Identify the students at risk by using various data sources including LMS. Identify the engagement level and intervene before it is too late. "One size DOES NOT fit ALL".

#DeepDiveIntoData 📘 Enhancing student engagement requires a blend of technology and personal touch. Utilize LMS data to trace their digital footprints in the learning journey, understanding where they thrive or stumble. Yet, don't overlook the power of face-to-face conversations. These discussions offer invaluable insights beyond digital data, revealing personal challenges and preferences that might not be captured in online platforms. By marrying quantitative data from systems like Canvas with qualitative insights from direct conversations, you create a holistic view of each student's experience. This dual approach enables targeted strategies that address both academic and personal barriers to engagement. 📘 #PersonalizedEngagement

Improving student engagement through data in higher education can be a multifaceted endeavor, leveraging various sources of information to enhance the learning experience and support student success. The strategies like Learning Analytics, Personalized Learning Paths, Predictive Analytics, Feedback and Assessment, Social Network Analysis, Gamification, Feedback Loops, Ethical Considerations, may be very effective particularly to address the students engagements. By harnessing the power of data, HEI Sector can gain valuable insights into student behavior and performance, enabling them to implement targeted interventions and create personalized learning experiences that enhance student engagement and support academic success.

Today While handling a case I asked groups to prepare on different aspects and talk about it without a PPT. Their contributions were more than what a single pasture of a case could cover. It was a very spontaneous analysis and value addition to the class discussion.

Customized assignments to every student based on his/her weakness is need of the hour. The student data regarding their performance, background and hobbies help in customizing the homework according to need. Also based on data and other criteria, self learning, tutored videos can help.

To enhance student engagement in higher education through data utilization, a strategy focused on personalizing the learning experience and monitoring progress can be implemented. Personalizing the education process is crucial. By analyzing data on students' preferred learning styles and methods, educators can tailor their instruction to better meet individual needs. This might involve incorporating visual aids for those who learn better visually or integrating interactive activities to boost engagement. Additionally, considering students' educational backgrounds and demographics allows for adjustments in support and resources offered, such as extra tutoring sessions or specific learning materials.

As an educator, my major n concern is about student engagement in the courses. data analytics in Canvas LMS is an effective tool to follow up and improve my teaching. It helps me on daily basis to analyze student activities by tracking course participation, assignments students participate in and identifying areas where engagement might be lacking. Also, monitoring students learning progress by tracking quiz and assignment scores. This is very important to Identify areas where students struggle and adjust my teaching methods accordingly.

Utilizing data analytics in Canvas is considered an effective English language teaching tool for teachers. As I mentioned earlier, it helps me to identify areas where students struggle and adjust my teaching methods accordingly. Using Canvas LMS analytics dashboards helps me to pinpoint topics or skills needing more attention and identifying potential time management issues among students.

I'll give an example of something I worked on recently that relates to this. I worked with a program that was trying to evaluate a grading standard they had for its efficacy toward a licensure exam. Within the process of that, I developed models to predict the pass rate on the licensure exam based on how they did in class. As we all anecdotally can attest, lack of engagement harms grades. After all, even the disengaged student was to pass a licensure exam for their career. The epitome of personalized content doesn't have to be a course material. It can be a "hey, based on your performance in these classes, our data from prior students suggests you're this likely to pass licensure." That often prompts: how do I fix this? Engagement.

In the class I found students struggling and I would try to get online discussions going. It was easier for them to interact, especially the introvert. Then using those online discussions to build on in the classroom. From there I would give students a chance to give opinions or observations.

Evaluating the impact of teaching actions through data analysis marks a crucial step towards continuous improvement in education. By assessing student satisfaction, engagement, and achievement, educators gain valuable insights into the effectiveness of their methods and course design. Analyzing metrics such as recommendation rates, interaction frequency, and learning outcomes provides a comprehensive understanding of the learning experience. This data-driven approach empowers educators to make informed adjustments, tailor their teaching strategies, and ultimately enhance student success and satisfaction in the learning journey.

From my experience, this is the first step that needs to be done. By having the evaluation data, we can immidiately see the gap and the issue that we have. From here we can formulate an understanding and then move to create a best possible next course of action.

