Instructor: Dr. Monica Linden, 2014 Teaching with Technology Award recipient
Course: NEUR1030 – Neural Systems
Course overview: NEUR1030 is a large lecture course serving about 150 students and required for Neuroscience and Cognitive Neuroscience concentrators. In the course, students are pushed to work on their higher-order cognitive skills including applying concepts to new situations and interpreting and analyzing data and research findings.
View course syllabus
Goal for project/technology use
- Helping students to really “think like neuroscientists”.
- Improve their higher-order cognitive skills.
Technologies and teaching methods used
- Canvas site: Allows students to be organized. Readings for each lecture are added to the calendar. Assessments and grades are in Canvas.
- Electronic course reader: provides students with a free option over the printed course reader and includes hyperlinks for easy referencing through the book.
- Lecture using multimedia PowerPoints: Allows Monica to spark interest in certain topics, and better illustrate complicated concepts.
- iClickers: Assessing students in real-time with iClickers gives an idea of where students are in terms of the lower order knowledge which allows Monica to move onto higher order ideas more efficiently.
- Lecture capture: Allows students to re-watch complicated parts of the lecture or to catch-up if they miss class. It was also used when Monica could not attend class due to a conference.
- Computerized exams with enhanced feedback: Students took their exams (which include multiple choice and short answer/brief essay questions) on the computer so that Monica and her TAs could easily generate detailed, personalized exam feedback forms for the students. The individualized feedback included a breakdown of exam performance based on subject material, learning objectives, and levels of Bloom’s Taxonomy, in an effort to help students refine their study habits to improve performance in the course.
See a sample student report
To assess the effects of the detailed exam feedback, exam results from the semester with the intervention (2014) were compared to exam results from the previous year’s course without the intervention (2013). In both years, student performance improved on all types of exam questions throughout the semester. Students’ performance on higher-order questions improved more throughout the semester in 2014 as compared to 2013. However, there was no difference between years in improvement on questions using lower-order cognitive thinking. A student attitudes survey suggests that while students understood the feedback, only around half of the students felt the reports supported their success in the course. Overall, these results suggest that assessment feedback detailing the level of thinking skills may improve student performance on assessment questions requiring higher-order cognitive skills. However, more effort may be needed to demonstrate the importance of this feedback to the students.
Looking back, moving forward
Future work planned:
- Would like to add interactive elements to the electronic course reader
- Put more effort to help students understand how to use the feedback to refine their study habits
Tips for colleagues:
- Do not try to do it alone. Ask for help from Academic Technology team.
- Take it one step at a time and follow iterative process rather than doing everything at once.
- When using exam proctoring software, conduct a trial quiz before the actual exam.
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