In spite of wide-spread interest in learning analytics, many educators are still uncertain about what data are available to them, whether these data are relevant to their specific contexts and how to put available data to work in the classroom in a way that is aligned with their values as teachers. This panel brings together thought leaders with experience in business, research, administration, teaching and instructional design to discuss complexities involved in the use of learning analytics, explore the challenges associated with rethinking student success in the 21st century and share some of the innovative ways they are using data to improve the lives of students today.
- Student intervention: who is the person doing the intervention, what is their motivation, what level of data/tools do we provide the?
- If you have the data > what are you going to do with it? It’s important and actually ethical to act.
- Faculty need useful data, faculty need to be convinced that using data is part of their profession and their role, faculty need to be taught what to do (if a student is “red”) what should I do?, faculty need to know they are having an effect.
- Move analytics and data to action is where to key.
- Privacy and ethics: who owns the data?, making student data public, are we profiling (and is that problematic)?
- Re: Data Privacy: What is the “contract” between the student and the institution and what is shared with whom and how. What is the level of transparency that is provided.
- How can the data be used for students to help themselves. The value of the data back to the student. Do students perceive the value.
- What is the cost benefit for the process and technology to capture the data vs the payback that that data provides. It’s not necessarily the more the better…
- Additional applications: enrollment and admissions, scheduling and program planning, course design.
- Based on data from Civitas schools, course grades have signals – students with grades of C in the first year will persist but will not graduate.
- Looking ahead: Better student decision making (remove the need for interventions), employment to careers is the goal. Can we aggregate data across our institutions to make the data more powerful and helpful to all.
- Challenges are for gathering up data from a wide array of “off campus” use of eTools in classes. Caliper and Experience APIS are helpful in providing a baseline standard.
- KEY > Use data to compliment the human intervention and decision making process vs diagnose the underlying cause using the data alone. The data is a signal and a piece, and an important signal. When an action is taken, does it have a positive effect on a student. We need to focus on measuring this interaction.
How do we get head of students and give them a “nudge” before it’s too late! Help students make better choices and give them feedback loops as to the impact of those actions.