Optional Learning Opportunities

Abstract

The effects of offering and seizing optional learning opportunities rarely have been investigated. Thus, university instructors have no basis on which to decide whether offering optional learning opportunities to their students would be worth the effort and which students would seize and benefit from them. To target these questions, we designed a teaching−learning format in which we offered psychology undergraduates optional learning opportunities throughout the semester. We investigated the cognitive and motivational prerequisites of N=108 students who seized versus forwent the learning opportunities and compared their learning outcomes both with and without controlling for prerequisites. Concerning prerequisites, we found that students who seized the learning opportunities had a better school grade point average, whereas they did not differ from the students who did not seize the learning opportunities regarding their prior knowledge or their motivational prerequisites and outcomes. Students who seized learning opportunities had better performance outcomes, even after initial prerequisites or time spent learning were controlled for. We conclude that there is a benefit of seizing optional learning opportunities for students, and therefore, instructors should enable their students to take this chance.

Keywords

optional learning opportunities learning-related prerequisites choice learning outcomes higher education

If all students have to accomplish the same tasks, one can assume that students with better prerequisites will take advantage of their better basis and outperform other students. However, it is less clear how students with better and less good prerequisites will react when confronted with optional learning opportunities. Unsworth and Kauter (2008) used a voluntary earlybird scheme to provide feedback to students on a draft of a literature review. The usage of the scheme was quite low, but it had positive effects on students’ revisions. However, the study neither analyzed characteristics of the students who used the scheme (e.g., their learning-related prerequisites) nor controlled for these characteristics when evaluating the scheme’s effect. Furthermore, the students received feedback on a draft of their course assignment so that direct feedback effects can be expected. However, it is less clear whether there are more general effects of seizing optional learning opportunities (and doing so more than once). If we knew more about the students who seize optional learning opportunities and whether or not there is a benefit from seizing them, instructors would be able to decide whether they offer optional learning opportunities.

Students’ Learning-Related Prerequisites

School grade point average (GPA) has been found to be a strong predictor of future academic success (Kobrin, Patterson, Shaw, Mattern, & Barbuti, 2008; Robbins et al., 2004; Schuler, Funke, & Baron-Boldt, 1990). Students’ school GPA comprises many grades over a longer period from different teachers, and it does not only reflect grades but also characteristics that are important for academic success (e.g., general and specific study skills, knowledge or personality traits).

A more proximal and domain-specific prerequisite of learning that has been shown to be an important predictor of future achievement is prior knowledge (Dochy, Segers, & Buehl, 1999).

Another important prerequisite for learning is motivation. Students who are highly motivated are supposed to put more effort into learning. At the same time, motivation is an important outcome of educational processes. A well-established theoretical framework is the theory by Wigfield and Eccles (2000), that is, expectancy-value theory. Both the beliefs about how well one will do on an activity and the extent to which one values an activity are related to educational achievement (Hansford & Hattie, 1982; Möller, Pohlmann, Köller, & Marsh, 2009; Schiefele, Krapp, & Winteler, 1992; Spinath, Spinath, Harlaar, & Plomin, 2006).

The Present Investigation

The aim of the present study was to answer three research questions: First, which students seize optional learning opportunities? That is, how do students who seize optional learning opportunities differ from students who do not seize optional learning opportunities in their cognitive and motivational prerequisites? Second, we were interested in whether there is a benefit when seizing optional learning opportunities. We hypothesized that students who seized optional learning opportunities would have better learning outcomes (i.e., performance and motivation) than students who did not seize optional learning opportunities. Third, we were interested in whether this benefit holds when controlling for students’ prerequisites.

Method

Participants

One hundred and twenty-two psychology undergraduates attended a mandatory course in educational psychology at a German university. Because 14 students did not complete the course, the sample for this study consisted of N = 108 students (n = 26 male, n = 82 female). Of this final sample, 77.8% were first-year, 6.5% were second-year, 11.1% were third-year, and 3.7% were fourth-year students; one person (0.9%) did not indicate her year. Furthermore, 87% of the students studied psychology as their major, 11.1% as their minor, and two students (1.9%) did not indicate their main subject.

