Faculty Performance Consideration | Origin: OP121
This is a general discussion forum for the following learning topic:
Managing Online Faculty at a Distance --> Faculty Performance Consideration
Post what you've learned about this topic and how you intend to apply it. Feel free to post questions and comments too.
Comment on Edgardo Eugenio Enamorado's post:
Your point about qualitative data fostering empathy with students stood out to me — that human dimension is easy to overlook when so much of the conversation centers on metrics and dashboards. The quantitative side gives us the ground floor, but it's the qualitative attention to each student that builds the trust needed for real learning to happen online.
With Benevolence, Shannon
Comment on Zhanna Martirosyan's post:
That summary captures it well — especially the move from generalized metrics to predictive, course-specific indicators. That shift seems small on paper but reframes how we think about both faculty development and curriculum refinement. Behavior-based feedback tied to actual course context gives instructors something they can act on, rather than abstract benchmarks that don't always reflect what the classroom is asking of them.
With Benevolence, Shannon
The most useful takeaway from this module was the shift from lagging, negative indicators (attrition, failing grades, post counts) to predictive, positive indicators built through regression analysis on specific instructor behaviors tied to specific curricular components. Generic averages and "best practice" thresholds often miss the mark — the 2009 US Department of Education meta-analysis confirmed that none of the general best practices showed significant evidence of contribution to student success.
What stood out most was the principle that each class has its own roadmap. Behavioral profiles built from course-specific statistics are far more useful than generalized expectations applied uniformly across instructors and weeks.
I also valued the reminder that corrective action shouldn't focus on the instructor alone. Curriculum materials and technology applications must be part of the analysis, since high performance in one section often points to a particular approach or tool worth replicating.
Application: At the CVCC Amherst Early College Center, I want to think of quantitative thresholds as the "ground floor" — a starting point — and shift more attention to the qualitative dimensions of instructor-student interaction once basic activity levels are met. I also plan to look more carefully at curriculum and technology when reviewing performance, rather than defaulting to instructor-focused corrections.
With Benevolence, Shannon
I learned that faculty performance in online education is best evaluated using both quantitative data and qualitative feedback, rather than simple activity counts or generic benchmarks. Effective improvement depends on clear expectations, ongoing monitoring, and course-specific, data-driven analysis of what actually supports student success. I would apply this by using consistent feedback and individualized support to help instructors improve within the context of their specific courses.
Faculty performance considerations should be reviewed holistically, taking into account teaching effectiveness, professional responsibilities, and adherence to institutional expectations. When performance concerns are identified, the focus is on timely feedback, clear expectations, and appropriate support to promote improvement and success.
Incorporating qualitative and quantitative data aligns with a thorough evaluation. Evaluations should occur within the first 30 days to also support faculty success, early recognition of items or practices that need to be revised or embellished could impact course outcomes.
From this module, I learned that effective online education depends on thoughtful faculty onboarding, clear expectations, strong LMS training, and data-informed monitoring of instructional practices. The module emphasized moving beyond generalized metrics and “one-size-fits-all” standards toward predictive, course-specific indicators that support meaningful improvement in both teaching and student outcomes.
I intend to apply this learning by supporting structured faculty orientation, emphasizing hands-on LMS training, and using contextual, behavior-based feedback to guide faculty development, curriculum refinement, and continuous instructional improvement.
Faculty should be evaluated online within 30 days of instruction.
Supervisor should review online class within 30 days of teaching the first class, then quarterly.
The supervisor should work with faculty to review measures about the instructional activities for classes taught
Focusing only on quantitative metrics can take away from what really matters in the online environment. Instructors may become too aware of making a certain number of posts or characters and less concerned with what will make the class successful.
When evaluating faculty, the use of qualitative and quantitative methods is essential. In addition, the faculty, curriculum, and technology are some of the variables that must be assessed as they impact student success and performance.
How to give feedback and implement the corrective actions.
I appreciate equally emphasizing qualitative since quantitative metrics are never a complete picture. Also appreciate the tips of evaluating performance.
An effective assessment of faculty performance requires a combination of quantitative and qualitative metrics.
Having a plan with multiple components should be followed to make sure you are addressing the different part of online instruction.
Comment on Edgardo Eugenio Enamorado's post:
El enfoque estandarizado no se ha considerado eficaz en la investigación de la última década.
Muchas actividades claves, datos cualitativos que en la virtualidad son muy importantes para lograr empatía con los estudiantes, muchos datos cuantitativos y sobre todo el seguimiento a cada actividad muy importante
focus on multiple areas of assessment.
