Dr Mary-Louise Roy Manchadi

Associate Lecturer

School of Biomedical Sciences
Faculty of Medicine
m.roymanchadi@uq.edu.au
+61 7 336 56978

Overview

I currently have a number of research interests, both in Biomedical and well as in Teaching-Focussed Research.

Biomedical projects have traditionally been done with collaborators, and some of the projects have included:

  • mechanisms of action of animal venoms and toxins, and we have used the organ bath laboratory and pharmacologoical techniques as bioassays
  • study of bitter tasting compounds on pig digestive processes, to better understand activation of bitter taste receptors in vivo

Teaching-focussed interested are around university student behaviour with regard to learning activities and engagement. Universities around the world are grappling with shifts in effective and engaging educational strategies, as well as student expectations, in their delivery of content. In an age where students can do on-line courses at universities far from Australia, academics are carefully considering student engagement and success here at UQ.

  • Lecture slots currently have the bulk of contact hours in most courses, with ~39 lectures per course across a semester. These are largely recorded and used as a teaching resource. Student attendance to the traditional lecture spaces has decreased significantly across all campuses, with a UQ average of ~60% across all courses. This type of analysis has recently led to UQ offering smaller venues for larger courses in which there have been patterns of partial attendance.
  • My work seeks to better understand what motivates students to attend these spaces in their traditional sense and in the transition to an increasing number of flipped classroom models and blended learning, where the academics are less on the stage, and are instead facilitating activities for learning, while students will be engaged in learning content largely outside the lecture slots.
  • "Embracing the Unknown" Experience in third year science courses is also an interest, in which research work and its associated uncertainties cause varying levels of anxiety in some students. Best understanding this process and supporting students through it is also an interest of mine.

Qualifications

  • Doctor of Philosophy, Northwestern University

Publications

View all Publications

Supervision

View all Supervision

Available Projects

  • In association with the Spaces Management team at UQ, we have access to accurate student numbers across the university so as to track lecture attendance based on body heat entering and exiting lecture venues. Aligning the use of these sensors with course, lecturer and topic will give a rich qualitative data set. In addition to this, surveys will be done with key courses across the university for those which have high attendance and those with low – and drivers identified and shared with the Course Coordinators, along with such learnings being used to inform the Teaching and Learning Community.

    A former Honours student has shown that the biggest motivator for lecture attendance between professional, science and therapies students is feeling part of a student cohort. As the professional and therapies students tend to do all of the same courses through their degree, the bonds of friendship and community can run deep and being together with friends in educational spaces has been identified as a main driver for attendance. Science students, however, do not have this profile, as there can be wide variation in courses chosen after first year.

    I have data from second and third year science students which asks them to reflect on their experiences as a university student in learning spaces, and such data can be analysed for quality statement and frequency of responses to better inform academics around what students are actually experiencing.

  • In our third year Pharmacology course for Science students (BIOM3401), we have a practical called “Identification of Unknowns”, in which students are given an unknown drug(s), and they are asked to design experiments around identifying which drug class this might be over 2-3 weeks. This has caused some minor (and major!) anxiety in some students, as the activity is assessed as a lab report, with marks being awarded for the arguments made, and not the correct identification.

    Students were surveyed before and after the experiments to capture their thinking and concerns, and these data are available for thematic analysis. Such analysis can enable future students to be better supported, or even less supported, depending upon feedback.

  • We have meta-learning data from second and third year science students about their habits, preferred types of learning and access to information, and their perceptions of live lectures. This data can be analysed thematically, and thus contribute meaningfully to the development of blended learning courses.

View all Available Projects

Publications

Book Chapter

  • Fry, B. G., Undheim, E. A. B., Jackson, T. N. W., Georgieva, D., Vetter, I., Calvete, J. J., Schieb, H., Cribb, B. W., Yang, D. C., Daly, N. L., Manchadi, M. L. Roy, Gutierrez, J. M., Roelants, K., Lomonte, B., Nicholson, G. M., Dziemborowicz, S., Lavergne, V., Ragnarsson, L., Rash, L. D., Mobli, M., Hodgson, W. C., Casewell, N. R., Nouwens, A., Wagstaff, S. C., Ali, S. A., Whitehead, D. L., Herzig, V., Monagle, P., Kurniawan, N. D., Reeks, T. and Sunagar, K. (2015). Research methods. In Venomous reptiles and their toxins: evolution, pathophysiology and biodiscovery (pp. 153-214) New York, NY, United States: Oxford University Press.

Journal Article

Conference Publication

Grants (Administered at UQ)

PhD and MPhil Supervision

Current Supervision

  • Doctor Philosophy — Associate Advisor

Completed Supervision

Possible Research Projects

Note for students: The possible research projects listed on this page may not be comprehensive or up to date. Always feel free to contact the staff for more information, and also with your own research ideas.

  • In association with the Spaces Management team at UQ, we have access to accurate student numbers across the university so as to track lecture attendance based on body heat entering and exiting lecture venues. Aligning the use of these sensors with course, lecturer and topic will give a rich qualitative data set. In addition to this, surveys will be done with key courses across the university for those which have high attendance and those with low – and drivers identified and shared with the Course Coordinators, along with such learnings being used to inform the Teaching and Learning Community.

    A former Honours student has shown that the biggest motivator for lecture attendance between professional, science and therapies students is feeling part of a student cohort. As the professional and therapies students tend to do all of the same courses through their degree, the bonds of friendship and community can run deep and being together with friends in educational spaces has been identified as a main driver for attendance. Science students, however, do not have this profile, as there can be wide variation in courses chosen after first year.

    I have data from second and third year science students which asks them to reflect on their experiences as a university student in learning spaces, and such data can be analysed for quality statement and frequency of responses to better inform academics around what students are actually experiencing.

  • In our third year Pharmacology course for Science students (BIOM3401), we have a practical called “Identification of Unknowns”, in which students are given an unknown drug(s), and they are asked to design experiments around identifying which drug class this might be over 2-3 weeks. This has caused some minor (and major!) anxiety in some students, as the activity is assessed as a lab report, with marks being awarded for the arguments made, and not the correct identification.

    Students were surveyed before and after the experiments to capture their thinking and concerns, and these data are available for thematic analysis. Such analysis can enable future students to be better supported, or even less supported, depending upon feedback.

  • We have meta-learning data from second and third year science students about their habits, preferred types of learning and access to information, and their perceptions of live lectures. This data can be analysed thematically, and thus contribute meaningfully to the development of blended learning courses.