Measures

Prerequisites

Students reported their school GPA as a measure of general prior achievement. Furthermore, students took a prior knowledge test that consisted of 15 sentences referring to topics that were covered in the course (e.g., “There are gender differences in general mental ability in favor of boys/men”). The students had to indicate whether these sentences were true or false. Depending on their answers, students received 1 point or 0 point per item.

As a measure of motivation, students indicated their agreement to several statements on a 5-point Likert-type scale (1 = strongly disagree to 5 = strongly agree): Students’ expectancies were measured with three items (e.g., “I think I will perform well in educational psychology”). Regarding the value component, students rated three aspects relating to educational psychology: usefulness (“The contents of educational psychology will be useful for my occupational life”), attainment (“For me, it is important to have a good knowledge of educational psychology”), and interest (“I think that what I am going to learn in educational psychology will be interesting”).

Outcomes

Two performance variables were assessed: students’ grades on required writing assignments (see below) and students’ score on a final exam. The final exam was of the same format as the prior knowledge test but consisted of 100 items. For motivation, students’ expectancies and values were assessed with a self-report questionnaire analogous to the self-report questionnaire in the first session.

In the questionnaire at the end of the semester, students also reported their time spent learning (“How much time on average have you spent learning every week, not including the lecture sessions?”).

Procedure

In the first session, students completed the prior knowledge test and reported their school GPA. Furthermore, they filled out a self-report questionnaire on their expectancies and values about educational psychology. Students received credit points for writing two required writing assignments (graded) and for passing a final written exam (not graded). Each writing assignment asked students to answer two questions that referred to but also exceeded the course’s contents. The required writing assignments were assigned after two thirds of the semester had passed. For two units, each consisting of two sessions, students could choose which assignment they wanted to submit. During the semester, there were six sessions in which students could submit optional writing assignments (see Table A1 in Appendix A). Based on a detailed specimen model solution, trained student tutors gave an individual verbal feedback that could consist of both short content–related and general remarks (e.g., “When discussing the possible implications of PISA, you should be aware of the fact that the design of PISA does not allow for any causal conclusions,” and “Please argue on the basis of empirical studies,” respectively). Furthermore, student tutors used a scoring scheme to evaluate students’ answers with an overall score ranging from 0 to 10 points. In the last session, students took the mandatory final exam on which they had to achieve a minimum score. Again, they filled out the questionnaire on their expectancies and values about educational psychology. Furthermore, students reported their time spent learning during the semester.

Results

Descriptives and Intercorrelations

The descriptives and intercorrelations for all variables used in the following analyses are displayed in Table 1. We categorized the students in four groups according to the number of optional writing assignments that they had submitted: (a) no (n = 33; 30.6%), (b) one (n = 26; 24.1%), (c) two (n = 21; 19.4%), and, to have comparable group sizes, (d) three to five optional writing assignments (n = 28¹; 25.9%). The mean number of submitted optional writing assignments was M = 1.58 (SD = 1.49).

Table 1.

Means (M), Standard Deviations (SD), and Correlations of Students’ Prerequisites and Outcomes.

