Students’ effort allocation to their perceived strengths and weaknesses: The moderating effect of instructional strategy

Highlights

• We examined the role of competence self-perceptions in effort allocation.

• We focused on competence self-perceptions at the dimensional within-person level.

• Students in a self-directed instructional strategy condition allocated more effort to their strengths.

• Students in a test-directed instructional strategy condition allocated more effort to their weaknesses.

• Students' effort allocation can be directed by instruction.

Abstract

To become competent professionals, students should work on both their strengths and weaknesses. Considering students' limited amount of time and energy to work on multiple subjects, it is important to know what determines their allocation of effort to their perceived relative strengths or weaknesses. In a series of five studies, we examined the moderating effect of instructional strategy (i.e., self-directed versus test-directed) on the within-person relation between perceived relative strength (i.e., strengths versus weaknesses) and allocated effort across multiple subjects. We used different methodologies (scenario, field, and experimental studies), research designs (within-person and mixed factorial), populations (secondary school, college, and university students), and measures of effort (intentions, self-reported, and behavioral). The results consistently indicate that students in a self-directed instructional strategy condition tend to allocate more effort to their relative strengths, whereas students in a test-directed instructional strategy condition tend to allocate more effort to their relative weaknesses.

Introduction

To become competent professionals who are attractive on the competitive job market, students should work on both their strengths and weaknesses. By definition, students are no experts: typically, there is ample room for improvement, both in the subjects they believe they are relatively good at (i.e., their perceived relative strengths) and in those they believe they are relatively not good at (i.e., their perceived relative weaknesses). On the one hand, improving weaknesses is indispensable for mastering a profession. Students need to diminish the gap between their present level of competency and the prevailing standard for a particular profession or degree. On the other hand, further improving their strengths enables students to excel in specific subjects, which may be a valuable asset for their future careers (Hiemstra & Van Yperen, 2015).

To guide students in their competence development, it is important for educators to know what determines students' effort allocation to their perceived relative strengths and weaknesses. Effort is key for developing competence (Ericsson and Lehmann, 1996, Ericsson et al., 1993). Therefore, students’ effort allocation to their perceived relative strengths and weaknesses amply determines how their competence evolves in the course of their education: which subjects they will be good and less good at and whether they will be more specialists or generalists by the time they graduate.

Unfortunately, the extant literature is incomprehensive on the role of perceived relative strengths and weaknesses in allocated effort. In achievement settings, both working on perceived strengths and working on perceived weaknesses can be motivating. On the one hand, perceiving a subject as a strength may foster individuals’ expectations and encourage them to set their standards even higher (Atkinson, 1964, Bandura, 1997, Ryan and Deci, 2000, Weiner, 1974). On the other hand, perceiving a subject as a weakness may signal that more effort is needed to achieve a certain goal, such as passing an exam (Carver and Schreier, 1981, Dunlosky and Ariel, 2011; Son and Metcalfe, 2000, Vancouver et al., 2008). Hence, we do not know under which conditions students who have a limited amount of time and energy to work on multiple tasks or subjects tend to allocate more effort to their strengths or their weaknesses.

Perceived relative strengths and weaknesses are competence self-perceptions that result from dimensional within-person comparisons (Möller & Marsh, 2013). Dimensional comparison entails that individuals use their competence in one dimension (e.g., spelling) as a reference for judging their competence in another dimension (e.g., calculating). Although individuals' self-evaluations are typically based on social comparison information (Klein, 1997, Van Yperen and Leander, 2014, Wheeler and Miyake, 1992, White et al., 2006), research shows that students engage in dimensional comparisons as well. For example, in a diary study among 67 university students, a total of 436 dimensional comparisons (M = 6.51) over a 14-day period was reported (Möller & Husemann, 2006). It is likely that these self-perceptions of intra-personal strengths and weaknesses affect students' learning behavior. Education is typically a multiple-tasks context, in which students work on different subjects during the same period of time. When attending lectures, following classes, doing homework, or preparing for tests, multiple subjects place competing demands on students' limited time and energy. To regulate their effort allocation, students may apply a range of strategies, including attending or skipping lectures, paying more or less attention in class, working more or less concentratedly on their homework, or spending more or less time on preparing for their tests. In such a multiple-tasks context, self-perceptions of strengths and weaknesses are likely to guide students’ allocation of effort across different subjects.

Students who believe they are good at a school subject tend to be more willing to put effort into that subject than students who believe they are less good at that subject. That is, at the between-person level, self-perceived competence is typically positively related to effort (e.g., Bandura and Locke, 2003, Latham and Pinder, 2005, Multon et al., 1991, Sadri and Robertson, 1993). However, at the within-person level, both positive and negative relations between competence self-perceptions and effort have been observed. For example, in a study in which participants engaged in a series of trials in a stock investment simulation, a positive within-person relation between self-efficacy and allocated effort was found (Seo & Ilies, 2009). In contrast, in a study on the relationship between students' self-efficacy and effort across a series of tests over an introductory course, a negative within-person relation was observed (Vancouver & Kendall, 2006). Furthermore, in a study in which participants’ self-efficacy and effort allocation were assessed across successive trials of a board-hitting game, Vancouver et al. (2008) found both positive and negative within-person relations between self-efficacy and allocated effort, depending on the level of task difficulty. Similarly, across a series of anagram tasks, both positive and negative within-person relations between self-efficacy and allocated effort were found, depending on the level of performance ambiguity of the task (Schmidt & DeShon, 2010).