Institutions are drowning in data. Leaders should involve data scientists to surface trends in large datasets and communicate recommendations to key stakeholders. HEI's should also involve faculty in all stages of data communication, including eliciting input from faculty on what types of data may be most helpful for understanding a problem, providing mid-point data insights as a project is on-going, and developing presentations of data results that are tailored to the discipline fields and needs of particular departments. Clear and easy-to-understand data communication ensures that the hard work of data analysis yields insights that benefit many at the institution, including students.

Providing feedback to students is crucial, and this should go beyond merely pointing out areas for improvement to also celebrate their successes. The aim is to foster an environment where students feel valued and motivated to continue their efforts. Achieving this involves adopting a personalized approach to feedback, highlighting the specific progress of each student and offering practical advice for further development. This method ensures that students not only understand their areas of weakness but also recognize their achievements and understand how they can continue to grow.

Privacy is a critical issue. I just published a paper about how privacy can be compromised even without direct and obvious PII. It might come from another source or it might be a combination which is a conditional functional dependency. That type of privacy violation is much harder to detect, but no less harmful.

In utilizing data to enhance teaching, it's imperative to secure informed consent from students, clearly outlining the use, benefits, and potential risks of their data, thereby respecting their autonomy and giving them control over their information. Concurrently, ensure equity and fairness in data use, critically evaluating data and algorithms for biases to prevent perpetuating inequalities - this might sound like a no brainer but might happen faster and more often than anticipated. Whether the whole process is automated or still done manually.

Improving student engagement in higher education significantly benefits from an ethical and responsible approach to data use. Central to this approach is the imperative to respect students' privacy and consent, ensuring the security and confidentiality of the information collected. The goal is to leverage data to enhance teaching without compromising student trust. To achieve this, it's critical to ensure students are thoroughly informed about the types of data collected, the reasons for collection, and the specific benefits derived from analyzing this data. This could involve organizing informational sessions or creating clear, accessible documents that detail these aspects.

Absolutely, engaging students in higher education (HE) requires more than just data collection and interpretation. HE students often face numerous personal, social, and professional challenges simultaneously, leading to distractions and potential disengagement. In addition to academic content, providing emotional support and guidance is crucial for their overall well-being and academic success. Class teachers play a vital role not only in delivering course material but also in creating a supportive and inclusive learning environment where students feel valued, understood, and empowered to overcome challenges.

Struggling to engage students in higher education is a common challenge faced by many instructors. Using data to improve teaching in higher education involves analyzing assessment data, student feedback surveys, and learning analytics to identify patterns and areas for improvement in teaching methods. Assessment data, such as exam scores and assignment grades, can reveal trends in student performance and highlight areas of difficulty. Student feedback surveys provide insights into students' experiences and preferences, guiding instructional adjustments. Learning analytics tools track student engagement and participation, helping identify disengaged students who may need additional support.

I use active data collection in the classroom to show students how much they are learning. For every topic in a course, we have a "check-in" and a "check-out". Students check in at the beginning of class by answering a few general questions about the topic. We review their responses so they can see how they are doing as a class before we start the lectures. I don't give them the correct answers, we just look at what the class totals. At the end of the lectures, they check out by answering the same questions they answered at check-in. We do a side-by-side comparison of their responses at check-in versus check-out. The data tells the story of their learning and they love it!

Understanding that the learning process is not centered on the teacher as the sole decision maker regarding how the course will be taught is crucial, especially when there is a generational gap. Listening to the students and counting on their help can enrich your teaching strategies portfolio and foster greater integration within the group, within a centrally outlined plan, obviously guided by your guidelines as a teacher.

A question that is often missed is what other factors are influencing your students? - Are there new, unusual, or difficult circumstances in the student's personal life? or world at large? - Perhaps switching from in-person to online learning in 2 weeks? _ New technology that is difficult to navigate? - Personal financial pressures? - New legal or illegal substances available? - Dorm alarms that went off at 2am? While it's easy for educators to focus solely on what they know and do (and are reluctant to change), these events can and do affect students.