The role of emerging IT-technologies in elective selection: AI, blockchain, and beyond

Revolution in the way universities and students interact with academic resources, administrative tasks and decision-making processes. Developments in IT technologies for elective selection in higher education. Opportunities provided by digitalization.

Рубрика Производство и технологии
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Язык английский
Дата добавления 08.06.2024
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National Qualifications Agency

Academician Stepan Demyanchuk International University of Economics and Humanities

The role of emerging IT-technologies in elective selection: AI, blockchain, and beyond

Semigina T.

Novak A.

Introduction

digitalization education technology

In the midst of a rapidly changing higher education landscape, students are faced with a multitude of decisions that go beyond required courses. One such critical decision is the selection of electives. Electives allow students to personalize their learning experience, explore a variety of topics, and deepen their expertise in specific areas of interest.

However, traditional methods often result in complexities and inefficiencies. In recent years, the education sector has undergone a remarkable transformation through the adoption of digital solutions [1; 2]. These solutions have revolutionized the way universities and students interact with academic resources, administrative tasks, and decision-making processes.

In this chapter, we address recent developments in IT-techonologies for elective selection in higher education, drawing on our literature review and an analysis of U.S. university websites. We examine current challenges and the opportunities presented by digitalization. The future of elective selection is increasingly digital, and this chapter will guide readers through this evolving journey, reflecting the idea that elective choice is a process that students and universities are embarking on together.

Key results

In traditional higher education settings, students typically select their elective courses by referring to printed course catalogs or browsing static course listings on university websites. These catalogs contain extensive information about available courses, including course titles, descriptions, credit hours, and prerequisites.

Students manually sift through these catalogs, reading course descriptions and checking prerequisites to make informed decisions. They often use paper forms to submit their choices, and these selections may need to be approved by academic advisors or administrators.

These challenges underscore the pressing need for modern, efficient, and user-friendly elective selection solutions. Digitalization offers an opportunity to tackle these challenges and establish a more efficient and informed elective selection process for students and educational institutions. However, it's important to emphasize that the quality of digital solutions is crucial in achieving this goal.

Many higher educational institutions in Ukraine currently rely on simple web interfaces for elective selection. These interfaces serve as online platforms or systems that help students choose elective courses or subjects. While they provide basic functionality for browsing available electives, making selections, and confirming choices [3; 4], these interfaces have several limitations.

One significant drawback is their limited customization options. This lack of flexibility makes it difficult to effectively address the diverse elective needs of students. For example, students with specific career goals or academic interests may find it challenging to identify and select the most relevant elective courses. Additionally, these interfaces often lack interactive features such as real-time feedback, dynamic course recommendations, or collaborative decision-making tools. These features could significantly enhance the overall user experience and help students make more informed elective choices.

As the student population and the number of available courses continue to grow, simple web interfaces may struggle to handle the increasing load. This can result in slower response times and, in some cases, system crashes. Furthermore, these interfaces may not be fully accessible to students with disabilities, introducing inequalities into the elective selection process.

Another notable limitation is the underutilization of data analytics and machine learning capabilities. Simple web interfaces may miss opportunities for data-driven insights and optimizations that are crucial for improving the elective selection process. For example, they could use data to identify trends in elective selection patterns, develop predictive models to recommend courses to students, or track student progress and performance. Additionally, simple web interfaces may fail to engage students effectively in the selection process, potentially leading to uninformed choices.

Integrating basic web interfaces with other university systems or external platforms can be a complex task, impeding seamless data exchange and coordination. Security concerns also arise if these interfaces lack adequate protection, potentially jeopardizing sensitive student data.

These interfaces often lack a robust feedback mechanism, making it challenging for universities to collect input from students and continuously enhance the elective selection process. Lastly, they may not be optimized for mobile devices, limiting flexibility for students who prefer accessing the system via smartphones or tablets.

