I recognize
that Day 1 afternoon went “missing”. I
presented my poster and that consumed the sum total of my time. While I am happy with all that I achieved with my poster (writing IRB protocol, independent work, analyzing my teaching, et cetera), it was not considered as a finalist for the student research competition (SRC). Yet I received significant feedback and a number of follow-ons that I will have to try to evaluate the next time(s) I teach. I have been doing an excellent job of networking and speaking with my colleagues. And I have seen several exciting techniques to improve my teaching.
In traveling, take some time to prepare students. Let them know what to expect. For example, it is okay to miss some paper sessions, and even return to your room entirely. It is okay to ask questions 1:1. Find groups where people are being introduced and join in. Student volunteering, while takes time, also gives an additional individuals that you will know. Use the people you know to introduce you to others at the conference.
This is just what it sounds. A Ruby based framework that enables writing simple unit tests that will then be applied to a full simulation of the assembly executed.
The presenter(s) were not at this poster, but it showed a high quality interface for seeing the scheduling of threads according to different scheduling policies. The intent here was not to explore races and parallelism, but rather see how scheduling decisions are made in an OS.
I was not expecting this poster. You are walking along and then see 4 Raspberry Pi's all networked together. Raspberry Pis and HPC?! A small setup, but it is an interesting development that takes advantage of the low cost Pi and still provide an HPC platform for students.
Plastic parts all worked together to form replicas of Pascal's mechanical calculator. Interesting and student assembled.
Teams of 4
students, approach is evaluated on courses from three years of major (sophomore
on up). Teams are formed with CATME
(particularly using dissimilar GPAs in a group), as well as partner selection
(when possible). Students provide peer
evaluations after each stage of the project.
Significant data collection looking particularly at what students prefer
for to be the evaluation policy (between 100% of grade for the group’s work to
100% of the grade for the individual’s contribution). This question was taken repeatedly throughout
the semester, which leads to whether student preferences change? More senior students prefer more weight being
attributed to group. The predictor for
what grade split is at what point in the course is this surveyed, and effectively
as soon as the teams are formed the students prefer to be graded primarily as a
group. Follow on study is looking at
experience with team projects, trust in the ability to evaluate individual
contribution, and other questions. This
is a hopeful data point.
How do faculty become aware and why do they try out teaching practices? 66 participants in CS, including chairs, tenure-track faculty, teaching faculty, and Ph.D. student instructors across 36 institutions. First, the mental model of what an instructor does can differ significantly from what the instructor is actually doing. Second, faculty can find out about practices through a variety of approaches, such as self-identifying that there is possible improvement in their teaching. Faculty often trust other faculty like them (researchers to researches, lecturers to lecturers). Third, when adopting a practice, faculty need to evaluate the effectiveness (see also my poster, student feedback, etc). -- My efforts in this have been having different faculty (my recommendation letter writers) view my lectures / teaching, and thereby giving them demonstrations of different practices.
"We lost the war on cheating" Instead, we have to meet with students such that they are demonstrating their understanding of the code. The requirements of submissions: attribute your sources and understand your submission. Enables students to work together, use all sources, develop interview skills. Enables reuse of assignments. Grading is now 40% correctness / 60% code interview. Rubric for each interview. Students should arrive early and have their laptop ready to present / explain. Students were better able to learn and complete the assignments, as well as feedback for improvement. Students also felt better able to learn the material by being able to collaborate and not constrained by a collaboration policy. There are some stressors, such as TAs having to meet with hundreds of students, as well as their inconsistencies. -- This was perhaps the most exciting new technique that I saw / heard about.
No comments:
Post a Comment