These findings indicate that, at the within-person level, both positive and negative within-person relations between competence self-perceptions and allocated effort exist. However, a shared characteristic of these studies is the reliance on temporal within-person designs. That is, participants' competence self-perceptions and allocated effort were assessed on a single task across multiple occasions (i.e., a series of subsequent occasions). In contrast, educational contexts are typically multiple-tasks contexts in which students have a limited amount of time to work on a number of competing subjects. To assess the within-person relations between competence self-perceptions and allocated effort across multiple competing tasks, a dimensional within-person design is required, which entails that participants’ competence self-perceptions (i.e., their perceived relative strengths versus weaknesses) and allocated effort are assessed across multiple tasks on a single occasion (Möller & Marsh, 2013).

To date, there is surprisingly little empirical information on the dimensional within-person relations between self-perceived competence and effort allocation across multiple tasks (Sun & Frese, 2013). In one study, in which students were instructed to self-direct their learning, a positive relation was found. Specifically, Hiemstra and Van Yperen (2016) found that students who worked on multiple online learning tasks tended to allocate more effort to the tasks that they perceived as their relative strengths rather than their weaknesses. In another study, in which participants were primed on external standards, a negative relation was found. That is, Schmidt and Dolis (2009) found that participants who worked on two different scheduling tasks tended to allocate more effort to the task they perceived as harder to complete. Furthermore, in a study on the relation between perceived goal-performance discrepancies and allocated effort to multiple tasks, controlling incentives were found to moderate this relation (Schmidt & DeShon, 2007). Hence, we suspected that self-directed versus externally-directed instructions may play a moderating role in individuals’ effort allocation to their relative strengths and weaknesses.

Instructional strategies refer to the approaches and methods that teachers use to achieve the aims of instruction (Akdeniz, 2016, Moore, 2014). In education, the extent to which students are instructed to pursue self-directed versus test-directed learning goals and activities may vary across time, situations, teachers, and schools. For example, at the beginning of a semester, teachers may apply a self-directed instructional strategy (Candy, 1991, Loyens et al., 2008, Valjataga and Laanpere, 2010), by offering students a choice of readings, assignments, and exercises, and encouraging them to pursue their own interests. In contrast, toward the end of the semester, teachers may apply a test-directed instructional stategy (Roediger et al., 2011, Rohrer and Pashler, 2010), by informing students of the standards they will have to meet, and instructing them to prepare for the upcoming test-week. Similarly, some schools may apply a more self-directed instructional approach, in which students are allowed a fair amount of choice in what and how to learn. Other schools may apply a more test-directed approach, in which students are educated to pass the tests of a fixed curriculum. It is likely that these different instructional strategies (i.e., self-directed versus test-directed) affect students’ effort allocation to their strengths and weaknesses.

Interestingly, the extant literature suggests that both self-directed and test-directed instructional strategies may have both positive and negative consequences for students' effort allocation (for reviews, see Black and Wiliam, 1998, Guay et al., 2008, Lee, 2008, Loyens et al., 2008, Roediger et al., 2011, Sheldon and Biddle, 1998). For example, students have been shown to put more effort into their learning as they pursued more self-directed learning goals (Sheldon & Elliot, 1998). However, students have also been shown to waste more time once their self-direction exceeded a moderate level (Wielenga-Meijer, Taris, Wigboldus, & Kompier, 2011). Similarly, students have been found to invest more effort as they were tested more frequently (Mawhinney, Bostow, Laws, Blumenfeld, & Hopkins, 1971), but students have also been shown to prefer less effortful learning tasks when they were motivated by external rather than intrinsic incentives (Pittman, Emery, & Boggiano, 1982). A important limitation of previous studies on the role of self-direction and test-direction in effort allocation is their reliance on single-task designs. This is a misalignment with educational practice, which is a multiple-tasks context. In multiple-tasks contexts, the positive effect of an intervention on one task may come at the expense of another task. For example, a teacher's decision to test students more frequently may boost students' effort in that particular class, but simultaneously diminish students' effort in another class without more frequent testing (Mawhinney et al., 1971, Wielenga-Meijer et al., 2011). When a single task design is used in a multiple-tasks context (e.g., only considering the class in which students are tested more frequently), these adverse side effects (e.g., the negative effects on effort in another class) remain unobserved, which may lead to invalid conclusions. Therefore, in the present research, we used multiple-tasks designs to examine the effects of instructional strategy (i.e., self-directed versus test-directed) on students' allocated effort across multiple subjects.

In the present research, we examined under which conditions students, who have a limited amount of time and energy to work on multiple subjects, tend to put more effort into their strengths or their weaknesses. We hypothesized that in a self-directed instructional strategy condition (i.e., a condition in which students were instructed to pursue their own interests), students would tend to allocate more effort to their relative strengths. Conversely, in a test-directed instructional strategy condition (i.e., a condition in which students were instructed to pursue test results), students were expected to allocate more effort to their relative weaknesses. That is, in a self-directed condition, self-perceptions of relative strengths represent a signal that more intrinsic gratification (Ryan & Deci, 2000) or a higher level of performance (Locke & Latham, 2002) is attainable in the subject concerned, whereas self-perceptions of relative weaknesses signal the likelihood of less intrinsic gratification or poor future performance. In contrast, in a test-directed condition, self-perceptions of relative strengths signal that less effort is required to meet the external standards on the tasks concerned (Carver and Schreier, 1981, Vancouver et al., 2008), whereas self-perceptions of relative weaknesses signal that more effort is needed to meet the standards.

Across five studies, we used a variety of methods and measures to test our hypothesis. Studies 1 and 2 are vignette studies in which we examined the effects of instructional strategy (i.e., self-directed versus test-directed) on students' self-reported effort allocation to their strengths and weaknesses. In Study 3, we used a repeated measures design in a field setting to examine students’ self-reported effort allocation to their strengths and weaknesses as a function of changes in the instructional strategy. Finally, Studies 4 and 5 are experiments in which we tested the impact of instructional strategy on the relation between perceived relative strengths versus weaknesses and behavioral effort.