Variable	M	SD	Range	Min–Max	1	2	3	4	5	6	7	8	9
1. School GPA^a	5.56	0.56	1–6	3.30–6.00	—
2. Prior knowledge	7.50	1.85	0–15	2.00–11.00	−.11	—
3. Expectancies t1	3.60	0.50	1–5	2.33–5.00	.06	.19	–
4. Values t1	3.84	0.70	1–5	1.67–5.00	.26**	−.04	.32**	—
5. Time spent learning	96.22	92.78		0.00–500.00	.15	−.19	−.14	.11	—
6. Grade on required writing assignments^a	5.17	0.65	1–6	2.00–6.00	.34**	−.09	−.07	−.08	.01	—
7. Final exam	84.57	10.00	0–100	37.00–97.00	.49***	.17	.05	.01	.11	.63***	—
8. Expectancies t2	3.66	0.52	1–5	2.00–4.67	.04	.11	.17	.17	−.10	.26*	.30**	—
9. Values t2	3.50	0.80	1–5	1.67–5.00	.24*	.03	.00	.38***	.09	.02	.09	.23*	—

Note. Range = theoretical minimum and maximum of each measure; Min–Max = empirical minimum and maximum of each measure.

^a For a better intuitive understanding, grades were recoded with larger scores representing better grades (in Germany, grades range from 1 = outstanding performance to 6 = insufficient performance). Cell sizes vary between N = 89 and N = 108 students.

*p < .05, two-tailed. **p < .01, two-tailed. ***p < .001.

Group Differences in Students’ Prerequisites

To analyze how students who submitted no, one, two, or three to five optional writing assignments differed in their prerequisites, we conducted a MANOVA with cognitive (prior knowledge and GPA) and motivational prerequisites (expectancies and values in the first session) as dependent variables. The MANOVA revealed a significant effect of the number of submitted optional writing assignments, V = 0.23, F(12, 285) = 2.01, p = .023, and η² = .08. Group differences were found for students’ school GPA, F(3, 96) = 5.58, p = .001, and η² = .15. Post hoc analyses revealed that students who submitted no optional writing assignments had a significantly worse GPA than students who submitted two (p = .017) or three to five optional writing assignments (p = .003); no other group differences in GPA were found (all ps > .05). By contrast, student groups performed equally well on the prior knowledge test, and they did not differ significantly neither in their expectancies nor in their values (all ps > .05).

Group Differences in Students’ Outcomes

To analyze how the students differed in their outcomes, we conducted a MANOVA with performance (grade on required writing assignments and score on final exam) and motivation (expectancies and values in the last session) as dependent variables. We included an a priori contrast (Helmert) to examine the difference between students who submitted no versus at least one optional writing assignment.

The MANOVA revealed a significant effect of the number of submitted optional writing assignments, V = 0.32, F(12, 252) = 2.54, p = .004, and η² = .11. Group differences were found for students’ score in the final exam, F(3, 85) = 8.15, p < .001, and η² = .22. According to the planned comparison, students who submitted no optional writing assignments performed significantly worse than students of the other groups (p < .001). Post hoc analyses revealed that students who submitted one optional writing assignment performed significantly worse than students who submitted three to five optional writing assignments (p = .015). No other post hoc comparisons revealed significant group differences (all ps > .05). Although the number of submitted optional writing assignments had no global effect on students’ grade in the required writing assignments, F(3, 85) = 2.32 and p = .090, the planned comparison showed that students who submitted no optional writing assignments had a significantly worse grade (p = .044). Furthermore, student groups did not significantly differ in their motivational outcomes (all ps > .05).

Because the student groups had differed in their prerequisites, we additionally conducted a MANCOVA with students’ prerequisites as covariates. Again, we included an a priori contrast (Helmert). The MANCOVA yielded a significant multivariate effect of writing assignment submission, V = 0.32, F(12, 225) = 2.25, p = .010, and η² = .11. Group differences were found for students’ score in the final exam, F(3, 76) = 7.21, p < .001, and η² = .22. According to the planned comparison, students who submitted no optional writing assignments achieved a significantly lower score in the final exam (p < .001). None of the post hoc comparisons revealed any further significant group differences (all ps > .05). Again, although the number of submitted optional writing assignments had no global effect on students’ grade in the required writing assignments, F(3, 76) = 2.17 and p = .098, the planned comparison showed that students who submitted no optional writing assignments had a significantly worse grade (p = .017). Again, student groups did not significantly differ in their motivational outcomes (all ps > .05).

