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Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77-101.  

Reading this paper was a light bulb moment for me, where I felt that I really understood what was involved with qualitative analysis. The authors discuss two main types of thematic analysis – inductive (coding derived from the data) and deductive (coding based on the literature). The authors also provide a detailed guide to thematic analysis, from the initial coding through to final report. Relevant to methods for data collection/analysis. 

Hartley, M. T. (2011). Examining the relationships between resilience, mental health, and academic persistence in undergraduate college students. Journal of American College Health, 59(7), 596-604.

The authors surveyed 605 university students to measure a variety of resilience variables they thought would be correlated with academic achievement. The results of this paper are quite difficult to interpret. However, the authors did find a small but significant relationship between GPA and the resilience factor ‘tenacity’. The questions used to measure ‘tenacity’ sound very similar to our category of ‘persistence’. In our current study, persistence was was reported significantly more often in students who were resilient (able to increase their grades from year 1 to year 2) compared to students who were poor achieving. Relevant to interpretation of results.


Jackson, N. (2004). Developing the concept of metalearning. Innovations in Education and Teaching International, 41(4), 391-403.  

This is a discussion paper that looks at the relationship between meta-cognition, meta-learning and self-regulated learning. The author views meta-learning as a construct that overlaps with both meta-cognition and self-regulated learning. This paper provides a solid rational for our own research, where we use ‘meta-learning tasks’ to encourage students to become aware of their learning and reflect on their self-regulated learning strategies. Relevant to rationale/motivation for study.


Krause, K.-L. D. (2005). Serious thoughts about dropping out in first year: Trends, patterns and implications for higher education. Studies in Learning, Evaluation, Innovation and Development, 2(3), 55-68.

This paper reports on the results of a nationwide survey on the first year experience in Australia. Of the 2000+ respondents, 28% of students reported having seriously considered dropping out of university in their first year. The authors report the characteristics of ‘potential dropouts’ vs. ‘persisters’. Of interest to my research, the author highlights differences in self-regulatory behaviour. For example, potential dropouts were more likely to report missing classes, spending less time on study, having difficulties with motivation and spending less time on preparation. Relevant to rationale/motivation for study.


Liem, G. A. D., & Martin, A. J. (2012). The Motivation and Engagement Scale: Theoretical framework, psychometric properties, and applied yields. Australian Psychologist, 47(1), 3-13.

This paper describes the ‘motivation and engagement wheel’, which provided the framework for the analysis of student strategies in our current research study. The wheel consists of adaptive and maladaptive dimensions, which are divided into behavioural and cognitive components. This paper also describes the motivation and engagement scale (MES), which is a survey that can be used to measure the attributes described in the wheel. Relevant to methods for data collection/analysis.


López, B. G., Cerveró, G. A., Rodríguez, J. M. S., Félix, E. G., & Esteban, P. R. G. (2013). Learning styles and approaches to learning in excellent and average first-year university students. European Journal of Psychology of Education, 28(4), 1361-1379.

In this study, excellent (n=148) and average (n=133) students completed two surveys - the Honey-Alonso Questionnaire on Learning Styles and the Revised Two-Factor Study Process Questionnaire (R-SPQ-2). The authors found that excellent students were more likely to use a deep approach to learning and to prefer a reflective learning style compared to average achievers. These results support our own results, which showed that high achieving students were more likely to report mastery orientation than low achieving students. Relevant to interpretation of results.


Martin, A. J., & Marsh, H. W. (2009). Academic resilience and academic buoyancy: Multidimensional and hierarchical conceptual framing of causes, correlates and cognate constructs. Oxford Review of Education, 35(3), 353-370.

This paper describes a framework for distinguishing between academic ‘buoyancy’ and academic ‘resilience’. By doing so, the authors distinguish between everyday academic challenges (such as a lower than expected mark on one assessment item) and academic adversity (such as repeated failure). This provides a useful framework for our current study, where we asked students about the factors that hindered their learning throughout semester and the strategies used to overcome hindrances. Relevant to rationale/motivation for study.


Tanner, K. D. (2012). Promoting student metacognition. CBE-Life Sciences Education, 11(2), 113-120.  

This article discusses various ways that metacognition can be incorporated into the tertiary biology curriculum. The author provides examples of meta-cognitive questions that can be embedded into teaching activities and assessment items, and provides the reader with general metacognitive concepts that can be targeted. The meta-cognitive questions outlined in this paper have guided the development of our own meta-learning questions used in the current study and beyond. Relevant to study design.


Turner, J. E., & Husman, J. (2008). Emotional and cognitive self-regulation following academic shame. Journal of Advanced Academics, 20(1), 138-173.

Describes a qualitative study of students’ reactions to academic shame. Participants  (n=8) were students who reported feeling shame after receiving exam 1 marks for an upper level psychology course, and who agreed to be interviewed at the end of semester. Of these eight students, three students increased their exam scores from 1 to 2, four students received similar exam scores for exam 1 and 2 but did not feel shame the second time, and one student did not improve in exam 2 but still felt shame. The authors describe the students as embarking on a path of self-regulation (those who improved) and non-regulation (those who did not improve). Self-regulators had important future goals and were determined to succeed. They made rapid, conscious decisions to improve and used strategies that were different from the first exam attempt. Non-regulators had unclear goals, had difficulty sustaining study efforts and used the same strategies as the first exam. This paper supports the idea that students can recover from academic adversity (shame) by developing self-regulatory skills. Relevant to rationale/motivation for study.


Zimmerman, B. J. (2000). Attaining self-regulation: A social cognitive perspective. In M. Boekaerts, P. Pintrich & M. Zeidner (Eds.), Handbook of Self-Regulation (pp. 13-39). San Diego, California: Academic Press.

This is one of Zimmerman’s earlier papers presenting his model of self-regulated learning. Although there are other models of self-regulated learning, Zimmerman’s model contains clearly defined processes that can be easily measured in students. This model of self-regulated learning is cyclical and contains three phases: forethought (processes that occur prior to a learning task, such as planning and goal setting), performance (processes that occur during a learning task) and self-reflection (processes that occur after a learning task, such as self-evaluation). Relevant to rationale/motivation for study.

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