To overcome these limitations, universities should consider adopting more advanced digital solutions that offer greater flexibility, interactivity, scalability, and accessibility. These advanced solutions should harness the power of data analytics and user engagement techniques to enhance the elective selection experience, ensuring it aligns with the evolving needs of both students and academic institutions.

The advent of digital technology has ushered in a new era in higher education, with a notable impact on elective course selection. Traditional methods, such as paper catalogs or face-to-face advising, have evolved into innovative digital solutions that offer students a wide range of features and functionalities.

The rapid advancement of IT-technologies is poised to bring about significant transformations in the landscape of elective course selection within higher education. Drawing from the insights of various researchers [10-15], several key trends and advancements have been anticipated.

Firstly, artificial intelligence (AI)-driven recommendation systems are expected to play a major role. These systems, fueled by machine learning algorithms and AI capabilities, will evolve to provide remarkably precise elective course recommendations. Leveraging vast datasets, they will optimize elective choices based on individual academic backgrounds, career aspirations, and personal interest profiles. The AI Personal Assistance tool could be also employed for the educational purposes.

In particular, Purdue University's Electives Discovery Tool uses AI-driven recommendation systems to provide students with personalized elective course recommendations.

Moreover, the implementation of blockchain technology is poised to revolutionize academic records within educational institutions. Blockchain offers a secure, decentralized ledger for recording and verifying academic achievements. This innovation ensures the integrity of elective course selections and facilitates the seamless transfer of academic credits across different institutions, fostering greater academic mobility. For example, a student who transfers to a new university could easily access their previous elective course selections and have them transferred to their new institution.

As an illustration, we can mention The University of California, Berkeley's Blockchain Academic Record. It is a pilot program that uses blockchain technology to create a secure and transparent record of student academic achievements.

Furthermore, the advent of advanced data analytics will enable institutions to gain valuable insights from elective selection patterns and student performance. This data-driven approach will empower universities to fine-tune their curricula, aligning course offerings with evolving industry demands and student preferences. For instance, a university may use data analytics to identify popular elective courses and offer more sections of those courses. Or, a university may use data analytics to identify areas where students are struggling and offer additional support or resources.

Augmented reality (AR) is emerging as a transformative tool, allowing students to interactively preview elective courses. Through the overlay of digital information onto the physical world, AR provides a visually immersive experience, enabling students to assess course content and learning environments before making informed selections. As a case in poin, The University of Southern California's AR Campus Tour allows students to explore the university's campus and facilities using augmented reality.

Lastly, the increasing reliance on digital systems underscores the critical need for robust cybersecurity measures. Educational institutions are expected to prioritize the safeguarding of student data and the preservation of the security and reliability of the elective selection process as they continue their digital transformation journey.

Based on a comprehensive literature review [5-8] and an analysis of US universities' websites, it is possible to state that educational institutions can leverage the following advanced digital solutions for elective courses' selection:

1. Online Course Registration Portals:

Web-Based Platforms: Many universities have transitioned to web-based portals that enable students to browse, search, and select elective courses online. These platforms offer user-friendly interfaces, comprehensive course information, and real-time updates.

Mobile Applications: Some institutions have developed mobile apps for elective selection, providing students with the flexibility to choose courses from their smartphones or tablets.

The good examples of such portals could be The University of Texas at Austin's Course Explorer and Arizona State University's My ASU portal.

Recommendation Systems:

Personalized Suggestions: Advanced algorithms analyze a student's academic history, major, and career goals to generate personalized course recommendations. These recommendations assist students in making informed choices aligned with their academic trajectory.

Peer Reviews and Ratings: Some systems incorporate peer reviews and ratings for courses and instructors, allowing students to benefit from the experiences and opinions of their peers when making selections.

Interactive Dashboards:

Interactive Displays: Digital dashboards provide students with interactive displays of course offerings, allowing them to filter courses based on various criteria such as department, time slots, or prerequisites. This feature simplifies the process of finding suitable electives.

