Is Intrinsic Motivation Related to Lower Stress among University Students? Relationships between Motivation for Enrolling in a Study Program, Stress, and Coping Strategies

Abstract

Transitioning from high school to university can be a challenging time for students, associated with uncertainty and stress, in part resulting from the vast number of subjects to choose from. Research has shown positive associations between intrinsic motivation and student well-being. Considering the detrimental roles that students’ stress and possibly dysfunctional coping strategies can play regarding general well-being, we investigate relationships between these constructs. Motivation for enrollment in a study program was analyzed in n = 201 first- and higher-semester students with regard to different facets of motivation. Part of the freshmen sample (n = 40) completed an additional follow-up survey in their second semester, expanding on stress and coping strategies. Cross-sectional results showed different patterns of intercorrelation among the motivational facets, but no significant differences between first- and higher-semester students. Longitudinally, only motivation based on social influences decreased over the course of the first semester. Motivation did not prove to be a suitable predictor for retrospectively judged stress during the first semester, but intrinsic motivation, especially, showed encouraging connections to some coping strategies. The findings can be used to improve student well-being and reduce dropout rates, as well as to design suitable marketing strategies for universities.

1. Introduction

Student stress and mental health have been an important and much-researched topic [1,2] not only since the COVID-19 pandemic, which worsened the prevalence of anxiety, depression, and stress among college students [3,4]. Therefore, stress and mental health among students are, on the one hand, currently being discussed in the context of sustainable academic performance [5,6] and health promotion at universities [7,8]. On the other hand, research tries to describe and explore factors that might influence or predict student stress [9], as these factors are starting points for possible interventions. One of these factors is the decision to choose a degree program.

This decision of choosing a career path may add to already prevalent uncertainty and stress in this transitional phase [10], in part resulting from the vast number of subjects to choose from [11]. In addition to subject-related interests, admission requirements, proximity to the place of residence, possibilities of incorporating a job to support themselves, social influences like their parents’ choice of degree program, etc., also play a role.

To put it in a more narrative way, the almost unmanageable number of subjects available, the need to finance their studies, the pressure to perform during their studies, and the challenge of gaining a foothold in the labor market after graduation are just a few of the difficulties that students have to deal with. Intrinsic motivation, in the sense of a genuine interest in the content, could play a special role in mastering the mentioned challenges in the degree program, as well as in the choice of subject. However, this paper is not primarily concerned with the sources of stress during studies, but rather with the question of what role intrinsic motivation plays in coping with stress before and during studies.

1.1. Motivation for Enrolling in a Study Program

Drawing on the classic dichotomous distinction between doing something for the sake of itself because of interest or enjoyment and doing something in expectation of an external outcome [12], research on academic motivation has often been focused on intrinsic and extrinsic factors. These have been studied extensively in school as well as higher-education settings [13,14,15]. Research generally shows a higher level of intrinsic motivation for enrolling in a study program compared to extrinsic motivation [16,17]. So, factors such as interest in the study program’s content seem more important to prospective students than future job prospects or the possibility of a higher income. Also, intrinsic motivation has been more extensively studied than extrinsic motivation and often served as a predictor for academic outcomes [18,19].

When looking at university education, at least two possible foci for studying motivational aspects present themselves: firstly, the day-to-day intrinsic and extrinsic factors that motivate students in their university life (e.g., enjoying learning new things or wanting to perform well in order to achieve good grades), and secondly, their motivation for taking up a university degree or specifically their study program in the first place (e.g., having an interest in the content or hoping for a well-paying job in their field after university). Studies in the former research area are, for example, concerned with relationships between everyday motivation and students’ performance [20], their goals [18], or their psychological well-being [21].

Our current research concerns itself with the latter area and aims to analyze students’ motivations for choosing and enrolling in their current study program. This area of research is connected to and somewhat based on research into motivation for choosing one’s professional career [22]. As the decision to obtain a university degree, in most cases, determines the choice of a professional career, they share a common conceptual background and can both be connected to job success in life after university [17].

