A Preliminary Analysis of the Logged Questions that Students Ask in Introductory Computer Science

Asking questions is widely believed to contribute to student learning, but little is known about the questions that students ask or how to exploit them in tutorial interventions to help students learn. This paper presents a preliminary analysis of student questions from an introductory computer science course, logged automatically when students requested help during open lab consulting hours. The data set consists of one hundred and forty two questions that introductory computer science students asked while working on four weekly programming assignments. The initial data suggest that student questions can be repetitive in nature and different students ask different kinds of questions. The paper concludes by suggesting that an analysis technique that is more sophisticated than cosine similarity applied to raw text with stop words removed will be necessary to classify student initiated questions.

• Type: Conference
• Year: 2008
• Where: EDM
• Authors: Cecily Heiner
• Keywords: Asking Questions, Data Mining, EDM 2008, Questions, Student Questions