Entrance-level predictors
When freshmen enter higher education, several variables are predictive for subsequent academic performance. First, background variables have been identified to relate to a higher probability of freshmen leaving in higher education. For example, being a male (Herweijer & Turkenburg, 2016; McNeeley, 1938), being younger (Astin, 1975) and having been educated at a lower pre- tertiary education level (Herweijer & Turkenburg, 2016) imply a higher probability of student
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leaving. The same finding holds for ethnic minority students, compared to ethnic majority students (Allen, 1999; Dutch Inspectorate of Education, 2015; Herweijer & Turkenburg, 2016; Meeuwisse, Severiens, & Born, 2010; Ooijevaar, 2010).
Teachers can take students’ background variables into account, and pay more attention with respect to how these students are progressing. However, teachers of course cannot change background variables and in this way increase academic performance. A way in which teachers might increase students’ academic performance is by improving their freshmen engagement in self-regulated learning (SRL). SRL refers to managing one’s own learning in a successful fashion by applying self-regulatory processes (SRPs) like planning, monitoring, and time management (Boekaerts & Niemiverta, 2000; Pintrich, 2000; Sitzmann & Ely, 2011; Winne, 2011; Zimmerman, 2000a). An insufficient use of SRPs for learning contributes to student delay and/or student leaving, especially in the first year of study (Gomes, 2016; Herweijer & Turkenburg, 2016; Poulussen & Roseval, 2016; Robbins et al., 2004). According to Sitzmann and Ely (2011) three kinds of SRPs that are related to academic performance can be distinguished. First, SRL has to be initiated by goals the student sets for his or her own learning (goal-setting). Second, the student is expected to use a variety of SRPs, not one SRP only, for goal-achieving. These SRPs concern metacognitive strategies such as planning, monitoring, and time management. Environmental structuring, meaning that students choose a study location that is fruitful for learning (Pintrich, 2000), is also an SRP for goal-achieving. The other SRPs for goal-achieving are the following. Attention: the degree to which students stay focused during training (Zimmerman, 2000b); motivation: the willingness to learn; and effort: the time that students devote to their learning (Zimmerman & Risenberg, 1997). According to Sitzmann and Ely (2011) a third group of SRPs consists of students’ beliefs about learning. For instance, attribution refers to what students believe to be the causes of their study progress (Zimmerman, 2000b). In addition, self-efficacy refers to trainees’ beliefs regarding their learning capability (Bandura, 1977).
Depending on the specific learning outcome, research has shown that different SRPs matter. With regard to the SRPs as formulated by Sitzmann and Ely (2011), earlier studies have found goal-setting, effort, and self-efficacy to be the strongest predictors for successful learning (successful learning is expressed in the grade point average and the quality of training transfer; Richardson, Abraham, & Bond, 2012; Robbins et al., 2004; Sitzmann & Ely, 2011). In Study 2 (Chapter 3) it was found that the strongest freshman-rated entrance-level SRPs that predict freshmen retention differ from those that predict successful learning (i.e., grade point average, training transfer) except for one: effort. That is, students’ metacognitive strategies (planning, monitoring, and time management), attention, motivation, and effort, were the strongest predictors of their retention. In addition, critical thinking was concluded to be the strongest predictor for freshmen retention, however in a negative way: critical thinkers were
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more inclined to leave or be delayed. Note that effort was concluded to be a strong predictor for both successful learning and freshmen retention.
Mentoring
Although it is possible to become a more self-regulated learner by oneself, it has been highly recommended to teach students better SRPs (Zeidner, Boekaerts, & Pintrich, 2000). In higher education, providing students support with respect to SRPs generally belongs to mentoring. Crisp and Cruz (2009) state that mentoring has the following main goals: 1) psychological and emotional support, 2) support for setting goals and choosing a career path, 3) academic subject knowledge support, and 4) being a role model. Mentoring students with respect to their SRPs can be categorized under setting goals and choosing a career path (goal 2). Such mentoring includes an assessment of the students’ strengths, weaknesses, and abilities and assistance with setting academic as well as career goals. Also, Crisp and Cruz (2009) report that the stimulation of students’ critical thinking and giving feedback on students’ plans, progress, achieving their goals, and facilitation of students’ actions is important. In line with these authors’ ideas, the current study focuses on a mentor-assessment of students’ SRPs for academic performance at entrance-level, in order to be able to give feedback and implement interventions for improving their SRPs — and thus their academic performance.
A large variety of interventions exists that teachers might implement to increase students’ SRPs, ultimately aimed at improving their academic performance (De Bruijn-Smolders, Timmers, Gawke, Schoonman, & Born, 2016; Dignath & Buettner, 2008, Dignath, Buettner, & Langfeldt, 2008; Hattie, Biggs, & Purdie, 1996). Thus, in order to offer tailored interventions to their freshmen, mentors play a crucial role in identifying to what extent students (in)sufficiently use entrance-level SRPs. However, research suggests that teachers might not be sensitive to freshmen needs with regard to SRPs that lead to delay/leaving (De Bruijn & Leeman, 2011; Gomes, 2016; Herweijer & Turkenburg, 2016; Poulussen & Roseval, 2016). In these studies, students retrospectively reported that incompetency with regard to their SRPs might have contributed to their leaving, and that their teachers had not identified a shortcoming in their SRPs, and thus had not intervened (Gomes, 2016; Herweijer & Turkenburg, 2016; Poulussen & Roseval, 2016). In the following, the literature on teacher-assessment-accuracy is reviewed to examine why mentors might not be sensitive with regard to assessing entrance-level SRPs, leading up to the present study.
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