An often-occurring methodological problem in research on the motivation for enrolling in a study program or for choosing a professional path is the retrospective nature of assessing those motivational factors. This example of the classic hindsight bias [23] may lead to distortions in reporting motivation from years previously. For example, in a satisfactory and well-managed study program, students may mistakenly remember a higher interest in the content as the basis for their decision-making even though the initial decision was based more on economic considerations.

For this reason, we decided to investigate whether the intrinsic motivation of students changes over the course of their studies. As most studies assume an appropriate validity of retrospectively judged motivation, differences should not occur in the reported motivational facets between the first and second semesters. Therefore, we pose the following first research question: do freshmen report different motivations for having enrolled in their study program than students in higher semesters?

1.2. Student Stress and Coping

Research on stress has increasingly focused on understanding the subjective experience of stress and how different groups cope with it. This trend is evident in the growing attention to stress among students, especially following the COVID-19 pandemic [3,4] and the significant reforms to European academic qualification programs outlined in the Bologna declaration [24]. A systematic review aimed to investigate the prevalence of anxiety, depression, and stress among college students during the COVID-19 pandemic [3] and analyzed data from 28 studies, including a total of 436,799 college students, and found the prevalence of anxiety, depression, and stress to be 29%, 37%, and 23%, respectively. These findings suggest a significant negative psychological impact of the COVID-19 pandemic on college students worldwide, which was also found in another large-scale study [4]. Researchers analyzed 104 studies (totaling 2,088,032 participants) and found even higher prevalence rates of depressive (32%) and stress (31%) symptoms. But what are the sources of stress? The following categories were found in an exploratory factor analysis: academic, relationships, equity, parenting, practical, and health [25]. Also, the sources of stress may differ cross-culturally or in the forms of studying: on-campus students more often report study- and performance-related areas of stress, whereas distance-learning students report more conflicts between their studies and their private life [1]. In a content analysis, on-campus students reported significantly more stress due to exams, tests, final theses, and anxiety about the future, but also performance (pressure) and pressure to succeed, whereas distance-learning students experienced significantly more stress due to time pressure and the compatibility of study and private life or leisure time.

Coping strategies are typically categorized based on how individuals manage their emotional responses to stressors and the methods they employ to handle stressful situations. There are several distinctions within coping strategies: [26] distinguished between problem-focused (e.g., planning) and emotion-focused coping (e.g., meditation). These strategies have been expanded upon by other researchers with further categories: avoidance coping (e.g., ignoring), social support coping (e.g., asking friends), meaning-focused coping (e.g., focus on personal growth), and dysfunctional coping (e.g., substance use). A study among 448 students has shown gender differences in the strategies used; female students are more likely to use emotion-focused coping strategies such as self-distraction, emotional support, instrumental support, and venting [27]. Freire et al. [28] aimed to examine four aspects of psychological well-being (self-acceptance, environmental mastery, purpose in life, and personal growth) in students and conducted a study including 1072 university students and used latent profile analysis. It was found that students with higher levels of psychological well-being were more likely to use positive coping strategies such as positive reappraisal, support-seeking, and planning.

Intrinsic and extrinsic motivation, though different in their sources and effects, might influence how stress impacts students’ ability to study and perform academically as well as their handling of stressors in university life. Understanding the dynamic between these types of motivation, stress, and coping with it might be a promising starting point for interventions in educational settings. The second research question is, therefore, how are motivation, stress, and coping strategies related?

2. Materials and Methods

2.1. Samples and Procedure

For this study, different samples were used to answer the research questions. The university where the data were collected is a private university of applied sciences approved by the German state of Baden-Wuerttemberg, established in 2012. At the time of the first data collection (September and October 2023), a total of N = 682 students were enrolled and studying one of several programs in areas of economics or media sciences (e.g., Digital Marketing, International Business, or Sports Management) or health and social Sciences (e.g., Psychology, Business Psychology or Social Work). About half of the students come from Baden-Wuerttemberg; the other half come from the other German federal states.

