Services for Faculty and Graduate Students
Individual consultations:
TEACHING AND LEARNING
Do you have questions about teaching and learning? Meet with our Faculty Developers to discuss any aspect of your teaching—from course design to specific activities, strategies, or ideas you want to try out in your class. We can meet with you to brainstorm, share resources and explore your questions. Email lli@lums.edu.pk to schedule a consultation.
LLI has always been devoted to quality enhancement in teaching and learning, and to facilitate you in your pedagogical pursuits, we offer consultation sessions to faculty.
These consultation sessions could be focused on providing support in areas such as (but not limited to) course delivery, teaching methodology, feedback and evaluation, assessments, informal/formal classroom observations etc.
We are offering two types of consultation sessions:
- Individual: Face to Face or Online
- Faculty as a group session
If you or your faculty are interested in booking a consultation session and/or have any queries regarding pedagogy, please feel free to make an appointment by contacting us at lli@lums.edu.pk an
Procedure to be followed for individual sessions:
- Describe your query in no less than 80-100 words.
- Suggest at least 3 time slots of 30 minutes each as your availability and preferred mode of communication (virtual via Zoom or F2F at the LLI) for the consultation. The slots should be timed at least a week after your consultation request.
- LLI team will then get back to you, suggesting an available slot.
Procedure to be followed for Faculty as a group consultation:
- Describe your query in no less than 80-100 words
- Faculty sessions should be requested at least 2-3 weeks after the request has been made.
- Sessions could be up 30 minutes to an hour long.
- These sessions can be face-to-face at the LLI or virtual via Zoom Please indicate your preference for the mode of session when the request is made.
- An attendance of at least 5-10 faculty members is required for the hour-long sessions.
- Topics should be related to teaching and learning
We are deeply motivated to provide support and guidance to you in your teaching process and look forward to hearing from you.
Early Course Feedback
Interested in collecting student feedback midway through the semester? An Early Course Feedback (ECF) is a great way to hear from students about their learning experience in your course and can give you valuable feedback in time to adjust during the semester! The ECF process involves three parts: a pre-ECF meeting with a Faculty Developer to discuss your course and any aspects you want feedback on, an ECF session where a Faculty Developer visits your class for 20-30 minutes to collect student feedback, and a post-ECF meeting to discuss the student feedback and next steps. You will also receive a written report containing the feedback.
Classroom Observations
Looking to enhance your teaching skills? Join us for a classroom observation with a colleague from the Trefny Center. This process is simple and consists of three steps:
- Pre-Observation Planning: First, we'll have a chat to decide which parts of your teaching you'd like to improve.
- Classroom Observation: Next, an LLI team member will observe one of your classes.
- Post-Observation Debrief: Finally, we'll discuss the observation, offering feedback and ideas to help you grow.
You'll also get a written report with all the feedback. Interested? Email lli@lums.edu.pk to set up your observation.
AI Integration
The LUMS Learning Institute offers invaluable support for integrating AI into the educational landscape. Faculty members across HSS, Education, SDSB, SAHSOL, and SSE can seek guidance on effectively incorporating AI into course design, assessment, and grading processes. LLI provides expertise on enhancing student engagement, tailoring learning experiences, and creating personalized learning journeys, ensuring that AI is leveraged to its full potential for improved educational outcomes, given that it has trained over 400 faculty and professionals from within and outside of LUMS in its AI workshops.
