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Study and learner behaviours of high school boys

Posted on 7 September 2018

The intersection between the cognitive sciences and education is a hot topic. Critical groups, like The Learning Scientists and Retrieval Practice, are bridging the divide that has traditionally existed between the fields. With a higher propensity to translate what works in the lab to the milieu of the classroom setting—how, when and what strategies students use—the conversations around learning have never been as rich or dynamic as they are now.

Much of the debate around teaching and learning reflects the ideology of the proponent rather than affecting long-term student behaviour. Various curriculum and pedagogical interventions by teachers, leaders and systems rarely consider or interrogate the impact of and interplay between students’ existing beliefs, perspectives and practices. Typically, students are the product of, rather than an active agent in, the learning process. The likes of Dunlosky, Rawson, Marsh, Nathan, and Willingham (2013), Hartwig and Dunlosky (2012) and Karpicke, Butler, and Roediger (2009) point to a deficit in tertiary students use of effective learning strategies, with an over-reliance on inefficient (i.e. re-reading textbook or notes, cramming, etc) techniques that have been shown to have cause limited learning gain. Agarwal, D’Antonio, Roediger, McDermott, and McDaniel (2014)presents the only study that has explored the study practices and preference of high school students. As a consequence, before launching a study skills intervention that seeks to correct learning issues, we need to better understand the existing study and learner behaviours of our boys.

The Making Effective Study Strategies Stick project (one of our university partnerships with UQ) addressed this gap in our understanding through the survey Years 7 to 11 students (aged 12 to 16 years) at Anglican Church Grammar School (Churchie). From a sample of 928 students (participation of 89.5 per cent), the superficial analysis presented a baseline measure of how each year level perceived their study behaviours and preferences. Also, the survey captured how they saw themselves as learners and their existing behaviours (this will be the subject of future articles).

Preliminary study behaviour analysis

Do students feel they know how to study?
This is a innocuous question, but one that needs to be asked before an intervention seeking to enhance the efficacy and efficiency of study behaviours. The analysis revealed little difference in how boys in Year 7 and Year 11 rated their study ability (Figure 1). The Year 10 cohort presented the lowest self-assessment of the five year-level cohorts. Further analysis of the distribution of their responses to the Likert-scale items (Figure 2) identified a higher level of uncertainty in their study ability when compared to their peers. Future analysis will explore the mediating factors that underpin how students view their ability to study.



Figure 1: Average cohort response (with 95 per cent confidence interval) to ‘I feel that I know how to study’?



Figure 2: Cohort distribution of Likert-scale response of self-assessment of their ability to study.

Study behaviours
The survey highlighted the various study strategies that the boys utilise and their preferred technique. Figure 3 outlines the multiplicitous nature of many boys’ study routines, with many identifying they employe four or more study techniques (see Figure 4). Many boys rely on the common practices of re-reading, memorisation and completing questions/problems.

Interestingly, there were age-based trends in the prevalence of both rewriting notes and cramming. Older Years 10 and 11 students are more likely to use these when compared to the younger students. However, these students also identified a greater number of strategies employed, when compared to those from the younger year-levels.


Figure 3: Study strategies used by students by cohort.


Figure 4: Number of study strategies used by students

Such a trend could reflect the changing nature of higher-stakes student assessment as they progress through the school, but warrants further investigation. However, these results are interesting from the perspective that the majority of each cohort utilises an array of study techniques. Such diverse use presents a different perspective on study strategies of university students found by Karpicke et al. (2009), which found that majority of university students used two to three strategies (see Figure 4). Karpicke et al. (2009) also found that most-frequent study strategy, by far, is a repetitive reading of notes or textbooks, with practice problems a distant second. Furthermore, the study found that a clear majority of students used two or three of the 11 listed strategies.

Figure 4: University student study strategy use and preference. Survey data from Karpicke, Butler, & Roediger (2009)

Preferred study strategy
The survey asked students to identify their preferred study strategy (see Figure 5). Unlike many similar studies that identified that university students preferred strategies are re-reading (for example Dunlosky et al., 2013; Karpicke et al., 2009), doing questions or problems from their OneNote notebook or textbook was by far the most preferred strategy. Furthermore, this dominance of this technique, coupled with the next most preferred technique of doing the practice test, does present an interesting comparison to the Agarwal et al. (2014)that found most students in their sample preferred ‘reviewing materials’.

The prevalence of re-reading as the most preferred strategy declined with the age of the student. At the same time, there was an increased propensity for older students to rewrite notes. The relatively high, but inconsistent, preferred use of the practice test, an excellent example of the highly effective ‘retrieval practice’ strategy (Karpicke & Roediger, 2008), does warrant further investigation. A potential explanation is an interplay between all cohorts use of doing questions/problem and the practice test, with both engaging in the process of retrieval practice.

When comparing student preference in technique with their self-assessment of their ability to study, the noticeable increase in the Year 10 cohort’s preference for cramming requires further investigation. Potentially, the increased preference in cramming in the Year 10 cohort (when compared to their peers) could reflect the low self-assessment of their ability to study. Cramming is a low-efficiency strategy that students call upon, often due to the absence of alternative and previous success on exams that favour short-term and superficial learning (Dunlosky, 2013; Kornell, 2009).


Figure 5: Preferred study strategies of students by cohort

Where to next?

Subsequent Churchie Research Centre articles will focus on student responses to the learner behaviours domains of the survey instrument. A more in-depth analysis will follow looking at the potential influence of the factors of IQ, Emotional Intelligence, work ethic, prior academic achievement (both internal and external data) and personality. Longitudinal application of the survey and analysis will illuminate how cohort and individuals’ study and learner behaviours change (or do not) throughout their secondary schooling.

 

Reference List

Agarwal, P. K., D’Antonio, L., Roediger, H. L., McDermott, K. B., & McDaniel, M. A. (2014). Classroom-based programmes of retrieval practice reduce middle school and high school students’ test anxiety. Journal of Applied Research in Memory and Cognition, 3, 131-139.

Dunlosky, J. (2013). Strengthening the student toolbox: Study strategies to boost learning. American Educator, 37(3), 12-21.

Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J., & Willingham, D. T. (2013). Improving students’ learning with effective learning techniques: Promising directions from cognitive and educational psychology. Psychological Science in the Public Interest, 14(1), 4-58.

Hartwig, M. K., & Dunlosky, J. (2012). Study strategies of college students: Are self-testing and scheduling related to achievement? Psychonomic Bulletin & Review, 19, 126–134.

Karpicke, J. D., Butler, A. C., & Roediger, H. L. (2009). Metacognitive strategies in student learning: do students practise retrieval when they study on their own? Memory, 17(4), 471-479. doi:10.1080/09658210802647009

Karpicke, J. D., & Roediger, H. L. (2008). The critical importance of retrieval for learning. Science, 319(5865), 966-968. doi:10.1126/science.1152408

Kornell, N. (2009). Optimising learning using flashcards: Spacing is more effective than cramming. Applied Cognitive Psychology, 23(9), 1297-1317. doi:10.1002/acp.1537