The students were recruited in lectures in the winter and summer semesters of 2023/24 as well as via posters and university-wide e-mails asking them to participate in the survey either at home or during specific time slots during lectures. After being informed about the purpose of the study, the intended use of the data, and the possibility of withdrawing their consent to participate at any moment, the students indicated their agreement to the terms on the first page of the online questionnaire before starting the survey. The field phase of the online survey lasted for four weeks.

Sample 1 comprised n = 101 students in their first semester at university (M_age = 20.04 years; SD_age = 1.53 years; 73.3% female; 54.5% economics and media sciences; 45.5% health and social sciences) and n = 100 students in higher semesters (M_age = 21.40 years; SD_age = 2.35 years; 59.0% in their third semester; 70.0% female; 61.0% economics and media sciences; 39.0% health and social sciences). A percentage of 28.9% had previously studied at a university (n = 26) or completed an apprenticeship (n = 32). Based on the overall enrollment numbers, this sample constitutes a response rate of 29.5% of all students enrolled in the university at the time of data collection.

Data collection in this first sample was part of a larger survey project at the university, and the participants filled out several questionnaires. Data on students’ motivations for enrolling in a study program are relevant for the current analyses.

Sample 2 consisted of n = 40 students that were part of the freshmen group from the first sample (M_age = 19.83 years; SD_age = 14.13 years; 80.0% female; 45.0% economics and media sciences; 55.0% health and social sciences). They were recruited again for the follow-up survey in the first week of their second semester to provide information about the previous semester, specifically about their perceived stress and their coping strategies. Additionally, the students again provided information on their motivation for enrolling in the program in order to analyze changes over the course of six months.

2.2. Instruments

Motivation for enrolling in a study program was assessed using the STUWA, a German inventory comprising seven facets of motivation: intrinsic, extrinsic—materialistic, extrinsic—social, socially induced, and coping-oriented, as well as motivation based on insecurity and motivational conflicts [29]. Each subscale is represented by three items that are judged on a 7-point Likert scale ranging from “completely disagree” to “completely agree”. The reliability and validity of this only recently published instrument were investigated in two validation studies [29]. The 7-factorial measurement model was found to be a good fit in exploratory as well as confirmatory factor analyses, and the reliability of the subscales was satisfactory, respectively (0.75 ≤ α ≤ 0.91). The subscales showed expected correlations with other constructs and proved to be suitable for gender and subject comparisons due to measurement invariance. Reliability coefficients in our current study ranged from α = 0.75 (intrinsic motivation) to α = 0.92 (motivational conflicts) in sample 1 and from α = 0.64 (intrinsic motivation) to α = 0.94 (extrinsic—materialistic) in sample 2. Exploratory factor analysis also provided support for the proposed 7-factorial model.

We used a slightly adapted version of the Perceived Stress Scale (PSS [30]) to measure students’ stress during their first semester. This questionnaire, in its German translation [31], consists of ten items rated on a 5-point Likert scale (“never” to “very often”). The original time reference of the previous month was adapted to reflect experiences in the previous (first) semester of university, e.g., “In the last semester, how often have you felt nervous and ‘‘stressed’’?”. Previous research on the questionnaire’s factorial structure has yielded support for a unidimensional as well as a two-dimensional structure with an advantage of two factors: perceived helplessness and perceived self-efficacy [31]. For our non-clinical sample, we chose a unidimensional solution (α = 0.87).

