakes includes only iron, folate, vitamin A, and vitamin B12 in Ghana. Therefore, women's dietary diversity score (W-DDS) is often used as a proxy measure of nutrient adequacy. It is hypothesised that there is no association between W-DDS and Nutrient Adequacy among WRA in peri-urban Ghana. Hence, this research evaluated the associations between W-DDS and nutrient adequacy ratio (NAR) and assessed the determinants of mean nutrient adequacy ratio (MAR) in the Bosomtwe District of Ghana. A community-based cross-sectional study was conducted, and data collected on anthropometry, food insecurity, socio-demographic characteristics and dietary intake using the 24-hour recall from 407 WRA. In all, 21 nutrients were assessed. The mean age, W-DDS, and MAR were 29.0 ± 6.7 years, 5.3 ± 1.9, and 0.65 ± 0.19 respectively. The NAR were generally high for the macronutrients as compared to micronutrients and the nutrients with low NAR included vitamin C (0.27 ± 0.19), vitamin A (0.15 ± 0.23), vitamin B12 (0.54 ± 0.32), calcium (0.28 ± 0.20), zinc (0.52 ± 0.23) and iron (0.57 ± 0.28) - signifying the WRA may be consuming monotonous carbohydrate-based diet. The hierarchical multivariable linear regression found a significant association between W-DDS and MAR after controlling for confounders (β = 0.404, p < 0.001). The determinants of MAR were ethnicity (β = 0.110, p = 0.006) and body mass index (β = 0.189, p < 0.001). This study supports the use of W-DDS as a proxy indicator of nutrient adequacy. Strategies meant to address nutrient inadequacies should be adaptable to different ethnic groups and overweight-reducing strategies should be incorporated into broader nutrition initiatives.

The Power of Play: Strategies for Enhancing Development in Children with Autism Spectrum Disorders.

The increasing prevalence of autism spectrum disorder (ASD) underscores its significant impact on individuals and the importance of early intervention. ASD affects various aspects of life, including education, emotional development, and social interactions. Besides traditional therapeutic approaches, a novel strategy incorporating digital games has been introduced. Four games developed using Makey Makey and Scratch aim to enhance cognitive skills in children with ASD. This approach facilitates emotional and intellectual development, tracks progress, and offers personalized and engaging interventions. This study demonstrated significant improvements in memory and concentration among participants, with an average improvement of 23.38 points. The most notable enhancements were observed in children aged 10, who showed an average improvement of 25.67 points. Additionally, female participants exhibited a slightly higher average improvement compared to males. The Memory Maze game also effectively enhanced cognitive skills in children with different types of ADHD. Children with the Hyperactive-Impulsive type showed the highest average improvement, with 25.00 points, followed by those with the Combined type, with 24.15 points, and the Inattentive type, with 23.53 points. These findings highlight the potential use of these tools in both ASD and ADHD therapy, providing a structured and enjoyable learning environment that supports cognitive development and therapeutic outcomes.

Exploring neural markers of dereification in meditation based on EEG and personalized models of electrophysiological brain states

With mounting evidence for the benefits of meditation, there has been a growing interest in measuring and quantifying meditative states. This study introduces the Inner Dereification Index (IDI), a class of personalized models designed to quantify the distance from non-meditative states such as mind wandering based on a single individual’s neural activity. In addition to demonstrating high classification accuracy (median AUC: 0.996) at distinguishing meditation from thinking states moment by moment, IDI can accurately stratify meditator cohorts by experience, and correctly identify the practices most effective at training the dereification aspect of meditation (decentering from immersion with thoughts and perceptions and recognizing them as mental constructs). These results suggest that IDI models may be a useful real-time proxy for dereification and meditation progress, requiring only 1 min of mind wandering data (and no meditation data) during model training. Thus, they show promise for applications such as real-time meditation feedback, progress tracking, personalization of practices, and potential therapeutic applications of neurofeedback-assisted generation of positive states of consciousness.