To rule out the possibility that it was plainly an effect of time investment why students who submitted no optional writing assignments had worse learning outcomes, we conducted a MANCOVA with time spent learning during the semester as a covariate. Again, according to the planned comparison, students who submitted no optional writing assignments achieved a significantly lower score in the final exam (p < .001). The student groups did not differ in neither their grade on the required writing assignments nor in their motivational outcomes (all ps > .05).

Discussion

The aim of this study was to examine how students who use or do not use optional learning opportunities differ in their prerequisites and outcomes. To this end, we implemented a teaching–learning format in which students could choose whether and to what extent they seized optional learning opportunities. Our analyses showed that students who seized optional learning opportunities were characterized by better learning prerequisites in that students who used two or more optional learning opportunities had a significantly better school GPA than students who did not seize any learning opportunities. Regarding their outcomes, students who used optional learning opportunities significantly outperformed students who did not use optional learning opportunities on the final exam. Furthermore, students who used three to five optional learning opportunities performed better than students who used only one optional learning opportunity. Effects on the final grade were less clear, but results indicated that students who did not seize any optional learning opportunity received worse grades on their required writing assignments than students who seized at least one optional learning opportunity. There was no difference between the student groups who seized or forwent the optional learning opportunities regarding their motivational outcomes, and the main results held after controlling for students’ initial prerequisites or their time spent learning during the semester. Thus, our study supports the common idea that “practice makes perfect” and that students with better learning prerequisites are better able to recognize and seize optional learning opportunities.

Although we conducted our study in an educational field setting, we were able to control for variables that are known to be related to educational outcomes. When controlling for important prerequisites, students who used optional learning opportunities still had better learning outcomes. This finding confirms our idea that seizing optional learning opportunities can lead to better learning outcomes for both students with good and students with lower learning prerequisites.

Due to the design of our study, we cannot state whether there is an optimal number of optional learning opportunities that a student should seize to have the best cost–benefit ratio. However, based on our results, we might conclude that one is better than none, that many might be better than one but that there seems to be no increase in positive effects beyond a certain number of seized optional opportunities. The nonexisting effect of seizing optional learning opportunities on students’ motivation is probably due to the fact that students might have received some comments that were helpful to perform better but nevertheless made students realize that they had not performed perfectly yet.

Results were not equally clear regarding the different performance measures. It might be important that students only had to pass the final exam but received a grade on their required writing assignments. Hence, all students might have invested a great deal of effort in their required writing assignments, leaving little scope for the effects of the optional learning opportunities.

In conclusion, we think that the results of our study indicate that offering optional learning opportunities can be a good way when instructors want to pursue different goals, that is, supporting students’ performance, their motivation, and their satisfaction with the learning conditions. Especially, the last two goals might be impaired when students are forced to seize additional learning opportunities. Offering choice should support students’ autonomy and thus their motivation (see self-determination theory; Deci & Ryan, 1985, 1987; see also Unsworth & Kauter, 2008).

Footnotes

Appendix A

Table A1.

Overview of the Semester Schedule.

Content of Session	Writing Assignment Submission
1. Introduction, aims, contents, and concept	—
2. Improving the quality of learning in higher education	Example
3. Large-scale assessments of school achievement	Optional
4. Improving the quality of schools and education	Optional
5. Determinants of successful school achievement	Optional
6. Giftedness	Optional
7. Learning disabilities: Dyslexia	Optional
8. Attention deficit hyperactivity disorder	Optional
9. Ability self-concepts	Required/graded: 1 out of 2
10. Performance evaluation in school	Required/graded: 1 out of 2
Christmas holiday
11. Training and advancement I	Required/graded: 1 out of 2
12. Training and advancement II	Required/graded: 1 out of 2
13. Final exam	—

Declaration of Conflicting Interests

The authors declare no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Note

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