Session 3: eLearning trends in Higher Education

eLearning trends in higher education are becoming more and more popular as a way to improve learning and teaching. This session will talk about some of these trends, including learning analytics, bring your own device (BYOD) and mobile learning, virtual reality and augmented reality, and makerspaces.

The session meets two of the ED403’s important CLOs which are critically review and analyse trends in higher education learning environment (CLO2) and Apply eLearning trends and application within your contexts of higher education (CLO3).

What is eLearning

eLearning, in essence, refers to the use of technology in the process of acquiring knowledge and skills (Nichols, 2003). Conventional education was limited to the physical boundaries of the classroom, and the knowledge imparted was solely determined by the instructor. The advent of the internet has brought about substantial changes in the learning environment. The rapid advancement and proliferation of technology have expanded the opportunities for learners. They now have access to a wider range of information sources and may actively engage in discussions in various settings such as classrooms, chatrooms, and online forums. Gone are the days when students had to wait for the commencement of physical classes to begin acquiring information (Alam et al., 2014). In the present day, students have the ability to access relevant educational resources in various formats such as films, animations, slideshows, and more, enabling them to begin the learning process in advance. The learning environment will undergo additional transformation with the introduction of virtual reality and augmented reality.

Some resources:

What is eLearning?

Learning Analytics

Learning analytics is the study of how to measure, collect, analyze, and share information about students and the situations they are in. The goal is to understand how the students connect with each other and then give them the feedback they need to improve their learning (Clow, 2013). Using models, machine learning, and data mining, among other prediction tools, past data can be used to guess how well students will do in the future (Leitner et al., 2017).

Learning analytics involves analyzing student interactions through a learning management system or the Internet, such as Moodle. For this, Moodle provides a plugin for a progress tracker, integrated completion analytics, and various log reports (Viberg et al., 2018). I was also collaborating with FSTE on an Early Warning System initiative in which we devised a system to identify at-risk students as early as week 4 by analyzing their interactions on Moodle and assessments (Singh et al., 2015). We have recently conducted additional research in the field, employing artificial intelligence to generate this prediction. The Pacific is in dire need of Learning Analytics, which is currently on-trend (Jokhan et al., 2022). I am monitoring students' progress in my course by utilizing completion tracking and EWS plugins. For the same purpose, I am also willing to utilize AI-based analysis on Moodle.

Learning Analytics

Bring Your Own Device (BYOD) and mLearning

Smartphones and tablets are among the electronic devices that students are encouraged to bring to class. The devices possessing high connectivity have the capability to conduct information searches and can also function as supplementary tools to aid in the learning process (Afreen, 2014). BYOD promotes mobile learning. The mLearning platform furnishes students with various services, including consistent updates regarding their course progress, notifications regarding significant assessment dates, and the timetable for examinations.

We have BYOD and mobile learning, both of which I worked on previously with FSTE. Mobile applications and mLearning are experiencing explosive growth due to the fact that an increasing number of students prefer to use mobile devices because they are portable, convenient, and accessible at any time and from any location. Initially offering an SMS-based service, FSTE subsequently progressed to the development of mobile applications containing various learning components (Sharma et al., 2019; Sharma et al., 2017). In addition, the application included quizzes and concise course modules covering various subjects. Additionally, USP encourages the use of personal devices by providing internet access for each student's device through ITS and previously distributing tablets to all first-year students via the Tablet Learning Project. Once more, I am convinced that mobile learning and bring-your-own-device (BYOD) policies are vital for our Pacific students, given that the majority of students now own mobile or smart devices. This will facilitate learning via a variety of educational applications. I use a variety of mobile applications in my course, which I distribute to students for installation and use in order to better comprehend topics (Singh, 2015).

Links to resources:

BYOD

mLearning

Virtual Reality (VR) and Augmented Reality (AR)

Augmented Reality (AR) and Virtual Reality (VR) are increasingly recognized as significant educational technologies, offering unparalleled immersion in the learning process that traditional methods fail to replicate. It facilitates enhanced comprehension, interactive learning, and secure simulation (Fitria, 2023). Prior to lab or field work, it may be more cost-effective and secure to use augmented reality (AR) or virtual reality (VR) for various courses at USP, particularly the marine biology program, given the high cost of lab and field work. It will be of tremendous advantage to the Pacific, where resources might be scarce. It is also beneficial for online courses in which students may be unable to physically attend lab sessions on campus or in the field. Additionally, it is safer, since errors are more tolerable in AR and VR simulations than in hazardous fields such as aviation, marine biology, and aerospace. Using augmented reality, we created a mobile application comparable to the Pokémon Go application in which students must navigate to various locations, answer questions, and receive hints regarding the next location.

Links to resources:

Makerspaces

Collaboration work environments known as makerspaces, hackerspaces, or FabLabs furnish individuals with the means to create, learn, explore, and share resources and tools (Konstantinou et al., 2021). Our Engineering department at STEMP utilizes a 3D printer to produce a variety of models and prototypes. It is crucial in the Pacific because acquiring actual resources is expensive, and these instruments aid in engineering by simulating what is recovered.

Links to resources:

eAssessment refers to the use of digital technology for the purpose of conducting assessments. This technique utilizes technology to manage, evaluate, and organize exams (Brink & Lautenbach, 2011). Assessments may vary in complexity, spanning from simple multiple-choice tests to more intricate essays, projects, or even hands-on exercises (Alruwais et al., 2018).

