Varying Student Behaviours Observed in the Library Prompt the Need for Further Research

• Main Author: Maria Melssen
• Format: Article
• Language: English
• Published: University of Alberta 2014-03-01
• Series: Evidence Based Library and Information Practice
• Subjects: study behaviours; non-study behaviors; library
• Online Access: https://journals.library.ualberta.ca/eblip/index.php/EBLIP/article/view/20918

Objective – To determine if the behaviours of students studying in the library are primarily study or non-study related, the extent to which these behaviours occur simultaneously, what types of study and non-study behaviours are most common, and if the time of day or use of social media have an effect on those behaviours. Design – Observational study. Setting – Two university libraries in New York. Subjects – A total of 730 university students. Methods – Two librarians at 2 separate university libraries observed and recorded the behaviours of 730 students. Observations were conducted over the course of several weeks during the Fall of 2011 in the designated study or quiet areas, reference room, and at computer terminals of the libraries. Observations were made by walking past the students or by observing them from a corner of the room for between 3 to 10 seconds per student. Student activities were recorded using a coding chart. The librarians also collected data on the perceived age, gender, and ethnicity of the students and whether the students were using a computer at the time of observation. If students displayed more than one behaviour during a single observation, such as talking on the phone while searching the library’s online catalogue, the first behaviour observed or the behaviour that was perceived by the observer to be the dominant behaviour was coded behaviour 1.The second behaviour was coded behaviour 2. Main Results – The behaviours of 730 students were observed and recorded. Two librarians at separate universities were responsible for data collection. Kappa statistical analysis was performed and inter-rater reliability was determined to be in agreement. Data was analyzed quantitatively using SPSS software. Over 90% of students observed were perceived to be under 25 years of age and 56% were women. The majority were perceived to be white (62%). Of the 730 observations, 59% (430) were study related and 37% (300) were non-study related. The most common study related behaviours included reading school-related print materials (18.8%) and typing/working on a document (12.3%). The most common non-study related behaviours included Facebook/social media (11.4%) and website/games (9.3%). The least common study related behaviour was using the school website (1.2%) and the least common non-study related behaviour was “other on the phone” (0.1%). Second behaviours were observed in 95 of the 730 students observed. Listening to music was the most common second behaviour (35.8%) and educational website was the least common (1.1%). Most study observations were made on Mondays and most non-study observations were made on Thursdays and Fridays. Throughout the entire day, study related behaviours were observed between 62-67% of the time regardless of the time of day. Students working on computers were more likely to be observed in engaging in non-study related behaviour (73%) than those not working on a computer (44%). Conclusion – Students display a variety of study and non-study behaviours throughout the day with the majority of the behaviours being study related. Students also blend study and non-study activities together, as evident in their switching between study and non-study related behaviours in a single observation and their ability to multitask. Data gathered from this study provides evidence that students view the library as not only a place for study but also a place for socialization. Several limitations of this study are acknowledged by the authors. First, behaviours that appear to be non-study related, such as watching videos on YouTube, could be study related. Many faculty members utilize social media tools such as Facebook, Twitter, and YouTube to support their course content. A student observed watching YouTube videos could be watching a professor’s lecture, not a video for entertainment purposes only. This lack of knowing definitively why students are utilizing social media while in the library may have led the authors to mistake non-study behaviour for study behaviour. An additional limitation is the short duration of time spent observing the students as well as the proximity of the observer to the student. Observations lasting longer than 3 to 10 seconds and made at a closer range to the students could provide more accurate data regarding what type of behaviours students engage in and for how much time. In addition to the before mentioned limitations, the authors acknowledge that they had no way of knowing if the individuals being observed were actual students: the assumed students could have been faculty, staff, or visitors to the university. Due to the study’s limitations, further research is needed to determine in greater detail what students are doing while they are studying in the library. This data would allow librarians to justify the need to provide both study and non-study space to meet the diverse needs of students. Conducting a cohort study would allow researchers to observe student behaviour longitudinally. It would minimize the limitations of short-term student observation as well as the proximity of the observer to the student. Research on the use of mobile technologies by students, such as smart phones, to access study related material while they are in the library would also yield valuable data regarding student study behaviours.