Real-Time Updates: Dashboards often include real-time updates on course availability and enrollment limits, ensuring students have access to the latest information.

For example, Georgia Tech's Course Analytics Dashboard provides universities with data-driven insights into elective selection patterns and student performance.

Academic Planning Tools:

Degree Audits: Some systems offer degree audit tools that help students track their progress toward degree completion, for example count of ECTS. These tools show how selected electives fit into an individual student's overall academic plan.

Scheduling Assistance: Students can use these tools to create personalized academic schedules that balance their elective choices with core requirements and other commitments.

Rutgers University's What-If Degree Planner, The University of North Carolina at Chapel Hill's Four-Year Plan, University of California, Los Angeles' Academic Planning may serve as examples of such tools.

Integration with Learning Management Systems (LMS):

Seamless Integration: Integration with the university's LMS streamlines elective selection by allowing students to directly access course materials, assignments, and grades through a single interface.

Collaborative Learning: LMS integration often includes collaboration features, facilitating group work and communication among students enrolled in the same elective courses, student and a lecturer and so on.

Canvas & Moodle could be named here among other systems.

Virtual Reality (VR) and Augmented Reality (AR):

Immersive Exploration: Forward-thinking institutions are experimenting with VR and AR technologies to create immersive elective selection experiences. Students can virtually explore classrooms, labs, and campus facilities, gaining insights into their elective choices.

University of Maryland, Baltimore County's VR Lab, Cal Poly Pomona's AR Campus Tour, University of Washington's Mixed Reality Lab are based on these technologies.

According to researchers [2; 6; 9; 11], digital solutions for elective course selection in higher education offer several advantages. Firstly, they simplify the elective selection process, providing students with user-friendly interfaces that make choosing courses more convenient and efficient. Moreover, these solutions enhance the overall educational experience by empowering students with the information they need to make well-informed decisions regarding their academic path.

Transparency is another key benefit of digital platforms. They offer real-time information about course availability, prerequisites, and enrollment limits, ensuring that students have access to the latest data. This transparency aids students in making informed choices aligned with their academic goals.

Additionally, digital solutions can encourage collaboration among students. Some systems incorporate peer reviews and ratings for courses and instructors, allowing students to benefit from the experiences and opinions of their peers when making selections. This collaborative element fosters a sense of community and shared knowledge among students.

However, the implementation of digital solutions in elective course selection is not without its challenges and concerns. These aspects, drawn from various research findings [6; 8; 11; 15], are crucial for universities to consider as they embark on their digital transformation journey.

Firstly, universities may encounter resistance to technological shifts from faculty and students, potentially hindering the transition from traditional methods. Effective change management strategies and measures to ensure user acceptance become paramount in this context.

Data security and privacy emerge as critical concerns. Safeguarding sensitive student information from unauthorized access and potential data breaches is of utmost importance. Robust data encryption protocols and stringent access controls are necessary to fortify data security measures.

Accessibility and inclusivity also pose significant challenges. Developing digital platforms that cater to the diverse needs of all students, including those with disabilities, requires strict adherence to WCAG (Web Content Accessibility Guidelines) and rigorous usability testing.

Furthermore, providing comprehensive training resources and responsive technical support is essential. Empowering users with the necessary knowledge and skills to effectively navigate digital systems is crucial for their successful adoption.

Integrating digital solutions with existing university systems, such as Student Information Systems (SIS) or Learning Management Systems (LMS), can be complex. This necessitates expertise in system interoperability to achieve seamless integration.

Technical reliability is paramount to ensure uninterrupted service during critical periods like elective course selection. This involves maintaining system uptime, optimizing performance, and having robust disaster recovery plans in place.

Financial considerations cannot be overlooked, with budgetary allocation required for various aspects, including software development, maintenance, and infrastructure costs. Aligning these financial aspects with the university's available resources is vital.