Students who have access to the internet are allowed to complete evaluations from any place. Implementing computerized grading for objective questions improves efficiency by saving time and effort. Automated grading methods may enhance uniformity and fairness by reducing the likelihood of human mistakes. Students get the chance to acquire instant outcomes and feedback, which is beneficial for their educational advancement (Stödberg, 2012).

Moodle is an excellent platform that enables the implementation of eAssessments for online education (Al-Azawei, 2019). The facilitator has a plethora of activities to choose from. Common examples are discussion forums and online quizzes. During a discussion forum, the instructor will provide a question that necessitates the students to engage in research. After doing the study, the students would analyze the facts in relation to their own circumstances and thereafter express their viewpoint on the forum. This feature will enable individuals to see and provide feedback on one another's answers to the presented inquiry. This process elicits a succession of cognitive processes and diverse perspectives in approaching the inquiry. Meanwhile, the facilitator may steer the discourse and provide comments. This tool may serve as an effective means of formative evaluation and monitoring students' progress throughout the learning process. Alternatively, Moodle may serve as a medium for summative evaluation via the administration of online quizzes. A limited number of multiple choice questions may be provided. The quiz must be completed within a certain time frame and adhere to time constraints. After finishing the quiz, it could be instantly graded and the results might be accessible to the students. Another kind of eAssessment includes the Assignment function and SCORM package, both of which enable the process of eAssessment.

Dealing with Plagiarism in Online Assessment

Similar to traditional methods of evaluation, e-assessment is likewise challenged by the problem of plagiarism. Several strategies to reduce plagiarism include:

  • Enable plagiarism plugin.
  • Ensure that there is no repetition of assignments or questions from one year to another.
  • The evaluation modality for evaluating the notion may be modified. For example, you may instruct the students to provide an oral presentation on a certain subject one year, and then the next year, you could assign them to construct a poster presentation or develop a blog. Establishing the blog exemplifies real assessment.
  • If the class size is small, pupils might be assigned distinct tasks. In a big class, the projects assigned may have similarities in their purpose, but the materials, methods, and equipment used might vary. In chemistry, while studying acid-base reactions, various mixtures of acids and bases may be provided to different groups.
  • Plagiarism education should be included into the evaluation.


Reference:

Alruwais, N., Wills, G., & Wald, M. (2018). Advantages and challenges of using e-assessment. International Journal of Information and Education Technology, 8(1), 34-37.

Alam, F., Hadgraft, R. G., & Alam, Q. (2014). eLearning: Challenges and opportunities. Using technology tools to innovate assessment, reporting, and teaching practices in engineering education, 217-226.

Al-Azawei, A., Baiee, W. R., & Mohammed, M. A. (2019). Learners’ experience towards e-assessment tools: A comparative study on virtual reality and moodle quiz. International Journal of Emerging Technologies in Learning (Online), 14(5), 34. Afreen, R. (2014). Bring your own device (BYOD) in higher education: Opportunities and challenges. International Journal of Emerging Trends & Technology in Computer Science, 3(1), 233-236.

Brink, R., & Lautenbach, G. (2011). Electronic assessment in higher education. Educational Studies, 37(5), 503-512.

Clow, D. (2013). An overview of learning analytics. Teaching in Higher Education, 18(6), 683-695.

Fitria, T. N. (2023). Augmented reality (AR) and virtual reality (VR) technology in education: Media of teaching and learning: A review. International Journal of Computer and Information System (IJCIS), 4(1), 14-25.

Jokhan, A., Chand, A. A., Singh, V., & Mamun, K. A. (2022). Increased digital resource consumption in higher educational institutions and the artificial intelligence role in informing decisions related to student performance. Sustainability, 14(4), 2377.

Konstantinou, D., Parmaxi, A., & Zaphiris, P. (2021). Mapping research directions on makerspaces in education. Educational Media International, 58(3), 223-247.

Leitner, P., Khalil, M., & Ebner, M. (2017). Learning analytics in higher education—a literature review. Learning analytics: Fundaments, applications, and trends: A view of the current state of the art to enhance E-learning, 1-23.

Nichols, M. (2003). A theory for eLearning. Journal of Educational Technology & Society, 6(2), 1-10.

Singh, V., Sharma, B. N., Jokhan, A. D., & Singh, S. (2015). Early Warning System. In 12th Pacific Science Inter-Congress (pp. 165-169). USP Press.

Sharma, B. N., Reddy, P., Reddy, E., Narayan, S. S., Singh, V., Kumar, R., ... & Prasad, R. (2019). Use of mobile devices for learning and student support in the Pacific region. Springer Nature.

Sharma, B., Kumar, R., Rao, V., Finiasi, R., Chand, S., Singh, V., & Naicker, R. (2017). A mobile learning journey in Pacific education. Mobile learning in higher education in the Asia-Pacific region: harnessing trends and challenging orthodoxies, 581-605.

Singh, V. (2015, December). Android based student learning system. In 2015 2nd Asia-Pacific World Congress on Computer Science and Engineering (APWC on CSE) (pp. 1-9). IEEE.

Stödberg, U. (2012). A research review of e-assessment. Assessment & Evaluation in Higher Education, 37(5), 591-604.

Soares, F., & Lopes, A. P. (2018). Online assessment through moodle plataform.

Viberg, O., Hatakka, M., Bälter, O., & Mavroudi, A. (2018). The current landscape of learning analytics in higher education. Computers in human behavior, 89, 98-110.

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