Active learning techniques, including collaborative programming and problem solving environments, have been widely adopted by many computer science educators. A related approach is the Treisman model, which was originally designed for the first-year calculus course and involves intensive workshops where students collaborate in small groups to solve problems. We have adapted the model for both the data structures and algorithms courses at our institution. Regression analysis indicates that students who participate in the workshops for the algorithms course perform better (0.561 grade points on a 4-point scale) than those who do not, even after accounting for prior academic performance. However, the workshops appear to have less of an effect on student grades in the data structures course. This study provides evidence that the workshop model can be an effective learning environment for students in courses primarily involving analysis, but that for courses that involve large amounts of programming, further adaptations to the model might be needed.

Active and problem-based learning environments strive to improve students' problem solving skills. To better understand students' problem solving processes and thus guide the structure and development of such environments, we asked students to solve data structures and algorithms problems and to verbalize their thoughts as they solved them. In this paper, we discuss methodological issues associated with the analysis of their verbalizations. We then analyze and discuss the relationship between statistics that describe students' problem solving process and their performance in the course they were taking at the time, either the data structures or algorithms course.

Objective. To describe an innovative active learning strategy that uses students' hands to facilitate learning and retention of major concepts related to nucleotide/nucleoside reverse transcriptase inhibitors (NRTIs). Methods. Students wrote the names of the NRTIs on their fingers, then an interactive activity used a variety of hand signs to teach the drugs. Focus groups were conducted with a total of 20 students one year after being exposed to the new teaching strategy. Students were asked five knowledge-based questions related to the subject matter to assess retention of the material. Results. On average, students answered 64% of the questions correctly. Most students (95%) used their hands to answer the knowledge-based questions. There was a statistically significant association between using hands to answer the question and answering the question correctly. When asked which active learning method was most effective, 14 (70%) participants reported "hands." Conclusion. Using students' hands was well received by this cohort of students. More research is needed to determine if this active learning method could be considered for use in other disease states to help students learn complex medications with many nuances.

No abstract

No abstract