The students’ coping strategies were assessed using the Brief COPE questionnaire [32] in the German version [33]. This questionnaire comprises 28 items measuring 14 possible coping strategies with two items each (4-point Likert scale ranging from “not at all” to “very”). The Brief COPE questionnaire has been extensively used in various samples and countries since its development more than 25 years ago, and its reliability and validity have been proven in the process [34]. The factorial structure of this instrument has also been a topic of much consideration over the years [34]. For our purpose (a non-clinical, not job-specific sample) we decided to use the questionnaire as a whole and categorized the subscales into the following categories:

• Problem-focused coping (active coping, planning, instrumental support; α = 0.72);
• Emotion-focused coping (positive reframing, acceptance, humor, religion; α = 0.64 after removing the subscale emotional support, which did not fit with the data);
• Dysfunctional coping (self-distraction, denial, behavioral disengagement, and self-blame; α = 0.67 after removing the subscales substance use and venting, for the same reason).

This subcategorization was suggested by [32] and has been implemented in assessments [35,36]. The instructions that were written before the items specified that answers were supposed to be given regarding behavior during the last (i.e., the students’ first) semester.

2.3. Statistical Analyses

As a first step, intercorrelations between the variables were calculated. Pearson correlations were used to determine relationships between the seven facets of motivation in sample 1, and Spearman correlations (due to the smaller sample size and violations of normality) were used to analyze relationships between motivations, stress, and coping strategies in sample 2. A further set of Spearman correlations was calculated regarding connections between the motivation in the first and second semesters.

To answer our first research question, we calculated differences between first- and higher-semester students in both a between-subject design and a within-subject design. A multivariate analysis of variances in sample 1 with the seven facets of motivation as the outcomes analyzed differences in a cross-sectional comparison between students at the beginning of their university life and another group of students further along in their education. The second analysis—the within-subject design comparing motivation in the students’ first semester to their motivation six months later—comprised individual Wilcoxon signed-rank tests instead of a repeated-measures analysis of variances because of the small sample size in sample 2.

Regression analyses were used to answer the second research question. First, we performed two separate analyses with perceived stress during the first semester as the outcome and motivation reported at the beginning of the first and second semesters, respectively, as the predictors. With regard to the outcome coping strategies, six separate models were calculated combining the three clusters of coping strategies with the two measurement points of motivation.

3. Results

3.1. Interrelation between the Variables

Before moving on to answering the research questions,

Table 1. Pearson correlations between facets of motivation for enrolling in a study program in sample 1 (n = 201).

Facet of Motivation	1	2	3	4	5	6
1 intrinsic
2 extrinsic—materialistic	0.10
3 extrinsic—social	0.13	0.37 ***
4 socially induced	0.10	0.03	0.16 *
5 coping-oriented	−0.09	0.07	0.16 *	0.32 ***
6 insecurity	−0.46 ***	−0.02	−0.06	−0.06	0.14 *
7 motivational conflicts	−0.37 ***	0.01	−0.09	0.05	0.18 *	0.28 ***

Notes: * p < 0.05. *** p < 0.001.

and

Table 2. Spearman correlation between facets of motivation for enrolling in a study program, stress, and coping strategies in sample 2 (n = 40).

Facet of Motivation	Stress	Problem- Focused Coping	Emotion- Focused Coping	Dysfunctional Coping
Intrinsic	−0.28	0.32 *	0.23	−0.32 *
Extrinsic—materialistic	−0.12	0.03	0.11	−0.19
Extrinsic—social	0.10	0.16	0.17	−0.06
Socially induced	0.28	−0.15	−0.11	0.28
Coping-oriented	0.21	−0.16	0.01	0.29
Insecurity	0.33 *	−0.11	−0.18	0.29
Motivational conflicts	0.22	−0.18	0.04	0.25

Notes: * p < 0.05.

show intercorrelations between the relevant variables measured in the two samples, respectively. Table 1 is based on sample 1, encompassing students in their first and second semesters. As it turned out, not all of the facets of motivation were correlated with each other.

