What are the best ways to use learning analytics tools for vocational education?

Vocational education primarily moves around skill development and interest. thus people are more creative and the same tool or app is used in different ways. This is a field that prepares them for real-life situations. Students make many innovations, Physical tools are replaced by alternate tools. Apps and platforms are used as combinations. in this field outcome is more important than process. many students use free online resources for editing, enhancing content, and changing context.

Tools such as moodle, blackboar or canva, which are among the analytical tools used to monitor the development of people preparing for professional life, can be used. In this way, the gap between the requirements of the profession and the person's performance and skills can be determined and precautions can be taken. On the other hand, Knewton and Smart Sparrow analytical tools can be used to increase student-teacher interaction in vocational education. Perhaps it would be useful to use an important analytical tool that can effectively predict the student's future performance. It may only be necessary to carefully evaluate how valid and reliable these tools provide results.

Usually, these are group projects to develop teamwork. people use waste materials and spare parts to design something new and useful. Besides this the skills of communication, handling team, delegation of work, acquiring resources, data collection and data protection, presentation skills, and collecting feedback are other skills that parallely develop with vocational projects.

Regardless of the tool, this notion of "metric" or "indicator" is the most critical element to implementing any kind of learning analytics. In a world full of competencies, outcomes, objectives, measures - what do you define as an "outcome achieved" and how can you ensure that your learning intervention and data analysis are synchronized? It's not an easy solve. Understanding that it takes continuous refined and review to ensure that the yields of the data speak truly to that which should be achieved. If not, you need to reasses either your measurement tool or importantly, your defined outcome and related learning pathway that leads to success. Striving for objectivity is most useful, benchmarked against recognized standards.

The seamless integration of learning analytics tools into the educational landscape is essential. These tools shouldn't exist in isolation but should be intricately woven into the learning environment, whether it's a learning management system, mobile app, or web platform. They should be seamlessly connected with learning content, encompassing various elements like videos, quizzes, and simulations. Furthermore, the alignment of these tools with learning strategies, such as providing feedback, fostering reflection, and encouraging collaboration, is pivotal. To maximize their effectiveness, it's imperative that these tools are designed to be accessible, user-friendly, and engaging for both learners and educators.

Thinking of Vygotsky's Zone of Proximal Development, we often over complicate simple and tested methods of measuring learning and skills development. The ZPD asks "Where am I currently", "Where do I need to be" in terms of skills, and what mediation should occur between these two points. In saying that, a mediator is not only Facilitator, but the learning analytics can also play a mediation role in navigating learners from one point to the next. If we think of learning analytics as a mediator for learning, we may start to embody more adoption, refinement and levels of excellence in how we deploy and interact with these tools.