The application of user-centric design principles is crucial to create intuitive, user-friendly interfaces. This approach is essential for ensuring a positive user experience and high adoption rates among faculty and students.

To maintain data accuracy and consistency across systems, mechanisms for data validation and synchronization must be implemented diligently.

Lastly, customization options for different academic departments, while maintaining scalability, can be technically intricate but necessary to accommodate the diverse needs of the university effectively.

Addressing these challenges and concerns is essential to the successful implementation of digital solutions in elective course selection within higher education. By proactively tackling these issues, universities can optimize the effectiveness of their digital transformation initiatives and provide an enhanced experience for both faculty and students.

In Ukraine, the transition from simple to advanced digital solutions for elective course selection involves several critical steps. Firstly, it is imperative to commence with a comprehensive assessment and strategic planning phase, aiming to evaluate the current selection processes and establish a clear roadmap for digital transformation. This transformation necessitates significant investment in technology infrastructure and software development to provide the essential support for the transition.

Moreover, orchestrating effective training programs for both faculty and students is essential to ensure the successful adoption of digital systems. These training initiatives should prioritize usercentric design principles, aiming to elevate the overall user experience and foster widespread acceptance of these advanced solutions. Notably, stringent data security measures, encompassing robust encryption and access controls, are indispensable to safeguard sensitive student information effectively.

Conclusions

The use of digital solutions in elective selection offers numerous benefits to both students and higher education institutions. These solutions provide a streamlined, user-friendly approach to course selection and improve accessibility, transparency, and data-driven decision making. Traditional methods of elective selection, characterized by challenges and limitations, require a shift to modernized systems.

It is imperative that universities recognize the importance of taking digital transformation into account when choosing a course of study. In this way, they can provide students with efficient tools for exploring and selecting courses. In addition, the use of new technologies such as AI, blockchain, data analytics, and augmented reality promises to revolutionize the educational experience.

If universities continue to adapt and innovate, they will not only meet the changing needs and expectations of their students, but also contribute to the advancement of higher education as a whole. The use of digital solutions in the selection of electives is a critical step toward a more dynamic and personalized educational experience.

References

1. Качурівський, В.О. & Качурівська, Г.М. (2022). Моделювання інформаційно-документальної системи презентації освітніх компонент освітньої програми. Центральноукраїнський науковий вісник. Технічні науки, 6(37)-ІІ, 17-23

2. Лондарь, С.Л., ред. (2020). Розвиток інформаційних систем управління освітою як інструмент реалізації державної освітньої політики. Київ: Інститут освітньої аналітики.

3. Новак, А.С. (2022). Інформаційна система для вибіркових дисциплін: індик/ дослідницький проект ... бакалавра: 126 Інформаційні системи та технології. https://ela.kpi.ua/handle/123456789/57662.

4. Триус, Ю.В. та ін. (2021). Інформаційно-аналітична система підтримки освітньої діяльності структурних підрозділів закладів вищої освіти. Вісник Черкаського державного технологічного університету. Технічні науки, 4, 27-38.

5. Al-Badarenah, A., & Alsakran, J. (2016). An automated recommender system for course selection. International Journal of Advanced Computer Science and Applications, 7(3), 166-175.

6. Eachempati, P., & Srivastava, P.R. (2019). Personalized elective selection: a multi-criteria perspective in academia. International Journal of Strategic Decision Sciences, 10(4), 43-63.

7. Laghari, M.S. (2014). Automated course advising system. International journal of machine learning and computing, 4(1), 47-51.

8. Liu, H. (2021). Research on the Application of Big Data and Cloud Computing Technology in the Smart Course Selection System. In: 2021 3rd International Conference on Artificial Intelligence and Advanced Manufacture (pp. 2634-2640).

9. Maphosa, M., Doorsamy, W., & Paul, B. (2020). A review of recommender systems for choosing elective courses. International Journal of Advanced Computer Science and Applications, 11(9), 287-295.

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