Additionally, we examined correlations within the individual facets of motivation for enrolling between the first and second semesters in sample 2. Because of the smaller sample size and the fact that not all variables showed a normal distribution, Spearman coefficients were calculated, and the following correlations were found:

• Intrinsic: ρ = 0.23, n.s.;
• Extrinsic—materialistic: ρ = 0.46, p < 0.01;
• Extrinsic—social: ρ = 0.34, p < 0.05;
• Socially induced: ρ = 0.02, n.s.;
• Coping-oriented: ρ = 0.35, p < 0.05;
• Insecurity: ρ = 0.38, p < 0.05;
• Motivational conflicts: ρ = 0.46, p < 0.01.

Correlations between facets of motivation for enrolling in a study program and stress, as well as coping strategies, in sample 2 are presented in Table 2.

3.2. Differences in Motivation between First- and Higher-Semester Students

To address research question 1, we firstly compared the freshmen sample to the sample from higher semesters using a multivariate analysis of variances. These independent samples provide a cross-sectional comparison. The overall multivariate analysis showed no significant differences between the two groups (F(7) = 1.52; p = 0.16). Descriptive statistics and individual comparisons for every facet of motivation can be found in

Table 3. Cross-sectional differences in motivation for enrolling between first- and higher-semester students.

Facet of Motivation	First-Semester Students (n = 101)	Higher-Semester Students (n = 100)	F
Intrinsic	6.11 (0.62) 1	6.01 (0.79)	0.911
Extrinsic—materialistic	5.16 (1.16)	5.33 (1.28)	0.998
Extrinsic—social	5.56 (1.02)	5.26 (1.37)	2.943
Socially induced	4.00 (1.77)	3.80 (1.83)	0.643
Coping-oriented	2.40 (1.03)	2.59 (1.15)	1.430
Insecurity	3.06 (1.47)	3.15 (1.54)	0.209
Motivational conflicts	2.04 (1.43)	2.00 (1.36)	0.041

Notes: ¹ M(SD) on a 7-point Likert scale.

. In line with the multivariate analysis, no significant differences were found between the two groups.

Secondly, we compared the motivation scores obtained from the freshmen in their first semester with their responses six months later, allowing for within-subject analyses. In this case, due to the small sample size in the longitudinal design (n = 40), we used individual Wilcoxon signed-rank tests instead of a repeated-measures multivariate analysis of variances.

Table 4. Longitudinal differences in motivation for enrolling between students in their first and second semesters.

Facet of Motivation	First Semester (n = 101)	Second Semester (n = 40)	z
Intrinsic	6.06 (0.71) 1	6.00 (0.65)	0.294
Extrinsic—materialistic	5.24 (1.22)	5.14 (1.09)	−0.265
Extrinsic—social	5.41 (1.21)	4.98 (1.16)	2.164 *
Socially induced	3.90 (1.80)	2.90 (1.61)	2.299 *
Coping-oriented	2.49 (1.09)	2.35 (1.09)	−0.448
Insecurity	3.10 (1.50)	3.28 (1.41)	−1.780
Motivational conflicts	2.02 (1.39)	1.90 (1.13)	1.213

Notes: n = 40. * p < 0.05. ¹ M(SD) on a 7-point Likert scale.

shows the results of these analyses. Only the extrinsic—materialistic motivation and the socially induced motivation showed differences, in that they were reported to be lower in the students’ second semester than in their first.

3.3. Relationships between Motivation, Stress, and Coping Strategies

As a first step to answering research question 2, we analyzed correlations between stress and coping strategies regarding the students’ first semester, both reported retrospectively at the beginning of their second semester. Perceived stress was not related to problem-focused coping (r = −0.27; p = 0.10), but was negatively related to emotion-based coping (r = −0.61; p < 0.001) and positively related to dysfunctional coping (r = 0.66; p < 0.001).

Linear regression analyses were used to examine relationships between motivation (measured at the beginning of students’ first and second semesters) and perceived stress during the first semester (

Table 5. Linear regression of perceived stress during first semester on motivation measured at two points in time (n = 40).