Design of a Web-Based Monitoring and Evaluation Application for Mentoring Using the Rapid Application Development Method at The Faculty of Computer Science UNIKA Santo Thomas Medan

The academic and thesis supervision processes at the Faculty of Computer Science, UNIKA Santo Thomas Medan, currently face various challenges, including a lack of clear structure in scheduling and difficulties in monitoring student progress. To address these issues, this research aims to develop a web-based application that supports monitoring and evaluation of the supervision process. The application is designed using the Rapid Application Development (RAD) method, which facilitates flexible and responsive development tailored to user needs. With features such as supervision scheduling, student progress tracking, and automatic evaluation, this application is expected to enhance the effectiveness of supervision, facilitate communication between lecturers and students, and support more structured academic management within the faculty. The implementation of this application has successfully improved the efficiency of the supervision process and ensured that students receive more structured guidance.

TRANSFORMATIVE PEDAGOGY IN THE DIGITAL AGE: UNRAVELING THE IMPACT OF ARTIFICIAL INTELLIGENCE ON HIGHER EDUCATION STUDENTS

Artificial Intelligence (AI) has become a transformative force in education, significantly influencing students. This research explores AI's impact on learning experiences, academic performance, career guidance, motivation, self-reliance, social interaction, and AI dependency. Utilizing a descriptive-comparative design, 194 student respondents were chosen through stratified sampling. The results show that students generally perceive AI positively. Students agree that AI enhances personalized learning, engagement, and critical thinking, although practical hands-on learning experiences received less favorable feedback. Academically, students concur that AI helps them identify weaknesses, improve assignments, and track progress, despite some reservations about its efficacy in exam preparation. For career guidance, students agree that AI effectively matches skills with career options, recommends internships, and provides resources, though it is less effective for long-term planning. Students also believe AI boosts motivation through gamified learning and progress tracking and fosters self-reliance via self-directed learning and critical thinking support. Socially, students agree that AI facilitates collaboration, peer learning, and networking. Additionally, students demonstrate a reliance on AI for their learning processes. Notably, female students report a more significant impact on social interactions than male students. The type of device used (laptop vs. cellphone) significantly affects the learning experience, with laptop users reporting a more substantial impact. Differences in AI's impact are noted among various courses, particularly benefiting education students more than those in hospitality management and agriculture. However, age and family income do not significantly influence AI's overall impact. Keywords: Artificial Intelligence, descriptive-comparative, impact on learning, higher education

Effectiveness of Virtual Reality-Based Multi-Therapy Systems for Physio-Psychological Rehabilitation: A Clinical Study

The worldwide increase in the number of disorders requiring rehabilitation is weighing more and more on healthcare systems, seriously affecting the quality of life of patients. Emergent technologies and techniques should be used more and more in both physical and psychological rehabilitation, after a thorough study of their potential and effects. Our paper presents an original virtual reality-based system including gamified immersive physio-psychological exercises, which was tested in a clinical setting with 25 patients suffering from various musculoskeletal, neuromotor, or mental disorders. A thorough testing protocol was followed during a two-week period, including repeated trials, progress tracking, and objective and subjective instruments used for data collection. A statistical analysis helped us identify interesting correlations between complex virtual reality games and people’s performance, and the high level of relaxation and stress relief (4.57 out of 5 across all games) which can be offered by VR-based psychotherapy exercises, as well as the increased ease of use (4.26 out of 5 perceived across all games) of properly designed training exercises regardless of patients’ level of VR experience (84% of patients with no or low experience and no patient with high experience).

Animal-free safety assessment of chemicals: an innovation system perspective.

This perspective paper, which is the result of a collaborative effort between toxicologists and scholars in innovation and transition studies, presents a heuristic framework based on innovation system literature for understanding and appraising mission achievement to animal-free chemical safety assessment using New Approach Methodologies (NAMs). While scientific and technical challenges in this area are relatively well known, the recent establishment of missions and roadmaps to accelerate the acceptance and effective use of NAMs for chemical safety assessment raises new questions about how we can grasp the systemic nature of all changes needed in this transition. This includes recognising broader societal, institutional, and regulatory shifts necessary for NAM acceptance and uptake. Our paper discusses how the innovation system approach offers insights into key processes and associated activities that include as well as transcend the technical and scientific realm, and can help to accelerate acceptance and uptake of NAMs. Based on these insights, we present a comprehensive framework that, next to scientific and technological developments, recognises the need for coordinated efforts in areas like education, training, funding, policy-making, and public engagement to promote the acceptance and uptake of NAMs. Our framework can be used to perform structural and functional analyses of the innovation system of NAMs and animal-free safety assessment and as such provides handholds to track progress and organise collective efforts of actors to make sure we are moving in the right direction.