Facet of Motivation	Perceived Stress during First Semester
	Motivation Measured at Beginning of First Semester β	Motivation Measured at Beginning of Second Semester β
Intrinsic	0.35	−0.26
Extrinsic—materialistic	0.27	−0.06
Extrinsic—social	−0.20	0.04
Socially induced	0.08	0.13
Coping-oriented	−0.25	−0.09
Insecurity	0.23	0.26
Motivational conflicts	0.06	0.28
Λ R2	0.15	0.27

). No significant relationships were found.

Additional linear regression analyses were used to predict coping strategies used during the first semester from motivation (measured at the beginning of students’ first and second semesters), the results of which are shown in

Table 6. Linear regression of coping strategies during first semester and motivation measured at two points in time (n = 40).

Facet of Motivation	Coping Strategies during First Semester
	Problem-Focused	Emotion-Focused	Dysfunctional	Problem-Focused	Emotion-Focused	Dysfunctional
	Motivation Measured at Beginning of First Semester β			Motivation Measured at Beginning of Second Semester β
Intrinsic	−0.22	−0.44 *	0.16	0.38 *	0.21	−0.30
Extrinsic—materialistic	−0.20	−0.17	0.16	−0.11	0.04	−0.06
Extrinsic—social	0.03	0.19	−0.28	0.08	0.20	−0.21
Socially induced	0.34 *	0.08	0.10	−0.09	−0.12	0.24
Coping-oriented	−0.25	0.16	0.01	−0.02	0.07	0.14
Insecurity	−0.17	−0.11	−0.04	0.06	−0.11	0.07
Motivational conflicts	−0.27	−0.26	0.14	−0.17	−0.01	0.14
Λ R2	0.38 *	0.18	0.10	0.17	0.12	0.28

Notes: * p < 0.05.

. Intrinsic motivation at the beginning of students’ first semester proved to be a significant negative predictor for emotion-focused coping strategies, and intrinsic motivation measured at the beginning of their second semester showed a positive relationship with problem-focused and a negative one with dysfunctional coping strategies during their first semester. Furthermore, students who initially felt influenced in their decision to enroll in a study program by their social network reported higher problem-focused coping during their first semester.

4. Discussion

Our interest in analyzing students’ motivation for enrolling in a specific study program was two-fold. Firstly, we sought to expand research on the multifaceted nature of motivation, expanding the construct beyond the dichotomous separation into intrinsic and extrinsic motivation. The focus lay on differences in motivation at the beginning of students’ university life and in higher semesters. Secondly, we sought to shed light on possible connections between motivation and stress and coping during students’ first semester. It is important to bear in mind that this study and its results should be interpreted as a first step towards the research objective, but more research is much needed.

4.1. Facets of Motivation and Their Changes

The intercorrelations between the facets of motivation in the larger sample point to a pattern among these different types of motivation. Intrinsic motivation did not prove to be connected to the externally oriented facets such as materialistic or social influences. This finding is in line with previous research and the conceptual assumption that extrinsic and intrinsic motivation are not necessarily connected with one another [37,38]. Intrinsic motivation, however, did show negative relationships with motivation based on insecurities—either regarding an insecurity about fit or about a lack of alternative options in a study program. In this sense, intrinsic motivation could serve as a buffer against quitting the study program, because students feel more secure in their choice. Unsurprisingly, most of the external factors were intercorrelated with each other, though with small effect sizes. Interestingly, coping-oriented motivation proved to be positively connected to both facets of motivation that are based on insecurity. This may point to a tendency in prospective students who are unsure about their choice to decide on a study program that they think might be more easily manageable than others. This pattern of interrelations between the facets is largely in line with the pattern found in the validation study of the instrument [29].

In order to analyze differences in motivation for enrolling in a study program, we first compared first-semester students to students in higher semesters. There were no significant differences between the two groups on any of the facets of motivation. This finding points to similar levels of perceived motivation right at the beginning of one’s university career and further along.

In addition to this cross-sectional analysis, the repeated measure among a part of the first sample allowed for longitudinal analyses regarding possible changes in motivation over the course of students’ first semester at university. The results showed positive relationships for most facets of motivation six months later. Only intrinsic motivation and socially induced motivation showed no significant connection. Looking at the extent of the motivational facets, a comparison of average ranks at the two measurement points showed differences only for extrinsic—social and socially-induced motivation, which were both reported to be lower six months into the study program than at the beginning. This effect might stem from a process of internalizing one’s motivation after making a decision, in this case for a study program. Even if, in the beginning, the students’ social network may have played a bigger role in their choice, this feeling may diminish over time. This relates to the idea that while intrinsic and extrinsic motivation may not occur in tandem, they might be end points of a motivational spectrum that allows a transition from one aspect to another over time [39].

The first research question, to summarize, cannot be answered conclusively. Cross-sectionally, no significant changes in the reported motivation for enrolling in the study program could be found, but in the longitudinal analysis, two of the seven facets of motivation had decreased over the course of one semester, and not all facets showed correlations between the two measurement points.

4.2. Motivation, Stress, and Coping Strategies

The results show that perceived stress is negatively associated with emotion-focused coping and positively associated with dysfunctional coping, which is consistent with previous research [28]. As the sample in our study was predominantly female, this could also support findings on gender differences in the use of coping strategies [27]. Interestingly, problem-focused coping was not associated with perceived stress; whether this is due to the sampling (e.g., low levels of stress or low levels of problem-focused coping) or whether there are other methodological or content-related reasons remains open. Since the only marginally significant regression coefficient points to a positive relationship between intrinsic motivation at the beginning of the study program and perceived stress during the first semester, we cannot clearly prove the role of intrinsic motivation as a stress buffer. Still, it is helpful to consider different factors in the development of stress. It is interesting to add that the model seems to be more complex and that the role of intrinsic motivation changes in the data over different time points: intrinsic motivation at the beginning of the first semester proved to be a significant negative predictor of emotion-focused coping strategies, and intrinsic motivation measured at the beginning of the second semester showed a positive correlation with problem-focused coping strategies and a negative correlation with dysfunctional coping strategies during the first semester. In this context, the importance of studying and the motives for choosing a course of study should not be ignored. The fact that students who initially felt influenced in their decision to study by their social network had a higher level of problem-oriented coping during the first semester could indicate that they were not as emotionally involved in the success of their studies. Therefore, intrinsic motivation could even work as a stress amplifier. This could be a starting point for examining subgroups of students to see whether intrinsic motivation has a buffering function for some and an amplifying function for others. All of these factors could be important to take into account for psychosocial counseling of students, and the experience of stress should also be recorded in the exploration in connection with the importance of studying and the motivation behind it.

Therefore, regarding the second research question, different motivation styles and their impact on perceived stress and coping strategies should not be hastily discarded, but more complex models could also include the locus of control or self-efficacy. However, more precise interpretations of the results here quickly come up against the methodological limitations of this first study, and should be investigated further.

4.3. Limitations and Future Research Directions

As in all empirical studies, there are certain limitations to the present study. The main drawback of the current study lies in the small sample size of sample 2 and the accompanying statistical and methodological constraints. Also, the sample only consisted of students at one university. Therefore, it is important to keep in mind that these results should be interpreted as a first step towards understanding the intercorrelations of motivation, stress, and coping, but further research using larger and more diversified samples is needed.

Larger sample sizes in future studies would, on the one hand, affect the reliability of the subscales, which were not satisfactory in all cases in the current study. On the other hand, multivariate testing for the repeated-measures design would be possible and allow for controlling interrelatedness between outcomes.

Furthermore, it is essential to gather more longitudinal data from these larger samples to reliably analyze changes in students’ motivation and their perception of stress at the individual and aggregate levels. Not only should the sample sizes be bigger, but there should also be more measurement points included. Our longitudinal analysis only compared first- and second-semester students, but continuous data collection over the course of the whole university experience would yield more differentiated results. A cross-lagged panel design would allow for controlling interrelations and artifactual influences from measurement points.

In addition, a certain bias is to be expected because participation in a survey is usually also a motivation in and of itself, and interest and involvement in a topic tend to influence participation in surveys. The “unmotivated” often do not take part, and this might prove to be an especially relevant factor in studies on the distinction between intrinsic and extrinsic motivation.

As for the differentiation between motivation for enrolling in a study program and motivation in an everyday educational setting, it would be interesting to analyze the relationship between the two constructs as well as their individual development. Research shows a decline in intrinsic motivation for learning over the course of a school career [39], but due to a possible internalization of the reasons for enrolling in a study program, this trend might not apply to those motivational aspects. In this context, subgroup analyses could also become relevant in order to possibly identify those subgroups in which motivation plays a more crucial role in perceived stress.

In order to obtain a more comprehensive view of students’ motivation and behavior, it would also be beneficial to include additional factors that may influence their experience. Previous studies have, for example, taken personality and individual differences such as gender or background into account [13,27,40]. It would also be interesting to examine the differences between the individual degree programs as students of business studies may have a higher extrinsic motivation to choose their study program than students of social sciences. However, the investigation of these presumed differences was not feasible in the longitudinal design due to the small number of cases.

In cross-sectional analyses, our data can provide insight into these questions as well as allow comparisons to other samples. The different types of universities in the German higher-education context may attract different types of students with different sets of motivations. Comparing our findings on motivation for enrolling in their study program at a private university to data from a public university may yield interesting results that are relevant to university administrators, especially regarding student acquisition and retention. In addition, such results could also provide interesting information about the design of study programs and their content in relation to students’ motivation levels and, thus, contribute to increasing students’ motivation to learn.

4.4. Practical Implications

These factors—attracting students to and keeping them at the university—are important practical aspects of research on student motivation and well-being. If students are unhappy with their program and not able to handle academic demands in a stress-free manner, they may drop out of their study program. Previous research indicates that goals ahead of entering university, motivation, and adaptation (among others) influence persistence in a program [41,42].

It is of great importance to pay attention to the motives for choosing a study program as early as the study counselling stage, to determine to what extent the expectations of future students match the content of the degree program and the career opportunities after graduation. This potentially increases satisfaction and performance in the degree program and reduces the drop-out rate in the study programs [43].

The results are of particular relevance for the psychosocial counselling of students, which sometimes includes perceived stress on the one hand and study choice and the decision to drop out on the other [44]. In a complex model of stress development, the motivation to start studying could be a factor, as well as the choice of coping strategies. As the results on the correlation between stress and motivation to start studying are not clear, they should be explored in a joint discussion including their individual significance.

The results can also be used to develop customized interventions (face-to-face or digitally delivered interventions) that can improve the fit between universities and students and lead to a high(er) level of student satisfaction. In addition, universities are called upon to offer their students measures from which they can learn coping strategies and incorporate them into their everyday studies [44]. This can also contribute to an improved situation for students at universities and prepare them for a satisfied and motivated life after graduation.

5. Conclusions

Our research expands on the concept of student motivation and on its relationships with stress and coping using cross-sectional and longitudinal data. We found evidence for a more complex structure of motivation compared to the dichotomous distinction between intrinsic and extrinsic motivation. These differentiated facets were similarly pronounced in first- and higher-semester students, which points to a relatively stable construct. Our analyses showed only a few connections between intrinsic and socially induced motivation and coping strategies, though this may be a statistical limitation due to a small sample size. Our future plans include an expansion to more participants and additional points of measurement over the course of students’ university life. Using this more complex construct of motivation may enable us to develop specific guidance offerings for students based on their motivational profile to ensure their well-being during higher education.